CONFERENCE ABSTRACT BOOK - ainfo.cnptia.embrapa.br

CONFERENCE ABSTRACT BOOK

LIVESTOCK, CLIMATE CHANGE AND FOOD SECURITY

CONFERENCE 19-20 May 2014

Madrid, Spain

Livestock, Climate Change and Food Security

Monday, May 19th 2014 8:30 Upper Lobby: Registration & Poster set-up

9:00 MEDICI Room: Welcome. Introducing the AnimalChange project and FACCE JPI

Jean-François Soussana, INRA, France

MEDICI Room: PLENARY SESSION 1

Setting the global scene: livestock futures and food security under climate change

Chair: Jean-François Soussana

9:30 1.1. Livestock in the Frame: Exploring alternative Visions of Sustainability

Tara Garnett, Oxford’s Environmental Change Institute, UK

10:05 1.2. Livestock in the XXIst century: Alternative Futures

Petr Havlík, IIASA, Austria

10:40 1.3. Climate Change Impacts and Vulnerability for Agriculture

Mark Howden, CSIRO, Australia

11:15 Upper Lobby: Coffee break and poster viewing: Poster Session 1

MEDICI I Room: Parallel Session 1a:

Climate Change Impacts

Chair: Peter Kuikman

MEDICI II&III Room: Parallel Session 1b:

Mitigation Options for Livestock

Chair: Harry Clark

12:15

1.a.1. What is the Impact of closing the global Gap in Pasture Performance on Land Use for

Food and Energy in a Carbon and Land-constrained World?

John Sheehan, University of Minnesota, USA

1.b.1. The Influence of Fat Supplement and Roughage Type on Feces Composition and

Methane Yield from Dairy Cows

Verónica Moset Hernández, Aarhus University, Denmark

12:30

1.a.2. Reconciling the Impacts of Extreme Rainfall Events and Extended Drought on Pasture and Livestock Production: a New Method for Generating Synthetic Climate

Sequences

Matthew Harrison, Tasmanian Institute of Agriculture, Australia

1.b.2. Nitrous Oxide Emission partly alleviates the Methane Mitigation Effect of Nitrate

Intake by dairy Cattle

Søren O. Petersen, Aarhus University, Denmark

12:45

1.a.3. MACSUR liveM – A Knowledge-Hub for integrated Modelling of Climate Change

Impacts on Livestock Production Systems: Lessons learned and future Developments

Eli R. Saetnan, Aberystwyth University, UK

1.b.3. Ammonia and Greenhouse Gases Emission from Slurry Storage with

impermeable Cover and Landspreading of Cattle Slurry

Maialen Viguria, NEIKER-Tecnalia, Spain

13:00

1.a.4. The Influence of GHG Metrics on Quantification of Agricultural Emissions and

Mitigation Options

Andy Reisinger, NZ Agricultural GHG Research Center, New Zealand

1.b.4. Methane Emission by Beef Steers on natural Grassland in Southern Brazil

Teresa Genro, EMBRAPA Southern Region Animal Husbandry, Brazil

13:15 RENACIMIENTO Room: LUNCH


Understanding the technical potential for mitigation and adaptation

Chair: Pete Smith

14:15 2.1. IPCC WGIII Findings on Animal Agriculture Mitigation Potential

Pete Smith, University of Aberdeen, UK

14:50 2.2. The Complexity of System Boundaries when it comes to Mitigation Measures

Christel Cederberg, Chalmers University of Technology, Gothenburg, Sweden

15:25 2.3. Climate Change and Livestock: Impacts and Adaptation




Mitigation Options for Grasslands

Chair: Frank O’Mara


Adaptation Options for Livestock and Grasslands

Chair: Andreas Jenet

17:00

2.a.1. Gain of Nitrogen from Legumes in Grassland is robust over a wide Range of

Mixture Legume Proportion and Environmental Conditions

Matthias Suter, WBF-Agroscope, Switzerland

2.b.1. Principles of Climate Change Adaptation in Livestock Systems

Jørgen E. Olesen, Aarhus University, Denmark

17:15

2.a.2. Paired Eddy Flux Tower Experiments and Modelling Carbon Fluxes Show Stronger Carbon Sink Activity Under Grazing than

Mowing

Abad Chabbi, INRA, France & Zoltán Nagy, Szent István University-IBE, Hungary

2.b.2. Impact of Heat Stress on Production in Holstein Cattle in four EU Regions. Selection

Tools.

Maria B. Carabaño, INIA, Spain

17:30

2.a.3. Mitigating GHG Emissions from Ruminant Livestock Systems through the Management of Carbon Sequestration in

Grasslands

Katja Klumpp, INRA, France

2.b.3. Potential Use of Forage Legume Intercropping Technologies to mitigate and adapt to Climate Change Impacts on mixed

Crop-Livestock Systems in Africa

Abubeker Hassen, University of Pretoria, South Africa

17:45

2.a.4. Capacity of tropical permanent Pastures to restore Soil Carbon Storage after

Deforestation of the Amazonian Forest

Vincent Blanfort, CIRAD, France

2.b.4. Livestock and Climate Change in East Africa: exploring Combinations of Adaptation

and Mitigation Options

Silvia Silvestri, ILRI, Kenya

19:00 RENACIMIENTO Room: CONFERENCE DINNER

Tuesday, May 20th 2014


Framing the Options: the Farm and Landscape Scales

Chair: Jørgen E. Olesen

8:45 3.1. Integrating Adaptation and Mitigation in extensive grazing Systems

Mario Herrero, CSIRO, Australia

9:20

3.2. Integrating Adaptation to and Mitigation of Climate Change in intensive Animal Production Systems

Frank O’Mara, Teagasc, Ireland

9:55

3.3. Integrating Adaptation and Mitigation in Smallholder farming Systems: a Focus on Sub-Saharan Africa

Ken Giller & Katrien Descheemaeker, Wageningen University, The Netherlands



The Farm Scale

Chair: Karen Beauchemin


The Landscape and regional Scale

Chair: Abubeker Hassen

11:15

3.a.1. Mitigation Options in Perspective of Greenhouse Gas Emissions and Production on

European Dairy Farms

Marcia Stienezen, DLO WUR Livestock Research, The Netherlands

3.b.1. Adaptation to Climate Change in the global Livestock Sector and Mitigation Co-

benefits

Jens Heinke, ILRI, Kenya

11:30

3.a.2. A Sequential Participatory Design Approach to adapt Grassland-based Livestock

Systems to Climate Change

Marion Sautier, INRA, France

3.b.2. The Greenhouse Gas Mitigation Potential of the World’s Grazinglands

Alessandra Falcucci, FAO, Italy

11:45

3.a.3. Adoption of Farm-level Adaptation Strategies in Africa: a Review of recent

Research and an Adoption Index

Silvestre García de Jalón, Technical University of Madrid, Spain

3.b.3. Assessment of Uncertainties in Greenhouse Gas Emission Profiles of Livestock

Sectors in Europe, Latin America and Africa

Hans Kros, Alterra Wageningen UR, The Netherlands

12:00

3.a.4. Ex-ante Farm-Scale Analysis of the Impacts of Livestock Intensification on

Greenhouse Gas Emissions of Mixed Millet-Groundnut-Beef Cattle Systems in Senegal

Jonathan Vayssières, CIRAD, Senegal

3.b.4. Mitigation of GHG Emissions in Livestock Production Systems: assessing Potential from

Modeling Packages of Options at regional Level

Anne Mottet, FAO, Italy

12:15 RENACIMIENTO Room: LUNCH


Framing the Options: the national/regional Scales

Chair: Mark Howden

13:15

4.1. Ambitions versus Constraints: Some further economic Issues relevant to sustainable Intensification of Agriculture

Dominic Moran, SRUC, UK

13:50

4.2. Barriers and Opportunities influencing the Implementation of Climate Changes Adaptation and Mitigation Measures in Agriculture

Ana Iglesias, Technical University of Madrid, Spain

14:25

4.3. How to shorten Livestock Shadows? Practice and Opportunities of Policy Instruments in Latin America

Andreas Jenet, CATIE, Costa Rica



Policy and Economics

Chair: Mario Herrero


Social and behavioral Changes

Chair: Silvia Silvestri

15:45

4.a.1. Bioeconomic Assessment of Climate Change Impacts on Agrifood Markets: a global

Approach with a Focus on the EU

Maria Blanco, Technical University of Madrid, Spain

4.b.1. Intensification of Grassland and Forage Use; Driving Forces and Constraints

Peter Kuikman, Alterra Wageningen UR, The Netherlands

16:00

4.a.2. Preparing Australian Dairy Businesses for extreme and more variable Climates – a

Research Project integrating economic, biophysical and social Aspects

Matthew Harrison, Tasmanian Institute of Agriculture, Australia

4.b.2. Reduction of GHG Emissions by regional specific reduced Livestock Production resulting

from dietary Changes in the EU

Natasa Sikirica, Alterra Wageningen UR, The Netherlands

16:15

4.a.3. Climate Change systemic Adaptation and financial Value across the southern

Australian Livestock Industry

Afshin Ghahramani, CSIRO, Australia

4.b.3. What drives Pastoralists’ Vulnerability to global environmental Change? A qualitative

Meta-Analysis

Marta G. Rivera-Ferre, University of Vic – Central University of Catalonia, Spain

16:30

4.a.4. Potential Effects of Climate Change on the European Grassland Production: Impact

Assessment of far Future

Parisa Aghajanzadeh-Darzi, INRA, France

4.b.4. A Framework for targeting and scaling out Adaptation and Mitigation Measures in

agricultural Systems

An Notenbaert, CIAT, Kenya

16:45 Garden: Coffee break

MEDICI Room: PLENARY ROUND TABLE

Addressing Options and Policies

17:00 The Economics of Resilience to Climate Change in Sub-Saharan Africa

Cees de Haan, World Bank, USA

17:20

Round Table

Moderator: Cledwyn Thomas, EAAP, Italy

Antonia Andúgar, COPA-COGECA, Europe

Cees de Haan, World Bank

Anne Mottet, FAO, AGAL

Marina Piatto, Imaflora, Brasil


CONFERENCE ROOMS FLOOR PLANS

Mezzanine

Main Floor

Livestock, Climate Change and Food Security Conference - Madrid 2014 1

Table of contents

Monday 19 may, 2014 - Arrival and registration

Monday 19 may, 2014 - Welcome from UPM. Introducing the AnimalChange projectand FACCE JPI (J-F Soussana)Medici

Monday 19 may, 2014 - Plenary session 1: Setting the global scene: livestock futuresand food security under climate changeMediciChair Person : J.-F. Soussana

9:30 Livestock in the Frame: Exploring alternative Visions of Sustainability 13T. Garnett

10:05 Livestock in the XXIst Century: Alternative Futures 14P. Havlik, D. Leclere, H. Valin, M. Herrero, E. Schmid, J.-F. Soussana and M. Obersteiner

10:40 Climate Change Impacts and Vulnerability for Agriculture 16M. Howden and J.-F. Soussana

Monday 19 may, 2014 - Coffee break and poster viewing - Poster session 1Upper Lobby

11:15 Ammonia and Greenhouse Gases Emission from a Laying Hen House in the BasqueCountry

17

O. Alberdi, S. Calvet, M. Viguria Salazar, H. Arriaga, F. Estelles and P. Merino

11:15 Greenhouse Gas Balance of a tropical sylvo-pastoral Ecosystem in Senegal’s semi-aridRegion

18

M.H. Assouma, J. Vayssieres, M. Bernoux, P. Hiernaux and P. Lecomte

11:15 Biserrula pelecinus L. shows persistent low Methane Production under a continuousCulture Fermentation System (RUSITEC) when mixed with Trifolium subterraneum L.

19

B. Banik, Z. Durmic, W. Erskine, C. Revell and P. Vercoe

11:15 Substitution of Maize Silage with Sorghum Silages in Cow Ration: Effect on GlobalWarming Potential of Milk Production

20

L. Bava, S. Colombini, M. Zucali, A. Sandrucci and A. Tamburini

11:15 Dietary Information and Laboratory Tests for indirect Monitoring of Methane Emissionfrom Cattle in the Sahel

21

B. Bois, A. Ickowicz, T. Diop, M. Doreau, D. Morgavi and P. Lecomte

11:15 Greenhouse Gas Emissions from the Dairy Sector in Thailand 22K. Boonyanuwat

11:15 Variability in Methane Production from ruminal Fermentation of temperate ForageLegumes and Grasses

23

Z. Durmic, J. Vadhanabhuti, K. Lund, A. Humphries and P. Vercoe

11:15 Typology of Cattle Production in Brazil at the Municipality Level 24M.D.C.R. Fasiaben, L.G. Barioni, A.G. Maia, M.M.T.B.A. Almeida and O.C. Oliveira

2 Livestock, Climate Change and Food Security Conference - Madrid 2014

11:15 Control of Fermentation in the Gut of growing Pigs fed Maize-Soybean Diets containinghigh Levels of fibrous Co- Product Feeds

25

F. Fushai, M. Tekere, M. Masafu, F. Siebrits and C. Nherera

11:15 In Vitro Enteric Methane Production as affected by the Inclusion of cold-pressed Rape-seed Cake in the Concentrate Formulation

26

A. Garcia-Rodriguez, C. Pineda-Quiroga, N. Mandaluniz and R. Ruiz

11:15 Effect of improving Diet Quality by Feeding Supplements on Methane Emission in dif-ferent Production Systems of Beef Cattle in Brazil

27

J. Geraldo De Lima, A. Bannink, A. Van Den Pol Van Dasselaar, L.G. Barioni and P. Menezes Santos

11:15 The Effect of Feed Additives rich in Lipids on Methane Production Mitigation in DairyCattle

28

A. Guerouali

11:15 Methane Emission from artificially reared Lambs and Response to the fibrous Diet 29M.N. Haque, P. Khanal, M.O. Nielsen and J. Madsen

11:15 Effect of Crystalyx R© Supplementation on Performance and Methane Emissions of graz-ing Heifers

30

K. Hart, C. Faulkner, C. Lister and J. Newbold

11:15 The Potential to mitigate Greenhouse Gas Emissions in Finland by intensifying BeefProduction from Dairy Herds

31

P. Hietala, P. Bouquet and J. Juga

11:15 Associative Effect of Fermenting a low methanogenic Plant Biserrula pelecinus withselected Forages in vitro

32

M. Joy, Z. Durmic, J. Vadhanabhuti and P. Vercoe

11:15 Grazing Intensity and Methane Emissions by growing Heifers in the Pampa Rangeland- Southern Brazil

33

I. Machado Cezimbra, O.J.F. Bonnet, M. Ritzel Tischler, M. Moreira Santana, B. Araujo, V. SilvaDutra, A. Fialho Heguaburu, J. Victor Savian, L. Barreto Mass, M. Moura Kohmann, T. CristinaMoraes Genro, A. Berndt, C. Bayer and P. Cesar De Faccio Carvalho

11:15 Methane Emissions from Nellore Heifers under integrated Crop Livestock Forest Systems 34R.A. Mandarino, L.G.R. Pereira, F.A. Barbosa, D.C. Santos, L. Vilela, G.D.A. Maciel, L.G. Barioniand R. Guimaraes Junior

11:15 Effect of Feeding Practices in different Production Stages on GHG Emissions in LatxaDairy Sheep

35

C. Pineda-Quiroga, N. Mandaluniz, A. Garcia-Rodriguez and R. Ruiz

11:15 The Effect of concentrate Supplementation on Methane Emission Intensity of Cattlegrazing tropical Pastures in the dry Season

36

S. Raposo De Medeiros, T. Zanett Albertini, L.G. Barioni, A. Berndt, R.D.C. Gomes, C.T. Marino,C.V. Andrade and M.C. Freua

11:15 Modeling enteric Methane Emission from Beef Cattle in Brazil: a proposed Equationperformed by principal Component Analysis and mixed Modeling multiple Regression

37

S. Raposo De Medeiros, L.G. Barioni, A. Berndt, M. Caslenani Freua, T. Zanett Albertini, C. CostaJunior and G.B. Feltrin

11:15 Dietary Nitrate but not Linseed Oil decreases Methane Emissions in two Studies withlactating Dairy Cows

38

J. Veneman, S. Muetzel, K. Hart, C. Faulkner, J. Moorby, G. Molano, H. Perdok, J. Newbold and J.Newbold

11:15 Air Emissions from Biogas Digester Effluent stored at different Depths 39Y. Wang, H. Dong, Z. Zhu, T. Li, K. Mei and H. Xin


11:15 Greenhouse Gas and Ammonia Emissions from Ceramsite covered compared with un-covered Dairy Slurry Storage

40

Z. Zhu, H. Dong, C. Liu and W. Huang

Monday 19 may, 2014 - Parallel session 1a: Climate Change ImpactsMedici IChair Person : P. Kuikman

12:15 What is the Impact of closing the global Gap in Pasture Performance on Land Use forFood and Energy in a Carbon and Land-constrained World?

41

J. Sheehan, E. Sheehan, A. Morishige, L. Lynd, N. Mueller, J. Gerber, J. Foley, G. Martha, J. Rocha,L. Cortez and C. West

12:30 Reconciling the Impacts of Extreme Rainfall Events and Extended Drought on Pastureand Livestock Production: a New Method for Generating Synthetic Climate Sequences

42

M. Harrison, B. Cullen and R. Rawnsley

12:45 MACSUR liveM - A Knowledge-Hub for integrated Modelling of Climate Change Im-pacts on Livestock Production Systems: Lessons learned and future Developments

43

E.R. Saetnan, R.P. Kipling, N.D. Scollan, D.J. Bartley, G. Bellocchi, N.J. Hutchings, T. Dalgaardand A. Van Den Pol Van Dasselaar

13:00 The Influence of GHG Metrics on Quantification of Agricultural Emissions and Mitiga-tion Options

44

A. Reisinger and S. Ledgard

Monday 19 may, 2014 - Parallel session 1b: Mitigation options for livestockMedici II&IIIChair Person : H. Clark

12:15 The Influence of Fat Supplement and Roughage Type on Feces Composition and MethaneYield from Dairy Cows

45

V. Moset Hernandez, H.B. Moller, M. Brask, M.R. Weisbjerg and P. Lund

12:30 Nitrous Oxide Emission partly alleviates the Methane Mitigation Effect of Nitrate Intakeby dairy Cattle

46

S.O. Petersen, A.L.F. Hellwing, M. Brask, O. Hojberg, M. Poulsen, Z. Zhu and P. Lund

12:45 Ammonia and Greenhouse Gases Emission from Slurry Storage with impermeable Coverand Landspreading of Cattle Slurry

47

M. Viguria Salazar, A. Sanz-Cobena, D.M. Lopez, H. Arriaga and P. Merino

13:00 Methane Emission by Beef Steers on natural Grassland in Southern Brazil 48T. Genro, B. Faria, M. Da Silva, G. Amaral, I. Cezimbra, J. Savian, A. Berndt, C. Bayer and P.Carvalho

Monday 19 may, 2014 - LunchRenacimiento


Monday 19 may, 2014 - Plenary session 2: Understanding the technical potential formitigation and adaptationMediciChair Person : P. Smith

14:15 IPCC WGIII Findings on Animal Agriculture Mitigation Potential 50P. Smith

14:50 The Complexity of System Boundaries when it comes to Mitigation Measures 51C. Cederberg and M. Persson

15:25 Climate Change and Livestock: Impacts and Adaptation 53J.-F. Soussana

Monday 19 may, 2014 - Coffee break and poster viewing - Poster session 2Upper Lobby

16:00 Determinants of Livestock Farmers’ Perception of future Droughts and Adoption ofmitigating Plans

55

M. Rakgase and D. Norris

16:00 Important Differences in Yield Responses to Drought among four functional Types ofSpecies and across three European Sites

56

D. Hofer, M. Suter, N. Hoekstra, E. Haughey, J. Finn, N. Buchmann and A. Luscher

16:00 Effect of Manure Treatment on Greenhouse Gas Emissions from Agriculture. The Caseof the Netherlands.

57

J. Mosquera Losada, P. Hoeksma, R. Melse and N. Verdoes

16:00 Alternative Techniques to appraise Adaptation Options in the Livestock Sector: arerobust Methods the Way forward?

58

R. Dittrich

16:00 Dietary Fibre in Pig’s Diets: Effects on Greenhouse Gas Emissions from Slurry Storageto Field Application

59

F. Estelles, A. Sanz-Cobena, A. Beccaccia, W. Antezana, M. Cambra-Lopez, P. Ferrer, A. Cerisuelo,P. Garcia-Rebollar, A. Vallejo, C. De Blas and S. Calvet

16:00 Effects of simulated Drought on Species Composition and Biomass Yield of semi-aridGrassland, South Africa

60

D. Gemiyo, A. Hassen and E. Tesfamariam

16:00 In Vitro Evaluation of tropical Forages from the Sahel region of Senegal for theirmethanogenic Potential

61

A. Baccouche, D. Morgavi, B. Bois, L. Genestoux, P. Lecomte, A. Ickowicz, T. Diop and M. Doreau

16:00 Seasonal Variation in Composition of Cow Milk for Grana Padano Cheese Production 62A. Vitali, L. Bertocchi, N. Lacetera, A. Nardone and U. Bernabucci

16:00 Effect of tropical Plants containing condensed Tannins on Fermentation, Digestibilityand Methane Production in Sheep

63

M. Rira, D. Morgavi, H. Archimede, C. Marie-Magdeleine, L. Genestoux, H. Bousseboua and M.Doreau

16:00 Evaluation of Crop Models SwbSci and STICS in South Africa 64E. Tesfamariam, G. Bellocchi, F. Ruget and A. Hassen

16:00 Effect of Tannin and Species Variation on in vitro Digestibility, Gas and Methane Pro-duction Characteristics of tropical Browse Plants

65

B.S. Gemeda and A. Hassen


16:00 Measured and modelled climatic Variability Effects on Ecosystem Carbon Exchange intwo grazed temperate Grasslands with contrasting Drainage Regimes

66

O. Ni Choncubhair, J. Humphreys and G. Lanigan

16:00 Influence of Addition of Corn on in vitro Gas Production of two Legumes Forages 67S. Lobon, F. Molino, M.A. Legua, M.P. Eseverri, M.A. Cespedes and M. Joy

16:00 Reintroducing Livestock to improve Village-Scale agricultural Productivity, NutrientBalance and Nutrient Use Efficiency: the Case of Senegalese Groundnut Basin

68

E. Audouin, M. Odru, J. Vayssieres, D. Masse and P. Lecomte

16:00 Carbon and Energy Balance in natural and improved Grasslands of an extensive Live-stock Ranch in the humid Tropics of central Africa (RDC)

69

P. Lecomte, A. Duclos, X. Juanes, S. Ndao, P. Decrem and M. Vigne

16:00 Coupled Effect of agricultural Practices and Climate on Carbon Storage in two contrastedpermanent tropical Pastures.

70

V. Blanfort, C. Stahl, K. Klumpp, R. Falcimagne, C. Picon-Cochard, P. Lecomte, J.-F. Soussana andS. Fontaine

16:00 Adaptation and Mitigation Options offered by ”Biodiverse Legume rich sown perma-nent Pastures” for the sustainable Improvement of Mediterranean Animal ProductionSystems facing Climate Change

71

D. Crespo and A. Barradas

16:00 Evolution of the Carbon and Soil Nitrogen Content in a Northern Senegal grazed Areabetween 1962 - 2011

72

T. Diop, O. Ndiaye, I. Dieme, I. Toure and M. Diene

16:00 Effect of Sprinkling and Ventilation on Performance of Heat stressed Awassi Sheep 73S. Abi Saab, N. Abdel Nour, I. Lahoud and P.Y. Aad

16:00 Emission Intensities by Holstein and Holstein x Jersey crossbreed lactating Cows in twoBrazilian grazing Systems

74

A. Berndt, A.P. Lemes, T.C. Alves, A.D.F. Pedroso, L.S. Sakamoto, L.G. Barioni and P.A. Oliveira

16:00 Effect of Herbage Intake on Methane Emission by grazing Sheep 75M. Moreira Santana, J. Victor Savian, A. Barth Neto, B. De Araujo Silva, P. Cardozo Vieira, M.Ritzel Tischler, R. Marinho Tres Schons, I. Machado Cezimbra, T. Cristina Moraes Genro, A. Berndt,C. Bayer and P.C. De Faccio Carvalho

16:00 Elevated CO2 overcomes the short-term Effect of a future Heat and Drought ClimateExtreme in a temperate Grassland

76

C. Picon-Cochard, J. Roy, A. Augusti, M.-L. Benot, D. Landais, C. Piel, C. Escape, O. Ravel, M.Bahn, F. Volaire and J.-F. Soussana

16:00 Developing a Nationally Appropriate Mitigation Measure from the Greenhouse GasAbatement Potential from Livestock Production in the Brazilian Cerrado

77

R. De Oliveira Silva, L.G. Barioni, T. Zanett Albertini, V. Eory, C.F.E. Topp, F. A. Fernandes andD. Moran

Monday 19 may, 2014 - Parallel session 2a: Mitigation options for grasslandsMedici IChair Person : F. O’Mara

17:00 Gain of Nitrogen from Legumes in Grassland is robust over a wide Range of MixtureLegume Proportion and Environmental Conditions

78

M. Suter, J. Connolly, J. Finn, R. Loges, L. Kirwan, T. Sebastia and A. Luscher

17:15 Carbon Sink Activity of Grasslands May Be Stronger under Grazing Than under Mow-ing: Results from a Paired Eddy Flux Towers Experiment

79

K. Pinter, J. Balogh, P. Koncz, D. Hidy, D. Cserhalmi, M. Papp, S. Foti, Z. Nagy and A. Chabbi


17:30 Mitigating GHG Emissions from Ruminant Livestock Systems through the Managementof Carbon Sequestration in Grasslands

80

K. Klumpp and J.-F. Soussana

17:45 Capacity of tropical permanent Pastures to restore Soil Carbon Storage after Deforesta-tion of the Amazonian Forest

81

V. Blanfort, C. Stahl, M. Grise, L. Blanc, V. Freycon, C. Picon-Cochard, K. Klumpp, D. Bonal, P.Lecomte, J.-F. Soussana and S. Fontaine

Monday 19 may, 2014 - Parallel session 2b: Adaptation options for livestock and grass-landsMedici II&IIIChair Person : A. Jenet

17:00 Principles of Climate Change Adaptation in Livestock Systems 82J.E. Olesen and C.F.E. Topp

17:15 Impact of Heat Stress on Production in Holstein Cattle in four EU Regions. SelectionTools.

83

M.J. Carabano, H. Hammami, B. Logar, M.-L. Vanrobays, C. Diaz and N. Gengler

17:30 Potential Use of Forage Legume Intercropping Technologies to mitigate and adapt toClimate Change Impacts on mixed Crop- Livestock Systems in Africa

84

A. Hassen, D.G. Talore, B.S. Gemeda, M. Friend and E. Tesfamariam

17:45 Livestock and Climate Change in East Africa: exploring Combinations of Adaptationand Mitigation Options

85

S. Silvestri, J. Heinke, A. Mottet, A. Falcucci and S. Chesterman

Monday 19 may, 2014 - Conference DinnerRenacimiento

Tuesday 20 may, 2014 - Plenary session 3: Framing the options: the farm and landscapescalesMediciChair Person : J. Olesen

8:45 Integrating Adaptation and Mitigation in extensive grazing Systems 87M. Herrero, P. Thornton, A. Ash, P. Havlik, R. Conant and A. Notenbaert

9:20 Integrating Adaptation to and Mitigation of Climate Change in intensive Animal Pro-duction Systems

88

F. O Mara, J.E. Olesen, G. Lanigan and A. Van Den Pol Van Dasselaar

9:55 Integrating Adaptation and Mitigation in Smallholder Farming Systems: A Focus onsub-Saharan Africa

89

K. Descheemaeker, K. Giller, S. Oosting, P. Masikati and S. Homann-Kee Tui


Tuesday 20 may, 2014 - Coffee break and poster viewing - Poster session 3Upper Lobby

10:30 A Novel Tool to Assess the N2O, CH4 and NH3 Mitigation Potential of environmentalTechniques in intensive Livestock Operations

90

M. Aguilar Ramirez, H. Arriaga, P. Dupard, S. Lalor, R. Fragoso, O. Pahl, A. Abaigar, L. Cordovin,M. Viguria Salazar, M. Boyle, G. Lanigan, L. Loyon and P. Merino

10:30 Value of process-based Models compared to Tier 2 Adoption to achieve case-specificGreenhouse Gas Emissions in Dairy Production Systems

91

A. Bannink, G. Lanigan, N.J. Hutchings, G. Bellocchi and A. Van Den Pol Van Dasselaar

10:30 Bayesian Calibration of the Pasture Simulation Model (PaSim) to simulate Emissionsfrom long-term Grassland Sites: a European Perspective

92

G. Bellocchi and H. Ben Touhami

10:30 Energy and economic Analysis of Inclusion of integrated Crop-Livestock-Forest Systemin Cattle fattening Farm in Brazilian Amazon

93

A. Bendahan, M. Vigne, R.D. Medeiros, M.-G. Piketty, R. Poccard-Chapuis and J.F. Tourrand

10:30 Characterising the fractal Nature of Precipitation across South Africa 94J. Botai, A. Hassen and E. Tasfamariam

10:30 Resilience and Vulnerability of Beef Cattle Production in the Southern Great Plainsunder changing Climate, Land Use and Markets: Consumer Focus Groups

95

B. Brown, S. Wilburn and J. Hermann

10:30 Evaluating the new ORDHIDEE-GM (Grassland Management) Model to tropical Areain Brazil

96

P.P. Coltri, N. Viovy, J. Chang, L.C. Araujo, L.G. Barioni, P.M. Santos and J.R. Pezzopanne

10:30 Impact of Extreme climate events on Livestock Productivity in South Africa 97L.K. Debusho, T.A. Diriba, J. Botai and A. Hassen

10:30 Analysis of extreme Climate Events and their Impact on Maize and Wheat Productionin South Africa

98

T.A. Diriba

10:30 Pasture Management and Livestock Genotype Interventions to improve whole FarmProductivity and reduce Greenhouse Gas Emissions Intensities

99

M. Harrison, K. Christie, R. Rawnsley and R. Eckard

10:30 Evaluating Mobility in Mediterranean Sheep farming Systems regarding Mitigation toclimatic Change

100

J. Lasseur, A. Vigan, M. Benoit, C. Dutilly, M. Eugene, F. Mouillot and M. Meuret

10:30 A Model of the Dynamics of Cattle Systems Types to study Greenhouse Gases Mitigationin the Brazilian Conditions

101

J.M.M.A.P. Moreira, L.G. Barioni, M.D.C.R. Fasiaben, A.F. Oliveira and R.D.O. Silva

10:30 Auditing the Carbon Footprint of Milk from commercial Irish grass-based Dairy Farms 102D. O’brien, P. Brennan, E. Ruane, J. Humphreys and L. Shalloo

10:30 Grazing Effects on Grassland Productivity - Linking Livestock Production to GrassYields

103

S. Rolinski, I. Weindl and J. Heinke

10:30 Testing CORDEX downscaled Weather Data against historical Data to predict WeepingLovegrass (Eragrostis curvula) Hay Yield in selected agro-ecological Zones of SouthAfrica

104

E. Tesfamariam, J. Botai and A. Hassen


10:30 Evaluation of Regional Agri-Environmetal Policy on Livestock Greenhouse Gas Emis-sions

105

A. Vitali, S. Lo Presti, T.M.I. Schipani, A. Nardone and N. Lacetera

10:30 Excellent Dairy Farming Profile 106M. Zucali, L. Bava, M. Guerci, A. Tamburini and A. Sandrucci

Tuesday 20 may, 2014 - Parallel session 3a: The farm scaleMedici IChair Person : K. Beauchemin

11:15 Mitigation Options in Perspective of Greenhouse Gas Emissions and Production on Eu-ropean Dairy Farms

107

M. Stienezen, D. O’brien, E. Cutullic, P. Faverdin, J.-L. Fiorelli, G. Holshof, N.J. Hutchings, J.E.Olesen, H. Perdok, L. Shalloo and C.F.E. Topp

11:30 A Sequential Participatory Design Approach to adapt Grassland-based Livestock Sys-tems to Climate Change

108

M. Sautier, M. Piquet, M. Duru and R. Martin-Clouaire

11:45 Adoption of Farm-level Adaptation Strategies in Africa: a Review of recent Researchand an Adoption Index

109

S. Garcia De Jalon and A. Iglesias

12:00 Ex-ante Farm-Scale Analysis of the Impacts of Livestock Intensification on GreenhouseGas Emissions of Mixed Millet- Groundnut-Beef Cattle Systems in Senegal

110

C. Birnholz, J. Vayssieres, N.J. Hutchings and P. Lecomte

Tuesday 20 may, 2014 - Parallel session 3b: The landscape and regional scaleMedici II&IIIChair Person : A. Hassen

11:15 Adaptation to Climate Change in the global Livestock Sector and Mitigation Co-benefits 111J. Heinke, S. Silvestri and A. Mottet

11:30 The Greenhouse Gas Mitigation Potential of the World’s Grazinglands 112A. Falcucci, B. Henderson, R. Conant, T. Hilinski, D. Ojima, M. Salvatore and P. Gerber

11:45 Assessment of Uncertainties in Greenhouse Gas Emission Profiles of Livestock Sectorsin Europe, Latin America and Africa

113

H. Kros, B. Zhu, J.P. Lesschen, P. Kuikman and W. De Vries

12:00 Mitigation of GHG Emissions in Livestock Production Systems: assessing Potential fromModeling Packages of Options at regional Level

114

A. Mottet, B. Henderson, C. Opio, A. Falcucci, G. Tempio and P. Gerber

Tuesday 20 may, 2014 - LunchRenacimiento


Tuesday 20 may, 2014 - Plenary session 4: Framing the options: the national/regionalscalesMediciChair Person : M. Howden

13:15 Ambitions versus Constraints: Some further Economic Issues relevant to sustainableIntensification of Agriculture.

116

D. Moran

13:50 Barriers and Opportunities influencing the Implementation of Climate Changes Adap-tation and Mitigation Measures in Agriculture

117

A. Iglesias

14:25 How to shorten Livestock Shadows? Practice and Opportunities of Policy Instrumentsin Latin America

118

A. Jenet

Tuesday 20 may, 2014 - Coffee break and poster viewing - Poster session 4Upper Lobby

15:00 Livestock Production: Vulnerability to Population Growth and Climate Change 119O. Godber and R. Wall

15:00 Sustainable Food Production Chain for sustainable Ecosystems 120M. Yossifov

15:00 Greenhouse Gas Emissions from a Chinese Dairy Farm based on LCA 121X. Wang, D. Lian and X. Wang

15:00 Farmer Understanding of environmental Risks from outwintered Cattle Systems 122B. Andrew, H. McCalman and S. Buckingham

15:00 Environmental Competences for Sustainability of small Ruminant Systems in NorthernSpain

123

I. Batalla, M. Pinto, P. Eguinoa, J.M. Intxaurrandieta, J.M. Mangado and O. Del Hierro

15:00 The Opportunities and Challenges in the Implementation of Beef Sector Policy in In-donesia

124

S. Gayatri and M. Vaarst

15:00 Legumes: Cost-Effective Greenhouse Gas Abatement in European Regions 125V. Eory, B. Dequiedt, J. Maire, C.F.E. Topp, R.M. Rees, P. Zander, M. Reckling and N. Shlaefke

15:00 Quantifying the Greenhouse Gas Mitigation Effect of intervening against bovine Try-panosomosis in Eastern Africa

126

M. Macleod, T. Robinson, W. Wint and A. Shaw

15:00 Sustainable Intensification of Crop Production in agro- sylvo-pastoral Territories throughthe Expansion of Cattle Herds in Western Africa

127

A. Vigan, J. Vayssieres, D. Masse, R. Manlay, M. Sissokho and P. Lecomte

15:00 Implementation of Mitigation and Adaptation Measures in the Farm-scale Model Far-mAC

128

N.J. Hutchings, M. Jørgensen and J. Vejlin

15:00 Global Assessment of marginal Costs for the Abatement of Ruminant GHG Emissions 129B. Henderson, A. Falcucci, A. Mottet and P. Gerber

15:00 Sustainable Livelihoods in Range Management: adaptive Livelihood Strategies for FoodSecurity

130

H. Khedri Gharibvand, H. Azadi and F. Witlox


15:00 The Importance of economical Analysis to Studies that foresee the Measurement ofGreenhouse Gases Effects in Cattle-Raising in the Pampa Biome in Brazil

131

J.L.S.D. Santos and M.A.K. Lucas

15:00 New Policies for Adaptation to Climate Change of Livestock on Grasslands in Uruguay 132D. Sancho and W. Oyhantcabal

15:00 Comparing the Cost Effectiveness of GHG Mitigation Options on different Scottish DairyFarm Groups

133

S. Shrestha, V. Eory and M. Macleod

15:00 Conserving indigenous Livestock Breeds for Adaptation to Climate Change and FoodSecurity of the small Holders in the Hindu Kush Mountains of Northern Pakistan

134

I.U. Rahim, H. Rueff and D. Maselli

Tuesday 20 may, 2014 - Parallel session 4a: Policy and economicsMedici IChair Person : M. Herrero

15:45 Bioeconomic Assessment of Climate Change Impacts on Agrifood Markets: a globalApproach with a Focus on the EU

135

M. Blanco, F. Ramos, B. Van Doorslaer, D. Fumagalli and F.J. Fernandez

16:00 Preparing Australian Dairy Businesses for extreme and more variable Climates - a Re-search Project integrating economic, biophysical and social Aspects

136

G. Hayman, M. Harrison, B. Cullen, M. Ayre, D. Armstrong, W. Mason, R. Rawnsley, R. Nettle, R.Beilin, S. Waller and C. Phelps

16:15 Climate Change systemic Adaptation and financial Value across the southern AustralianLivestock Industry

137

A. Ghahramani, A. Moore, S. Crimp and M. Howden

16:30 Potential Effects of Climate Change on the European Grassland Production : ImpactAssessment of far Future

138

P. Aghajanzadeh-Darzi, S. Laperche, R. Martin and P.-A. Jayet

Tuesday 20 may, 2014 - Parallel session 4b: Social and behavioral changesMedici II&IIIChair Person : S. Silvestri

15:45 Intensification of Grassland and Forage Use; Driving Forces and Constraints 139O. Oenema, P. Kuikman, C. Deklein and M. Alfaro

16:00 Reduction of GHG Emissions by regional specific reduced Livestock Production resultingfrom dietary Changes in the EU

140

J.P. Lesschen, P. Kuikman, N. Sikirica, H. Westhoek and O. Oenema

16:15 What drives Pastoralists’ Vulnerability to global environmental Change? A qualitativeMeta-Analysis

141

F. Lopez-I-Gelats and M.G. Rivera-Ferre

16:30 A Framework for targeting and scaling out Adaptation and Mitigation Measures inagricultural Systems

142

A. Notenbaert, M. Herrero, S. Silvestri and C. Pfeifer

Tuesday 20 may, 2014 - Coffee breakGarden


Tuesday 20 may, 2014 - Plenary round table: addressing options and policiesMediciChair Person : C. Thomas

18:00 The Economics of Resilience to Climate Change in Sub-Saharan Africa 143C. De Haan

Tuesday 20 may, 2014 - Concluding remarksMedici


Plenary session 1: Setting the global scene: livestock futuresand food security under climate change


Mon. 9:30 Medici Plenary session 1: Setting the global scene: livestock futures and food security under climate change

Livestock in the Frame: Exploring alternative Visions of Sustainability

T. Garnett

University of Oxford, Environmental Change Institute, Food Climate Research Network, 4 Evershot Road, N4 3BBLondon, UK

[email protected]

The urgency and scale of the food-sustainability challenge is well recognised and has now been exhaustively analysed.Everyone agrees that the food system should be sustainable - that the environmental problems it faces and generatesshould be addressed and that people should have enough to eat. However, stakeholders often have very different visionsof what sustainability actually looks like. These differences reflect their beliefs about how far they feel the politicaleconomy status quo can and should be changed, the policy approaches they judge to be feasible or legitimate, howthey prioritise among competing social, economic and environmental objectives, and more fundamentally, on differentvalues and ideologies about what constitutes ’a good life’. Livestock sit at the heart of the debate about sustainability,attracts the attention of multiple stakeholders with different interests and as such tends to arouse particularly vocaland often emotive responses.This paper seeks to understand how these different stakeholders approach the challenge of food system sustainabil-ity, focusing particularly on the livestock question. Analysing the positions of diverse actors - the food industry,environmental, animal welfare and international NGOs, and the policy community - it considers the knowledge andperspectives they bring to the problem and to the possible solutions, and the values that underpin these. It articulatesfour normative scenarios based on a simplified representation of their positions and explores what their respectiveworlds would look like were these different visions to be realised and followed through to their logical conclusions. Inparticular it considers how the following key issues would be conceptualised, navigated and addressed: GHG mitigationand land use, food security and human nutrition, animal welfare, economic growth and development, and notions ofpersonal responsibility and freedom.It is argued that each of these perspectives has something useful to contribute to addressing the food system challengeand there can also be overlaps between perspectives in the least expected places. However one approach currentlydominates at the expense of others and this dominance closes down policy consideration of alternative options. Thechallenges we face demand imaginative and integrative solutions and as such we need to look beyond mainstreamperspectives and analysis. Ultimately there is a need for more open and explicit consideration of how values andideologies shape the food system discourse, and the solutions that are proposed. An essential part of this will bea more honest recognition that science is never just about the ’facts’ but about how stakeholders select, frame andinterpret the evidence to accord with their particular values.


Mon. 10:05 MediciPlenary session 1: Setting the global scene: livestock futures and food security under climate change

Livestock in the XXIst Century: Alternative Futures

P. Havlika, D. Leclerea, H. Valina, M. Herrerob, E. Schmidc, J.-F. Soussanad and M. Obersteinera

aIIASA - International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg, Austria; bCSIRO,Box 2583, 4001 Brisbane, Australia; cUniversity of Natural Resources and Life Sciences, Feistmantelstraße 4, 1180

Vienna, Austria; dINRA UR 874, Grassland Ecosystem Research, 63100 Clermont Ferrand, [email protected]

Livestock are the source of 33% of the protein in human diets and continued population and economic growth coulddouble the total demand for livestock products by 2050 (Alexandratos and Bruinsma, 2012). 30% of the global landarea is used for livestock rearing already now (Steinfeld et al., 2006), meaning that substantial efficiency gains arerequired to satisfy the rising demand within the physical constraints related to land, and to some extent water (Doreauet al., 2012). At the same time, global mean surface temperature is projected to rise by 0.4-2.6◦C until 2050, andthe contrast in precipitations between wet and dry regions and wet and dry seasons will also increase according tothe IPCC 5th Assessment Report. The increased demand and potentially squeezed supply could represent a majorchallenge for the 21st century.The distant future is however full of uncertainties and one way to deal with them is to explore a multitude of plausiblescenarios. Here we adhere to the basic logic of the new framework for developing climate change scenarios whichdelineates the possible future space along two dimensions: i) socioeconomic development, and ii) level of climatechange (Vuuren et al., 2014). The space of plausible future socioeconomic developments spreads in this frameworkthrough five Shared Socioeconomic Pathways (SSPs), which provide quantitative information about future populationand economic development, and narratives with semi-quantitative elements about different sectors including agricultureand land use. The spread of future climate developments is covered by four alternative Representative ConcentrationPathways (RCPs), which are further input in general circulation models. In the framework of this study, we haveelaborated three SSPs for the agricultural sector in general, and for the livestock sector in particular, and we havecombined these socioeconomic scenarios with the strongest climate change scenario resulting from RCP8.5. Outputsfrom five general circulation models were considered and alternative assumptions on the CO2 fertilization effect weretested in the crop and grass models in order to cover also these important sources of uncertainty.The analysis is carried out using the global partial equilibrium agricultural and forestry sector model GLOBIOM(Havlık et al., 2014). The model represents agricultural production at a spatial resolution going down to 5 x 5minutes of arc. Crop and grassland productivities are estimated by means of biophysical process based models, likeEPIC (Williams, 1995), at this resolution for current and future climate scenarios. Livestock representation follows asimplified version of the Sere and Steinfeld (1996) production system classification. This approach recognizes differencesin feed base and productivities between grazing and mixed crop-livestock production systems across different agro-ecological zones (arid, humid, temperate/highlands). Recently published global livestock production systems dataset(Herrero et al., 2013) has been used to parameterize the model.Our results show that under business as usual (SSP2) without climate change, the livestock sector would be ableto satisfy future meat and milk demand without substantial increases in market prices by 2050, however still withexpanding crop and grassland at the expense of natural habitats like tropical forests. The land use change andGHG emissions from the livestock sector would be lower if a share of the ruminants reared in developing regionsin the rather extensive grazing systems would be converted to mixed crop-livestock systems. The overall social andenvironmental impacts would be more positive under the scenario SSP1, where a shift towards more sustainable dietsin the developed world, and fast technological change, would allow satisfying the future needs with limited naturalresources. The worst socio-economic scenario is SSP3, where sustained demand and slow technological progress wouldlead to high commodity prices, land and water use, and also the highest GHG emissions. Climate change impacts varysubstantially depending on the general circulation model and on the assumption about the CO2 fertilization effect buttheir impacts are globally limited to +/-10% deviations from the values projected without climate change by 2050.An interesting aspect of the climate change impacts is that they seem to favor the grass productivities over the crop


productivities, which under some scenarios would lead in particular in Sub-Saharan Africa to a change in the trendand a relative increase in ruminants reared in the grazing systems.References:Alexandratos, N., Bruinsma, J., 2012. World Agriculture Towards 2030/2050: The 2012 Revision. ESA WorkingPaper. Food and Agriculture Organization of the United Nations (FAO), Rome.Doreau, M., Corson, M.S., Wiedemann, S.G., 2012. Water use by livestock: A global perspective for a regional issue?Animal Frontiers 2, 9-16.Havlık, P., Valin, H., Herrero, M., Obersteiner, M., Schmid, E., Rufino, M.C., Mosnier, A., Thornton, P.K., Bottcher,H., Conant, R.T., Frank, S., Fritz, S., Fuss, S., Kraxner, F., Notenbaert, A., 2014. Climate change mitigation throughlivestock system transitions. Proceedings of the National Academy of Sciences.Herrero, M., Havlık, P., Valin, H., Notenbaert, A., Rufino, M.C., Thornton, P.K., Blummel, M., Weiss, F., Grace, D.,Obersteiner, M., 2013. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestocksystems. Proceedings of the National Academy of Sciences.Sere, C., Steinfeld, H., 1996. World Livestock Production Systems: Current status, issues and trends. FAO AnimalProduction And Health Paper FAO, Rome.Vuuren, D., Kriegler, E., O’Neill, B., Ebi, K., Riahi, K., Carter, T., Edmonds, J., Hallegatte, S., Kram, T., Mathur, R.,Winkler, H., 2014. A new scenario framework for Climate Change Research: scenario matrix architecture. ClimaticChange 122, 373-386.Williams, J.R., 1995. The EPIC model. In: Singh, V.P. (Ed.), Computer Models of Watershed Hydrology. WaterResources Publications, Highlands Ranch, Colorado, pp. 909-1000.


Mon. 10:40 MediciPlenary session 1: Setting the global scene: livestock futures and food security under climate change

Climate Change Impacts and Vulnerability for Agriculture

M. Howdena and J.-F. Soussanab

aCSIRO, Black Mountain Laboratories, Black Mountain, ACT, Clunies Ross Street, 2601 Canberra, Australia;bINRA UR 874, Grassland Ecosystem Research, 63100 Clermont Ferrand, France

[email protected]

A major activity in agriculture is matching technologies, practices and farm resources to the prevailing environmentin which farm decisions are made: whether this environment is climatic, economic, market or regulatory. To not dothis will result in either underperformance or incurring increased risk. The accumulating evidence that the climate ischanging at global to local scales, and that much more change is likely, rationally means that agricultural decisionsand technologies should also change. Of particular concern are extreme climate events which can impact on livestocksystems even though they are inherently more buffered than cropping systems.We summarise and critically analyse recent literature on climate impacts and vulnerability for livestock systems ad-dressing productivity and production risk, economics, land-use change, pest and diseases, net greenhouse gas emissions,adaptive capacity, vulnerability and psychological status. In doing so, we document the asymmetry between the lit-erature dealing with livestock systems and that on cropping systems and the implications of this for food securitystudies. In the process, we also identify some research gaps. We address briefly possible adaptations and the barriersto these, looking at evidence for adoption of practices and strategies that are aligned with climate-change even if notattributed to this.


Upper Lobby Coffee break and poster viewing - Poster session 1

Ammonia and Greenhouse Gases Emission from a Laying Hen House in the Basque Country

O. Alberdia, S. Calvetb, M. Viguria Salazarc, H. Arriagac, F. Estellesb and P. Merinoc

aLarrabe Oilotegia S.A.T., c/ Elexalde s/n, 48113 Gamiz-Fika Bizkaia, Spain; bUniversitat Politecnica de Valencia,Camino de Vera s/n, 46022 Valencia, Spain; cNEIKER-Tecnalia, Berreaga 1, parcela 812, E-48160 Derio, Spain

[email protected]

Ammonia (NH3) is the main pollutant gas associated with intensively managed laying hen houses. Nonetheless, layinghen houses may also contribute to greenhouse gas (GHG) emissions through methane (CH4) and nitrous oxide (N2O)losses. In EU, most of NH3 studies have been carried out in Central and Northern countries. However, scarce datasetexists either on NH3 or GHG losses in Southern Europe where climatic conditions are warmer. The objective wasto study the seasonal NH3 and GHG emission pattern in an intensively managed laying hen facility in the BasqueCountry (northern Spain).Approximately 52,000 Lohmann-Brown hens were housed in a commercial laying hen unit in a vertical tiered cagesystem adapted to Directive 1999/74/EC. Manure removal was conducted through belt system in which manure wasremoved 2-3 times per week. Gas concentrations (NH3, N2O, CH4, CO2) and ventilation rates were continuouslymonitored from April 2012 to September 2013. Gas concentrations were measured by a photoacoustic infrared gasanalyser (INNOVA 1412). Exhaust air samples were taken from 8 fans whereas inlet samples were taken from 4outdoor points. The ventilation rate was calculated taking into account the mean percentage of activation of eachfan recorded every 5 minutes. Ventilation rates ranged between 1.8 m3 h−1 hen−1 and 5.5 m3 h−1 hen−1 in winterand summer respectively. Gas emission was determined by multiplying the ventilation rate and the difference betweenexhaust and outdoor gas concentrations.The pattern of CO2, CH4 and N2O emissions were not affected by seasonality. The higher differences between winterand summer were observed for NH3 emission, with a 62.4 % higher NH3 emission in summer, although the highvariability found prevents us from establishing a clear effect of seasonality on these emissions. This was probably dueto other factors affecting NH3 emissions such as day-associated variation and manure management.This work has been funded by BATFARM Interreg-Atlantic Area Project (2009-1/071) entitled ”Evaluation of bestavailable techniques to decrease air and water pollution in animal farms”. Oier Alberdi holds a grant from IKERTUprogram of training and promotion of research of the Department of Economic Development and Competitivenessof the Basque Government. The authors are especially grateful to Larrabe Oilotegia S.A.T. that provided livestockinfrastructure.



Greenhouse Gas Balance of a tropical sylvo-pastoral Ecosystem in Senegal’s semi-arid Region

M.H. Assoumaa, J. Vayssieresa,b, M. Bernouxc, P. Hiernauxd and P. Lecomtee,f

aCIRAD, 37 av. Jean XXIII, Dakar Etoile, BP 6189 Dakar, Senegal; bCIRAD - Umr Selmet, Campus ISRA/IRD deBel Air, Route des hydrocarbures BP 1386, 18524 Dakar, Senegal; cIRD - Umr Eco&Sols, SupAgro, 2 place Viala,34060 Montpellier, France; dCNRS - Umr Get, 14 avenue Edouard Belin, 31400 Toulouse, France; eCIRAD - UMRSelmet, Campus International Baillarguet, 34398 Montpellier Cedex 5, France; fINRA SupAgro, Cirad Campus

international, 34700 Montpellier, [email protected]

Extensive pastoral systems of sub-Saharan Africa are said to be responsible for the highest rates of greenhouse gas(GHG) emissions per unit of animal products. Tropical sylvo-pastoral systems, which make use of rangelands in aridand semi- arid areas, are characterized by a high mobility of cattle as a response to a high seasonal variability of theavailability of forages, which makes their evaluation in terms of environmental sustainability particularly complex.This study offers a first GHG balance at the sylvo-pastoral ecosystem scale in the Ferlo, a semi-arid region of Senegal.The Ferlo is organized in a network of well drillings. The drilling access territory (706.5 Km2) was used as the unitof area for this analysis. The net balance includes the main direct emissions and the accumulation of carbon (C)stocks in soil and in trees. The Tier 1 IPCC method was used to evaluate emissions. An inventory of animal stockswas made by cross-checking data collected from statements at the drilling with data from surveys conducted at thecamps (n=354). Emission and sequestration factors as well as technical coefficients (e.g. productivity and mortalityof animals) were extracted from literature.According to this first assessment, soil represents the most important reservoir of C (66% of the total C stock). Takinginto account annual carbon sequestration by the soil and trees, the net GHG balance is - 0.12t C.ha−1.year−1, i.e.emissions from herds are compensated by the accumulation of C in soil and trees. The main sources of emissionsare enteric fermentation (56%) and deposition of faeces by ruminants (16%). Fire and termites, two other importantsources of emissions, together represent about 20% of emissions. The GHG balances per kg of animal products arehigh due to the low productivity of animals and the high methanogen potential of feed rations. They are similar tothose found in the literature: 69 kg eq. CO2.kg

−1 of carcass weight and 9 kg eq. CO2.kg−1 FPCM (Fat and Protein

Corrected Milk) for cattle and roughly 28 kg eq. CO2.kg−1 of carcass weight and 11 kg eq. CO2.kg−1 FPCM for

sheep.In the authors’ view, these balances per kg of animal product are incomplete. They recommend making the assessments”consequential”, i.e. also taking into account changes in the functioning of the ecosystem due to livestock. Adjustmentssuch as the reduction in bush fires and termite activity can represent in some situations avoided emissions (which shouldbe subtracted from these first balances).



Biserrula pelecinus L. shows persistent low Methane Production under a continuous Culture Fermen-tation System (RUSITEC) when mixed with Trifolium subterraneum L.

B. Banika, Z. Durmica, W. Erskineb, C. Revellc and P. Vercoea

aUWA, 35 Stirling Hwy, M085 School of Animal Biology, 6009 Crawley, Australia; bUWA, 35 Stirling Hwy, M082,School of Plant Biology, 6009 Crawley, Australia; cDAFWA, 3 Baron-Hay Court, 6151 South Perth, Australia

[email protected]

Methane emission from fermentation of feedstuff in the rumen is one of the most significant sources of greenhousegas produced by agricultural industries. Manipulating animal diet, particularly through forages offered in grazingsituations, is one of the most effective ways to reduce methane from this source. Biserrula pelecinus L. is an importantannual pasture legume widely distributed throughout Mediterranean countries and well adapted to acidic sandy soils.There is growing research interest in B. pelecinus because of its low methanogenic potential when fermented by rumenmicrobes. However, there are some limitations to its use by livestock (possible effects on animal health) and the legumemay be more suited to grazing in a plant mixture rather than as a monoculture.We hypothesised that the anti-methanogenic property of B. pelecinus would persist when mixed with a common pasturelegume (i.e. Trifolium subterraneum L.) in a continuous culture fermentation system (RUSITEC). We examinedfermentation profiles, including methane production of a binary forage mix containing 0, 250, 500, 750 and 1000 g/kgof freeze dried B. pelecinus combined with T. subterraneum as fermentation substrate.When B. pelecinus was included at level of 500 and 1000 g/kg substrate, there was a significant reduction (P<0.001)in methane production (average 2.2 and 2.8 mL/100 mL total gas production, respectively) compared to the solesubstrate of T. subterraneum (3.4 mL/100 mL total gas produced). The low methanogenic potential at these levels ofB. pelecinus persisted throughout the experiment (18 days in RUSITEC), with no effect on overall microbial activity(i.e. total volatile fatty acids and ammonia production), but some reduction in microbial gas production was reportedat the 500 g/kg level. However, there was no correlation between the level of B. pelecinus inclusion and any of thefermentative characteristics measured.These results showed that B. pelecinus, when fermented in a continuous culture fermentation system, over a periodof time and in a mixture with another legume, can maintain low methanogenic activity without affecting microbialactivities, but only at selected levels of inclusion. These results provide a platform to progress B. pelecinus further,with the next stage being in vivo confirmation in grazing livestock.These findings might ultimately provide farmers with an environmentally-friendly option to help reduce methaneemission from grazing animals.Acknowledgement: Funded by CSIRO, UWA and DAFWA.



Substitution of Maize Silage with Sorghum Silages in Cow Ration: Effect on Global Warming Potentialof Milk Production

L. Bava, S. Colombini, M. Zucali, A. Sandrucci and A. Tamburini

Universita degli Studi di Milan, via Celoria 2, 20133 Milano, [email protected]

About 45% of Green House Gas (GHG) emission from livestock sector is methane. In cow milk production, entericemissions load for nearly 45% on the total GHG emissions and CH4 represents about 50% of GHG from enteric andmanure fermentations. Sorghum is growing in popularity as alternative silage crop for dairy cattle feeding, because oflower requirements of water and agronomical inputs in comparison to maize. The aims of the study were to estimatethe effects of replacing maize silage with sorghum grain and sorghum forage silages on the global warming potential(GWP) of milk production and to compare the results obtained using both estimated and in vivo measured entericmethane emissions.The study compared three different scenarios where cropping systems and cow diets were based on maize silage (MS),whole plant grain sorghum silage (WPGS) and forage sorghum silage (FS). The GWP (kg CO2 eq. 100-year horizon)of milk production in the scenarios was evaluated through a ”cradle to farm-gate” Life Cycle Assessment. Theemissions related to on-farm activities (forage production, fuel and electricity consumptions, manure and livestockmanagement), off-farm activities (production of fertilizers, pesticides, bedding materials, purchased feed, replacinganimals, electricity, fuel) and transportation were considered. Functional unit was 1 kg Fat and Protein CorrectedMilk (FPCM). Enteric emission of methane of lactating cows was obtained from in vivo experiment with respirationchambers or from the equation by Ellis et al. (2007) based on ration DM, NDF, ADF and DMI.Methane estimated from enteric fermentation and manure storage was the major contributor (46%) to GHG for milkproduction and 73.1% of estimated methane produced derived from enteric emission. Daily enteric methane emissionper cow estimated by equation was higher than the average emission measured from in vivo trials with the three diets(363 vs 312 g/d per cow). The average value of GWP using the estimated values of methane was 1.53 g CO2 eq./kgFPCM. The lowest CH4 emission per kg FPCM was obtained with MS diet, particularly when in vivo CH4 entericmeasurements were used.As a consequence, MS diet was the best option, in terms of GWP per kg FPCM. Purchased concentrate feed showeda great load on GWP (29% on average), especially in the FS scenario, because of the high off-farm purchased energyfeed. Contribution of crop production on-farm to GWP was lower for sorghum scenarios, particularly FS, due toreduced water and fertilizer use.



Dietary Information and Laboratory Tests for indirect Monitoring of Methane Emission from Cattlein the Sahel

B. Boisa, A. Ickowicza, T. Diopb, M. Doreauc, D. Morgavic and P. Lecomted,a

aINRA SupAgro, Cirad Campus international, 34700 Montpellier, France; bISRA, Dakar, Senegal; cINRA, TheixCentre, 63122 St Genes Champanelle, France; dCIRAD - UMR Selmet, Campus International Baillarguet, 34398

Montpellier Cedex 5, [email protected]

The aim of this preliminary study was to assess whether the information obtained from field observations of grazingbehaviour, in vitro fermentation, forage analysis and NIR indicators derived from biochemical properties of faecescould be combined and used as indirect indicators of enteric methane emission of cattle in pastoral systems of theSahel region.The study took place in North Senegal (±520 mm rain, 15◦21’N, 15◦29’W) where two transhumant herds of zebus weremonitored during 4 months (April-July) in the dry season. During this first period, variation in the grazed biomassand botanical composition of the diet ingested were measured. Samples were taken for chemical and near-infraredspectroscopy analysis and rumen fluid in vitro tests. Diets of the animals varied during the period of the study, withthe advance of the dry season the forage quality decreased and zebus compensate the lack of forages by eating ligneousspecies (up to 25.2% ± 5.7). These changes in feeding weren’t associated with particular biochemical variations ofthe diet since all elements had very poor qualities: from the start of the experiment with straw diets (NDF 68.1,ADL 6.6, MAT 5.4 % DM) to the end with trees branches diets (NDF 73.9, ADL 5.2, MAT: 3.2 % DM). PotentialMethane Emission (PME) characterised by in vitro analysis has to be interpreted carefully: total volume of methaneemitted varied through the season and decreased along diet evolution. Methane production was only correlated toNDF content (r=0.65, p=0.02) of the faecal samples. This first single correlation was insufficient to make indirectindicators of PME.The study put in light that PME of ruminants in the Sahel region might vary through the dry season, with the changesin zebus’ diet. However, even if the number of samples gathered for this study wasn’t sufficient to clearly understandthe mechanisms implied, it constitutes a promising initial work on the subject, and the follow up should be extendedto a whole year.



Greenhouse Gas Emissions from the Dairy Sector in Thailand

K. Boonyanuwat

Department of Livestock Development, Bureau of Animal Husbandry and Genetic Improvement, Rachathewi, 10400Bangkok, [email protected]

This study assessed the greenhouse gas (GHG) emissions from the dairy cattle sector in Thailand in 2011. Theobjectives of the study were 1) to develop a methodology based on the Life Cycle Assessment (LCA) approachapplicable to the dairy sector, and 2) to apply this methodology to assess GHG emissions from the dairy cattle sector.It focused on the encompassing the life cycle of dairy products from the production and transport of inputs (fertilizer,pesticide, and feed) for dairy farming. The study quantified the major greenhouse gas emissions associated withdairy farming, namely, carbon dioxide, methane and nitrous oxide, and included all animals related to milked cows,including replacement animals and surplus calves from dairy cows, fattened for their meat. In 2011, the dairy sectoremitted 2.01 million tonnes CO2-eq. They emitted 1.46 tonnes per 1 ton milk production at farm gate. Cradle tofarm gate emissions contributed, on average, 74.13 percent of total dairy GHG emissions. Methane contributed tothe global warming impact of milk about 74.13 percent of the GHG emissions. Nitrous oxide emissions accounted for25.87 percent of the GHG emissions.This report did not present a model for estimating the full environmental impact from the entire livestock sector,rather it focused on GHG emissions, notably carbon dioxide, methane and nitrous oxide, from the dairy cattle sector.The assessment took a food chain approach in estimating emissions generated during the production of inputs into theproduction process, dairy production. Given the global scope of the assessment and the complexity of dairy systems,several hypotheses and generalisations had been used to overcome the otherwise excessive data requirements of theassessment. The uncertainties introduced by these assumptions were estimated and used to compute a confidenceinterval for the assessment results. Although estimating GHG emissions from the sector provided an importantstarting point for understanding the sector’s potential for mitigating emissions, the real challenge lied in identifyingapproaches to reduce emissions. However, the purpose of this current study was not to provide recommendationsregarding appropriate mitigation options for the dairy sector. This would be done at a later stage, when the programmeof biophysical and economic analysis of mitigation options would be completed.



Variability in Methane Production from ruminal Fermentation of temperate Forage Legumes andGrasses

Z. Durmica, J. Vadhanabhutib, K. Lundc, A. Humphriesd and P. Vercoea

aUWA, 35 Stirling Hwy, M085 School of Animal Biology, 6009 Crawley, Australia; bUWA, 35 Stirling Hwy, M085School Of Animal Biology, 6009 Crawley, Perth, Australia; cAarhus University, Blichers Alle 20, Postboks 50,

DK-8830 Tj Foulum, Denmark; dSARDI, Waite Campus, Plant Research Centre 2b Hartley, 5064 Urrbrae, [email protected]

Manipulating an animal’s diet is one of the most efficient, economical and non- intrusive ways of reducing entericemissions from livestock. In grazing situations, methane emissions can be reduced by selecting pasture species that,when consumed by the animal and fermented by rumen microbes, produce relatively less methane per unit of intake.However, studies that systematically evaluate the diversity of pastures and identify their potential for reducing methanefrom grazing animals are lacking.The aim of the current study was to examine temperate, herbaceous forage species for variability in methane productionduring in vitro rumen fermentation. The study included 31 annual and 14 perennial species from a selection ofcommercial, ’pipeline’ and promising experimental temperate pasture species. All plant species were grown in fieldplots and samples were collected at both the vegetative and reproductive stages. All plant samples were tested inan in vitro batch fermentation system, where methane production, along with other fermentability parameters, wasmeasured.Amongst the annual forage species, there was a limited variation between the measured parameters, except for onespecies, Biserrula pelecinus, which produced up to ten times less methane (per unit of DM incubated) than the highestmethane-producing species. Significant differences in methane production were observed amongst perennial foragespecies. For example, three plant species, Dorycnium hisutum, Dactylis glomerata and Trifolium pratense produced40% less methane than the highest producing species. Amongst the annual species, the average methanogenic potentialwas higher in plants in the reproductive stage compared to those in vegetative stage, while the opposite was observedamongst the perennials. Only some plant species retained their ranking between the phenology stages.Overall, there was some variability in methane production from ruminal fermentation of different temperate foragespecies. It is possible to select plant species that are less methanogenic and that can progress towards helping to mit-igate methane from grazing animals, provided that they meet other criteria (agronomic, productivity). Investigatingplants grown under various conditions and in vivo experiments will help assess the suitability of these pasture speciesin terms of their ability to reduce methane emissions without affecting livestock productivity in grazing systems. Ulti-mately, this information will help develop plant evaluation tools which land managers can use for methane mitigationstrategies based on temperate pasture species.



Typology of Cattle Production in Brazil at the Municipality Level

M.D.C.R. Fasiabena, L.G. Barionia, A.G. Maiab, M.M.T.B.A. Almeidac and O.C. Oliveirac

aEmbrapa Agriculture Informatics, Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil;bIE/UNICAMP, Rua Pitagoras, 353, 13083-857 Campinas, Brazil; cIBGE, AV. BEIRA MAR, 436 -13◦ ANDAR,

20021-060 Rio De Janeiro, [email protected]

Brazil is one of largest beef producers in the world. Data from the Brazilian Agricultural Census 2006, carriedout by the Brazilian Institute of Geography and Statistics (IBGE), has shown that approximately 2.7 million farmshad bovine cattle, i.e. more than half of the farms in the country, raising 176.1 million head. In the last threedecades, the expansion of beef production has relied strongly on increasing stocking rates and animal productivityrather than expansion of pasture area. Still, there is high variability in productivity levels and technology adoptionthroughout the territory. Identifying and characterizing such variations is essential to allow improving the estimatesof greenhouse gases flows, and to better evaluate mitigation and adaptation options besides other issues related totechnology adoption and public policies.A typology of the Brazilian municipalities (totalling 5.517 municipalities) was carried out through factorial and clustermultivariate statistical analysis on data of the last available Agricultural Census (2006). Data was filtered for farmswith bovines and regrouped by municipality. Forty-seven variables, either as originally collected or calculated fromprimary data were selected. Those variables encompass socioeconomic and technological information aggregated atmunicipality level, such as land use, herd size, pasture area (natural and planted), production activity, productivity,stocking rate, pasture management, input usage, source of producer’s income, percentage of the income that comesfrom cattle, family or conventional farming, among the most important.The analysis identified 10 different groups of bovine cattle production municipalities. Results were validated withcattle production expert researchers and were considered consistent with the Brazilian reality. Spatial patterns of con-centration of some municipality aggregate types of production systems were evidenced. For instance, the concentrationof low technology and productivity cattle production in the semi-arid Northeast and the trend for extensive productionin large farms in the Brazilian center-east. However, several types of cattle-producing municipality types coexist inseveral regions. For instance, the state of Minas Gerais has both municipalities with technologically advanced beefcattle production systems and low productivity dairy production.Based on the experience of this municipality-level study, a new typology project has been initiated to classify cat-tle production systems at farm level (around 3 million records) applying the same techniques but selecting mainlytechnology and productivity related variables, aiming at providing more detailed information for modeling productionsystems and future scenarios construction for the Brazilian beef and dairy industries.



Control of Fermentation in the Gut of growing Pigs fed Maize-Soybean Diets containing high Levelsof fibrous Co- Product Feeds

F. Fushaia, M. Tekerea, M. Masafua, F. Siebritsb and C. Nhererac

aUniversity of South Africa, P.O. Box 392, Unisa, 0003 Florida, South Africa; bTshwane University of Technology,Private Bag X680, 0001 Pretoria, South Africa; cARC-Animal Production Institute, P/Bag X2, 0062 Irene, South

[email protected]

The study examined the effects of dietary fibre (DF) fermentability and Roxazyme R© G2 (RX) on fermentation in thelower gut of growing pigs fed high fibre, maize-soybean diets in which the basal ingredients were partially replaced withmixtures of co-product feeds. The co-product feeds included maize hominy chop and cobs, soybean hulls, brewer’sgrains and wheat bran. Upper tract digestion was simulated in an Ankom R© Daisy II incubator, by pepsin (porcine,200 FIP-U/g, Merck No, 7190) followed by pancreatin (porcine, grade IV, Sigma No P-1750) digestion, with recoveryof the fibrous residues. Fermentation gas and short chain fatty acid (SCFA) production of the fibrous residues weredetermined using buffered pig faecal inoculum, in an Ankom R© gas production system. The product of the feedconcentration of the fibre extract and its 48-hour gas production was included in diet formulation to mix two iso-nutritive, 319 g total DF kg−1 dry matter (DM) pig diets of high (HF) versus low (LF) fermentability of DF. Fibreextraction and the fermentation test were similarly performed on the high fibre, and a standard, 140 g total DF kg−1

DM diet. Each of the high fibre diets was duplicated, and one mixture was supplemented with 270 mg RX kg−1 feed.The four dietary treatments were allocated to 8 65kg Large White X Landrace intact male growing pigs fitted withileal T-cannula, in a duplicate 4 x 4 Latin Square design. Fermentation tests were similarly performed on the ilealdigesta.Relative to the standard, the HF and LF diets reduced (p<0.05) SCFA production of the in vitro extracted fibre by 8and 33%, respectively. Gas production was reduced (p<0.05) by 9 and 44 %, respectively. The acetate: propionate andbutyrate ratios for the HF, LF and standard diets were different (p<0.05), at 56:34:10, 51:38:11, 48:39:13, respectively.In the ileal digesta, the HF diet produced 37 % more (p<0.05) short chain fatty acids, 40 % more (p<0.05) gas thanthe LF diet. The acetate: propionate and butyrate ratios for the HF and LF diets were different (p<0.05), at 61:31:08and 59:33:08, respectively. RX did not affect fermentation, other than a tendency (p=0.06) to enhance gas productionof ileal digesta of the HF diet.In conclusion, screening feeds on the fermentability of DF significantly altered fermentation patterns. The results didnot justify the use of Roxazyme R© G2 to control fermentation.



In Vitro Enteric Methane Production as affected by the Inclusion of cold-pressed Rapeseed Cake inthe Concentrate Formulation

A. Garcia-Rodriguez, C. Pineda-Quiroga, N. Mandaluniz and R. Ruiz

NEIKER, Campus Agroalimentario Arkaute, E-01080 Vitoria-Gasteiz, [email protected]

Agricultural CH4 and N2O emissions have increased by nearly 17% from 1990 to 2005, an average annual emissionincrease of about 60 MtCO2- eq/yr . Carbon dioxide neutral systems will be a key objective for future farming.Rapeseed can be mechanically extracted on farm. As this process is performed by cold-pressing, the resulting cake isrich in fat, and fats have been shown to depress enteric methane production. Therefore, the objective of the currentwork was to assess the effect of the inclusion rate of cold-pressed rapeseed cake in the formulation of concentrates forruminants on methane production in vitro.Four concentrates, differing in the cold-pressed cake inclusion level (0, 7, 12 and 17%) were formulated to containequal amounts of crude protein and energy. Two total mixed rations (TMR) that differed in the forage-to-concentrateratio (60:40 vs. 75:25) were evaluated. Approximately 500 mg of each TMR were weighed into 125-ml serum bottles,50 ml of culture fluid was added (1:4 ruminal fluid and buffer, respectively), and bottles were crimp sealed. All TMRwere tested in triplicate for three different periods. Total mixed rations were incubated at 39 ◦C in a water bath for 24h. A sample of the gas cumulated in the bottle head-space was taken to determine the methane production. The finalpH of each bottle after 24 h of fermentation was measured, and samples were collected for determination of volatilefatty acid (VFA) concentration. In vitro organic matter digestibility (IVOMD) was calculated. Data were analysedas a factorial design (4 inclusion levels x 2 ratios) including the interaction between factors.No interactions between inclusion level and forage-to- concentrate ratio was observed. Inclusion of cold-pressed rape-seed cake reduced methane production when the inclusion level was 7% (1.63 vs. 1.53 mmol/d; P<0.01), 12% (1.63vs. 1.52 mmol/d; P<0.01) or 17% (1.63 vs. 1.44 mmol/d; P<0.001). Similarly, inclusion of cold-rapeseed cake re-duced CO2 production when the inclusion level was 7% (2.64 vs. 2.46 mmol/d; P<0.01), 12% (2.64 vs. 2.44 mmol/d;P<0.001) or 17% (2.64 vs. 2.28 mmol/d; P<0.001). The inclusion of cakes reduced VFA production when the inclusionlevel was 7% (4.82 vs. 4.52 mmol/d; P<0.001), 12% (4.82 vs. 4.51 mmol/d; P<0.001) or 17% (4.82 vs. 4.25 mmol/d;P<0.001). Inclusion of cakes, however, did not reduce IVOMD at any of the studied inclusion levels.In conclusion, cold-pressed rapeseed cake formulation reduced green-house gases production without affecting di-gestibility in vitro.



Effect of improving Diet Quality by Feeding Supplements on Methane Emission in different ProductionSystems of Beef Cattle in Brazil

J. Geraldo De Limaa, A. Banninkb, A. Van Den Pol Van Dasselaarb, L.G. Barionic and P. Menezes Santosd

aUniversity of Sao Paulo, Avenida Padua Dias, 11, 13418-900 Piracicaba, Brazil; bWageningen UR LivestockResearch, PO Box, 65, 8200 A Lelystad, Netherlands; cEmbrapa Agriculture Informatics, Av. Andre Tosello, 209,Barao G., 13083-886 Campinas - Sp, Brazil; dEmbrapa Southeast Livestock, Rodovia Washington Luiz, km 234,

13560-970 Sao Carlos, [email protected]

In Brazil, the national inventories on methane emission are carried out using the Tier 2 approach published by theIntergovernmental Panel on Climate Change (IPCC). Although, IPCC recommends the use of a more specific Tier 3approach, this is hampered by a lack of consolidated data for development, evaluation and application of such a Tier3 approach.The purpose of this study was to estimate the effect of improving diet quality by feeding supplements on methaneemission, calculated by both a Tier 2 and an extant Tier 3 approach, in different production systems of beef cattle inBrazil:(1) high quality diet and feedlot feeding from weaning to slaughter- FSFF - Feedlot finishing (14 mth);(2) energy and protein supplementation - ESPF - Pasture finishing (20 mth);(3) protein supplementation during dry and wet season - PSFF - Feedlot finishing (24 mth);(4) protein supplementation dry at first and second dry seasons combined with ad libitum mineral salt supplementationand protein supplementation wet at first and second wet season, respectively- PSPF - Pasture finishing (30 mth);(5) urea supplementation with mineral salt during the dry season and ad libitum salt during the wet season - USFF -Feedlot finishing (36 mth);(6) urea salt during the dry season and ad libitum mineral salt during the wet season - USPF - Pasture finishing (44mth).Tier 2 and Tier 3 approaches estimated a profound effect of supplementation on methane emission. Tier 2 estimatesranged from 168 (USPF) to 35 kg per animal (FSFF) while Tier 3 estimates ranged from 145 (USPF) to 32 (FSFF)kg per animal. Using a Tier 3 approach for Brazilian conditions led to lower predictions of enteric methane comparedto the IPCC Tier 2 approach.This study is part of the FP7 AnimalChange project (Grant Agreement 266018) and co-financed by the Dutch Ministryof Economic Affairs (KB-12-006.04-003). The first author also acknowledges the financial support of the Capes(Cordenacao de Aperfeicoamento de Pessoal de Nıvel Superior) for granting a graduate scholarship (2013/9820/12-4),besides financial support for training at Wageningen University Research Centre.



The Effect of Feed Additives rich in Lipids on Methane Production Mitigation in Dairy Cattle

A. Guerouali

Agronomic and Veterinary Institute, P.O.Box 6202 Madinat Elirfane, 11000 Rabat, [email protected]

Development of simple and inexpensive means of decreasing methane emission by ruminants would contribute to effortsto slow and stop global warming. New feeding additives were explored to reduce methane emissions in ruminants bythe incorporation of lipids in the diet.For this, an experiment was conducted to test the effect of feed additives, rich on medium chain fatty acids, on methaneproduction in dairy cattle. For this, four Holstein dairy cows were selected from a herd and used for this study, theywere housed individually and fed at maintenance requirements a ration composed of 40% of concentrate and 60%of forages corresponding to 4 kg of barley grains and 6 kg of lucerne hay. After 2 weeks of adaptation, Methaneproduction was measured, by using a face mask connected to an open circuit composed of flow-meter and infraredmethane analyzer, first in cows without feed additive then the feed additive was added to the same ration (50 g / day/ animal) during another 2 weeks of adaptation and a second measurement of methane was performed.The feed additive rich in lipids was behind a reduction by 32% in methane production in the cows. Methane emissionwas decreased from 5.46 to 3.74 liters / hour, from 14.10 to 9.54 liter / kg of dry matter intake and from 16.20 to10.33 liter / liter of milk. It is recommended that small amount of feed additive rich in lipids incorporated in the dairycattle diet would contribute to the effort of slowing down the emission of greenhouse gases.



Methane Emission from artificially reared Lambs and Response to the fibrous Diet

M.N. Haque, P. Khanal, M.O. Nielsen and J. Madsen

University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, [email protected]

Methane emission was investigated in artificially reared growing lambs fed milk replacer and dairy cream. A totalnumber of 18 lambs (average age 90 days and body weight 21±3.6 kg (mean ± SD) were selected for this study.They were housed in individual pens (1.5x1.5 m), and were fed from 3 days until 6 months of age either a ”Hay” dietconsisting of good quality artificially dried green hay fed restrictedly, or a ”Cream” diet consisting of 50% milk replacerand 50% dairy cream ad libitum until a daily maximum allocation of 2.5 (L/d). In addition, rolled maize was fed adlibitum (maximum allowance 1 kg/d). Methane and CO2 were measured in 4 different periods (appr. 90, 150, 185and 235 days of age). The measurements were performed every 15 seconds over 24 hours for 3 lambs, consecutively.Subsequently, the same process was followed for the rest of the lambs. The 3rd and 4th CH4 measurements wereperformed 4 and 50 days after the diet for the cream lambs was changed to the conventional hay diet, respectively.Weight gain (WG) was higher in cream group (P=0.004) during 1st and 2nd period. Total dry matter intake (DMI)g/d and organic matter intake (OMI) g/day was significantly lower (P < 0.001) in cream group. Methane production(g/d) was 72 and 74% lower in the cream group compared to hay during periods 1 and 2, respectively. Lower emissionwas observed when CH4 was expressed in terms of DMI, OMI and DE (P<0.001). After changing the cream lambsto a hay diet at 180 days of age, the CH4:CO2 ratio increased by 306 (period 3) and 350 % (period 4) compared tomeasurements on same lambs in period 1.In conclusion, artificial rearing of lambs with milk replacer and cream retarded development of rumen epithelium andestablishment of rumen microorganism followed by the microbial fermentation, and consequently, markedly depressedCH4 production. Dietary change to a fibrous diet dramatically changed the fermentation pattern, and CH4: CO2

ratio. Within 1-2 weeks, methane production was restored almost completely to levels observed in the conventionallyfed hay group.



Effect of Crystalyx R© Supplementation on Performance and Methane Emissions of grazing Heifers

K. Harta, C. Faulknera, C. Listerb and J. Newbolda

aIBERS, Aberystwyth University, IBERS, Aberystwyth University, SY23 3DA Aberystwyth, UK; bCrystalyx,Solway Mills, CA7 4AJ Silloth, UK

[email protected]

Crystalyx R© is a low moisture feed block, manufactured by a patented cooking process with the following compositionME 12 MJ, CP 12%, Sugars 35% and 24% ash. Previous scientific evidence has shown that cattle offered ad libitumaccess to Crystalyx R© molassed feed blocks have an increased live weight gain compared to their non-supplementedcomtempories despite only consuming between 50 and 200 g of block/animal/day. The aim of this experiment was toasses the effects of Crystalyx R© cattle booster on the performance and methane emissions of heifers grazing autumnalpasture.Twenty Holstein Friesian heifers, mean live weight 240 kg and mean age of 10 months, were blocked according to weightand age and randomly allocated to one of two experimental treatments: control (CON) no block supplementation andCrystalyx R© (LYX) supplementation. Cattle were grazed on split pastures with the only difference being cattle onLYX had access to two Crytsalyx R© cattle booster feed licks. Cattle had ad libitum access to drinking water at alltimes. Due to the lateness of the grazing season cattle were supplemented with 1.5 kg sugar beet pulp/head/day.The experiment lasted 9 weeks with cattle weighed fortnightly and at the end of week 9. Two methane measurementperiods were undertaken at week 6 and 8 using the SF6 tracer gas technique. Block intakes were recorded throughoutthe experiment by weekly changing of the blocks and daily weighing during the measurement periods. Data wasanalyzed by ANOVA using Genstat.Cattle offered LYX gained an additional 148 g/d (P=0.047) compared to those offered CON. There was no difference(P=0.890) in total daily methane emissions with a mean of 56 g/d. However, when corrected for weight gain cattleoffered LYX tended (P=0.101) to have a lower methane emission than those offered CON. Mean block intake for heiferson LYX during the measurement periods was 108 g/head/day. Results from this experiment demonstrate that cattleoffered LYX have increased performance relative to their un- supplemented contemporaries and that total methaneemissions did not differ. However, the increased performance of heifers offered LYX would allow them to reach bullingweight earlier. This in turn could result in lower methane emissions associated with the non milk-producing phase ofa heifer’s life.



The Potential to mitigate Greenhouse Gas Emissions in Finland by intensifying Beef Production fromDairy Herds

P. Hietala, P. Bouquet and J. Juga

University of Helsinki, Koetilantie 5, 00014 Helsinki, [email protected]

In Finland, the level of self-sufficiency in beef is about 85% and beef production is mainly based on dairy herds. Duringthe past ten years, the number of dairy cows has declined considerably leading to decreased domestic beef productionwhich is partly compensated by increased suckler beef production. However, greenhouse gas (GHG) emissions perunit of meat have been shown to be higher for beef produced in suckler cow systems than for beef produced as a by-product of dairy systems. Therefore, when safeguarding beef self-sufficiency in a sustainable way, intensification ofbeef production from dairy herds is one of the options to consider.To assess the potential of different production options for improving the efficiency of dairy-beef production, thefollowing different scenarios were studied; 1) increased use of crossbreeding with beef bulls in dairy herds for producingcross-bred slaughter animals, 2) an increased lifetime of cows resulting in a reduced replacement rate and 3) use of sexedsemen for producing replacement heifers and cross-bred male calves for beef production. In addition, the possibilityto mitigate GHG emissions from beef production by increasing beef production from dairy herds instead of sucklerherds was investigated. The emission factors applied in our study were average values estimated based on the differentwhole farm modelling studies for suckler and dairy beef.Increasing a crossbreeding rate from the current 5% to 30% would result in an increase of 2.8% in annual beefproduction and a potential saving of 1.1% in annual GHG emissions. When 40% of inseminations in crossbreedingwere carried out with sexed male semen assuming the current crossbreeding rate of 5%, an increase of 0.5% in annualbeef production and a potential saving of 0.2% in the annual GHG emissions were achieved. The reduction in thereplacement rate and the use of sexed semen to produce replacement heifers increased annual dairy beef productiononly when combined with a higher crossbreeding rate. However, the reduced replacement rate would enhance thepotential for crossbreeding and additionally would improve the efficiency of the whole dairy system.When considering the different studied scenarios, increasing the use of crossbreeding in dairy herds appeared to bethe most efficient strategy for intensifying dairy-beef production.



Associative Effect of Fermenting a low methanogenic Plant Biserrula pelecinus with selected Foragesin vitro

M. Joya, Z. Durmicb, J. Vadhanabhutic and P. Vercoeb

aCITA (Centro de Investigacion y Tecnologıa Agroalimentaria de Aragon), Avda. Montanana, 930, 50059 Zaragoza,Spain; bUWA, 35 Stirling Hwy, M085 School of Animal Biology, 6009 Crawley, Australia; cUWA, 35 Stirling Hwy,

M085 School Of Animal Biology, 6009 Crawley, Perth, [email protected]

Feeding management is one of the most developed strategies to reduce methane emission. In grazing situations, theproduction of methane depends on the plant species of forages. Biserrula pelecinus is a pasture legume recentlydiscovered to have a very low methanogenic potential, however it had as some inhibitory effect on overall rumenmicrobial gas, without affecting volatile fatty acid (VFA) production and prompting propionate production in vitro.We hypothesize that it may be possible to dilute some of the negative effects of B. pelecinus by mixing it with otherforages species in order to reduce methane without inhibiting fermentation.The objective of this study is to evaluate combinations of B. pelecinus with either grass (L. multiflorum) or legumes(Medicago sativa, Ornithopus sativus) on the in vitro fermentation properties, including methane. The mixturescontained 0, 25, 50, 75 and 100% of B. pelecinus in combination with selected pasture species and were tested in an invitro batch fermentation system. Each mixture were tested by triplicate using 100 mL serum vials, 500 mg substrateand 50 mL buffered ruminal fluid during 24h. All samples were analysed in one single run. After measuring gaspressure, 5mL of headspace gas was transferred to an exetainer tube for subsequent analysis of methane concentrationby gas chromatography.The inclusion of B. pelecinus at 50% and above with any of the other species tested resulted in a decrease of gasand methane production (P<0.001), but at 25% inclusion, reduction in gas was only 14.3%. There was no effect ontotal VFA at any of the level tested, but the mixtures containing B. pelecinus at level of 50% and above had greaterproduction of propionate and lower acetate : propionate ratio than the mixtures that contained 25% of B. pelecinusor less. There was a clear dose-effect of B. pelecinus on the all parameters measured.These results show that B. pelecinus retains its bioactivity in plant mixes, but when included at level of 50 % andabove, it was accompanied with some small but significant effect on gas production. It would be necessary to lookinto narrower range of doses, i.e. between 25% and 50%, to find the optimal level of inclusion for methane mitigation.Acknowledgements: Margalida Joy had a ”Salvador de Madariaga” support from the Spanish Government (PR2011-0265).



Grazing Intensity and Methane Emissions by growing Heifers in the Pampa Rangeland - SouthernBrazil

I. Machado Cezimbraa, O.J.F. Bonneta, M. Ritzel Tischlera, M. Moreira Santanaa, B. Araujoa, V. Silva Dutraa, A.Fialho Heguaburua, J. Victor Saviana, L. Barreto Massa, M. Moura Kohmanna, T. Cristina Moraes Genrob, A.

Berndtc, C. Bayera and P. Cesar De Faccio Carvalhod

aUniv. Federal do Rio Grande do Sul (UFRGS), Av. Bento Goncalves 7712, 90050321 Porto Alegre, Brazil;bEMBRAPA, BR 153 Km 603., 242 Bage, Brazil; cEmbrapa Southeast Livestock, Rodovia Washington Luiz, km 234,13560-970 Sao Carlos - Sp, Brazil; dUniversity of California, One Shields Avenue, 2306 PES Bld, Davis, 95616, USA

ian [email protected]

Methane (CH4) production from enteric fermentation in cattle is an important source of anthropogenic greenhousegas emission. Current inventories for enteric CH4 emission are mostly based on measurements made from animals inopen circuit respirometers in strictly controlled environments. On the other hand, a large part of the world ruminantproduction, like in South America, is based on animals grazed in open rangelands. Reducing uncertainty on CH4

emission in such systems needs field measurements under a large range of conditions to identify viable mitigationoptions such as improved animal productivity or dietary manipulation.We report here the results of a two years study of enteric CH4 emission from growing heifers grazed on native Pamparangeland, South Brazil. The experimental area, in the state of Rio Grande do Sul, is managed under continuousvariable stocking since 1986 and divided in five treatments of forage allowances (invers of grazing intensity), repeatedtwice. Treatments were 4, 8, 12 and 16% forage allowances (in kg DM.ha−1.day−1/ kg LW.ha−1). A fifth treatmentconsisted in 8% offer during spring and 12% during the rest of the year. We estimated CH4 emission, over the fourseasons of 2012 and 2013, by using the SF6 marker technique.CH4 emission per animal increased with forage allowances from 100 g.day−1 (4% offer) to 150 g.day−1 (12 and 16%offer). However, when considering emission in relation to live weight gains, the pattern is inversed. The 4% offertreatment, which suffered high grazing pressure and low live weight gain, had emission of 6.2 g.day−1 kg−1 LWgainanimal−1. With moderate to low grazing pressure (8-12, 12 and 16% forage allowances treatments), CH4 emissionsstabilized around 2 g.day−1 kg−1 LWgain animal−1.These values of CH4 emission per kg live weight gain we collected in the field are not different from the IPCC estimatesmade with the Tier 2 model, confirming the quality of these estimations for South American native Pampa. Moderategrazing intensity is an efficient management policy for native Pampa, allowing high animal production, low CH4

emission per unit of production and maintaining high plant diversity and ecosystems services.



Methane Emissions from Nellore Heifers under integrated Crop Livestock Forest Systems

R.A. Mandarinoa, L.G.R. Pereirab, F.A. Barbosaa, D.C. Santosc, L. Vilelad, G.D.A. Macield, L.G. Barionie andR. Guimaraes Juniorf

aUniv. Federal de Minas Gerais, Av. Antonio Carlos, n◦ 6627, Pampulha, 31270-901 Belo Horizonte, Brazil;bCNPGL, PECUS/RumenGases, Financiado CNPq e FAPEMIG, Eugenio do Nascimento, 61, Dom B, 36038-330

Juiz De Fora, Brazil; cUniversidade Federal de Goias, Campus Samambaia, UFG, 74001-970 Goiania, Brazil;dEmbrapa Cerrados, BR 020, Km 18, Zona Rural, 73310-970 Planaltina, Brazil; eEmbrapa Agriculture Informatics,

Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil; fEmbrapa Cerrados,PECUS/RumenGases/AnimalChangeFP7, BR 020, Km 18, Zona Rural, 73310-970 Planaltina, Brazil

[email protected]

Adoption of Integrated Crop-Livestock-Forestry Systems (ICLFS) has been encouraged as a greenhouse gases (GHG)mitigation measure in Brazil. Accurate estimate of enteric methane emission (ECH4) is essential to compute carbonfootprint and, consequently, to improve the evaluation and design of GHG mitigation strategies for cattle productionsystems.ECH4 and dry matter intake (DMI) of Nellore heifers (322 ± 33 kg of live weight (LW)) grazing Brachiaria (Urochloa)brizantha CV Piata were evaulated under three different types of ICLFS at Embrapa Cerrados (lat -15.604088◦; long:-47.713837◦), in the autumn of 2013. Three replicates, containing two animal testers each, were set in a randomizedcomplete block design. The treatments were integrated to the crop-livestock system with:a) 6 years old pasture (control) - ICLS6;b) one year old pasture - ICLS1, and;c) one year old pasture established under Eucalyptus urograndis trees in a north-south orientation and spacing betweenrows of 22m (417 trees.ha−1) - ICLSF1.Enteric CH4 production was measured using the SF6 tracer gas technique collected for 6 days after 14 days adaptationperiod. Dry matter intake (DMI) was estimated using LIPE R© fecal marker in association with in vitro dry matterdigestibility (DMD) of pasture samples simulated on all treatments by hand pulling pasture. The grazing pressurewas set to 10% per kg of LW for all treatments. Tukey test (P<0.05) was used to compare treatment means.Mean DMD was 46.3%, 56.9% and 55.0% for ICLS6, ICLS1 and ICLFS1, respectively. ICLS6 differed from ICLS1and ICLFS1, suggesting that trees did not influence DMD. The same pattern was verified for DMI. ICLS1, ICLFS1and ICLS6 resulted in mean DMI of 6.2, 6.0, 4.3 kg.day−1, corresponding to 2.2, 1.9 and 1.3 DMI in % of live weight,respectively. Comparing ICLS6 and ICLS1, for each percentage point reduction in DMD animals ingested 180 g lesspasture. Despite the differences in DMD and DMI, ECH4 emissions were similar (P>0.05). ICLS1, ICLFS1 and ICLS6CH4 emissions were 112.4, 96.6 and 88.5g.animal−1.day−1, respectively. When it comes to the ratio between ECH4 andDMI(gCH4.kgDM−1) treatments means also did not differ (P>0.05), with overall mean of 18.6. Pasture age, i.e. timeafter planting, affects DMD and DMI but not ECH4 and ECH4/DMI in ICLFS during the Cerrado autumn season.



Effect of Feeding Practices in different Production Stages on GHG Emissions in Latxa Dairy Sheep

C. Pineda-Quiroga, N. Mandaluniz, A. Garcia-Rodriguez and R. Ruiz

NEIKER, Campus Agroalimentario Arkaute, E-01080 Vitoria-Gasteiz, [email protected]

Dairy sheep production in the Basque Country has been traditionally based on the Latxa breed managed throughdifferent feeding practices during the productive cycle. The assessment of the quality of the diets, in terms of nutritionalvalue, digestibility, and fermentation kinetics, is critical to evaluate and improve the efficiency and reduce emissions.The objective of this study was to characterise the diets provided during prelambing (P), lactating indoors (LI) andspring lactation with part-time grazing (LG), and to assess GHG emissions for these diets. Feed samples (concentrates,forages and fresh pasture) were collected in 4 flocks between autumn 2012 and spring 2013. The fermentation kineticsof the diets, organic matter digestibility (IVOMD), volatile fatty acids (VFA) and methane were monitored in vitroby gas production technique. Data were analysed considering the production period (P, LI and LG) as fixed effect.The concentrate:forage:fresh pasture ratio was 30:70:0 in P, 40:60:0 in LI and 27:24:49 LG. The potential gas production(ml/g Incubated organic matter) was lower during LI and P compared to LG (268 LI; 310 P vs. 524 LG; P<0.05); theincubation time required for maximum gas production was lower for P diets (11 vs. 21 LG and 19 LI; P<0.05) andthe percentage IVOMD was higher in LI diets (66 vs. 52 LG, P<0.01 and 59 P, P<0.05). The percentage of propionicacid was lower in LG (16 vs. 18 LI, P<0.05 and 23 P, P<0.001), while the percentage of acetic acid was higher (69 vs.60 LI and 59 P, P<0.001), the ratio acetic/propionic (4.2 vs. 3.3 LI and 2.5 P, P<0.001) and the total VFA (mmol)were higher in LG (5.47 vs. 4.45 LI; P<0.01). Finally, total methane emissions (mmol/day) and methane referred todigestible organic matter (mmol/g DOM) were higher in LG diets (1.91 vs. 1.46 LI and 1.45 P, P<0.01 LG and 19.45LG vs. 5.22 LI and 5.64, P<0.01, respectively).In conclusion, grass-based diets produce higher GHG emissions and showed the worst efficiency. The utilisationof supplementary feedstuffs specifically designed for mitigation of grass-based systems is critical to improve theirsustainability.



The Effect of concentrate Supplementation on Methane Emission Intensity of Cattle grazing tropicalPastures in the dry Season

S. Raposo De Medeirosa, T. Zanett Albertinib, L.G. Barionic, A. Berndtd, R.D.C. Gomesa, C.T. Marinoa, C.V.Andradea and M.C. Freuae

aEmbrapa Beef Cattle, Av. Radio Maia, 830 - Zona Rural, 79106-550 Campo Grande - Ms, Brazil; bUniversity ofSao Paulo, Av. Padua Dias, 11, 13418-900 Piracicaba - Sp, Brazil; cEmbrapa Agriculture Informatics, Av. Andre

Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil; dEmbrapa Southeast Livestock, Rodovia Washington Luiz,km 234, 13560-970 Sao Carlos - Sp, Brazil; eUniversity of Sao Paulo, Av. Duque de Caxias Norte, 225, Campus da

USP, 13635-900 Pirassununga-Sp, [email protected]

The purpose of this study was to establish the relationship between the level of concentrate supplementation forgrazing animals and methane (CH4) emission intensity (Ei, kg CH4/kg average daily weight gain).First, a polynomial regression was developed to predict average daily weight gain (ADG) with increasing levels ofsupplement (DMIsup, g/kg live weight) for grazing beef cattle using meta-analytical data (n = 24) from Brazilianpublished scientific papers: ADG, kg/d = 0.1773 (SE ± 0.07976) + 0.06225 (± 0.02929) × DMIsup - 0.00122 (±0.002105) × DMIsup2 (P < 0.05; Eq. 1). Total dry matter intake and diet quality information were estimated uponthe same dataset referred above (n = 24) using the Invernada Simulation Model (Embrapa Invernada), a softwaredeveloped by Embrapa. A principal component analysis was performed followed by multiple linear regression analysisto predict enteric methane emission derived from another dataset (n = 36 studies), based also on grazing animalsusing the hexafluoride method (SF6): CH4, kg/d = - 0.1011 (± 0.02903) + 0.02062 (± 0.002834) × DMI + 0.001648(± 0.000417) × NDF (P < 0.05; Eq. 2). Then a polynomial regression was used to predict the CH4 emission for eachkg of ADG: Ei, kg CH4/kg ADG = 0.4182 (± 0.0618) + 0.712 (± 0. 2244) × ADG + 0.4872 (± 0.2914) × ADG2 (P< 0.01; Eq. 3). In all equations, experiment was considered as a random effect as well as the intercept using mixedmodeling performed with the SAS system. ADG values used in the Eq. 3 were derived from Eq. 1 varying DMIsupfrom 0 to 12 g/kg live weight.Methane emission intensity was drastically reduced as supplementation level increased. Without supplementation, Eiwas estimated as 0.39 kg CH4/kg live weight while 12 g concentrate/kg live weight reduced the emissions estimateto 0.16 CH4/kg live weight equivalent to a 60% reduction. The reported effect is due to a combination of increasedgain, as forage is used more efficiently, and the improvement in diet digestibility due to a direct (higher digestibility)and indirect effect (improved rumen fermentation) caused by concentrate supplementation. It can be concluded thatsupplementation is an effective strategy to reduce GHG emission intensity in tropical areas with a well-defined andlong lasting dry season as it occurs in Brazil.



Modeling enteric Methane Emission from Beef Cattle in Brazil: a proposed Equation performed byprincipal Component Analysis and mixed Modeling multiple Regression

S. Raposo De Medeirosa, L.G. Barionib, A. Berndtc, M. Caslenani Freuad, T. Zanett Albertinie, C. Costa Juniore

and G.B. Feltrine

aEmbrapa Beef Cattle, Av. Radio Maia, 830 - Zona Rural, 79106-550 Campo Grande - Ms, Brazil; bEmbrapaAgriculture Informatics, Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil; cEmbrapa SoutheastLivestock, Rodovia Washington Luiz, km 234, 13560-970 Sao Carlos - Sp, Brazil; dUniversity of Sao Paulo, Av.Duque de Caxias, 225, USP, 13635-900 Pirassununga - Sp, Brazil; eUniversity of Sao Paulo, Av. Padua Dias, 11,

13418-900 Piracicaba - Sp, [email protected]

Brazil has the largest commercial beef cattle herd in the world but does not have its own model to predict methane(CH4) emission. The aim of this study was to create the first empirical enteric CH4 emission equation from variablesthat describe the animal diet using a meta-analytical data from Brazilian scientific publications (n = 50, publishedfrom 2003 to 2012).The frequency statistics (FREQ procedure, SAS) were used to evaluate the animal characteristics: 60% came fromgrazing systems (other 40% from feedlot), about 80% were classified as beef cattle and Nellore was the predominantgenotype (76%). The Principal Component analysis was performed using the PRINCOMP procedure for CH4 entericemission using the hexafluoride technique (CH4, kg/d; 0.137 ± SD 0.0721 kg/d), dry matter intake (DMI, kg/d; 7.3± 3.11 kg/d), neutral detergent fiber (NDF, % in DM basis; 55.3 ± 13.89%), acid detergent fiber (ADF, %; 36.9 ±18.02%), lignin (%; 4.6 ± 1.67%), and fat (%; 4.1 ± 3.42%).Using Principal Component analysis, the cumulative variance explained by the first 3 principal components (CH4,DMI, and NDF) was about 96%. Consequently, DMI and NDF were used as independent variables in the multipleregression analysis using the MIXED procedure. In this regression model, the experiment was considered as a randomeffect as well as the intercept. Just 36 studies were used in the final model (once observations without DMI or NDFwere removed). The final regression model was: CH4, kg/d = - 0.1011 (SE ± 0.02903) + 0.02062 (± 0.002834) × DMI+ 0.001648 (± 0.000417) × NDF. The approximate Z-test for the DMI random effect and the intercept probabilitiesvalues were P < 0.001 and P = 0.0015, respectively. The residual based on covariance parameter estimates of themodel was 0.000249.As suggested by IPCC we encourage the use and improvement of the developed equation in order to increase theaccuracy and precision of the Brazilian greenhouse gases estimates.



Dietary Nitrate but not Linseed Oil decreases Methane Emissions in two Studies with lactating DairyCows

J. Venemana, S. Muetzelb, K. Hartc, C. Faulknerc, J. Moorbyc, G. Molanob, H. Perdokd, J. Newboldd and J.Newboldc

aIBERS, Aberystwyth University/C, IBERS New Building (Penglais), Aberystwyth University, SY23 3DAAberystwyth, UK; bAgResearch Limited, Grasslands Research Centre, 4442 Palmerston North, New Zealand;

cIBERS, Aberystwyth University, IBERS, Aberystwyth University, SY23 3DA Aberystwyth, UK; dCargill AnimalNutrition, Cargill Innovation Center, 5334 LD Velddriel, Netherlands

[email protected]

Linseed oil (LO) and nitrate (NO3) both have the potential to mitigate methane production from enteric fermen-tation in ruminants. NO3 could serve as an alternative hydrogen sink as it is reduced through nitrite to ammonia.Stochiometrically, reduction of 100g of nitrate could prevent the production of 25.8g of methane.The aim of these studies was to test the effect of dietary LO and NO3 on methane production and rumen fermentationin lactating dairy cows in two geographical locations with different basal diets. Treatments in both experiments were acontrol diet, diet supplemented with LO at 4% of feed DM and NO3 at 2% DM. Experiment 1 (Exp1) was a continuousstudy with 18 cows (533±65 kg BW, 20.5±2.6 L of milk) in New Zealand. Animals were fed a maize silage baseddiet, twice daily at 95% of previous ad libitum intake within each block (3 cows per block). Experiment 2 (Exp2)consisted of a replicated 3 x 3 Latin Square with 6 cows (578±52 kg BW, 21.5±4.5 L of milk) in the UK. Cows werefed a mixed ration of grass and maize silages and concentrates once daily ad libitum. Diets were kept isonitrogenousby adding urea in both experiments and equal in fat content by adding a rumen inert fat source in Exp2. Methanewas measured in open circuit respiration chambers. Data was analysed using the PROC MIXED procedure in SAS.Feeding NO3, but not LO, reduced methane emissions in g per day (Exp1 and Exp2 both 21%; P<0.02) and per kgDMI (16 and 13%; P<0.04 in Exp1 and Exp2, respectively), but were below the stoichiometric potential of NO3 toreduce methane (68 and 66% for Exp1 and Exp2 respectively). Methane emissions per kg milk were reduced by NO3

feeding only in Exp1 (P<0.05).Feeding NO3 also increased hydrogen emissions in both studies (P<0.03). LO or NO3 did not affect total VFAconcentration in the rumen, but NO3 increased the acetate to propionate ratio in both studies (P<0.02). Theseresults suggest changes in the distribution of metabolic hydrogen among methanogenesis, nitrate reduction and theproduction of individual VFAs when feeding NO3. NO3 reduced methane emissions in both experiments by a similarmagnitude (21% per day), whereas LO did not affect emissions.Research conducted as part of AnimalChange, a project funded by EC-FP7/2007-2013 under grant agreement no.266018.



Air Emissions from Biogas Digester Effluent stored at different Depths

Y. Wanga, H. Donga, Z. Zhua, T. Lia, K. Meia and H. Xinb

aIEDA, CAAS, 12 Southern Street of Zhongguan, 100081 Beijing, China; bABE, Iowa State University,, 1202National Swine Research and, and Information Center, Ames, Iowa, 50011-3310, USA

[email protected]

Substantial amounts of carbonaceous and nitrogenous gases can be produced during storage of livestock manure, withthe magnitude of emissions affected by chemical properties of the manure and physical conditions of the storage.This study was conducted to quantify methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O), nitric oxide (NO)and ammonia (NH3) emissions from biogas digester effluent (BDE) stored at different depths using dynamic emissionvessels. Storage depths of 1.0, 1.5, and 2.0 m were selected to reflect the typical range of livestock manure on-farmstorage depths in China. The storage vessels were held at 15◦C temperature with a head-space air exchange rate of11.5 air changes per hour (ACH) for 78 days. Each depth regimen was replicated four times.The results showed that the mean (±SE) daily gas emission rates for the BDE stored at 1 m, 1.5 m, and 2 m depthswere, respectively, 9.1 (±0.7), 10.1(±0.6), and 10.1(±0.4) g CH4 m−3 d−1 (p=0.39); 38.0 (±2.2), 34.5 (±1.3), and30.7 (±0.6) g CO2 m−3 d−1 (P<0.05); 1905 (±111), 1315 (±81), and 921 (±30) mg NH3 m−3 d−1 (p<0.05); and6.7 (±0.5), 5.0 (±0.8), and 3.4 (±0.2) mg N2O m−3 d−1 (P<0.05). Nitric oxide emissions were negligible. The totalgreenhouse gas (GHG = CH4 + N2O + CO2) emissions were dominated by CH4 that accounted for more than 85% ofthe CO2-eq emissions for each of the three storage depths. The CH4 emissions peaked during the early storage period,with the cumulative CH4 emissions in the first 20 days of storage accounting for 56-58% of the total CH4 emittedduring the entire storage period.The results showed that the storage depth of 1.0, 1.5, and 2.0m had no effect on the CH4 emissions, while 2.0 mstorage depth had the least CO2, NH3, N2O and NO emissions. Hence, for typical BDE storage depths in China, thegreater storage depth of 2.0 m would be more conducive to mitigating gas emissions.



Greenhouse Gas and Ammonia Emissions from Ceramsite covered compared with uncovered DairySlurry Storage

Z. Zhu, H. Dong, C. Liu and W. Huang

IEDA, CAAS, 12 Southern Street of Zhongguan, 100081 Beijing, [email protected]

Dairy slurry storage before field use is the major liquid manure management practice in China, however, air emissionsincluding methane, nitrous oxide and ammonia occur during the slurry storage period. The goal of this study was tocompare greenhouse gas (CH4, N2O) and ammonia (NH3) emissions from a dairy liquid slurry under a covering oflightweight expanded clay aggregate with uncovering and their temporal variations at different seasons. A commercialdairy cattle farm was chosen for this study. The manure was collected daily and solid-liquid separated, the liquid slurrywas pumped into the lagoon for storage, when the solid manure was used as raw material for composting. A lagoonof about 200 m length, 50 m width and 3.5 m depth was chosen for this study, two areas were separated, one areawas covered with a depth of about 5 cm of ceramsite while the rest of the area was without cover, the gas emissionswere measured with dynamic chamber method with three replications; gaseous concentrations were measured using amulti-gas infrared photoacoustic analyzer with multi-channel sampler; fresh air supply (VR) was measured with flowmeters, the gas emission rate was computed from the VR and gases concentration. Slurry and air temperature weremonitored using HOBO temperature sensor and data logger, the slurry was sampled both at inlet and outlet for carbonand nitrogen properties analysis, five days were selected for continuous measure for each season. The result showedthat for all gas emissions strong diurnal variations exist in different seasons, highest CH4 and N2O emissions werefound in the spring season, while the highest NH3 emissions were found in summer season, and the ceramsite coveronly reduced NH3 emissions. The annual average CH4, N2O and NH3 emissions were 143.1±124.5g/m2/d, 118.9±79.6mg/m2/d and 633.0±317.6 mg/m2/d for uncovered storage, respectively, while the annual average CH4, N2O and NH3

emissions were 139.7±117.9 g/m2/d, 109.7±118.3mg/m2/d and 594.1±301.4mg/m2/d for ceramsite covering storage,respectively.The results of this study will contribute to the development of gas emissions inventory for manure management andmitigation practices.


Mon. 12:15 Medici I Parallel session 1a: Climate Change Impacts

What is the Impact of closing the global Gap in Pasture Performance on Land Use for Food and Energyin a Carbon and Land-constrained World?

J. Sheehana,b, E. Sheehanc, A. Morishiged, L. Lynde, N. Muellerf , J. Gerberg, J. Foleyg, G. Marthah, J. Rochai, L.Cortezj and C. Westk

aColorado State University, Fort Collins, Fort Collins, 80523, USA; bUniversity of Campinas, Barao Geraldo,Campinas, Sao Paulo, 13083-970 Campinas, Brazil; cUniversity of Minnesota, 7044 Fox Paw Trail, Littleton, 80125,USA; dMassachusetts Institute of Techn, MIT, Cambridge, 02139, USA; eDartmouth College, Thayer School ofEngineering, Hanover, 03755, USA; fHarvard University, Center for the Environment, Cambridge, 02138, USA;

gUniversity of Minnesota, Institute on the Environment, St. Paul, 55108, USA; hEMBRAPA, Empresa Brasileira dePesquisa, 70770-901 Brasilia, Brazil; iUniversidade Estadual de Campina, Faculdade de Engenharia Agricola, Av.Candido Rondon 501, Cidade Universitaria, 13083-875 Campinas, Brazil; jUniversidade Estadual de Campina,Nucleo Interdisciplinar de Planejamento Energetico, Rua Cora Coralina 330, Cidade Universitaria, 13083-875

Campinas, Brazil; kTexas Tech University, Department of Plant and Soil Sci, Lubbock, 79409, [email protected]

Sustainably increasing agricultural production on existing managed lands is a key strategy for meeting anticipatedfood and energy needs from a finite amount of land. Use of climatically-defined ”bins” is a leading approach forevaluating the potential of intensifying per hectare crop yields.In this study we apply the climate binning approach to global pastureland for the first time, and initiate evaluationof the potential for intensification of pastured livestock production within this framework. Although animal productyield per hectare would be preferable, stocking density is used as a performance variable due to limitations of availabledata. Livestock densities considered in climate space show a strong positive correlation with precipitation but a muchweaker correlation with temperature. Nearly half the land classified as pasture by Ramunkutty et al. does not havelivestock on it according to the FAO Gridded Livestock Study.We find that increasing stocking densities to climate-appropriate, maximum currently attainable levels would allowexisting pastureland to support nearly four-fold more animals, and that bringing the poorest-performing pastures up to50% of maximum livestock densities attained within their climate bin would double the global stock of grazing animals.The intensification potential for pasture appears to be substantially larger than for grain crops determined using asimilar approach. Including increased animal performance in the analysis could increase estimated intensificationpotentials by several fold. Comment is offered on refining and extending analysis of pastured livestock productionusing climate binning, including evaluating the impact of climate change.



Reconciling the Impacts of Extreme Rainfall Events and Extended Drought on Pasture and LivestockProduction: a New Method for Generating Synthetic Climate Sequences

M. Harrisona, B. Cullenb and R. Rawnsleya

aTasmanian Institute of Agriculture, Post Office Box 3523, 7320 Burnie, Australia; bUniversity of Melbourne,Melbourne School Land & Environ, 3010 Melbourne, Australia

[email protected]

Past work examining the effects of climate change on agricultural productivity typically uses downscaled weatherforecasts generated from global circulation models. Use of prescribed emission scenarios and time horizons in suchapproaches predefines the number of extreme climatic events (ECEs) that occur in forecasts of future climate. Further,forecasts containing both gradual climate change and more frequent ECEs make it difficult to partition and identifythe impact of each factor on farm production.Here we outline a new approach for generating synthetic sequences of weather containing extreme rainfall events andextended drought. Our approach preserves historical climate characteristics and does not include effects of gradualclimate change, allowing the sensitivity of pasture and livestock production to ECEs to be determined. The methodrandomly selects a defined proportion of rainfall events based on their magnitude and scales each event accordingly.A key advantage of this framework is retention of dependencies in daily weather variables, including the couplingbetween minimum and maximum daily temperatures, and the duration of contiguous dry days.We modified a 20-year sequence of historical weather measured at a site in Tasmania, Australia, such that the averagemaximum continuous duration of dry days per annum increased by 40%, the average maximum daily precipitationintensity increased by 40-50%, and the average annual rainfall decreased by 15% (in line with climate forecasts for2070-99). We used the synthetic weather sequence in a dairy farming systems model and found that runoff increasedby up to 5 mm/month, yet soil water draining from the base of the profile decreased by as much as 36 mm/month.Together these factors reduced peak annual pasture growth rates and caused earlier declines in plant growth ratesas spring progressed into summer. This lowered biomass production such that pasture intake per animal decreasedby 11%. To maintain the same level of historical milk production, grain and hay feeding requirements increased by11-14%, while the range in milk production increased by 19%.Our new approach for constructing synthetic weather sequences will facilitate further analyses of the effects of extendeddrought and reduced rainfall on farm production. In future this methodology will be extended to temperature extrema,allowing examination of the potential impacts of more heat waves and cold snaps. The overall effects of more severeand frequent ECEs on biophysical production on will ultimately be integrated within a wider framework containingeconomic, social and cultural aspects of dairy businesses.



MACSUR liveM - A Knowledge-Hub for integrated Modelling of Climate Change Impacts on LivestockProduction Systems: Lessons learned and future Developments

E.R. Saetnana, R.P. Kiplinga, N.D. Scollana, D.J. Bartleyb, G. Bellocchic, N.J. Hutchingsd, T. Dalgaarde and A.Van Den Pol Van Dasselaarf

aAberystwyth University, IBERS, Penglais campus, SY23 3FG Aberystwyth, UK; bMoredun Research Institute,Pentlands Science Park, EH26 0PZ Penicuik, UK; cINRA, UREP-Grassland Ecosystem Research, 5 chemin du

Beaulieu, 63039 Clermont-Ferrand, France; dAarhus University, Department of Agroecology, Blichers Alle, DK-8830Tjele, Denmark; eAarhus University, Department of Agroecology, DK-8830 Tjele, Denmark; fWageningen UR

Livestock Research, PO Box, 65, 8200 A Lelystad, [email protected]

A knowledge hub concept creates an arena for collaboration between diverse research groups, disciplines and projectsessential for tackling complex global issues such as the impact of climate change on agriculture. The MACSUR(Modelling Agriculture with Climate Change for Food Security; www.macsur.eu) knowledge hub brings togetherpartners from across Europe to develop a pan- European integrated modelling capability in the area of agriculturalsystems modelling.As part of this project, the livestock theme (LiveM) brings together modelling teams within and between disciplines toimprove the accuracy of predictions of the effects of climate change adaptation and mitigation on European livestockproduction systems. The project is focused on collating, sharing and evaluating datasets for modelling use, developingmethods of model inter-comparison, exploring ways to improve the impact and relevance of modelling outputs, andscaling up model predictions to the regional level. Through the project, inventories of relevant European grassland,animal and farm-scale datasets and models have been compiled. Model inter-comparisons have taken place for grasslandand farm-scale models, and a model evaluation protocol is being developed. Work to develop links between modellersand dataset holders has proved a challenge, so that the creation of online inventories of meta-data has emerged as apriority in the formation of a more cohesive research community.The further development of links between related projects is an essential step in building the capacity to address com-plex global issues in a joined-up way, using the pooled resources of different research groups, projects and disciplines.There is an urgent need for livestock and grassland researchers to develop a more coherent approach to the complexchallenges facing the sector, through the development of resources which facilitate increased understanding betweengroups and disciplines. Providing the space for such interactions is a key advantage of the knowledge hub set-up, whichcreates an arena of exchange from which future integrated research is generated. The MACSUR knowledge hub is animportant step in developing a joined-up approach to livestock research. The ultimate aim is to realise the potentialof a more integrated research community that effectively links experimental researchers, modellers, stakeholders andpolicy-makers.



The Influence of GHG Metrics on Quantification of Agricultural Emissions and Mitigation Options

A. Reisingera and S. Ledgardb

aNZ Agricultural GHG Research Ce, Private Bag 11008, 4442 Palmerston North, New Zealand; bAg Research,Ruakura Campus, 3210 Hamilton, New Zealand

[email protected]

Quantifying greenhouse gas (GHG) emissions and abatement options for livestock systems needs to consider a rangeof different GHGs, most notably CH4 and N2O in addition to CO2. These emissions are commonly aggregated usinga single unit, called ”CO2-equivalent”, with the weighting for non-CO2 gases based on their 100-year Global WarmingPotential (GWP). However, an increasing literature emphasises that many alternative metrics can be devised tocompare emissions of different GHGs, and the most appropriate choice of metric depends crucially on policy objectives.In contrast to previous reports, the most recent assessment by the IPCC does not recommend the 100-year GWP asmetric of choice but presents a range of alternative metrics.Alternative metrics and time horizons would result in different weightings for short-lived GHGs, most notably CH4.The current best estimate for the 100-year GWP of CH4 is 28 (updated from 25 in the previous IPCC assessment,and 21 being used in reporting under the UNFCCC), but any weighting between about 4 and more than 50 couldbe argued for scientifically based on alternative policy goals and time horizons. This implies that well-publiciseddifferences in GHG emissions from different livestock systems or abatement options could change significantly if aGHG emission metric other than the predominant 100-year GWP were chosen. We review the most recent IPCCassessment of mitigation options and potentials for agriculture to test whether and where alternative metrics wouldmaterially change conclusions and recommendations about emissions abatement strategies. We show that differentmetric choices would change not only the overall significance of the agriculture and livestock sector in global emissions,but also the contribution of particular farm systems and processes to emissions. We demonstrate that some abatementstrategies are relatively robust against the choice of metric (in particular those that related to reduced nitrogen inputs)- but for other abatement strategies that involve a trade-off between reduced methane emissions per unit of productbut higher production intensity, the choice of metric can even determine whether a particular strategy would lead toa net decrease or increase of emissions.We conclude that the choice of GHG metric deserves much more explicit attention in the assessment of net GHGemissions from livestock systems and development of abatement options to avoid a historical reporting convention(the 100-year GWP) influencing strategic decisions to reduce the contribution of livestock systems to global GHGemissions.


Mon. 12:15 Medici II&III Parallel session 1b: Mitigation options for livestock

The Influence of Fat Supplement and Roughage Type on Feces Composition and Methane Yield fromDairy Cows

V. Moset Hernandez, H.B. Moller, M. Brask, M.R. Weisbjerg and P. Lund

Aarhus University, Blichers alle 1, 8830 Tjele, [email protected]

Dietary strategies to diminish ruminant enteric methane (CH4) production by changes in forage type and quality andsupplementation with fat are currently being studied and preliminary results indicate a positive effect. However, theeffects of changing diets in terms of potential CH4 losses from manure storage and biogas potential from slurry inbiogas plants have not been sufficiently studied.The objective of the present work was to evaluate the effect of different strategies to mitigate enteric CH4 emission,including different types of rapeseed (RS) as fat source and varying roughage type and harvest time of silage, on thefeces composition and the subsequent CH4 potential from manure; additionally, these results were compared with thecorresponding enteric CH4 emission. For this purpose two experiments were designed. In the first experiment, sixdifferent diets, divided into two fat levels (low and high) and three different roughage types (early cut grass silage, latecut grass silage and maize silage), were used. The high fat level was achieved by adding crushed RS. In the secondexperiment, the influence of increasing the fat level by using three different types of RS: RS cake, whole seed and RSoil against a low fat ration with no rapeseed fat supplementation was studied. In both experiments feces compositionand ultimate CH4 yield from feces derived from the different diets were analyzed and compared with the correspondingenteric methane emission.The diet and fat level had a significant influence on feces composition and CH4 yield. In general, ultimate CH4 yieldswere higher than the present international default values for diets without extra fat (8-9%) and in feces from dietswith extra fat supply the yield was 25-31% higher. It was possible to predict ultimate CH4 yields from feces by amodel including feed and feces characteristics; in fact, the best correlation was obtained by including both feed andfeces characteristics.Addition of crude fat to diets to dairy cows reduced enteric CH4 emission but at the same time increased CH4 potentialfrom feces, both in terms of organic matter in feces and dry matter intake, which might lead to increasing emissions,unless proper manure handling such as anaerobic digestion is included. Without subsequent anaerobic digestion toproduce energy, the positive effect achieved at cow level is counteracted by increasing manure emissions.



Nitrous Oxide Emission partly alleviates the Methane Mitigation Effect of Nitrate Intake by dairyCattle

S.O. Petersen, A.L.F. Hellwing, M. Brask, O. Hojberg, M. Poulsen, Z. Zhu and P. Lund

Aarhus University, Blichers alle 1, 8830 Tjele, [email protected]

Nitrate supplementation to cattle diets can reduce emissions of CH4 from enteric fermentation. It has been proposedthat NO3

− serves as an alternative H2 sink, but the fate of NO3− in freshly ingested feed is not well understood; if

partly released as N2O as a result of denitrification activity, this could reduce the effectiveness of dietary NO3− for

CH4 mitigation.We quantified N2O emissions as part of a dairy cattle feeding experiment where urea was substituted in iso-N dietswith 0, 7, 14 or 21 g NO3

−-N kg−1 DM from Bolifor. The feeding experiment was designed as a Latin square withrepetition of period 1. Each period lasted 4 wk where CH4 emissions were measured in week 4 using respirationchambers.During period 3, N2O concentrations in outlet air from the chambers were monitored during 48-h periods with a QClaser (LGR Inc.). High, but fluctuating N2O concentrations were seen at the two highest NO3

− levels. To bettercapture the temporal dynamics of N2O emissions, a different strategy was adopted during periods 4 and 5. Gassamples for GC analysis were collected manually from the outlet of all respiration chambers at 15-min intervals during7 h, starting before morning feeding. Feed intake was determined from weight of feed trays every 15 min. Two suchcampaigns were carried out on different days in each period.Overall a clear correlation between feed intake and N2O emission was observed, again with significant emissions atthe two highest NO3

− intake levels. GHG balances for CH4 and N2O (CO2 eq head−1) were calculated for eachNO3

− intake level. Emissions varied considerably between animals and measurement periods. Overall, CH4 emissionalways declined with increasing NO3

− intake, but when N2O emission was taken into account, the CH4 mitigationeffect of NO3

− was to a large extent neutralized. Feed and NO3− excretion via urine were considered as potential

sources of N2O, but could not account for the N2O observed. Pathways to N2O production in the digestive system arenot known at present. There was a strong, but transient accumulation of NO2

− in rumen fluid shortly after feeding.Toxicity effects of HNO2 towards methanogens and nitrifiers, known from other environments, are being explored withmolecular methods.



Ammonia and Greenhouse Gases Emission from Slurry Storage with impermeable Cover and Land-spreading of Cattle Slurry

M. Viguria Salazara, A. Sanz-Cobenab, D.M. Lopeza, H. Arriagaa and P. Merinoa

aNEIKER-Tecnalia, Berreaga 1, parcela 812, E-48160 Derio, Spain; bUniversidad Politecnica de Madrid, CampusCiudad Universitaria, Avenida Complutense 3, 28040 Madrid, Spain

[email protected]

Intensive farm systems handle large volume of livestock wastes, resulting in adverse environmental effects, such asgaseous losses into the atmosphere in form of ammonia (NH3) and greenhouse gases (GHG), i.e. methane (CH4),carbon dioxide (CO2) and nitrous oxide (N2O). In this study, the manure management continuum of slurry storagewith impermeable cover and following cattle slurry band spreading and incorporation to soil was assessed for NH3 andGHG emissions. The experiment was conducted in an outdoor covered storage (flexible bag system) (study I), whichcollected the slurry produced in 7 dairy cattle farms (2,000 m3 slurry) during 12 days in northern Spain. Thereafter,stored slurry was mixed and removed from the storage during 2 hours in order to be applied to land. The landexperiment (study II) consisted on a rectangular plot (2 ha) where 145 m3 of slurry was applied to a bare soil ata rate of 323 kg TN ha−1 using a tanker fitted with trailing-hoses. One day after slurry application, fertilized soilwas turned by means of a moldboard plough machine. The mass-balance integrated horizontal flux (IHF) techniquewas used for estimating gas emissions based on NH3 concentration measurements from masts supporting passive fluxsamplers (PFS) at different heights and GHG concentrations from grab air samples. Furthermore, the backwardLagrangian stochastic (bLS) technique (Windtrax 2.0 software) was compared with NH3 emission estimates from theIHF technique along the manure management continuum. Our results showed low NH3 and GHG emissions fromthe flexible bag storage system, with the highest NH3 and N2O emissions caused by slurry removal from storage.After slurry band spreading to soil, NH3 emission peaked within the first 10 hours (271.5 g N ha−1 h−1). Slurrylandspreading led to higher CO2 and N2O emissions than covered storage, contributing to 75% and 99% of totalemissions, respectively. Differences on NH3 estimates between the bLS and IHF techniques were high in study I andII, which could be attributed to the low NH3 emissions registered and insufficient plot coverage by the PFS underchanging wind directions.In conclusion, the flexible bag system was found to be an effective method of gas emission mitigation in outdoor slurrystorage. A delay in incorporating slurry to soil reduced the efficacy of incorporation on NH3 abatement. AverageNH3 concentration and wind direction within 24 hours could result in uncertain bLS estimates under changing winddirections.



Methane Emission by Beef Steers on natural Grassland in Southern Brazil

T. Genroa, B. Fariab, M. Da Silvaa, G. Amaralc, I. Cezimbrab, J. Savianb, A. Berndtd, C. Bayerb and P. Carvalhob

aEMBRAPA Southern Region Animal, BR 153 Km 633, Cx. Posta 242, 96401-970 Bage/rs, Brazil; bUniv. Federaldo Rio Grande do Sul (UFRGS), Av. Bento Goncalves 7712, 90050321 Porto Alegre, Brazil; cFEPAGRO, BR 293,km 165, 96400-970 Bage, Brazil; dEmbrapa Southeast Livestock, Rodovia Washington Luiz, km 234, 13560-970 Sao

Carlos - Sp, [email protected]

Natural grasslands are the main basis for beef cattle production systems in South Brazil, North Argentina and Uruguay.The data about methane emission in this environment are few and not available yet. This work aimed evaluatingmethane emission (CH4) per animal and per kilogram of meat produced by finishing beef steers on natural grass-lands with different levels of intensification. The experiment was carried out at Embrapa Southern Region AnimalHusbandry, Bage (lat 31◦19’51S, long 54◦06’25W and 212 m a.s.l.), Rio Grande do Sul, Southern Brazil. Three plotsof 7 ha natural grasslands were assigned to each of the three treatments: (i) natural grassland (NG); (ii) NG plusfertilization (NGF) ie 70 kg ha−1 P2O5 in 2007 and 100 kg N ha−1 in 2008; and (iii) NGF plus overseeding of annualryegrass (Lolium multiflorum) and red clover (Trifolium pretense) (NGFS). Each treatment was three replicationspaddock and each paddock had three animals testers (nine animals testers per treatment), and variable stocking ratein order to maintain 12% of herbage allowance. The animals were 27 Hereford steers with 1-2 years. Methane emissionswere measured using the sulfur hexafluoride (SF6) technique by stainless collecting tubes connected to the animals’nostrils during five days in each evaluation. Evaluations were made during the summer (January, 21-26), autumn(June, 5-10), winter (July, 22-27), and spring (October, 28 - November, 2) in 2013. The CH4 concentration in thetube was measured with gas chromatograph. The animals were weighed in the beginning of experiment and every 28days to determine live weight gain (LWG).No difference was observed (P>0.05) in the amount of kg of CH4 emission per kg of live weight gain per hectare per year(g CH4.kg

−1 LWG). Means values were 183 ± 0.78, 199 ± 0.78 e 320 ± 0.74 kg CH4.kg LWG−1.ha−1.year−1 to NG,NGF and NGFS treatments, respectively. No difference was observed (P>0.05) in kg CH4 emission.animal−1.year−1,with means values of 31.60 ± 7.31, 42.87 ± 6.93 e 46.33 ± 7.31 to NGF, NGFS and NG treatments, respectively. It isimportant highlight that the average values to methane emissions per animal are below the proposed values by IPCCfor this animal category. Natural grasslands when well managed present potential to produce quality meat with lowvalues of methane emission, reducing the impact to the environment.


Plenary session 2: Understanding the technical potential formitigation and adaptation


Mon. 14:15 Medici Plenary session 2: Understanding the technical potential for mitigation and adaptation

IPCC WGIII Findings on Animal Agriculture Mitigation Potential

P. Smith

University of Aberdeen, Institute of Biological & Environmental Sciences, 23 St Machar Drive, AB24 3UU Aberdeen,UK

[email protected]

Feeding 9-10 billion people by 2050 and preventing dangerous climate change are two of the greatest challenges facinghumanity. Both challenges must be met while reducing the impact of land management on ecosystem services thatdeliver vital goods and services, and support human health and well-being. Few studies to date have consideredthe interactions between these challenges. The supply- and demand-side climate mitigation potential available inthe Agriculture, Forestry and Other Land Use (AFLOU) sector, as synthesised in the IPCC WGIII AR5 are brieflyreviewed, with a special focus on animal agriculture. Some of the synergies and trade-offs afforded by mitigationpractices are outlined, before an assessment of the mitigation potential possible in the AFOLU sector under possiblefuture scenarios is presented, in which demand-side measures co-deliver to aid food security.We conclude that while supply-side mitigation measures, such as changes in land management, might either enhanceor negatively impact food security, demand-side mitigation measures, such as reduced waste or demand for livestockproducts, should benefit both food security and greenhouse gas (GHG) mitigation. Demand-side measures offer agreater potential (1.5-15.6 Gt CO2-eq. yr−1) in meeting both challenges than do supply-side measures (1.5-4.3 GtCO2-eq. yr−1 at carbon prices between 20 and 100 US$ tCO2-eq. yr−1), but given the enormity of challenges, alloptions need to be considered. Supply-side measures should be implemented immediately, focussing on those thatallow the production of more agricultural product per unit of input. For demand-side measures, given the difficultiesin their implementation and lag in their effectiveness, policy should be introduced quickly, and should aim to co-deliverto other policy agendas, such as improving environmental quality or improving dietary health.These problems facing humanity in the 21st Century are extremely challenging, and policy that addresses multipleobjectives is required now more than ever.



The Complexity of System Boundaries when it comes to Mitigation Measures

C. Cederberg and M. Persson

Chalmers University of Technology, Department Energy & Environment, SE 41296 Gothenburg, [email protected]

Two critical factors to address in environmental system analysis of future livestock production are: 1) the link betweenmilk and beef production, and 2) the competition for land, possibly leading to land use change (LUC) with greenhousegas (GHG) emissions and loss of biodiversity as important implications. System boundary setting is an importantmethodological choice concerning these factors. Different approaches can lead to contradictory results in studies ofenvironmental impact of animal products which are exemplified and discussed in this presentation.Interaction between milk and beef productionIntensification (increasing milk yield per cow) is typically one of the solutions suggested in order to reduce GHGemissions from milk production. This conclusion is made from several LCA and footprint studies that so far mostlyhave calculated GHG emissions from dairy farming with the farm gate as system boundary using a fixed allocationratio (e.g. based on price relation between meat and milk) (Flysjo et al., 2012). When instead modelling a milk systemalso including the affected background system beef, this means expanding the system boundary in the analysis. Thisis a dynamic approach better reflecting the ”real world” and it recognizes that there is a higher beef production perkg milk in lower yielding milk systems. Zehetmeier et al. (2013) compared GHG emission intensity for a high-yieldingmilk-oriented Holstein Friesian system (10 000 kg milk/cow*yr) with a dual-purpose Flekvieh system (6 000 and 8000 kg milk/cow*yr) and when expanding the milk system also to include beef production outside the dairy system,the results showed that the dual purpose systems produced milk with lower GHG emission intensity than the highintensity Holstein Friesian system, due to high GHG credits for avoided beef production from pure beef systems. Inanalysis of future strategies for milk production, we recommend that extended system boundaries should be examinedin the analysis, so that milk and beef are studied in an integrated approach in order to avoid sub- optimisation. Adevelopment towards more dual-purpose milk systems can have positive side-effects when it comes to animal welfareand health, reduced dependence of high quality feed and cropland without compromising GHG emissions.LUC emissionsDespite the fact that agriculture is the main driver of deforestation, LCA and footprint studies of agriculture com-modities (also including livestock products) generally do not include LUC impacts (due to the lack of a consensusmethodology) and studies that do account for LUC arrive at very different results depending on the choice of ap-proach (Persson et al., 2014). Much of the differences in results can be attributed to differences in the choice of systemboundaries, specifically whether one account solely for the direct contribution of a commodity to LUC or also itsindirect effects. In the one end of the spectra, one can analyze the carbon footprint of production directly on clearedforest land, leading to very high estimates (e.g. 726 tCO2/tCW and 6.1 tCO2/t for beef and soy, respectively, inthe Brazilian Amazon; Cederberg et al., 2011, Persson et al., 2014). On the other end, one can distribute the globalemissions from LUC over all agricultural production or all crops that are expanding in area, generally leading to muchlower footprints for the commodities directly causing LUC.These different approaches have implications also for the policies aiming to mitigate LUC. The direct approach wouldpoint to measures targeted to the producers and commodities implicated in LUC, the Brazilian soy moratorium beinga case in point. However, targeted interventions run the risk of causing leakage effects (e.g. Brazilian soy productionexpanding on pastures, pushing cattle farmers instead into the forest). The indirect approach, on the other hand,would favor lowering the overall (global) land demand. However, it provides no incentive to individual producers toimprove production practices by reducing deforestation, as the footprint is equal for all producers and is determinedby the national or global deforestation rate and the total area expansion rate for the commodity in question.ReferencesCederberg C, Persson M, Neovius K, Molander S, Clift R. 2011. Including carbon emissions from deforestation in thecarbon footprint of Brazilian beef. Environmental Science & Technology 45:1773-1779


Flysjo, A., Cederberg, C., Henriksson, M, and Ledgard, S. 2012. Interaction between milk and beef production andemissions from land use change - Critical considerations in life cycle assessment and carbon footprint studies of milk.Journal of Cleaner Production, 28, 132-142.Persson M, Henders S, Cederberg C. 2014. A method for calculating a land-use change carbon footprint (LUC-CFP)for agricultural commodities - applications to Brazilian beef and soy, Indonesian palm oil. Manus submitted to GlobalChange BiologyZehetmeier M, Baudracco J, Hoffman H, Heißenhuber A. 2012. Does increasing milk yield per cow reduce greenhousegas emissions? A system approach. Animal 6:1, 154-166.



Climate Change and Livestock: Impacts and Adaptation

J.-F. Soussana

INRA UR 874, Grassland Ecosystem Research, 63100 Clermont Ferrand, [email protected]

Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decade since1850 (IPCC, 2013a) and the current mean global temperature is slightly above the temperature range experiencedsince the start of agriculture (ca. 10,000 yrs BP).Livestock production is impacted by heat. In the U.S., current economic losses due to heat stress of livestock areestimated at several billion USD annually. With intensive systems, heat stress reduces dairy and meat productionfor mean air temperatures above ca. 21◦C. Metabolic heat production increases and the capacity to tolerate ele-vated temperatures decreases in highly productive breeds and heat tolerance is reduced by single-trait selection forproductivity.Climate change has affected animal health. The spread of bluetongue virus in sheep across Europe has been partlyattributed to climate change through increased seasonal activity of the Culicoides vector. Ticks, the primary arthropodvectors of zoonotic diseases in Europe (e.g. Lyme disease and tick- borne encephalitis), have changed distributionstowards higher altitudes and latitudes with climate change (IPCC, 2013b).Climate extremes had large impacts on livestock systems over the past decades. Between 1980 and 1999, severedroughts have caused mortality rates in national herds of between 20% and 60% in several arid sub-Saharan countries.Extreme heat and drought events (e.g. summer 2003 in Europe, USA in 2005-2007, Australia in 2001-2007) negativelyaffected pastures and grazing livestock. For instance, a green fodder deficit of up to 60% affected regions in France andSwitzerland during the summer 2003 heat and drought and fodder had to be imported from as far away as Ukraine.In many semi-arid and arid regions, livestock systems face multiple stressors that can interact with climate changeand variability to amplify the vulnerability. These stressors include rangeland degradation, increased variability inaccess to water, fragmentation of grazing areas, changes in land tenure, conflicts and insecure access to land, markets,and other resources.By the end of the XXIst century, depending on the level of radiative forcing by anthropogenic greenhouse gas emissions,the global temperature rise may vary between 1.5 and 4◦C relative to 1850-1900 (IPCC, 2013a). Amplification of thehydrological cycle is forecast to lead to more extreme intra-annual precipitation regimes characterized by larger rainfallevents and longer intervals between events. Increased aridity and persistent droughts are projected for northern andsouthern Africa, southern Europe and the Middle East, parts of the Americas, Australia and South East Asia.Problems of water supply for increasing livestock populations will be exacerbated by climate change in many placesin sub-Saharan Africa and South Asia. Although small in comparison to the water needed for feed production,drinking water provision for livestock is critical, and has a strong impact on overall resource use efficiency in warmenvironments. The cost of supplying livestock water from boreholes is likely to increase. Livestock production willbe indirectly affected by water scarcity through its impact on crop and pasture production and subsequently theavailability of forage, crop products and crop residues for livestock feeding.Without adaptation, warming and drying conditions are projected to reduce milk and meat production in a numberof sub-tropical and tropical regions, partly through direct heat and water scarcity impacts and partly through indirecteffects on feed resources. Loss of livestock under prolonged drought conditions is a critical risk (IPCC, 2013b).Heat-tolerant livestock may become more prevalent in response to warming trends. For example, higher temperaturesin lowland areas of Africa could result in reduced stocking of dairy cows in favor of cattle, a shift from cattle to sheepand goats, and decreasing reliance on poultry. Conversely, livestock keeping, in cold-limited regions, would potentiallybenefit from increased temperatures. Epidemiological surveillance and increased coordinated regional monitoring andcontrol programs have the potential to reduce the incidence of vector-borne animal diseases.Pastures response to climate change is dominated by compensatory effects of elevated CO2 and temperature on soilwater availability and use. In temperate regions, climate change may increase grassland production into late fall and


early spring, thereby reducing the need for forage stocks in winter. However, increased risks of forage production lossesduring summer are likely. Changes in forage quality could increase the nutritional stress for cattle grazing nutrientpoor pastures.Resistance, resilience and transformation strategies can be used for adaptation. Resistance strategies seek to main-tain the status quo over the near term. They include re-sowing a pasture after it has failed because of a drought,frequently burning a degraded and encroached rangeland to restore herbage growth, etc... Such resistance strategiesare widespread currently, and they may be useful in the short term to cope with climatic variability. However, theyare likely to fail in regions exposed in the future to e.g. prolonged droughts and heat waves as they may underminethe long-term livelihood security.Resilience strategies (or more systemic adaptation) are typically proactive actions that increase the adaptive capacityso as to return to a healthy condition after a climate disturbance with minimal management intervention. Resiliencecan be increased by changes in grazing management, in forage and grain crop species, in animal breeds and in farmbuildings. Such strategies are already in place in some regions, but their future development may require advancedtechnologies such as seasonal forecasting of weather conditions and geo-monitoring of crops and pastures.Transformation strategies may require livestock farmers to rely to a greater extent on diversified feed sources (e.g.conserved forage, crop residues and by- products) and to change farming systems e.g. through crop-livestock integrationand sylvo-pastoralism. Contrasted options are available in temperate and tropical climates and in extensive andintensive livestock systems.Climate smart systems that sustainably increase productivity and resilience (adaptation), reduce greenhouse gasemissions (mitigation), and enhance food security and development could be promoted to face climate change. Byreducing productivity gaps and increasing livestock production efficiency, they would also contribute to mitigateclimate change from tropical deforestation and the expansion of grasslands into savannahs.ReferencesIPCC 2013a. Working Group I contribution to the Fifth Assessment Report. Climate Change 2013. The PhysicalScience Basis.IPCC 2013b. Working Group II contribution to the Fifth Assessment Report. Climate Change 2014: Impacts,Adaptation, and Vulnerability.



Determinants of Livestock Farmers’ Perception of future Droughts and Adoption of mitigating Plans

M. Rakgasea and D. Norrisb

aUniversity of the Free State, P.O. Box 339, 9300 Bloemfontein, South Africa; bUniversity of Limpopo, Departmentof Animal Science, Private Bag X1106, 0727 Sovenga, South Africa

[email protected]

A number of studies suggest that climate change effects such as global warming are causing more frequent and intensedroughts throughout the world. The Southern African region with its relatively low rainfall index and a variabilitythat even exceeds that of the Sahel region is prone to frequent drought occurrences. Climate change is regarded as akey emerging environmental issue in South Africa as the country is located in one of the regions most prone to thephenomenon. Understanding of farmers’ perceptions of drought and climate change may assist in informing policydecisions and development of appropriate intervention strategies.The objective of the study was therefore to determine if there is an association between socio-economic profile oflivestock farmers and their perception of climate change and related events (drought). The study was conductedat five local municipalities (Molelemole, Aganang, Blouberg, Polokwane and Lephalale) of the Limpopo Province,South Africa. Discriminant analysis was used to assess the relative importance of the discriminating characteristics(socio-economic characteristics) through the utilization of the weights of the discriminant function. Group Statisticsand Tests of Equality of Group Means (Wilk’s Lambda and F-ratio) were used to examine whether there were anysignificant differences between groups on each of the independent variables. The standardized canonical coefficients,structure matrix, eigen values, structure coefficients and Wilk’s Lambda values were used to evaluate the importanceand contributions of each socio-economic characteristic. Age, education and literacy levels and farm type, locationand gender were important predictors of how farmers perceive climate change and drought phenomena.The findings suggest that factors that influence perceptions of farmers on climate change should be incorporated intolong-term planning and adjustment of adaption and mitigation programs.



Important Differences in Yield Responses to Drought among four functional Types of Species andacross three European Sites

D. Hofera, M. Sutera, N. Hoekstrab, E. Haugheyb, J. Finnb, N. Buchmannc and A. Luschera

aAgroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland; bTeagasc, Johnstown Castle, Wexford, Ireland; cETHZurich, Institute of Agric. Sciences, Zurich, Switzerland

[email protected]

Summer droughts are predicted to increase in frequency due to climate change and to impair forage production ingrassland leading to considerable loss of income for farmers. We evaluated drought resistance in intensively managedgrassland by using four model species representing different functional types, which were defined as the factorialcombination of traits related to symbiotic dinitrogen (N2) fixation and rooting depth, resulting in the following set: anon-fixing, shallow-rooted species (Lolium perenne L.), a non-fixing, deep-rooted species (Cichorium intybus L.), anN2 fixing, shallow-rooted species (Trifolium repens L.), and an N2 fixing, deep-rooted species (Trifolium pratense L.).A summer drought period of ten weeks with complete exclusion of precipitation was simulated using rainout sheltersin a common field experiment at three sites (Tanikon CH, Reckenholz CH, Wexford IE; three replicates of speciesand treatment per site). Nitrogen content in aboveground biomass was analysed (Swiss sites only) and compared tocritical N concentrations known to limit plant growth.Aboveground biomass production was impaired in the drought treatment at all three sites, the mean reduction (com-pared to a control) was 30% at Tanikon, 48% at Reckenholz, and 85% at Wexford. Different functional types of speciesvaried in their drought resistance: N2 fixing species showed only 8% and 28% biomass reduction at Tanikon and Reck-enholz, respectively, compared to 51% and 68% for the non-fixing species. At Wexford, however, only the deep-rootedspecies C. intybus was able to counteract drought to some degree (57% biomass reduction compared to 94% reductionfor the other three species). Regarding N concentrations in biomass, N2 fixing species were not N- limited at the twoSwiss sites, neither under control nor under drought conditions, while non-fixing species were strongly N-limited underdrought. It was hypothesized that the differences in pattern of species’ responses are related to differences in droughtseverity among sites. Under moderate drought, as at the Swiss sites, the N2 fixing species had a growth advantagebecause they have access to N through symbiotic N2 fixation despite restricted uptake from dry soil. In contrast, thenon-fixing species did suffer from reduced availability of mineral N under drought. Under severe drought stress, as atthe Irish site, N2 fixation is strongly impaired and deep-rooted species might better resist the stress.We conclude that cropping combinations of N2 fixing and deep-rooted species can be an important management optionunder future climate conditions.



Effect of Manure Treatment on Greenhouse Gas Emissions from Agriculture. The Case of the Nether-lands.

J. Mosquera Losada, P. Hoeksma, R. Melse and N. Verdoes

Wageningen UR Livestock Research, Vijfde Polder 1, 6708 WC Wageningen, [email protected]

The Netherlands reports every year its annual greenhouse gas emission level following the Guidelines provided by theUnited Nations Framework Convention on Climate Change (UNFCCC), the Kyoto Protocol and the European Union’sGreenhouse Gas Monitoring Mechanism. The in-country review of the UNFCCC in 2011 strongly recommended toinclude the effects of manure treatment on the emissions of non- CO2 greenhouse gases (i.e. methane and nitrousoxide) in the Dutch National Inventory Report (NIR). Manure treatment is seen as an option to reduce the manuresurplus in the Netherlands, and its use is expected to increase as a result of announced new manure policies, which willforce livestock farms to process their manure surplus. However, knowledge of the environmental impact (emissions ofmethane, nitrous oxide, ammonia, odour, particulate matter) of manure treatment techniques is still scarce.Manure treatment affects the storage time of fresh manure and the amount of raw manure that is applied directly onagricultural land. Besides, as a result of manure treatment other end products are generated that might be furthertreated, stored or applied to soil as a fertilizer. Greenhouse gas mitigation measures may influence emissions differentlyat different stages of the manure management chain. Therefore, the associated impact on emissions through the wholemanure chain should be considered.In this paper, the main manure treatment technologies used in the Netherlands which affect greenhouse gas emissionsare identified, based on the actual and expected amount of manure treated. Main treatment processes are brieflydescribed, the main emission sources related to manure treatment systems are identified, and measurement methodsto estimate emissions from these sources described. Finally, the available emission data concerning the treatmentprocesses themselves and from the entire treatment chain (i.e. including emissions from storage and application ofmanure products) are discussed.



Alternative Techniques to appraise Adaptation Options in the Livestock Sector: are robust Methodsthe Way forward?

R. Dittrich

Scotland’s Rural College, West Mains Road, EH9 3JG Edinburgh, [email protected]

Some climate change adaptation in the livestock sector will be reactive but the greatest benefits will come fromreducing risks before the impacts occur and impose high costs. It is thus vital to ensure that under- or over-investmentin adaptation is avoided. Hence, a thorough understanding of the likely costs and benefits of adaptation is crucial.This work explores alternative methods to appraise adaptation options to climate change with an application to thelivestock sector. Appraising (adaptation) investment aims to provide the best possible guidance for the allocation ofresources, i.e. the optimum choice. Yet, applying standard optimality methods such as cost-benefit analysis in an areaof high uncertainty such as climate change adaptation is challenging. The costs of adaptation might be observable andimmediate, the benefits are uncertain. While still widely used in investment appraisal, the limitations of traditionaloptimisation methods have been recognised. Alternative decision making methods, so called robust approaches aretherefore being explored. Robust approaches select projects that meet their purpose across a variety of futures byintegrating a wide range of climate scenarios and are thus particularly suited for deep uncertainty. However whilethe potential of robust methods is widely discussed, their take up in project appraisal and specifically in the livestocksector is low.Given this context, the weaknesses and strengths of different robust methods are explored with regard to the mech-anisms used to integrate climate scenarios, the measurement of costs and benefits and data requirements. For eachmethod, the applicability to the livestock sector is discussed.While there appears to be potential for applying robust methods to the livestock sector, lack of data is a limitingfactor and the characteristics of adaptation options do not lend themselves easily to their application. Furthermore, itappears that possible higher upfront costs and a productivity-robustness trade-off can prevent the implementation ofrobust methods if decisions are made with a short-term view. It also seems that so far the complexity of many robustmethods may play a limiting role. While it is thus necessary to develop, where possible, more generic toolkits in thelong term, a first step guidance for decision makers is required to understand which method is best suited to evaluatedifferent adaptation options.This work addresses this difficulty by presenting a simple framework based on characterising the adaptation problemwith regard to uncertainty, the structure of the adaptation options and the data availability.



Dietary Fibre in Pig’s Diets: Effects on Greenhouse Gas Emissions from Slurry Storage to FieldApplication

F. Estellesa, A. Sanz-Cobenab, A. Beccacciab, W. Antezanaa, M. Cambra-Lopeza, P. Ferrera, A. Cerisueloc, P.Garcia-Rebollarb, A. Vallejob, C. De Blasb and S. Calveta

aUniversitat Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia, Spain; bUniversidad Politecnica deMadrid, Campus Ciudad Universitaria, Avenida Complutense 3, 28040 Madrid, Spain; cCITA-IVIA, Poligono la

Esperanza, 100, 12400 Segorbe, [email protected]

Pig’s slurry is a key source of greenhouse gases (GHG). In Spain, GHG emissions (CH4 + N2O) from pig slurry (storageand land application) accounted in 2011 for 18.4% of total GHG emissions (in CO2- equivalent) of the agriculture sectoraccording to the National Inventory Report (NIR). Slurry composition can be modified through diet manipulation.The aim of this work was to evaluate the effect of different fibre types in fattening pigs’ diets on GHG emissions frompig slurry storage and field application.Thirty fattening pigs (85.4±12.3 kg initial live weight) were fed five diets with similar contents on NDF: a commercialdiet (C) based on wheat and barley, two diets with orange pulp (OP) as fermentable fibre source at two inclusion levels(7.5%, OP7.5 and 15%, OP15), and two diets with carob bean (CB) as non- fermentable fibre source at two inclusionlevels (7.5%, CB7.5 and 15%, CB15). Slurry was collected from each animal individually during 7 consecutive days.Slurry was chemically analysed for volatile solids content (VS) and CH4 yield potential (B0). Emission factors formanure storage were calculated for each animal following Intergovernmental Panel on Climate Change (IPCC) andNIR guidelines. Moreover, slurry samples from each treatment were experimentally surface-applied to a grassland(Lollium perenne) soil and CO2-equivalent (N2O + CH4) fluxes were measured during 40 consecutive days.Average volatile solid excretions (VS, kg/animal and day) were significantly higher in animals fed the highest non-fermentable fibre level (CB15) compared to the other dietary treatments (P<0.05). The B0 (ml CH4/kg VS) werenot different among treatments averaging 350 ml/kg VS. The CH4 EF (kg CO2- equivalent/animal and year), was notdifferent among treatments (p>0,05), resulting in the following values: 132.72 (C), 160.86 (OP7.5), 135.03 (OP15),152.67 (CB7.5) and 165.27 (CB15). If considering total slurry produced from animals in each treatment, greenhousegas fluxes from soil expressed as mg CO2- eq/animal and day resulted in 11.55 (C), 6.43 (OP7.5), 4.62 (OP15), 9.97(CB7.5) and 9.85 (CB15).Our results indicate that fermentable fibre (from OP) has a strong potential in reducing GHG in field application ofpig slurry not affecting EF from pig storage.This project was funded by the Spanish Ministry of Science and Innovation (AGL2011-30023-C03) and the ValencianGovernment (ACOMP/2013/118).



Effects of simulated Drought on Species Composition and Biomass Yield of semi-arid Grassland, SouthAfrica

D. Gemiyoa, A. Hassena and E. Tesfamariamb

aUniversity of Pretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria,South Africa; bUniversity of Pretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South Africa, 0028 Pretoria,

South [email protected]

Water availability is the primary constraint to biomass yield and aboveground net primary productivity in grasslandecosystems, and is one of the main variables that will be significantly influenced by future climate changes in SouthernAfrica. This study was conducted at the experimental farm of University of Pretoria to assess the efficiency of rainoutshelters in intercepting fixed proportion of rain water to simulate different level of drought and the effect of simulateddrought on species composition and biomass yield.Four different levels of rainfall interception (0%, 15%, 30% and 60%) were tested in a completely randomized blockdesign with five replications. Water and light interception and biomass yield of major plant species were estimatedat first harvest in November 2013 and second harvest in January 2014. Generally, percent light transmittance wasnot significantly different between the treatments and had an average value of 91.4 + 3.2%. The 15%, 30% and60% rainfall interception plots diverted 18.70 + 2.17 %, 32.22 + 2.81 % and 58.95 + 1.49 % of the ambient rainfallevents, respectively. The ambient, 15% and 30% interception plots were dominated by Ipomoa crassipes (forb) andElephantorrhiza elephantina (dwarf shrub) and Digitaria eriantha and setaria sphacelata var. Torta as major grassspecies. In contrast, Eragrostis Lehmanniana was a dominant grass in the 60% interception plots. The herbage yieldof the first harvest for 0% (20.62 + 1.75 g/m2) interception was higher (P <0.0001) compared with 15% (10.13 +1.69 g/cm2), 30% (10.81 + 1.50 g/cm2) and 60% (8.55 + 1.47 g/cm2) rain interception plots. Similarly, the herbageyield of the second harvest for 0% (56.45 + 5.64 g/cm2), 15% (47.21 + 4.33 g/cm2) and 30% (50.20 + 4.93 g/cm2)interception was significantly higher (P <0.001) than 60% (28.71+ 2.29 g/m2) plots. Rainfall use efficiency (RUE) ofthe first harvest ranged from 1.71 + 0.24 kg/mm in 15% to 2.45 + 0.20 kg/mm in 0% plots. In the second harvest, the30% rain interception plots had significantly higher (P <0.05) RUE (9.79 + 1.01 kg/mm) than the other treatments.The results indicate that simulated drought of 60% results in an overwhelming negative effect on biomass yield of thesemi-arid grassland ecosystem.



In Vitro Evaluation of tropical Forages from the Sahel region of Senegal for their methanogenic Po-tential

A. Baccouchea, D. Morgavib, B. Boisc, L. Genestouxb, P. Lecomted,c, A. Ickowiczc, T. Diope and M. Doreaub

aINRAT, Rue Hedi Karray, 2049 Ariana, Tunisia; bINRA, Theix Centre, 63122 St Genes Champanelle, France;cINRA SupAgro, Cirad Campus international, 34700 Montpellier, France; dCIRAD - UMR Selmet, Campus

International Baillarguet, 34398 Montpellier Cedex 5, France; eISRA, Dakar, [email protected]

The capacity of forages from the Sahel area to produce methane is scarcely known. In this semi-arid tropical region, invivo measurements are difficult to implement. Therefore, prediction of the methanogenic potential of forages would bea useful tool for evaluating methane emission. Tropical grasses, legumes and shrubs were harvested in Senegal duringdry and rainy seasons. They were collected mainly in the Ferlo area (Sahelian climate <400 mm annual rainfall),and also in Sine Saloum area (Sudano-Sahelian climate) and Casamance region (Sudanian climate, >900 mm annualrainfall).The aims of this study were to evaluate the methanogenic potential of these forages using the in vitro gas productiontechnique, and to correlate this methanogenic potential to plant chemical composition and fermentation characteristics.Ninety-seven samples of forage plants were used in this study. Each sample (0.4 g) was incubated under anaerobicconditions with rumen fluid and a buffered mineral solution at 39◦C. Rumen fluid was taken before the morning feedingfrom three rumen-cannulated Texel wethers receiving daily 1 kg of tropical hay. After 24 h incubation, gas productionwas measured using a pressure transducer and composition was analyzed by gas chromatography (GC). Volatile fattyacids (VFA) in the liquid were determined by GC. Contents of the fermentation bottles were centrifuged and pelletdried for determination of the dry matter degradability (DMD). The chemical composition of forages (NDF, ADF,crude protein) was estimated by near infrared reflectance spectroscopy (NIRS).Crude protein and ADF varied widely among samples (from 1.3 to 33.9% and from 15.4 to 56.8%, respectively).Methane production also varied in a large range (from 10.2 to 44.6 ml per g DM in our experimental conditions),and this range remained high when methane was expressed per g digestible DM or per g fermented organic mattercalculated from VFA production. Regression analysis was used to determine the relationship between gas production,methane, VFA, DMD and chemical composition.The first results show that prediction of methane emission from chemical composition is of low accuracy within therange of studied forages. Methane emission was higher for rainy season than for dry season and for grasses than forshrubs.



Seasonal Variation in Composition of Cow Milk for Grana Padano Cheese Production

A. Vitalia, L. Bertocchib, N. Laceteraa, A. Nardonea and U. Bernabuccia

aUniversity of Tuscia, Via S. Camillo de Lellis, snc, 01100 Viterbo, Italy; bIZS Lombardia e Emilia Romagna, ViaBianchi, 9, 25124 Brescia, Italy

[email protected]

A retrospective study on seasonal variations in the characteristics of cow’s milk used to produce Grana Padano cheesewas conducted on bulk milk samples collected from 2003 to 2012. Data were referred to 316,761 bulk milk data itemsrecorded in 2,471 dairy farms from the Lombardy region, Italy. Milk characteristics data were somatic cell count(SCC as cell/ml), total bacterial count (TBC as colony-forming units/ml), fat percentage (FA%), protein percentage(PR%), lactose percentage (LCT%), anaerobic sporigens (SP as spore/l), and urea (UR as mg/ml).The model showed a significant association between the parameters of milk with the season. The results showed anincrease in SCC and TBC and a decrease in FA% and PR% in correspondence of summer months. The means values(±SD) of SCC and TBC were greater in the summer (p<0.01) and the higher values were recorded in August andJuly for SCC (376,914±214,060) and TBC (43,257±158,265), respectively. The FA% and PR% were lower (p<0.01)in summer, and July represented the most critical month with values of 3.70±0.22 and 3.31±0.12 for FA% and PR%,respectively. The LCT% was related to milk yield and it was greater in spring and lower in fall (p<0.01) with maximum(5.04±0.08) and minimum (4.97±0.09) values in March and September, respectively. The SP were lower in spring(p<0.01) compared to the other seasons and, among months, March (225±635) and August (330±839) presented thelowest and highest SP values, respectively. The UR was greater in spring and summer (p<0.01) and June showed outthe highest values (24.02±4.94).Results indicated seasonal differences in milk composition. The higher values in UR and LTC in spring might berelated to the photoperiod. The increase in daylight affects positively the feed intake with consequent increases in UR,LTC and milk yield. The lower values of SP in spring are hypothesized to be a dilution effect related to the greater milkyield. High temperatures in the summer were critical for milk quality with a negative impact on milk price, cheese yieldand cheese seasoning. The present climatic condition suggests the necessity of adopting structural (fans, sprinklers,shades) and management (feeding, reproduction, milking) adaptation strategies and to develop selection schemes toget animals more thermo-tolerant for long-term adaptation response. Such options should be implemented to ensurewelfare and productivity of dairy cows and to limit the related economic losses under the present Mediterraneanclimate and even more for future warming scenarios.



Effect of tropical Plants containing condensed Tannins on Fermentation, Digestibility and MethaneProduction in Sheep

M. Riraa, D. Morgavia, H. Archimedeb, C. Marie-Magdeleineb, L. Genestouxa, H. Boussebouac and M. Doreaua

aINRA, Theix Centre, 63122 St Genes Champanelle, France; bINRA, Unite Recherches Zootechniques, 97170Petit-Bourg, Guadeloupe; cUniversite Mentouri, LGMA, 25000 Constantine, Algeria

[email protected]

Tannins can have adverse or positive effects on ruminants depending on their source and concentration in the diet.Glyricidia sepium, Leucaena leucocephala and Manihot esculenta are tannin-rich plants abundant in humid tropics.In this work a) the effect of increasing doses of Glyricidia, Leucaena and Manihot on fermentation was tested in vitroand b) digestibility and methane production were tested in sheep receiving diets rich in Glyricidia, Leucaena andManihot which contained 39, 75 and 92 g/kg condensed tannins, respectively.In vitro, these substrates were incubated in fermentors for 24 h alone or mixed with Dichanthium spp, a tannin-freeforage, so that proportions of tannin-rich forage were 0:100, 25:75, 50:50, 75:25 and 100:0.All tannin-rich plants reduced methane emissions in a dose-dependent way but volatile fatty acids (VFA) productionand thus fermented organic matter decreased too, especially for Manihot. In contrast, VFA composition was un-changed. The effect of tannin was more pronounced for Leucaena and Manihot than for Glyricidia, because of a lowertannin concentration in this latter forage, without significant interactions between dose and forage type. The responseto increasing doses of tannin-rich plants was linear for most variables. For low to medium tannin doses, the extent ofmethane decrease was more pronounced than that of VFA, suggesting that moderate abatement in emissions mightbe achieved with minor negative effects on feed fermentation.The in vivo trial was performed on eight wethers from two breeds (Texel and Blackbelly) in two 4 X 4 Latin squaredesigns. Animals received four diets ad libitum: Dichanthium hay alone (Con) or combined with pellets made fromleaves of Glyricidia, Leucaena or Manihot with on average 44% pellets in the diet. Dry matter intake increased inmixed diets (P<0.01) and was lower (P = 0.04) with Texel than with Blackbelly.Organic matter digestibility did not change among diets and genotypes. Methane production per kg DM intake washigher with Con than with tannin-rich diets (P<0.01) and in Texel than in Blackbelly (P = 0.03). As for in vitro, effectof Glyricidia was lower than that of Leucaena and Manihot, certainly due to a lower tannin content. Methanogens andprotozoal numbers were unchanged. Decreased retention time of feed in the rumen with pelleted diets may partiallyexplain reduction in methane production.Condensed tannins showed in vitro and in vivo potential to mitigate CH4 production in ruminants, without noticeableadverse effects on ruminal fermentation and digestibility.



Evaluation of Crop Models SwbSci and STICS in South Africa

E. Tesfamariama, G. Bellocchib, F. Rugetc and A. Hassend

aUniversity of Pretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South Africa, 0028 Pretoria, South Africa;bINRA, UREP-Grassland Ecosystem Research, 5 chemin du Beaulieu, 63039 Clermont-Ferrand, France; cINRA,

UMR 1114, EMMAH, F 84914 AVIGNON Cedex 9, 84914 Avignon, France; dUniversity of Pretoria, Department ofAnimal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria, South Africa

[email protected]

STICS and SwbSci are process-based crop models with a mechanistic view of crop growth and development, andwater and nitrogen balances, which are simulated daily based on soil, weather, crop and management inputs. STICShas been developed at INRA (France) since 1996 and has been successfully used to simulate crops and grasses intemperate and Mediterranean areas. The model has never been tested in sub-Saharan African conditions. SwbSci hasbeen developed at University of Pretoria (South Africa) since 1997 and has been successfully tested in South Africafor various crops, grasses and vegetables.The aim of this study was to evaluate the performance of STICS and SwbSci models to simulate, under the SouthAfrican climatic conditions, C4 plants such as weeping lovegrass (Eragrostis curvula (schrad.) Nees) and maize (Zeamays Pan6966). Both models were calibrated for these crops using data collected during the 2004/05 growing seasonfrom irrigated and rainfed experimental plots at the East Rand Water Care Works, Johannesburg, Gauteng, SouthAfrica (1577 m a.s.l., 26o 01’ S, 28o 16’ E). Model validation was performed using independent data sets collectedduring the 2005/06 growing season. Model accuracy was assessed based on a set of performance indicators. Bothmodels were successfully calibrated for weeping lovegrass as all the statistical parameters were within the prescribedranges [index of agreement (d) > 0.8; relative mean absolute error (MAE%) < 20%; coefficient of determination(r2) > 0.8]. The results indicate that STICS simulated aboveground biomass (TDM) of weeping lovegrass with highaccuracy (d = 0.85, MAE% = 20%, and r2 = 0.99) but with a slight overestimation by 1.86 t ha−1. Similarly, STICSsimulated maize TDM and grain yield (HDM) with acceptable accuracy (d = 0.82, MAE = 16%, r2 = 0.96) althoughit underestimated the TDM and HDM by 0.44 and 2.7 t ha−1, respectively. SwbSci underestimated the TDM ofweeping lovegrass by 2.7 t ha−1. Nonetheless, the simulation was reasonably accurate (d = 0.84, MAE = 22%, r2 =0.91). For maize, SwbSci simulations were more accurate under irrigated systems (d = 0.92 - 0.94, MAE = 15 - 16%,r2 = 0.97) than dryland systems (d = 0.87, MAE = 20%, r2 = 0.91-0.99).Both models performed well and can be used as reasoning support tools with some caution especially when workingwith row crops whose yield is a function of the row spacing, which is not explicitly represented in both models.



Effect of Tannin and Species Variation on in vitro Digestibility, Gas and Methane Production Charac-teristics of tropical Browse Plants

B.S. Gemeda and A. Hassen

University of Pretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria,South Africa

[email protected]

Nineteen tanniferous browse plants were collected from South Africa to investigate their digestibility, gas productioncharacteristics and methane production. Fresh foliages (leaves and stems <3 mm diameter) were harvested from atleast five randomly selected and tagged representative plants of each species at the same time when they were atthe same maturity stage; almost early vegetative stage. The fresh samples were collected and immediately frozen inthermo-flask containing frozen ice and then dried in forced oven at 55◦C for 48 hours, and ground and analyzed fornutrient and phenolic compositions. In vitro gas production (GP) and organic matter digestibility (IVOMD) weredetermined using rumen fluid collected, strained and anaerobically prepared. A semi-automated system was usedto measure gas production by incubating the sample in a shaking incubator at 39◦C. The methane concentrationwas determined using a gas chromatography equipped with a solenoid column packed with silica gel and a FlameIonization Detector (FID). Two replicates and four different runs were executed for every sample for GP study whilethree replicate and two different runs were executed for every sample for IVOMD.There was significant (P<0.05) variation in chemical composition and phenolic of studied browses. Crude protein(CP) content of the species ranged from 86.9 to 305.0 g/kg DM. The neutral detergent fiber (NDF) ranged from 292.8to 517.5 g/kg DM while acid detergent fiber (ADF) ranged from 273.3 to 495.1 g/kg DM. The ash, ether extract(EE), non-fibrous carbohydrate (NFC), neutral detergent insoluble nitrogen (NDIN), and acid detergent insolublenitrogen (ADIN) and crude protein (CP) were negatively correlated with methane production. Methane productionwas positively correlated with NDF, ADF, cellulose and hemi-cellulose. Methane production showed significantly(P<0.001) negative correlation with phenolic compounds (TP, TT, CT and HT) and positive correlation with fibercomponents.In this study, tannin reduced methane production and browses with higher phenolic contents generally producedlower methane regardless of their CP, NDF, ADF and lignin contents. Moreover, tannin suppressed volume of gasproduction, IVOMD and total VFA.The observed low methanogenic potential and substantial ammonia generation of some of the browses might bepotentially useful as rumen manipulating agents. However, a systematic evaluation is needed to determine optimumlevels of supplementation in a mixed diet in order to attain a maximal depressing effect on enteric CH4 productionwith a minimal detrimental effect on rumen fermentation of poor quality roughage based diet.



Measured and modelled climatic Variability Effects on Ecosystem Carbon Exchange in two grazedtemperate Grasslands with contrasting Drainage Regimes

O. Ni Choncubhaira, J. Humphreysb and G. Lanigana

aTeagasc, Environmental Research Centre, Johnstown Castle, Wexford Co. Wexford, Ireland; bTeagasc, Moorepark,Animal & Grassland Research and Innovation Centre, Co. Cork Fermoy, Ireland

[email protected]

The susceptibility of many ecosystems, including grasslands, to extreme climatic events and inter-annual variability hasbeen demonstrated previously. Predicted future global warming is expected to increase weather volatility in temperatezones, thereby altering carbon cycling in grasslands. Temperature anomalies as well as modifications in the temporalpattern and quantity of precipitation alter the balance between carbon uptake and release processes and a mechanisticunderstanding of ecosystem response to such changes is still lacking.In the present study, the impact of extreme inter-annual variability in summer rainfall and temperature on carbondynamics in two rotationally-grazed grasslands in Ireland was examined. These results were subsequently used tocalibrate DNDC 9.5 which was employed to assess the impact of increasing weather volatility on C dynamics intothe future. The sites experience similar temperate climatic regimes but differ in soil drainage characteristics. Eddycovariance measurements of net ecosystem exchange of carbon were complemented by regular assessment of standingbiomass, leaf cover, harvest exports and organic amendment inputs.The summers of 2012 and 2013 showed contrasting climatic conditions, with summer precipitation 93% higher and 25%lower respectively than long-term means. In addition, soil temperatures were 7% lower and 11% higher than expected.Cool, wet conditions in 2012 facilitated net carbon uptake for more than ten months of the year at the poorly-drainedsite, however the ecosystem switched to a net source of carbon in 2013 during months with significantly reducedrainfall. In contrast, net C accumulation continued at the well-drained site despite the summer drought conditions.Total cumulative annual ecosystem respiration was 20% higher at the poorly-drained site than at the well-drained sitein 2013, while a more modest increase in cumulative gross production (9.6%) was observed at the poorly-drained sitefor the same period. Following calibration of DNDC using measured data, three weather scenarios with different levelsof stochastic variability were run. Increased levels of drought and/or extreme precipitation were predicted to decreasenet C sinks by up to 25%.This research highlights the susceptibility of poorly-drained soils to accelerated efflux of carbon during soil dryingcycles and points towards potential negative impacts of future warming scenarios, with significant carbon balanceimplications for grassland ecosystems.



Influence of Addition of Corn on in vitro Gas Production of two Legumes Forages

S. Lobon, F. Molino, M.A. Legua, M.P. Eseverri, M.A. Cespedes and M. Joy

CITA (Centro de Investigacion y Tecnologıa Agroalimentaria de Aragon), Avda. Montanana, 930, 50059 Zaragoza,Spain

[email protected]

Methane is a common by-product of ruminal fermentation of food in the rumen. In recent years many researches havebeen involved identifying enteric methane mitigation strategies. Many studies show that tannins can reduce methaneemissions by ruminants. Alfalfa is widely used in the ruminant and is characterized by containing no tannin whilesainfoin has a medium content of tannins. The main objective of this study is to evaluate the in vitro gas and methaneproduction at 48 hours of two forage legumes, alfalfa (Medicago sativa) and sainfoin (Onobrychis viciifolia) and theeffect of the addition of corn in two different proportions (20 % and 40 %).The gas production was determined by the Ankom system (Ankom Technology, Ankom 2011), with 0.5 g of sample and120 ml of buffer solution (2:1). Methane detection was realized by GC-FID (gas chromatograph with flame ionizationdetector, Agilent HP-4890).Gas and methane production was significantly lower in sainfoin than alfalfa (P<0.05). Alfalfa hay had a gas andmethane production of 286.90 ml gas/g DM and 38.55 ml methane/g DM whereas sainfoin hay had a production of187.11 ml gas/g DM and 24.76 ml methane/g DM. The effect of addition of corn depended on the forage species. Inalfalfa, the inclusion of corn did not affect the gas production (286 vs 302 ml gas/g DM; P>0.05), but affected themethane production, although significantly only when it was added at higher proportion (38.55 vs 46.74 ml methane/gDM, alfalfa vs alfalfa+40% corn respectively; P<0.05). Regarding to sainfoin, the inclusion of corn increased gas andmethane production, regardless of the proportion of corn added (187.11 vs 251.52 ml gas/g DM; 24.7 vs 41.05 mlmethane/g DM, sainfoin vs sainfoin+corn, repectively ; P<0.05).In conclusion, the gas and methane production of the forage depends on the species used. The addition of cornincreased the amount of gas and methane production, that increase being more considerable in sainfoin hay.Acknowledgements: This study was supported by INIA-RTA-2012-0080 and Sandra Lobon has a Scholarship supportfrom the Aragon Government.



Reintroducing Livestock to improve Village-Scale agricultural Productivity, Nutrient Balance and Nu-trient Use Efficiency: the Case of Senegalese Groundnut Basin

E. Audouina, M. Odrua, J. Vayssieresb,a, D. Massec and P. Lecomted,e

aCIRAD - Umr Selmet, Campus ISRA/IRD de Bel Air, Route des hydrocarbures BP 1386, 18524 Dakar, Senegal;bCIRAD, 37 av. Jean XXIII, Dakar Etoile, BP 6189 Dakar, Senegal; cIRD - UMR Eco&Sols, Campus ISRA/IRD deBel Air, Route des Hydrocarbures, BP 1386, 18524 Dakar, Senegal; dCIRAD - UMR Selmet, Campus InternationalBaillarguet, 34398 Montpellier Cedex 5, France; eINRA SupAgro, Cirad Campus international, 34700 Montpellier,

[email protected]

In Western Africa, food security and living standards improvement are still major issues. Until the 20th century,the former Senegalese groundnut basin’s main features were livestock, cropping and tree integration. From 1960 thistraditional agrosilvopastoral Sereer system was impacted by environmental changes such as climate change, populationgrowth, declining groundnut market, etc... These evolutions emphasised tensions around biomass management (cropresidues, manure) and led to the decline in wooded parkland and soil fertility. As a consequence, distinct agrariantransitions developed depending on the village. Common features are the extension of bovine herds’ transhumance,and therefore the decrease in crop manuring. It puts into question the sustainability of these new systems.The study focused on two villages within the former groundnut basin that adopted contrasting agricultural strategies;the first one kept a relatively traditional system maintaining common fallow (Diohine), while the second developed asystem based on livestock fattening (Barry Sine). Visible multi- scale nutrient balances (plot, household and villagescales), built on stakeholders surveys that inventoried and quantified biomass flows, were the indicators used to assessthe sustainability of current agricultural systems.Household scale nitrogen balances (13 kgN.ha−1 for Diohine, 25 kgN.ha−1 for Barry Sine) and village scale’s ones (9kgN.ha−1 for Diohine, 25 kgN.ha−1 for Barry Sine) demonstrate that Barry Sine village is more sustainable in terms ofsoil fertility maintenance. Its higher nitrogen balances are mainly due to larger use of mineral fertilizers (1 kgN.ha−1

in Diohine, 6 kgN.ha−1 in Barry Sine) and manure (1.83 kgN.ha−1 in Diohine, 2.86 kgN.ha−1 in Barry Sine).Introduction of livestock fattening activity in farming systems improves animal presence (0.96 TLU.ha−1 in Diohine,2.31 TLU.ha−1 in Barry Sine), and provides an additional nitrogen supply through imported concentrate feeds (3.14kgN.ha−1 in Diohine, 17.6 kgN.ha−1 in Barry Sine). However similar plot scale nitrogen balances (-20 kgN.ha−1 inDiohine, - 23 kgN.ha−1 in Barry Sine) point out that the traditional fallow system in Diohine is still relevant forsoil fertility management at plot scale and that Barry Sine’s livestock fattening manure management is not optimal.Livestock reintroduction in villages improve N use efficiency at both household and village scales (0.15 in Diohine,0.64 in Barry Sine).There is still room for progress in N use efficiency through improvement of manure management (urine collection, bettermanure transport facilities, covered manure heaps, in-soil manure incorporation), especially in Barry Sine where mostof the manure is managed contrary to Diohine where most of the manure is directly deposited on-fields.



Carbon and Energy Balance in natural and improved Grasslands of an extensive Livestock Ranch inthe humid Tropics of central Africa (RDC)

P. Lecomtea,b, A. Duclosc, X. Juanesd, S. Ndaoe, P. Decremf and M. Vigneg

aCIRAD - UMR Selmet, Campus International Baillarguet, 34398 Montpellier Cedex 5, France; bINRA SupAgro,Cirad Campus international, 34700 Montpellier, France; cISA Groupe, 48 Boulevard Vauban, 59046 Lille, France;

dCIRAD - UMR Selmet, Campus International Baillarguet, 34398 Montpellier, France; eISRA, CRZ Kolda, BP 53,none Kolda, Senegal; fORGAMAN, Avenue Lt Colonel Lukusa n◦ 4854, none Kinshasa, The Democratic Republic of

Congo; gCIRAD - UMR Selmet, Campus International de Baillarguet, 34398 Montpellier Cedex 5, [email protected]

In the African extensive livestock systems improved management practices and technologies can deliver a significantportion of the necessary mitigation effort needed (FAO 2013).The ”Kolo” ranch is located 14◦45’ - 15◦00’ E, 5◦15’- 5◦52’ S (Bas-Congo, DRC). 20 000 N’dama cattle heads aremanaged for a production of 1200 tons live weight (LW) on 50 000 ha: 47 500 ha of natural ”Hyparhenia” savanna(NS) and 2 500 ha of Brachiaria improved grasslands (BiG). Farm gate LCA methodology and IPCC references werecontextualized to the local practices to estimate the level and diversity of non-renewable energy (NRE) and GHGemissions efficiency of the system.The results show a NRE consumption of 6 259 MJ t LW−1 year−1 (vs 30 200 and 9 724 in French and Brazil systemsrespectively). The system based on abundant pasture resources and fire use to stimulate regrowth in NS, using veryfew inputs and light infrastructures, is a low consumer of energy. GHG emissions are important: 30 t CO2-e t LW−1

exported, (14,2 and 10-44 t CO2-e t LW−1 in French and Brazil systems respectively). Biomass burning and entericemissions shares are 50% and 36% respectively of the emissions. On the ecologically intensified surfaces (BiG) of theranch, where fire use is strictly avoided and where the finishing animals are concentrated performances are increaseddue to biomass and forage quality improvement, the carrying capacity is raised from averages of 0,41 on (NS) to 4,51TLU / ha on (BIG). The annual LW gain per ha is in proportion 12 vs 254 kg ha−1. Related to meat production weobserve a lower energy consumption 7 978 and 4 405 MJ/ton LW Gain and GHG is reduced 51,7 and 8,5 t CO2-e t ofLW Gain on average NS and BIG surfaces respectively. The production costs are 2,14 and 1,23 /Kg carcass eq. LWgain for NS and BIG surfaces respectively.In such tropical environments and livestock systems, grassland improvement and changes of management practicesare probably the most effective investment to mitigate climate impact and improve environmental and economicefficiencies.



Coupled Effect of agricultural Practices and Climate on Carbon Storage in two contrasted permanenttropical Pastures.

V. Blanforta, C. Stahla, K. Klumppb, R. Falcimagneb, C. Picon-Cochardb, P. Lecomtea,c, J.-F. Soussanab and S.Fontaineb

aCIRAD - UMR Selmet, Campus International Baillarguet, 34398 Montpellier Cedex 5, France; bINRA UR 874,Grassland Ecosystem Research, 63100 Clermont Ferrand, France; cINRA SupAgro, Cirad Campus international,

34700 Montpellier, [email protected]

More than 15% of the Amazon forest has been converted to pastures these last decades. Forests contain more Cthan a pasture. However, only little information is available on the potential C sequestration of those pastures inthe long term and with respect to climatic variability. In the current context of climate change in Amazonia, intra-and inter-annual variability of precipitation can lead to major modifications of carbon storage capacity of forest andpotentially of pasture. A better insight on how climatic variability and agricultural management affects net carbonexchange (i.e. NEE) of cattle pastures is, thus, important to increase C storage and to prevent increasing greenhousegas emission.Since 2010, we measured C sink potential (eddy covariance technique) of two pastures. The pastures differed in ageafter grassland establishment and livestock density; a young (4-year) intensively grazed (3.5 UGB ha−1 yr−1) and anold (33-year) extensively grazed (1.3 UGB ha−1 yr−1) paddock.Our results show a higher carbon storage potential of the old pasture subjected to a low instantaneous livestock densitycompared to the young pasture. Concerning dry and wet seasons both pastures showed a lower NEE compared tothe nearby forest site. The old pasture was, however, less affected by the dry season than the young pasture. Thatcould be due to a higher vegetation (grass) density preventing soil drying and enabling the vegetation to maintaina photosynthetic activity (GPP). Further impacts of inter and intra annual climate variation and management on Cfluxes will be discussed in presentation.



Adaptation and Mitigation Options offered by ”Biodiverse Legume rich sown permanent Pastures” forthe sustainable Improvement of Mediterranean Animal Production Systems facing Climate Change

D. Crespo and A. Barradas

FERTIPRADO LDA, Herdade dos Esquerdos, Vaiamonte, 7450-250 Monforte, [email protected]

In the Mediterranean region most of the grazing resources are provided by poor natural pastures occupying marginalsoils of low fertility, particularly with a very low content in organic matter (SOM) and phosphorous (P). In order toincrease their productivity the use of pasture legumes together with the application of P fertilizers is fundamental.Although most pasture legumes are of Mediterranean origin, their contribution to improve pasture productivity hasbeen relatively insignificant. However, in the mid-sixties, a system named ”Biodiverse legume rich sown permanentpastures (BLRSPP)” was developed in Portugal, involving different permanent pasture mixtures, each one adaptedto a particular soil and climate condition, and composed by a large range of species and cultivars (10 to 20), mainlyof legumes, but also grasses and eventually other plants, chosen among 36 species and more than 100 cvs. of selfreseeding annuals and drought resistant perennials, all from Mediterranean origin.Previously to mixing and sowing, the seeds of each legume species are inoculated with specific strains of Rhizobium toenhance symbiotic N fixation, making the pasture self sufficient in nitrogen. Provided BLRSPP mixtures are properlyformulated according to the average condition of each site, particularly soil (pH, texture, depth, drainage, etc.) andclimate (mainly rainfall and its distribution), and well fertilized (particularly with P), they have proved to increase by2-3 fold the carrying capacity of the natural pastures and withstand considerable inter-annual variability induced byclimate change (CC), e.g. more frequent and prolonged periods of drought, concentrated rainfall inducing floods ortemporary soil waterlogging, raise in air temperature, and simultaneously contributing to mitigate the effects of CCby sequestering considerable amounts of atmospheric CO2, and replacing the use of industrial N fertilizers, which arealso responsible for considerable emissions of CO2 to the atmosphere.Various examples of plant adaptation to CC are given, and some figures of carbon sequestration by BLRSPP incomparison with natural pastures, in different soil layers and with different ages, are presented. The CO2 sequestrationresults from the incorporation in the soil profile of animal faeces, dead roots, and other non grazed plant residues,inducing an increase of the SOM, although its annual rate decreases with higher SOM contents.Finally, this presentation points out the considerable differences in pasture productivity between BLRSPP and naturalpastures.



Evolution of the Carbon and Soil Nitrogen Content in a Northern Senegal grazed Area between 1962- 2011

T. Diopa, O. Ndiayeb, I. Diemec, I. Toured and M. Dieneb

aISRA, Dakar, Senegal; bISRA / CRZ, BP 01, 42200 Dahra, Senegal; cDA, DA, 10200 Dakar, Senegal; dCIRAD /UMR Selmet, CILSS 03 BP 7049, 03 Ouagadougou, Burkina Faso

[email protected]

The study took place at the Centre for Zootechnical Research (CRZ) Dahra located in silvopastoral Region of Senegal.Plots CRZ are subject to permanent pasture since its inception in the 50s by a herd consisting mainly of cattle. Itsarea is 5,500 ha and soil types are:-CFC = calcimorphe Complex ferruginous sandy areas limestone caps;-CMD = Complex poorly drained lowland and temporary ponds;-SBR = red brown soils;-SD = Soil Diors;-SFT = ferruginous tropical soils medium or poor drainage.In 2011, 124 soil samples (0-20 cm and 20-40 cm) were collected at the same sites as those that have been the subjectof soil analysis in 1962. The number of samples depends on the size of different types of soils encountered. Similarly,samples were also taken for determination of bulk density.On the carbon content, statistical analysis revealed no significant difference for horizons 0-20 cm between 1962 (2.79± 1.51%o) and 2011 (2.62 ± 2.09%o) and horizon 20-40 cm 1.36 ± 0.39%o in 1962 and 1.89 ± 0.87% o in 2011. It isthe same for soil units.As for the nitrogen content, it is significantly higher for horizons 20-40 in 2011 (0.23 ± 0.08%o) than in 1962 (respec-tively 0.16 ± 0.04%o). However, it does not reveal any significant difference at 0-20 cm (0.27 ± 0.12%o in 1962 and0.28 ± 0.22%o in 2011). Compared to soil unit, there is no significant difference at 0- 20 cm. However at the horizon20-40 cm, the CFC unit has a significantly higher content of nitrogen in 2011 (0.3 ± 0.12%o) than in 1962 (0.2 ±0.05% o).The bulk density data are not found in the literature for the past periods. But those of 2011 indicate no significantdifference between the horizons 0-20 cm (1585.3 ± 104.6 kg/m3) and 20-40 cm (1590 ± 64.4 kg/m3). We can thereforeconsider on the basis of these analyses that the rate of carbon and nitrogen did not decrease during this period andthat the livestock was not a loss factor for these items.



Effect of Sprinkling and Ventilation on Performance of Heat stressed Awassi Sheep

S. Abi Saaba, N. Abdel Nourb, I. Lahoudb and P.Y. Aadc

aLebanese University- ULFA, Dekwaneh, NA Dekwaneh, Lebanon; bUSEK, Kaslik, NA Kaslik, Lebanon; cNotreDame University-Louaize, 072 Zouk Mikael, NA Zouk Mosbeh, Lebanon

[email protected]

Lebanon is characterized by long dry summers, where high temperatures, low humidity and high solar radiations leadto heat stress on local sheep and goat populations reared under transhumance.Two experiments were designed to study the effect of heat stress alleviation of both ventilation and sprinkling onyoung (27 animals of 4 months of age) or older animals (12 males of 2-3 years of age) during summer, includingan adaptation period from 15 June to 1 July, followed by an experimental period from July to October. In bothexperiments, environmental temperature and humidity were recorded to calculate the RHI. Animals were divided into3 groups, namely control, ventilation and sprinkling to test for the effect of heat stress and its possible alleviationon body weight, adaptation indicators (heart and respiration rate and body temperature), testicular temperature,circumference and volume, in addition to semen quality.Results showed that sprinkling reduced the ambient temperature by 3±0.2◦C while ventilation reduced humidity by10%, both reducing RHI index significantly (P<0.05) from control. In both experiments, all animals under ventilationand sprinkling showed a greater (P<0.05) body weight compared to the control, a decreased (P<0.05) respirationand heart rate in both treated males and females, irrespective of age. No significant difference (P>0.10) of testiculartemperature was observed among treated or untreated males in both studies, however younger treated rams hadbetter (P<0.05) overall semen evaluation compared to control, with no significant difference (P>0.10) observed inolder males. In young males (experiment 1), semen concentration was higher (P<0.05) and abnormalities lower(P<0.05) in sprinkling vs both ventilation and control groups, whereas no significant difference (P>0.10) was observedin older males (experiment 2).These results show that younger animals are more prone to heat stress and both their productive and reproductiveperformance is affected if stress is not alleviated. Older animals show a better adaptation to heat stress, possiblyindicating the ability of the Awassi sheep to accommodate to the dry hot summers of Lebanon.



Emission Intensities by Holstein and Holstein x Jersey crossbreed lactating Cows in two Braziliangrazing Systems

A. Berndta, A.P. Lemesa, T.C. Alvesa, A.D.F. Pedrosoa, L.S. Sakamotoa, L.G. Barionib and P.A. Oliveiraa

aEmbrapa Southeast Livestock, Rodovia Washington Luiz, km 234, 13560-970 Sao Carlos - Sp, Brazil; bEmbrapaAgriculture Informatics, Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil

[email protected]

In recent years the concern with methane (CH4) emission by enteric fermentation has become indispensable for dairyproduction systems. The aim of this study was to evaluate CH4 emissions from pure Holstein (HOL) and 1/2Jersey1/2Holstein (JH) high producing lactating cows grazing two different forages.The experiment was conducted at EMBRAPA’s (Brazilian Agricultural Research Corporation) experimental stationin the Southeast region of Brazil. Cows were allocated in two grazing conditions systems: extensively grazed pastureswith low stocking rate (ELS) or irrigated pastures under intensive management and high stocking rate (IHS). Pasturesin the ELS system were composed mainly of Brachiaria decumbens and Cynodon nlenfuensis (10.5% CP; 49.8% DMD)while the IHS system was composed of 27 paddocks of Panicum maximum cv Tanzania (21.0% CP; 62.8% DMD).Forage availability were 22.2 and 37.2 kg DM/AU respectively for ELS and HIS. A total of 24 dairy cows were used(2 breeds x 2 systems x 3 animals per paddock x 2 replicates), grouped according to age, stage of lactation and levelof milk production. Cows were kept at pasture and supplemented with minerals and concentrates in accordance withmilk yield (1 kg of concentrate/3 kg of milk produced). IHS pasture was rotationally managed and both IHS and ELSwere managed under variable stocking rate (”put-and-take”). Forage production and animal performance variableswere measured in order to subsidize environmental, technical and economic assessments. Methane emission evaluationtook place in January 2013, using the SF6 tracer technique (Johnson et al., 1994). Samples were collected every 24hours for five consecutive days. Gases were analyzed on a Shimadzu GC 2014. For statistical analyses we used theMIXED procedure of SAS and results were presented as least square means.No interactions between grazing system and breed were observed. Milk production and CH4 emission were similar inboth breeds and forages. Methane emissions were higher than the average in this season and milk production lowerbecause cows were in the end of lactation. Consequently methane intensities were higher in this experiment for HOLand JH (average of 30.4±2.3 vs. 27.9±2.6 LCH4/kg milk). Efficiency of milk production can be a mitigation strategybecause less methane is emitted per Litre of milk, but the treatments evaluated in this research in the rainy seasoncould not confirm that.Acknowledgements: AnimalChange is a project supported by the EU - FP 7 (2007- 2013) under the Grant Agreementn◦ 266018.



Effect of Herbage Intake on Methane Emission by grazing Sheep

M. Moreira Santanaa, J. Victor Saviana, A. Barth Netoa, B. De Araujo Silvaa, P. Cardozo Vieiraa, M. RitzelTischlera, R. Marinho Tres Schonsa, I. Machado Cezimbraa, T. Cristina Moraes Genrob, A. Berndtc, C. Bayera and

P.C. De Faccio Carvalhoa

aUniv. Federal do Rio Grande do Sul (UFRGS), Av. Bento Goncalves 7712, 90050321 Porto Alegre, Brazil;bEMBRAPA, BR 153 Km 603., 242 Bage, Brazil; cEmbrapa Southeast Livestock, Rodovia Washington Luiz, km 234,

13560-970 Sao Carlos - Sp, [email protected]

The level of dry matter intake (DMI) by animals, the quality of diet and food processing, among other factors,can influence the CH4 emission by ruminants. We hypothesized that combinations of stocking methods and grazingintensities provokes differences in the quantity and quality of herbage ingested, thus altering methane (CH4) emissionsby sheep grazing Italian ryegrass (Lolium multiflorum Lam.).The experiment was conducted at the Federal University of Rio Grande do Sul, Rio Grande do Sul State, Brazil.Experiments were carried out in 2011 (lambs, n=36) (Experiment 1) and 2012 (lactating ewes (n=72), all with asingle lamb) (Experiment 2). Two stocking methods (continuous or rotational) and two grazing intensities (herbageallowance: moderate and low, 2.5 and 5 times the potential daily DMI, respectively) in a randomized complete blockdesign with three replicates were studied. To determine daily DMI (n-alkanes technique) and CH4 emission (SF6tracer technique) by sheep, three tester animals from each experimental unit were utilized. Linear regressions weretested, the best model being defined by the highest coefficient of determination (R2) significant at 5% level (P<0.05).The statistical package SAS version 9.3 was used.Positive linear relationship between DMI (g animal−1 day−1) and CH4 emission (g animal−1 day−1) by sheep grazingItalian ryegrass was observed (Experiment 1: y=0.007x+14.6; R2=0.18; P=0.026 and Experiment 2: y=0.008x+25.2;R2=0.23; P<0.001). Negative linear relationship between DMI (g animal−1 day−1) and CH4 emission (g CH4 kgDMI−1) by sheep grazing Italian ryegrass was observed (Experiment 1: y=-0.011x+32.7; R2=0.33; P=0.001 andExperiment 2: y=-0.010x+41.8; R2=0.59; P<0.001).Thus, we conclude that the CH4 emission by sheep grazing Italian ryegrass increased with herbage intake increasing.If herbage intake by animals is greater, CH4 emission per kg of herbage ingested is lower.



Elevated CO2 overcomes the short-term Effect of a future Heat and Drought Climate Extreme in atemperate Grassland

C. Picon-Cocharda, J. Royb, A. Augustia, M.-L. Benota, D. Landaisb, C. Pielb, C. Escapeb, O. Ravelb, M. Bahnc, F.Volaired and J.-F. Soussanaa

aINRA UR 874, Grassland Ecosystem Research, 63100 Clermont Ferrand, France; bCNRS Ecotron, Chemin du Riou,34980 Montferrier-Sur-Lez, France; cUniversity of Innsbruck, Sternwartestraße 15, A-6020 Innsbruck, Austria;

dINRA CEFE CNRS, Route de Mende, 34000 Montpeliier, [email protected]

During the 21st century, droughts and heat waves are projected to increase in intensity and in frequency in some worldregions including southern Europe, while the CO2 concentration will continue to rise. Data at various scales haveshown that such climate extremes can affect the balance between photosynthesis and respiration, with potentiallysignificant consequences for ecosystem carbon storage and agricultural productivity. An increase of atmospheric CO2

may improve plant growth through its primary effects on both leaf photosynthesis and stomatal conductance.In the present study 48 intact large monoliths of an upland grassland were acclimated the first year to future climaticconditions (+4◦C and -56 mm for summer precipitations). The second year, the same climate was maintained buthalf of the experimental units were subjected to a summer drought and heat wave (50% reduction of precipitationsfor a month and then 100% precipitation reduction combined with a 3,4◦C air warming for two weeks). A CO2

treatment (520 vs 380 µmol mol−1) was applied with the climatic treatment from early spring and net CO2 fluxeswere measured continuously. Aboveground biomass production (ANPP) and belowground net primary production(BNPP) were measured at different time points.In moderate drought conditions and after rehydration in fall, elevated CO2 induced higher net ecosystem exchange(NEE) and BNPP than in ambient CO2, with a net photosynthesis twice as high in elevated CO2 compared to theambient. This positive effect is partly linked to a slight increase of soil water content. During the heat weave, totalsenescence of the canopy was observed whatever the CO2 treatment and no aboveground production occurred insummer. In fall, higher BNPP but not ANPP increased due to higher root growth rate.We show here for the first time that rising atmospheric CO2 may mitigate the negative impacts of extreme heat anddrought events on an agricultural ecosystem and preserve its carbon balance by increasing recovery.



Developing a Nationally Appropriate Mitigation Measure from the Greenhouse Gas Abatement Po-tential from Livestock Production in the Brazilian Cerrado

R. De Oliveira Silvaa, L.G. Barionib, T. Zanett Albertinic, V. Eoryd, C.F.E. Toppd, F. A. Fernandese and D. Morana

aSRUC, West Mains Road, EH93JG Edinburgh, UK; bEmbrapa Agriculture Informatics, Av. Andre Tosello, 209,Barao G., 13083-886 Campinas - Sp, Brazil; cUniversity of Sao Paulo, Av. Padua Dias, 11, 13418-900 Piracicaba -

Sp, Brazil; dSRUC, West Mains Road, EH9 3JG Edinburgh, UK; eEmbrapa Pantanal, Rua Vinte Um deSetembro,1880, Ns. de Fat, 79320-900 Corumba-Ms, Brazil

[email protected]

Brazil is one of the first major developing countries to commit to a national greenhouse gas (GHG) emissions targetthat requires a reduction of between 36.1% and 38.9% relative to baseline emissions by 2020. The country intendsto submit to agricultural emissions reductions as part of this target with livestock production identified as offeringsignificant abatement potential. Focusing on the Cerrado core (central Brazilian savanna), this paper investigatesthe cost- effectiveness of this potential, which involves some consideration of both the private and social costs andbenefits (e.g. including avoided deforestation) arising from specific mitigation measures that may form part of Brazil’sdefinition of Nationally Appropriate Mitigation Measures (NAMAs).The analysis was made using the EAGGLE optimization model (Economic Analysis of Greenhouse Gases for LivestockEmissions), which helps define abatement costs. A baseline projection suggests that the region will emit 2.6 Gt from2010 to 2030, the equivalent of 9% of the country’s total net emissions.According to our results, around 66% of livestock emissions in Cerrado are due to enteric fermentation. Deforestationdue to cattle grazing responded for 26% of these emissions. By implementing negative-cost measures identified in amarginal abatement cost curve (MACC), by 2030, regional emissions could be reduced by 27.8 MtCO2e.yr

−1, whilethe abatement potential of all measures shown by the MACC is 28.2 MtCO2e.yr

−1. The key finding from the use ofthe EAGGLE economic optimization model is the representation of the cost-effectiveness of key mitigation measures.Specifically, that pasture restoration is the most promising mitigation measure in terms of abatement potential volumeand that it offers a cost saving for the livestock sector.As the Brazilian Cerrado is seen as model for transforming other global savannas, the results offer a significantcontribution by identifying alternatives for increasing productivity whilst minimizing national and global externalcosts.


Mon. 17:00 Medici I Parallel session 2a: Mitigation options for grasslands

Gain of Nitrogen from Legumes in Grassland is robust over a wide Range of Mixture Legume Propor-tion and Environmental Conditions

M. Sutera, J. Connollyb, J. Finnc, R. Logesd, L. Kirwane, T. Sebastiaf and A. Luschera

aAgroscope, Reckenholzstrasse 191, 8046 Zurich, Switzerland; bUniversity College Dublin, School of MathematicalSciences, Dublin 4, Ireland; cTeagasc, Johnstown Castle, Wexford, Ireland; dChristian-Albrechts-Universitat, Institutfur Pflanzenbau, Kiel, Germany; eWaterford Institute Technology, Cork Road, Waterford, Ireland; fUniversitat de

Lleida, Dept HBJ, Lleida, [email protected]

Grassland-based livestock production faces global challenges to meet growing demands for meat and milk. This goalhas to be achieved using fewer resources in a more sustainable way than so far, which calls for i) reduction of highinput of industrial nitrogen (N) fertilizers and ii) high N self-sufficiency through home-grown protein crops. Legumesoffer great potential to address such challenges, as they can produce substantial amounts of plant-available N throughsymbiotic N2 fixation. Introducing legumes into grassland can thus substantially reduce nitrous oxide emissions dueto reductions in N fertilizer input. Further, while symbiotic N2 fixation is greenhouse gas (GHG) neutral, emissions of3.3 and 8.6 kg CO2 equivalents are calculated per kg of urea- and ammonium nitrate-N, respectively, for productionand transport.In a continental-scale field experiment conducted over three years across Europe, the amount of total nitrogen yield(Ntot) and yield from apparent symbiotic N2 fixation (Nsym) was quantified from grass-legume stands with greatlyvarying legume proportions. Stands consisted of monocultures and mixtures of two N2 fixing legumes and two non-fixing grass species (30 stands per site). The sixteen investigated sites spanned a gradient of climate from Atlantic tocontinental and from temperate to arctic.Legumes in mixtures resulted in a significant gain of Ntot (P ≤ 0.05) compared to that of grass monocultures atthe majority of sites at all three years. The positive effects of legumes on Ntot were evident over a wide range oflegume proportion; across sites, mixtures with one third of legume proportion attained amounts of Ntot that werenot significantly different from maximal amounts in mixtures with much higher legume proportion (including 100%legume stands). Across sites, and with one third of legume proportion in mixtures, Ntot was 287, 252, and 216 kg ha−1

year−1 in years 1, 2, and 3, respectively, while the corresponding Nsym was 104, 79, and 76 kg ha−1 year−1. Acrosssites and years, 34% of Ntot of the whole sward originated from symbiotic N2 fixation.The realized legume proportion in stands, Ntot and Nsym, were all positively correlated to minimum temperatures ofsites (P < 0.01), suggesting that low winter temperatures hampered the legumes’ growth and symbiotic N2 fixation.While Ntot was also highly correlated to site productivity (P < 0.001), the proportion of Nsym to Ntot was not (P> 0.4). This suggests that, within imperative climatic restrictions, well balanced grass-legume mixtures can equallyprofit from symbiotic N2 fixation across largely differing productivity levels across Europe. The resulting benefitsinclude high productivity and increased protein self-sufficiency, reduced GHG emissions, lower costs of production,and a reduced dependency on fossil energy and inorganic N fertilizer.



Carbon Sink Activity of Grasslands May Be Stronger under Grazing Than under Mowing: Resultsfrom a Paired Eddy Flux Towers Experiment

K. Pintera, J. Balogha, P. Konczb, D. Hidyb, D. Cserhalmib, M. Pappb, S. Fotib, Z. Nagya and A. Chabbic

aSzent Istvan University, IBE, Pater K. u. 1., H-2100 Godollo, Hungary; bMTA-SZIE Plant Ecology Res.Group,Pater K. u. 1, H-2100 Godollo, Hungary; cINRA, Centre de Recherche Poitou-Charentes, Le Chene - RD150 , BP

80006, 86600 Lusignan, [email protected]

Effect of grazing vs. mowing on carbon balance of a species rich (species number above 100) dry sand grassland wasinvestigated in an experiment with a pair of eddy towers (one of them measuring the grazed, the another the mowedtreatment) at the Bugacpuszta site (HU-Bug, 46.69N, 19.6E, 110m asl, 10.4 ◦C annual mean temperature, 562 mmannual precipitation sum) located in the Hungarian Plains. Eddy covariance measurements on the pasture belongingto a nature conservancy area started in 2002. Electric fencing was set up around the selected area in spring of 2011.The area of the mowed treatment is 1 ha, and it is located within the grazed treatment (500 ha). Study years onmanagement (grazing vs mowing) include 2011, 2012 and 2013. The pasture is managed extensively (average grazingpressure of 0.5 cattle per hectare), the cattle herd regularly took several kilometres during a grazing day.Annual net ecosystem exchange (NEE) of the grassland was strongly limited by precipitation, there were 2 sourceyears within the 11 years of measurements, during which the average annual balance was -109 gCm−2year−1 withstandard deviation of 106 gCm−2year−1. High variation of the carbon balance at lower annual precipitation sums arelinked to years following either the extraordinarily wet year of 2010, or highly favourable precipitation distribution(rains during the main growing season) as in 2012. Carbon-sink activity was stronger in the grazed treatment thanin the mowed treatment during the three year study period. In the grazed treatment the average sink strength was-142.8 ±40 gCm−2year−1, while in the mowed treatment the average sink strength was -61.5 ± 46.5 gCm−2year−1.The stronger source character in the mowed treatment resulted from the inferior sink capacity under drought and theweaker regeneration capacity after rains than in the grazed treatment as shown by the different temporal patterns ofthe cumulative NEE.Differences of C-balances between the treatments were positively correlated to the annual sum of evapotranspiration(ET), while ETs of the treatments were almost identical in the study years leading to higher water use efficiency inthe grazed than in the mowed treatment. Minor but consistent differences in Reco (higher in the mowed treatment by5-11%) and GPP (lower in the mowed treatment by only up to 3%) resulted in significantly weaker sink activity withNEEmowed to NEEgrazed ratios of 56%, 60% and 10% in 2011, 2012 and 2013, respectively.



Mitigating GHG Emissions from Ruminant Livestock Systems through the Management of CarbonSequestration in Grasslands

K. Klumpp and J.-F. Soussana

INRA UR 874, Grassland Ecosystem Research, 63100 Clermont Ferrand, [email protected]

A network of grassland sites equipped for eddy flux covariance measurements of CO2 exchanges with the atmospherehas been established in a range of national and EC funded research projects, starting with EC FP5 (Greengrass project,see Soussana et al., 2007), followed by FP6 (CarboEurope IP) and contributing to the FP7 projects CarboExtreme,GHG-Europe and AnimalChange. A data base from ca. 40 sites spanning the European continent and includinggrasslands, wetlands and moorlands with a diversity of managements (grazing, cutting or abandoned, with or withoutinorganic and organic N fertilization) has been assembled.Below, we review the corresponding data and we show that the net carbon storage in European grasslands can beassessed from climate and management drivers. The annual Gross Primary Productivity (GPP) reached 1218 ± 42.8gC m−2 yr−1 (mean ± s.e.) with a net carbon storage (NCS) equal to 76.4 ± 11.06 gC m−2 yr−1 showing carbonsequestration at approximately three out of four grassland sites. Gross primary productivity of temperate grasslandsis shown to be affected by climate conditions, with maximal values for the temperate grassland biome reached in mildand wet climates, with optimal temperature and precipitation values reaching 10.0±0.45 ◦C and 1241±84 mm yr−1,respectively. The NCS to GPP ratio reaches on average 9.0±1.4 %. This ratio increases with N supply and declineswith the net export of organic C from the grassland that is induced by agricultural management. This net exportis calculated as the arithmetic sum of organic C removals (harvests and intake at grazing) and of organic C supply(manure). A highly significant model (n=181, P<0.001) accounts for 23.6% of the total variance in measured annualNCS. It predicts NCS from climate (T and P) and management (N supply and net C export).This statistical model provides a first tool for predicting C sequestration in grasslands through agricultural manage-ment. Trade-offs and synergies between mitigation of GHG emissions and grassland use for livestock production arediscussed from this simple statistical approach. Finally, we discuss modeling approaches that may be used to reduceuncertainties on the role of management for grassland C sequestration.



Capacity of tropical permanent Pastures to restore Soil Carbon Storage after Deforestation of theAmazonian Forest

V. Blanforta, C. Stahla, M. Griseb, L. Blancb, V. Freyconc, C. Picon-Cochardd, K. Klumppd, D. Bonale, P.Lecomtea,f , J.-F. Soussanad and S. Fontained

aCIRAD - UMR Selmet, Campus International Baillarguet, 34398 Montpellier Cedex 5, France; bCIRAD, UR 105,/Embrapa Amazonia Oriental, EMBRAPA, Tv. Eneas Pinheiro s/n, 66095-100 Belem Para, Brazil; cCIRAD, UR105, TA C-105 / D, 34398 Montpellier Cedex 5, France; dINRA UR 874, Grassland Ecosystem Research, 63100Clermont Ferrand, France; eINRA, UMR 1137 EEF, INRA, 54280 Champenoux, France, Metropolitan; fINRA

SupAgro, Cirad Campus international, 34700 Montpellier, [email protected]

Conversion of tropical forest to cattle pasture has impacts on the carbon (C) stocks. In recent decades, more than 15%of Amazonian has been converted into pasture, resulting in net C emissions (∼200 tC ha−1) mainly due to biomassburning.The main goal of this study was to understand the long-term dynamics of soil C in permanent tropical pasturesestablished after deforestation. Two independent approaches were used to estimate C sequestration in pastures:chronosequence study including the inventory of soil C and N stocks to a depth of 100 cm in 24 pastures from 6months to 36 years old and 4 natives forest sites; and eddy covariance flux measurements on one young pasture (4yr), one old pasture (33 yr) included in the chronosequence study and one native forest. Our results show that therecurrent C sequestration in native rainforest is recovered in old pastures (> 24 years old). Eddy covariance fluxmeasurements and chronosequence study showed that these pastures are a major C sink: 1.8 to 5.3 tC ha−1 yr−1

compared with 2.6 tC ha−1 yr−1for native forest. The results of isotopic analysis of C (δ13 C) indicate that therecovery of long-term C sequestration in C4 tropical pasture is linked to the development of C3 species (includinglegumes), which increase the input of N to the ecosystem. C is sequestered in recalcitrant soil organic matter (SOM )in the deep soil layers (0.2-1 m). Grazing induces an emission of CH4 and N2O of 0.9 tCO2-C equivalents ha−1 yr−1,which was lower than the grassland C sequestration rate. Beyond this mitigation potential capacity, these resultssuggest also that Amazonian pastures can be a major global C sink (∼0.12 GtC) if sustainable pasture management isapplied. Efforts to curb deforestation have enabled a major reduction in forest clearing, but progress remains fragiledepending on the sustainability of agricultural systems. Our findings show that old tropical pastures accumulate SOMover time, suggesting that they can be exploited by farmers in the long term with appropriate practices (no fire andno overgrazing, but a mixture of C3 and C4 plant species and a grazing rotation plan. Conservation of soil fertilityshould help limit the rush to find new fertile areas and consequently, deforestation.Acknowledgements: This study was co- funded by CIRAD, INRA, CNES, European regional development found(ERDF 2007-013) and Animal Change project (FP7 KKBE 2010-4).


Mon. 17:00 Medici II&III Parallel session 2b: Adaptation options for livestock and grasslands

Principles of Climate Change Adaptation in Livestock Systems

J.E. Olesena and C.F.E. Toppb

aAarhus University, Department of Agroecology, Blichers Alle, DK-8830 Tjele, Denmark; bSRUC, West Mains Road,EH9 3JG Edinburgh, [email protected]

Climate change will impact on livestock production systems in several ways depending on livestock type, system designand local conditions. These effects are direct through impacts on animal performance and indirect through effects onfeed and fodder productivity and quality as well as through livestock diseases. Climate change may be expected toaffect livestock production most severely through changes in variability of the climate and thus through changes inclimatic extremes such as heat, drought and flooding. This necessitates adaptations to cope with the changed climateand climatic variability. Such adaptations need to operate at a multitude of spatial and organizational scales.The primary adaptation will occur at the farm scale, but this needs to be supplemented at higher scales in termsof providing the infrastructure for factors such as water and feed supply, livestock disease prevention and insurance.The adaptation can be categorized in three main categories: feed production, feed supply (feeding) and livestockmanagement. Feed production adaptations concern changes in species and cultivars of feed crops, change in grasslandmixtures, irrigation and fertilization. Feed supply adaptation concern changes in grazing intensity and duration,storage of feed and import of feed. Livestock adaptation concern breeding, change of livestock species or breed,cooling of houses, shading in open areas, water for livestock, manage herd size (during the year) and moving livestockto other regions. Several of these adaptation options have impact on greenhouse gas emissions and thus on themitigation potential. There is therefore need to align measures for reducing greenhouse gas emissions with the likelyadaptations to be adopted.



Impact of Heat Stress on Production in Holstein Cattle in four EU Regions. Selection Tools.

M.J. Carabanoa, H. Hammamib, B. Logarc, M.-L. Vanrobaysb, C. Diaza and N. Genglerb

aINIA, Ctra. de La Coruna km 7.5, 28040 Madrid, Spain; bUniversity of Liege, Gembloux, Passage des Deportes 2,5030 Gembloux, Belgium; cAgricultural Inst. of Slovenia, Hacquetova ulica 17, 1000 Ljubljana, Slovenia

[email protected]

Data from four European regions characterized by different management systems and environments were used toexplore the use of alternative statistical models to estimate thermotolerance thresholds and production loss of Holsteincows due to heat stress, as well as the development of selection tools.Test-day records of milk, fat and protein yield of Holstein cows provided by national milk recording organizations ofWalloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO) and Spain (SPA) were used. Production levelswere high, corresponding to populations that have undergone intensive selection. Meteorological data were providedby the corresponding national agencies. Two definitions of a thermal index (THI) were used, THIavg using averageambient temperature (Tdb) and average relative humidity (RH) and THImax using maximum Tdb and minimum RH.THIavg/THImax ranged from 25/32 to 70/78 (BEL and LUX), 22/28 to 74/84 (SLO), and 39/46 to 76/83 (SPA).Effects of heat stress in the four regions were evaluated using two approaches 1) the classical broken line (BL) modelused in heat stress studies, which provides a direct measure of the threshold and the linear slope of decay, and, 2) themore flexible polynomial (PL) approach, where quadratic and cubic Legendre polynomials were alternatively fitted.Overall, the cubic PL model with THIavg was the model providing the best fit with the data, with some exceptions.For daily milk yield, estimated losses from this model were 69, 11, 4 and 85 g/ THIavg for BEL, LUX, SLO, andSPA, respectively, at THIavg=70 and went up to 136 g/ THIavg at THIavg=75 for SPA. For daily fat/protein yieldslosses at THIavg=70 were 5.2/5.6, 4.3/3.0, 2.1/2.1 and 4.9/5.7 g/ THIavg for BEL, LUX, SLO, and SPA, respectivelyand went up to 5.8/8.13 g/ THIavg at THIavg=75 for SPA. Thermotolerance thresholds estimated from the BL modelwere higher for milk vs. fat and protein yields and in SPA vs. the rest of the countries. However, because of thestringent assumptions of the BL model, this model did not provide a sensible fit in many cases and estimated tolerancethresholds and slopes have to be interpreted cautiously. Genetic components of heat tolerance were then exploredusing random regression models fitting cubic Legendre polynomials. Estimated correlations between the interceptand linear additive genetic coefficients were negative, indicating an antagonism between level of production and heattolerance that ought to be considered when designing selection strategies.



Potential Use of Forage Legume Intercropping Technologies to mitigate and adapt to Climate ChangeImpacts on mixed Crop- Livestock Systems in Africa

A. Hassena, D.G. Talorea, B.S. Gemedaa, M. Friendb and E. Tesfamariamc

aUniversity of Pretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria,South Africa; bCharles Sturt University, School of Animal & Veterinary Sciences, Building 268 Room 157, NSW2678 Wagga Wagga, Australia; cUniversity of Pretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South

Africa, 0028 Pretoria, South [email protected]

Forage legumes are widely grown in mixed crop-livestock farming systems of Africa, though their potential has notbeen fully exploited. This paper summarizes the significance of forage legume intercropping in mixed crop- livestockfarming systems and discusses its potential role in adaptation to climate change and reducing greenhouse gases. Inparticular, the paper summarizes the effect of forage legume intercropping on grain and fodder yield, land equivalentratio, residual soil fertility, diseases and insect pest risk reduction. The effects of these factors are discussed inimproving the productivity and resilience of the system under climate change, and possible reduction of greenhousegas emissions.Research undertaken in various parts of Africa demonstrates that intercropping forage legumes with cereals improvesoverall yield, soil fertility, reduces the risk of crop failure due to rainfall variability, diseases, and weeds and pests.Forage legume intercropping improves digestibility and efficiency of utilization of the fodder, thereby minimizes theloss of energy in the form of methane per unit of digestible dry matter. Additional roles that forage legumes mayplay include minimizing erosion, the loss of organic matter, reducing N leaching and C losses, and promoting carbonsequestration. The nitrogen fixed by fodder legumes is an affordable source of ”natural fertilizer”, and improves theproductivity of cereals while minimizing nitrous oxide that could be potentially produced from the use of inorganicfertilizers.While this review identifies the many benefits of including forage legumes in crop-livestock systems in sub-SaharanAfrica, the actual benefits realized will depend on optimization of the intercropping technology to best fit the localconditions, and minimizing the confounding effect of other factors such as water, soil, light, and microclimate. Adaptiveresearch, aimed at the selection of compatible varieties, spatial and temporal arrangement of plants in the variousintercropping system at different locations and under different management scenarios needs to be undertaken to refinethe technologies further.Acknowledgment: The authors gratefully acknowledge funding from the University of Pretoria, Dept. of Scienceand Technology and the European communities, 7th framework programme under the grant agreement No. 266018,AnimalChange project.



Livestock and Climate Change in East Africa: exploring Combinations of Adaptation and MitigationOptions

S. Silvestria, J. Heinkea, A. Mottetb, A. Falcuccib and S. Chestermana

aILRI, P.O. Box 30709, 00100 Nairobi, Kenya; bFAO, Viale delle Terme di Caracalla, 00153 Rome, [email protected]

Climate change is expected to adversely affect agricultural production in Africa. The Sub-Saharan regions are par-ticularly at risk, considering the high dependence on crop and livestock of the population in those areas. Significantconcern surrounds the potential impacts an increase in greenhouse gas concentration will have in exacerbating thedrought conditions in subtropical agriculture. Tackling climate change has therefore become tremendously urgentboth from an adaptation and a mitigation perspective. Public and private sector policies will play an essential role insupporting the application of existing technologies and practices that have proved to mitigate emissions and improveproductivity at the same time. Yet, given the wide diversity of production systems and conditions, interventionsshould be carefully designed and targeted. In order to do so, policy makers need evidence-based assessment of thepotential of mitigation and adaptation options.The objective of this study was to design adaptation and mitigation combinations suited to the levels of vulnerabilityand mitigation potentials of mixed livestock systems in East Africa, and assess the likely effects of implementing thesestrategies. These combinations cover categories of interventions related to feed, herd and environment. The designedcombinations are modelled in the Global Livestock Environmental Assessment Model (GLEAM) to estimate changesin emissions, productivity and herd dynamics. The findings of this study help the understanding of whether and wherethere are co-benefits from application of combinations of options that could address environmental footprint and foodsecurity at the same time.


Plenary session 3: Framing the options: the farm andlandscape scales


Tues. 8:45 Medici Plenary session 3: Framing the options: the farm and landscape scales

Integrating Adaptation and Mitigation in extensive grazing Systems

M. Herreroa, P. Thorntonb, A. Asha, P. Havlikc, R. Conantd and A. Notenbaerte

aCSIRO, Box 2583, 4001 Brisbane, Australia; bCGIAR, Research Programme on Climate Change Agriculture andFood Security, ILRI, 30709-0010 Nairobi, Kenya; cIIASA - International Institute for Applied Systems Analysis,Schlossplatz 1, 2361 Laxenburg, Austria; dColorado State University, Natural Resource Ecology Lab, Fort Collins,

80523-1499, USA; eCIAT, Kasarani Road, 00100 Nairobi, [email protected]

Extensive grazing systems occupy the largest land areas occupied by livestock in the world. They play a vitalimportance in supporting the nutritional security and incomes in communal and commercial pastoral systems in theseregions. Additionally, they help maintain ecosystems services like water cycles, biodiversity, and carbon stocks ofglobal and regional importance.Grazing systems are important for the production of beef in Latin America (22%) and Oceania (55%), small ruminantmilk in Sub-Saharan Africa (56%) and Middle East and North Africa (31%), and small ruminant meat in most regions,where they account for 25- 40% of production. The production from grazing systems in the developing world is modest,mostly because of low productivity, low feed availability, and poor quality of feed resources in these predominantly aridregions (with the exceptions of the humid rangelands of LAM) (Herrero et al., 2013). The impacts of climate changeon some of these systems will be large in places, but highly differentiated. In the tropics, many of these systems arelikely to experience increasingly drier and more variable climate that could lead to further resource constraints andhigher vulnerability; while in temperate regions, increases in temperature might remove constraints on pasture growththus opening options for increasing productivity. In both situations, adaptation to climate change will be necessary;and in many cases it will have strong synergies with climate change mitigation.Diversification and sustainable intensification are likely to play significant roles in adapting extensive grazing systems(Thornton et al., 2014). Practices like improved feeding, supplementation, forage conservation, and improved herdmanagement are likely to lead to improved productivity and in many cases reduced greenhouse gas emissions fromboth livestock and land use in these systems. Schemes for payments for ecosystems services as a means of diversifyingincomes could also lead to overall improved systems productivity and reduced emissions. The incentives systems,supporting policies and the economics of implementing these practices under significant climatic risk will dictate theirfeasibility (Havlik et al., 2013). These are topics that warrant further investigation due to the close link betweensystems productivity, ecosystems function, rural development and human welfare in these systems.References:Havlik, P., Valin, H., Herrero, M., Obersteiner, M., Schmid, E., Rufino, MC, Mosnier, A., Thornton, P.K., Bottcher,H., Conant, R.T., Frank, S., Fritz, S., Fuss, S., Kraxner, F., Notenbaert, A. 2014. Climate change mitigation throughlivestock system transitions. PNAS 111, 3709-3714.Herrero, M., Havlık, P., Valin, H., Notenbaert, A., Rufino, M.C., Thornton, P.K., Blummel, M., Weiss, F., Grace, D.,Obersteiner, M. 2013. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestocksystems. PNAS 110 (52), 20888-20893.Thornton, PK, Ericksen, PJ, Herrero, M., Challinor, A. 2014. Climate variability and vulnerability to climate change:a review. Global Change Biology (in press)



Integrating Adaptation to and Mitigation of Climate Change in intensive Animal Production Systems

F. O Maraa, J.E. Olesenb, G. Laniganc and A. Van Den Pol Van Dasselaard

aTeagasc, Head Office, Oak Park, N/A Carlow, Ireland; bAarhus University, Department of Agroecology, BlichersAlle, DK-8830 Tjele, Denmark; cTeagasc, Environmental Research Centre, Johnstown Castle, Wexford Co. Wexford,

Ireland; dWageningen UR Livestock Research, PO Box, 65, 8200 A Lelystad, [email protected]

The development of livestock mitigation and adaptation strategies to climate change has principally focused on oneor other of these aspects in isolation. However, in reality, both will have to occur simultaneously. Therefore, farmpractices which have both mitigation and adaptation potentials are especially valuable as they avoid possible trade-offs.In intensive, grass-based systems, one promising option is mixed species swards which show both greater productionpotential under drought conditions and resilience to weather extremes, and with the inclusion of legumes, there is thepotential for reduced nitrous oxide emissions. Silvo-pastoralism has also been shown to have positive effects on animalproduction under higher temperatures because of the positive impact of shading and improvements in soil conditionsand water management, while the extra carbon sequestered represents a mitigation measure. For some other adaptionoptions that maintain feed production in the face of climate related stress (e.g. heat, drought), the increased feedproduction (compared to the absence of adaptation) will reduce greenhouse gas emission per unit of product. Examplesare irrigation of pastures (or possibly drainage in some situations) and forage plant breeding. In the case of the latter,its long term nature allows new cultivars to adapt to climate as it changes, while the increased production potential ofnew cultivars should increase animal output per hectare leading to reduced emissions per unit of animal product. Otherproposed options for intensive grass-based systems with both adaptation and mitigation potential include optimisingfertilisation rates, pest management, animal breeding and improved animal health. Another management strategywhich could have positive adaptation and mitigation effects is the use of precision agriculture to better predict andmanage fodder supply, both deficits and surpluses. This has application in both intensive and extensive ruminantproduction systems which are dependent on grazed or conserved forage.There are few options with both mitigation and adaptation potential for confinement-based livestock productionsystems (pigs, poultry, intensive ruminant). The main adaptation requirement of such animals is likely to be activecooling in response to higher temperatures, which is likely to require fossil fuel usage and thus be negative for greenhousegas mitigation. On the other hand, this intervention is likely to improve animal performance, thus reducing emissionsper unit of product. Other adaptation requirements relate to the feed production systems for these livestock, wherenew crop species or varieties would be needed along with new management systems. Some of these such as watermanagement (e.g. irrigation), tillage intensity and optimising fertilisation rates could have a mitigation co-benefit asoutlined above. There are also new biorefinery technologies in the pipeline which may allow conversion of biomass fromgrass and other perennial species to the converted to feeds for monogastric animals, leading to substantial benefits forboth mitigation and adaptation.



Integrating Adaptation and Mitigation in Smallholder Farming Systems: A Focus on sub-SaharanAfrica

K. Descheemaekera, K. Gillera, S. Oostingb, P. Masikatic and S. Homann-Kee Tuib

aWageningen University, Plant Production Systems, P.O. Box 430, 6700 AK Wageningen, Netherlands; bWageningenUniversity, Animal Production Systems, P.O. Box 338, 6700 AH Wageningen, Netherlands; cICRISAT (International

Crops Research Institute for the Semi Arid Tropics), PO Box 776, 00 Bulawayo, [email protected]

Livestock play an important role in the smallholder farming systems of sub Saharan Africa. Rangeland-based systemscover a larger area on the continent, but mixed crop-livestock systems support the majority of rural and urbanlivelihoods and contribute significantly to food security. Livestock provide multiple products and services, includingdraught power for cultivation and transport, manure for soil fertility improvement, cultural status and insurancemechanisms to cope with (drought related) shocks. Farmers often sell livestock to buy food when crop harvests fail.In many cases livestock are kept primarily to support crop production, with milk and meat considered as useful by-products of livestock keeping. Crop residues constitute an important part of the livestock diet in mixed systems, theremainder being provided by rangelands, which are often communally managed. Livestock-based farming systems areaffected by climate change through impacts on feed quantity and quality, through changes in crop production andcomposition, and through changes in rangeland production and their species composition. Climate change intricatelyaffects the spread and incidence of livestock diseases, and more directly, increasing temperature affects livestockperformance. Whereas animals are in general less vulnerable to drought than crops, extreme droughts can wipe outregional or national herds, which take a long time to recover.The high diversity of farming systems both across agro-ecological zones and within communities, coupled with the va-riety of and uncertainty around climate change trends, make generalized conclusions on the most promising adaptationoptions difficult. Moreover, in many places, other drivers such as population increase, urbanization, changing policyand institutional contexts, and expanding markets might exert a stronger, more immediate influence on smallholdersystems than climate change.Nevertheless, smallholder systems are vulnerable to climate change, and adaptation is necessary. In mixed-croplivestock systems, three broad intervention categories exist: cropping-related, feed-related and animal-related inter-ventions. The first category comprises crop choice and crop management, including adjusting planting date andcultivar, and nutrient management based on judicious use of mineral and organic fertilizers. Feed-related interventionscan close feed gaps through, for example, on-farm fodder production, fodder storage, improving feed quality, andrangeland management and rehabilitation. Thirdly, animal-related options include veterinary care, herd managementand provision of shade. In general, good agricultural and livestock management practices that improve current pro-ductivity also increase the resilience of farming systems to climate change. System diversity and configurations arealso likely to change with climate change. Complete systems shifts are not unlikely, and in locations where the climatewill get drier, this may increase the importance of livestock.Although some adaptation options could reduce greenhouse gas emissions, the potential for mitigation in smallholdersystems is limited. Moreover, contrary to the general conclusion that greenhouse gas emissions per kg of milk ormeat are much greater in smallholder systems than in more intensive livestock systems, the emissions per sustainedlivelihood are far smaller in the African context. Furthermore, especially in areas that are likely to become drier,the role of extensive livestock keeping is likely to become more important as systems adapt to climate change. Thisis likely to result in even larger greenhouse gas emissions per kg of milk or meat. Thirdly, evidence across Africashows that farmers adopt improved feeding practices and intensify livestock production systems only where marketincentives and enabling institutions are present. We conclude that mitigation will only be possible through placinggreater emphasis on adaptation.



A Novel Tool to Assess the N2O, CH4 and NH3 Mitigation Potential of environmental Techniques inintensive Livestock Operations

M. Aguilar Ramireza, H. Arriagab, P. Dupardc, S. Lalord, R. Fragosoe, O. Pahlf , A. Abaigara, L. Cordovina, M.

Viguria Salazarb, M. Boylef , G. Lanigang, L. Loyonc and P. Merinob

aINTIA, S.A., Avda. Serapio Huici, N◦ 22, 31610 Villava, Spain; bNEIKER-Tecnalia, Berreaga 1, parcela 812,E-48160 Derio, Spain; cIRSTEA, Groupement de Rennes, 17, avenue, 35044 Rennes, France; dTeagasc, JohnstownCastle Research Centre, N/A Wexford, Ireland; eInstituto Superior de Agronomia, ISA, Tapada da Ajuda, 1349-017

Lisbon, Portugal; fGlasgow Caledonian University, Cowcaddens Road, G4 0BA Glasgow, UK; gTeagasc,Environmental Research Centre, Johnstown Castle, Wexford Co. Wexford, Ireland

[email protected]

1. Introduction:To successfully and efficiently reduce pollution from agriculture, it is necessary to determine appropriate mitigationoptions for particular farms, and to select among these options on the basis of their cost-effectiveness along the entireproduction process. We present a novel tool (Batfarm software) to assess the mitigation potential of nitrous oxide(N2O), methane (CH4) and ammonia (NH3) losses as a consequence of different strategies and techniques implementedon intensive cattle, pig and poultry farms.2. Material and Methods:We have reviewed emissions and consumptions from different environmental strategies implemented on farms to beincorporated in the software data base. Some of these data came from on-farm measurements obtained at regionalscale. Default values, modifiable by the user, have been included to develop versatile and user-friendly software.Regionalizable input values for zootechnical data, climatic information and emission factors have been defined inorder to reflect different climatic and production conditions within Portugal, Spain, France, UK and Ireland. As aresult, both nutrient balance and gaseous emissions were calculated throughout the different stages of the animalproduction system (housing, storage, treatment and landspreading) based on particular farm management criteria asdefined by the user. All calculations were performed on a cumulative monthly and annual basis. Users have the optionof introducing parameters to calculate the cost of the techniques selected and they also can compare two differentscenarios.3. Results:The main outputs of the model are: (i) whole farm feed, energy and water consumption; (ii) whole farm animalproduction; (iii) whole farm NH3, N2O, CH4 emissions; (iv) whole farm solid and liquid manure production andcomposition; (v) farm effects on faecal indicator organisms; and (vi) farm scoring (when two scenarios are compared).4. Conclusion:This work integrates existing information on the potential of different strategies and environmental techniques im-plemented to reduce gaseous and nutrient losses in livestock farms. The software enables simulation and comparisonof the combined effects of different environmental techniques throughout all the farm process, and takes account ofspecific management and climatic conditions, with the aim of facilitating the selection of the most suitable techniquesfor a particular situation. Further test will be necessary to validate the results provided by this tool.Acknowledgements: This work has been co-financed by BATFARM Interreg-Atlantic Area Project (2009- 1/071)entitled ”Evaluation of best available techniques to decrease air and water pollution in animal farms”.



Value of process-based Models compared to Tier 2 Adoption to achieve case-specific Greenhouse GasEmissions in Dairy Production Systems

A. Banninka, G. Laniganb, N.J. Hutchingsc, G. Bellocchid and A. Van Den Pol Van Dasselaara

aWageningen UR Livestock Research, PO Box, 65, 8200 A Lelystad, Netherlands; bTeagasc, Environmental ResearchCentre, Johnstown Castle, Wexford Co. Wexford, Ireland; cAarhus University, Department of Agroecology, Blichers

Alle, DK-8830 Tjele, Denmark; dINRA, UREP-Grassland Ecosystem Research, 5 chemin du Beaulieu, 63039Clermont-Ferrand, [email protected]

Process-based models are available for the farm components animal, field/soil and stored manure. These models areused to unravel the key mechanisms involved with variation in farm greenhouse gas (GHG) emissions in the farmcomponents. However, while process-based models exist for each of the key categories of farm emissions, linking themodels within a common framework offers a unique insight into the biotic and abiotic mechanistic drivers of emissions.All process-based models describe microbial activity and decomposition of organic matter, giving rise to the methane,nitrous oxide or carbon dioxide emissions.Apart from the representation of in situ conditions, every model adopts the concept of microbial activity being limitedby both degradable organic matter and available nitrogen. As a consequence, inputs and outputs of the individualmodels could be related in the present project AnimalChange (FP7-266018). This enabled the use of the models incombination to study GHG emissions for a specific farm case or management option. The models covered emissionsfrom enteric fermentation in dairy cattle and from soils and stored manure on dairy farms. Farm cases under varyingclimatic conditions were selected for availability of data to allow realistic model simulations. Predictions of GHGemissions by process-based models were compared to the values obtained when adopting the more generic Tier 2approach.The extent to which adoption of concepts represented by process-based models may aid in obtaining a more accurateand farm specific survey of GHG emissions is discussed. This includes the need to delineate any potential trade-offsbetween individual GHGs as well as the need to explore any potential impact of future climate change.



Bayesian Calibration of the Pasture Simulation Model (PaSim) to simulate Emissions from long-termGrassland Sites: a European Perspective

G. Bellocchi and H. Ben Touhami

INRA, UREP-Grassland Ecosystem Research, 5 chemin du Beaulieu, 63039 Clermont-Ferrand, [email protected]

The Pasture Simulation model (PaSim, https://www1.clermont.inra.fr/urep/modeles/pasim.htm), a biogeochemicalmodel to simulate water, energy, carbon and nitrogen cycles, is extensively used to investigate greenhouse (GHG)emissions from European grasslands. The model is difficult to calibrate over large territories and the values of mostof its parameters are assumed to be fixed and identical for all model realizations. Based on a sensitivity analysis, wedetermined parameters to be calibrated under European conditions.The study documents the improvements obtained with Bayesian calibration in estimating carbon fluxes (NEE, NetEcosystem Exchange), using long-term observations from a range of semi-natural grassland systems in Europe. Thesites involved in this study cover a broad gradient of geographical and climatic conditions, as well as soil types andmanagement options (intensive, extensive; cutting, grazing; fertilisation, non-fertilisation). The Bayesian approachwas used to update prior parameter distribution (expression of current imprecise knowledge about parameter values)to achieve a posterior distribution (expression of reduced uncertainty and more precise parameter values) by incor-porating the information contained in the measured data of seven multi-year observational grassland sites in Europe:Amplero (Italy), Bugac-Putsza (Hungary), Easter Bush (United Kingdom), Fruebuel and Oensingen (Switzerland),and Laqueuille intensive and extensive plots (France). A further four sites were held back for assessing model perfor-mance against independent data: Vall D’Alinya (Spain), Grillenburg (Germany), Monte Bondone (Italy), and Cabauw(The Netherlands).The improvement of simulations after parameter calibration is reflected in the posterior estimates (thanks to maximumlikelihood) of NEE daily values, which are closer to observations than using the prior distribution. Posterior probabilityestimations were also effective in reducing the uncertainty related to model outputs. These results show that theparameterization of PaSim obtained via Bayesian calibration at multiple European sites has improved simulation ofC fluxes, though without compensating for limitations in the model structure to account for daily fluctuations in thefluxes. Even if the modelling of C fluxes from grasslands still merits further investigation, the new parameter setwould improve the reliability of large-scale simulations in Europe. This study is being extended towards estimationsof non-C GHG emissions from grasslands.



Energy and economic Analysis of Inclusion of integrated Crop-Livestock-Forest System in Cattle fat-tening Farm in Brazilian Amazon

A. Bendahana,b, M. Vigneb, R.D. Medeirosa, M.-G. Pikettyb, R. Poccard-Chapuisc,d and J.F. Tourrande

aEmbrapa Roraima, EMBRAPA - Center for Agroforestry Research of Roraima, BR 174 - Km 08 - CP: 133,69301-970 Boa Vista, Brazil; bCIRAD - UMR Selmet, Campus International de Baillarguet, 34398 Montpellier

Cedex 5, France; cCIRAD, Embrapa Amazonia Oriental - NAPT, Belem-Brasilia Rodovia PA256, Km, 68625-970Paragominas, Brazil; dCirad, UMR SELMET TA C /112, Campus de Baillarguet, 34398 Montpellier Cedex 5,

France; eCIRAD, CIRAD Lavalette, Bat.4, Bur. 127, 34398 Montpellier Cedex 5, [email protected]

Integrated crop-livestock-forest systems (ICLF) could be a land use alternative for intensification of food and woodproduction in the Amazon compared to the traditional and high climatic impact cattle ranching systems based on”slash and burn”. The objective of this research is to assess the economic and GHG-energy balance and biomassproduction of ILCF in the northern Brazilian Amazon.The studied farm is located in the municipality of Iracema in the State of Roraima (2◦17’56.33”N 61◦15’16.18”W).Climate of the region is characterized by average temperature of 27◦C and rainfall of ± 2.000mm. The local Acrisols(Argisol dystrophic Red-Yellow - Brazilian system Classification of Soils) contain 33.9% of clay in the first 40cm. Thephysic chemical showed low levels of phosphorus (1.48mg dm−3), 2.63% organic matter around, and a pH (water)of 5.8. Pasture area of the farm is 475ha and herd raises 500 males of Nelore-zebu. Weaned Animals are bought tobreeding farms in Roraima, with an average weight of 180 kg LW and are sold to slaughterhouses at a weight between480-500 kg LW. Feed system is solely based on Brachiaria brizantha and B. humidicola grazing. Mineral salt is offered”ad libitum” to all animals and throughout the year. Data on inputs and services used (quantity and price) andproduction of the different components (annual crops, trees and animals) were collected through the monitoring of aspecialized fattening farm.The communication presents an analysis of results performed by comparing the economic and energy balances of thefarm with or without inclusion of the ILCF system. Economic analysis was led via the Operating Cost Effectiveindicator. The energy balance was assessed via an energy analysis tool adapted to the Brazilian Amazonian context:the ANERPAAM method.First results based on real farm data show that inclusion of agroforestry systems in specialized cattle fattening farmpositively impacts the economy and energy balance.



Characterising the fractal Nature of Precipitation across South Africa

J. Botaia,b, A. Hassenc and E. Tasfamariamd

aUniversity of Pretoria, Department of Geography, Geoinformatics and Meteorology, 0028 Pretoria, South Africa;bUniversity of Pretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South Africa, 0028 Pretoria, South Africa;cUniversity of Pretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria,South Africa; dUniversity of Pretoria, Department of Plant Production, University of Pretoria, 0028 Pretoria, South

[email protected]

Precipitation is highly significant not only in meteorology because of its role in Earth’s energy and water budget butalso in hydrology and climate change and variability. The high variability structure and scale invariant characteristicsof precipitation demonstrate an inherent distinct peculiarity that has attracted the attention of researchers fromdiverse disciplines of natural and agricultural sciences. Variations in precipitation time series involve a modulation ofsmall- scale structures by large ones via a repetitive scale invariant mechanism across all spatial-temporal scales. Thismultifractal behaviour is often analyzed through the assessment of the degree of temporal multi-scaling behaviour aswell as the maximum probable singularity in the rainfall distribution.The goal of the present contribution is to examine the spatial-temporal scaling properties of the accumulated observed,three of the Coordinated Regional Downscaling Experiment (CORDEX) and reanalysed (European Center for MediumRange Weather Forecasting (ECMWF) Integrated Forecast System, ERA interim) rainfall, dry and wet spells for theperiod 1998 to 2008 based on the universal multi-fractality.Results demonstrate that both observed and downscaled rainfall, wet and dry spells across South Africa exhibitmultifractal parameters that have clear spatial dependence with high frequency of extreme values and yet generallyclose to climatological mean. The present study contributes towards a thorough understanding of climate change andvariability and therefore is vital to climate change impacts decision and policy makers as well as in adaptation andvulnerability particularly in the livestock production systems.



Resilience and Vulnerability of Beef Cattle Production in the Southern Great Plains under changingClimate, Land Use and Markets: Consumer Focus Groups

B. Brown, S. Wilburn and J. Hermann

Oklahoma State University, 301 Human Sciences, Oklahoma State University, Stillwater, 74078, [email protected]

The purposes of the study was to identify factors consumers considered when purchasing beef, to determine if theenvironmental impact of beef cattle production was a factor in the amount of beef consumers purchased and consumed,and if information that the beef cattle industry was working to reduce environmental impacts of production wouldchange the perceptions of beef consumers and beef purchase practices. Beef production in the Southern Great Plainsis changing as the climate becomes warmer and drier. Ranchers cope with environmental changes by reducing herdsize and exploring alternate methods of production and breeds raised. Their decisions impact consumer beef choices.Focus groups were held in Oklahoma in three population density categories: below 10,000, between 10,000 and 50,000people and more than 50,000 people. The median household income across population density groups was $30,000-$50,000, representative of the median household income for Oklahoma ($44,891, U.S. Department of Commerce 2012).Ninety percent of participants were female. Beef was the overwhelming protein of choice across all population densitygroups yet many had switched to other protein sources (frequently chicken and legumes) because, while they consideredbeef a healthful choice, they were concerned with the cost of beef and the use of growth promoters during production.When participants bought beef they considered factors including price, taste preference, quality of marbling andfreshness, intended use, number to be served, health (leanness) and production factors (grass vs. grain fed, organic,use of hormones and antibiotics, locally produced). This supported previous studies where price of beef, quality ofmarbling and freshness were found to be considerations when meat was purchased (Lusk and Briggeman 2009 andMennecke 2007).Environmental impacts of beef cattle production were specifically discussed in the last section of the focus groupquestion lines but participants, with few exceptions, responded they did not think reducing the environmental impactof beef cattle production would change their perception of beef or purchase practices regarding beef foods. However ifthe cost of beef increased due to production changes they indicated they would probably consume less beef. Resultsfrom this study add to the knowledge of the consumer’s considerations when purchasing beef and their perception ofbeef production practices on the environment.Acknowledgement: This research was funded by USDA Project No. 2012-02355 through the National Institute forFood and Agriculture’s Agriculture and Food Research Initiative (AFRI), Regional Approaches for Adaptation to andMitigation of Climate Variability and Change.



Evaluating the new ORDHIDEE-GM (Grassland Management) Model to tropical Area in Brazil

P.P. Coltria, N. Viovyb, J. Changb, L.C. Araujoc, L.G. Barionid, P.M. Santose and J.R. Pezzopannee

aFEAGRI/UNICAMP, Av. Candido Rondon, 501, 13083-875 Campinas, Brazil; bLSCE, Bat. 709, Orme desMerisiers, F-91191 Gif-Sur-Yvette, France; cUNESP, Rua Moncao, 226, 15385000 Ilha Solteira, Brazil; dEmbrapaAgriculture Informatics, Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil; eEmbrapa Pecuaria

Sudeste, Rodovia Washington Luiz, km 234, 13560-970 Sao Carlos - Sp, [email protected]

The elevation on greenhouse gases (GEE) concentration is causing significant changes to the climate, with importanteconomical and social consequences. In Brazil, cattle is under the spotlight both due the magnitude of GEE flow andbecause of its potential to mitigate emissions, particularly when considering the capacity of carbon sequestration insoils under pastures. On the other hand, cattle may suffer significant impacts with climate change. Forage species,animal breeds and productive systems, previously adapted, may be vulnerable under future scenarios, mainly due tothermal and hydric stress, resulting from adverse climate.To evaluate the net balance of gases flows and the impacts of climate on livestock production systems, models ofpasture ecosystem must be used. In this context, the new model ORCHIDEE-GM (Grassland Management), whichis enabled with a management module inspired from a grassland model (PaSim, version 5.0), has been successfulyused within European sites. The main objective of this work was to evaluate ORCHIDEE-GM against Brazilian fielddata. Biophysical parameters of Mombaca Guinea grass (Panicum maximum Jacq.) were set based on an experimentcarried out at Embrapa’s Southeast Cattle Research Center at Sao Carlos, Sao Paulo, Brazil.ORCHIDEE-GM showed a good performance to simulate leaf area index (LAI) (R2=0.79; p-value>0.0001; RMSE=1.93),leaf biomass (R2=0.79; p-value>0.0001; RMSE=929.7 kg/ha) and dry matter (R2=0.89; p-value>0.0001; RMSE=4443.5kg/ha). However, the results were not good at simulating specific leaf area (SLA) (R2=0.4; p-value =0.0198;RMSE=48.54 g/cm2). Total biomass was overestimated, particularly in winter. Analyzing seasonal response, the bestcorrelation to LAI occurred in summer and spring (R2=0.83), followed by winter (R2=0.79) and autumn (R2=0.76).To leaf biomass, the best correlation occurred in spring (R2=0.89), followed by autumn (R 2=0.83), summer (R2=0.78)and winter (R2=0.76). To dry matter simulation, the best correlation happened in autumn (R2=0.93), followed bysummer (R2=0.87), spring (R2=0.85) and winter (R2=0.66). To specific leaf area, the best correlation happened insummer (R 2=0.51), and the correlation to other seasons was inferior to 0.2.The ORCHIDEE-GM showed good responses and good correlations when compared to real data, especially to leafarea index and leaf dry matter. Results indicate the model needs improvement in estimating variations in specificsurface area and total biomass.



Impact of Extreme climate events on Livestock Productivity in South Africa

L.K. Debushoa, T.A. Diribaa, J. Botaib,c and A. Hassend

aUniversity of Pretoria, Department of Statistics, Private Bag X20, Hatfield, 0028 Pretoria, South Africa; bUniversityof Pretoria, Department of Geography, Geoinformatics and Meteorology, 0028 Pretoria, South Africa; cUniversity ofPretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South Africa, 0028 Pretoria, South Africa; dUniversity ofPretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria, South Africa

[email protected]

Recent report of South African Weather Service shows that in some part of the country prolonged droughts existbecause of below-normal rainfall recorded over a period of one year or longer and some regions even experiencedseverely to extremely dry conditions. In addition, some parts of the country have been prone to floods and coldweather which have had severe negative impacts on road infrastructure and agricultural production. The change inclimate, such as rise in temperature, change in rainfall patterns, extreme weather events (e.g. storms, flooding, droughtand heat waves) affects the animal production through either direct effect such climate on animal or indirectly throughits impact on forage production. According to Kimaro and Chibinga (2013), the climate variability will have a seriouseffect on pastoralists whose livelihood depends upon livestock for food and economic security. The climate change canalso cause livestock diseases which can result in severe effects on livestock survival, marketability, animal health andlivelihoods (Gardner 2012). The objective of this paper was to assess the impact of climate change including extremeclimate events on livestock production. To achieve this objective more than 30 year historical data for livestockproduction were used for the study, and subjected to statistical models. Furthermore, the study has examined thevulnerability of the production under future climate scenarios using climate data generated by the global circulationmodels (GCM). The statistical results revealed that climate change is highly likely to affect negatively livestockproduction. Furthermore, based on the GCM scenarios that we have considered, our preliminary analyses results alsoshowed that the climate change could impose some risk on livestock production in the country.



Analysis of extreme Climate Events and their Impact on Maize and Wheat Production in South Africa

T.A. Diriba

University of Pretoria, Department of Statistics, Private Bag X20, Hatfield, 0028 Pretoria, South [email protected]

An extreme event is an event with a very high or low value with a low probability of occurrence. It can be characterizedas a very seldom, as rare as or rarer than the 10th or 90th percentile of the observed probability density function(IPCC, 2007) and very intense event with severe impacts on society and biophysical systems. Changing temperatureand weather pattern have great influence on increasing magnitude of climate change impacts. As reported by IPCC(2007), the average global surface temperature has risen by 0.8◦C in the past century and by 0.6◦C in the past threedecades (Hansen et al 2006).The extremes of most meteorological variables, such as precipitation and temperature, are of interest because theycan have tremendous impact on humans among other things through their effect on agricultural production. Thus itis crucial to characterize their behaviour statistically, as it is expected that an extreme climate event could directlyimpact agricultural production.The aims of this study were (i) to characterize statistically the extreme climate events for selected locations in SouthAfrica using both the frequentist and Bayesian approaches, and (ii) to determine the impact of the extreme climateevents at these selected locations on maize and wheat production.The results showed that the extreme events fitted better in Bayesian approach than in frequentist. Furthermore, itis observed that maize and wheat yield decreased with the prevalence of the extreme climate events. However, thelater results need further investigation as the analyses did not consider potential effects of, for example, the type offertilizer used on the field.



Pasture Management and Livestock Genotype Interventions to improve whole Farm Productivity andreduce Greenhouse Gas Emissions Intensities

M. Harrisona, K. Christiea, R. Rawnsleya and R. Eckardb

aTasmanian Institute of Agriculture, Post Office Box 3523, 7320 Burnie, Australia; bUniversity of Melbourne,Melbourne School Land & Environment, 3010 Melbourne, Australia

[email protected]

Livestock greenhouse gas (GHG) emissions form the largest proportion of emissions from agricultural activities. Herewe seek intervention strategies for sustainably intensifying the productivity of prime lamb enterprises without increasingnet farm emissions. We apply a biophysical model and an emissions calculator to determine the implications of severalinterventions to a prime lamb farm in Victoria, Australia. We examine the effects of lamb liveweight or age at sale,weaning rate, maiden ewe joining age, genetic feed-use efficiency, supplementary grain feeding according to greenpasture availability, soil fertility and botanical composition. For each intervention, stocking rates were optimised tothe lesser of a minimum ground cover or a maximum amount of supplementary grain feed.Total animal production of the baseline farm was 478 kg clean fleece weight plus liveweight (CFW+LWT)/ha.annumand ranged from 166 to 609 kg CFW+LWT/ha.annum for interventions that replaced existing pastures with annualryegrass or increased soil fertility, respectively. Annual GHG emissions intensity of the baseline farm was 8.7 kg CO2-e/kg CFW+LWT and varied between 7.7 and 9.2 kg CO2-e/kg CFW+LWT for interventions that reduced maidenewe joining age or increased sale liveweight, respectively. Stocking rate primarily governed production, and in manycases production drove emissions, so interventions that increased production did not always reduce emissions intensity.Indeed, replacing existing perennial ryegrass/subterranean clover pastures with perennial legume swards caused largereductions in both production and emissions, and interventions that increased soil fertility caused large increases inproduction and emissions; as a consequence both strategies had little effect on emissions intensity.Stacking several beneficial interventions together further increased production and reduced emissions intensity relativeto individual interventions alone. Baseline production increased by 61% by increasing soil fertility, improving feed-useefficiency and reducing the joining age of maiden ewes, while baseline emissions intensity was reduced by 17% bystacking together three similar interventions. We suggest that imposing several beneficial strategies on existing sheepfarming systems simultaneously is more conducive to sustainable agricultural intensification compared with imposingany single intervention alone. The best strategies for both sustainably increasing production and reducing emissionsintensity were those that decoupled the linkage between production and emissions, such as interventions that shiftedthe balance of the flock away from adults and towards juveniles while holding average annual stocking rates constant.



Evaluating Mobility in Mediterranean Sheep farming Systems regarding Mitigation to climatic Change

J. Lasseura, A. Viganb, M. Benoitc, C. Dutillyb, M. Eugenec, F. Mouillotd and M. Meuretc

aINRA-UMR SELMET, 2 place viala, 34060 Montpellier, France; bCIRAD - UMR Selmet, Campus InternationalBaillarguet, 34398 Montpellier, France; cINRA-UMR H, Theix, 63122 St Genes-Champanelle, France; dCEFE

CNRS, route de mende, 34000 Montpellier, [email protected]

In the Mediterranean area, a recent and strong assumption is that pastoral livestock systems actively contribute tothe dynamics of ecosystems. They are highly structuring landscapes on mid and long term scales, thus being involvedin the issues of mitigation and adaptability to climate hazards across the socio-ecological system as a whole.Mobility practices in these livestock systems could be seen as options regarding mitigation to climate change. Toevaluate suitability of such practices, we present hypothesis, methodological framework and models involved in thecase of pastoral sheep farming systems.We formulate following hypotheses:- Mobility decreases the competition with croplands, as the proportion of the annual diet of the herd will come mostlyfrom rangeland and other non-arable lands.- Mobility contributes both to a better animal production energy balance (e.g. lowering the fossil fuels requirementsof the farm) and to some ecosystem services (e.g. targeted grazing to improve wildlife habitats’ quality and reducewildfire hazard).- Mobility, facilitating grazing on natural areas, impact biogeochemical cycles particularly C cycle.In terms of research methodology and tools, assessing mobility’s impact on climate change mitigation requires to betterunderstand GHG balance while comparing different mobility strategies in line with: i) the related contributions ofdifferent forage resources, ii) the types and levels of inputs used in each farming system (and manure management),iii) the overall farming activities across the landscape and their respective contribution on land use changes.We perform analysis with a methodological chain using four steps: i) making a typology of farming systems regardingmobility and describing their operating system, distribution of grazing in space along the year, and resulting per-formance indicators of such systems; ii) evaluating the diversity of required fodder resources in each type of sheeppastoral systems and the associated digestive processes in order to compare their CH4 emissions; iii) modeling theimpact of grazing practices at landscape level on biogeochemical cycles and the associated C sequestration/emissionswith CASA model; iv) integrating the results from the three previous steps within OSTRAL, a farm economic andenvironmental performance model.The first results of simulation of on-farm processes enable us to build a hierarchy between main factors affectingmitigation performances within the diversity of farm types we identified.



A Model of the Dynamics of Cattle Systems Types to study Greenhouse Gases Mitigation in theBrazilian Conditions

J.M.M.A.P. Moreiraa, L.G. Barionib, M.D.C.R. Fasiabenb, A.F. Oliveirab and R.D.O. Silvab

aEmbrapa Florestas, Estrada da Ribeira, km 111, 83411-000 Colombo, Pr, Brazil; bEmbrapa AgricultureInformatics, Av. Andre Tosello, 209, Barao G., 13083-886 Campinas - Sp, Brazil

[email protected]

This work reports on the development of a multiperiod linear programming model to optimize private profitability of thetrajectories of land use of the most representative types of cattle production systems in Brazil. Each type of productionsystem (TPS) carries intrinsic properties such as stocking rates, productivity, profitability and greenhouse gasesemissions, among others. The decision variables correspond to the area of each TPS in each biome and each year. Themodel represents the dynamics of land use through transition of one type of production system to another, computingthe costs associated with each transition. The dynamics of TPS is constrained by technically feasible transitionpathways, financial resources available for investment, maximum greenhouse gases emissions, legally protected areas,dynamics of land use by other activities and the demand for cattle products over time. The model also considers,independently, the resistance of farmers to a change of the current TPS and to the adoption of a new TPS.As a first test, the model prototype was run with data aggregated for Brazil for a 17 years period (2008 a 2025). Thetypes of production systems allowed were: degraded pastures; extensive pastures; crop-livestock integrated systems;feedlot finishing and spare land (i.e. land that was left to other uses).Seventy-five optimal solutions were obtained by combining five levels of availability of financial resources for investmentand fifteen levels of emission constraints. Profit was sensitive both to financial resources available and to the maximumlevel of emission allowed. At a given (constrained) level of emissions, investments always increased profit. However,profit was more sensitive to emissions constraints under higher levels of investment and, therefore, returns on investmentwere lower when emissions constraints were tighter.The next steps are the discussion of the model with experts on beef and dairy production in order to define regionaldata and to validate and refine the model. The sequence of those modeling studies will enable improved evaluationand substantiate public policies related to mitigation, particularly the Brazilian National Policy for Climate Change,and will also address the analysis of representative agriculture pathways.



Auditing the Carbon Footprint of Milk from commercial Irish grass-based Dairy Farms

D. O’briena, P. Brennanb, E. Ruanea, J. Humphreysa and L. Shallooa

aTeagasc, Moorepark, Animal & Grassland Research and Innovation Centre, Co. Cork Fermoy, Ireland; bBord Bia,Clanwilliam Court, Lower Mount Street, 2 Dublin, Ireland

[email protected]

Life cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass- based farms are usually limited toless than 30 farms and rarely certified to international standards e.g. British Standards Institute publicly availablespecification 2050 (PAS 2050). The goals of this study were to conduct an audit of CF of milk from a large sample(>100) of grass-based farms according to PAS 2050 and to assess relationships between farm practices and CF of milk.Annual farm audits were conducted using on-farm surveys, milk processor records and national livestock databasesfor 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fedinto a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model inCO2 equivalents (CO2-eq) and allocated economically between dairy farm products, except exported crops. Carbonfootprint of milk was estimated by expressing GHG emissions attributed to milk per kg of fat and protein correctedmilk (FPCM). The Carbon Trust tested the LCA model for non- conformities with PAS 2050. PAS 2050 certificationwas achieved when non- conformities were fixed or where the effect of all unresolved non-conformities on CF of milkwas < ± 5%.The combined effect of LCA model non-conformities with PAS 2050 on CF of milk was < 1%. Consequently, PAS 2050accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO2-eq/kg of FPCM,but varied from 0.87-1.72 kg of CO2-eq/kg of FPCM. Although some farm attributes had stronger relationships withCF of milk than others, no attribute accounted for the majority of variation between farms. However, CF of milk couldbe reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacementrate (R2 = 0.75). Management changes can be applied to improve each of these traits. Thus, grass-based farmers canpotentially significantly reduce CF of milk.The certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approachto quantify CF of milk at a farm or national level. The application of the certified model highlighted that differencesbetween 124 grass-based farms’ CF of milk were explained by variation in various aspects of farm performance. Thisimplies that improving farm efficiency can mitigate CF of milk.



Grazing Effects on Grassland Productivity - Linking Livestock Production to Grass Yields

S. Rolinskia, I. Weindla and J. Heinkeb

aPotsdam Inst for Climate Impact, Telegrafenberg, A31, 14473 Potsdam, Germany; bILRI, P.O. Box 30709, 00100Nairobi, Kenya

[email protected]

The implementation of grazing options into a global dynamic vegetation model including the agricultural sector(LPJmL) enables locally specific analysis of feedbacks between primary productivity and grass biomass removal byanimals on the global scale. Using different animal densities as well as grazing durations, consequences can bedistinguished between the grazing pressure itself and the timing of grazing. Varying the density of grazing animalsalso enables to find local optimal densities which enhance primary productivity and grass yield simultaneously. It isexpected that low animal densities increase grass productivity whereas high grazing pressure deteriorates the plantsability to recover. The global application of this concept gives information on potential grass yields under varyingclimatic conditions, thus, potentials for livestock production under sustainable conditions for pasture.Using these optimal grass yields, the impacts of livestock production on resource use is assessed by applying theglobal land use model MAgPIE. This model integrates a detailed representation of the livestock sector and integratessocio-economic regional information with spatially explicit biophysical data. With the analysis of scenarios varying thedemand side as well as the supply side of the world food equation, we analyze the impact of livestock production onfuture deforestation and land and water use. Our results indicate that the reduction of animal derived calory demandin the developed world has a huge potential to spare land for nature and reduce deforestation. On the supply side,feeding efficiency gains especially in Africa, Latin America and Pacific Asia can help to decrease demand for land andoverall biomass requirements.



Testing CORDEX downscaled Weather Data against historical Data to predict Weeping Lovegrass(Eragrostis curvula) Hay Yield in selected agro-ecological Zones of South Africa

E. Tesfamariama, J. Botaib,a and A. Hassenc

aUniversity of Pretoria, Dept of Plant & Soil Sciences, Hatfield, Pretoria, South Africa, 0028 Pretoria, South Africa;bUniversity of Pretoria, Department of Geography, Geoinformatics and Meteorology, 0028 Pretoria, South Africa;

cUniversity of Pretoria, Department of Animal and Wildlife Sciences, University of Pretoria, Hatfield, 0028 Pretoria,South Africa

[email protected]

African countries face serious impacts from climate change in this century and beyond. The technology and method-ology behind regional climate models, downscaled from global climate models, are improving to provide informa-tion about future climate change and its impact in finer detail. The Coordinated Regional Downscaling Experi-ment (CORDEX) program was recently established by the World Climate Research Program (WCRP). The aim ofCORDEX is to develop an international coordinated framework for generating improved regional climate change pro-jections worldwide. Results from the CORDEX analysis will be used as input to the IPCC Fifth Assessment Reportas well as to meet the growing demand for high-resolution downscaled projections to inform climate change impactand adaptation studies.The aim of this study was to evaluate the downscaled weather data using CORDEX and predicted crop yield againsthistorical weather data for selected sites representing eight of the nine provinces of South Africa.The evaluation was conducted for eight sites from eight provinces of South Africa (Bloemfontein, Nelspruite, Johannes-burg, Kimberly, Lady Smith, Queenstown, Rustenburg, and Thabazimbi) representing various agro-ecological zones.The dominant soil type in each site was selected to simulate weeping lovegrass (Eragrostis curvula) hay productionusing the SwbSci model simulations. The amount of rainfall predicted using CORDEX was four to seven times higherthan the historical data. The historical rainfall record for the study sites during the growing seasons varied between200 to 400 mm. This is in contrast to the CORDEX generated rainfall data which ranged 1100 to 2200 mm. Simulatedhay yield using historical measured data ranged between 1.3 t ha−1 in Thabazimbi to 8.3 t ha−1 in Nelspruit. Incontrast, simulated weeping lovegrass hay yield using weather data generated from CORDEX ranged between 7.6 tha−1 in Thabazimbi to 19 t ha−1 in Kimberly. In summary, downscaled rainfall data from CORDEX for the selectedsites across South Africa had low accuracy to rely on for future climate change prediction.Acknowledgment: The authors gratefully acknowledge funding from the University of Pretoria, Dept. of Scienceand Technology and the European communities, 7th framework programme under the grant agreement No. 266018,AnimalChange project.



Evaluation of Regional Agri-Environmetal Policy on Livestock Greenhouse Gas Emissions

A. Vitalia, S. Lo Prestib, T.M.I. Schipanic, A. Nardonea and N. Laceteraa

aUniversity of Tuscia, Via S. Camillo de Lellis, snc, 01100 Viterbo, Italy; bAgriconsulting S.P.A., Via Vitorchiano,123, 00189 Roma, Italy; cRegione Emilia Romagna, Via della Fiera, 8, 40127 Bologna, Italy

[email protected]

The study is part of the evaluation process of the Rural Development Policy adopted by the Italian Region of EmiliaRomagna during the period 2007-2013. The main objective was the assessment of the environmental effects of theagri-environmental support, axis 2, measure 214, included in the Rural Development Program. In details, the analysisevaluated the effect of the conversion of dairy cow and cow-calf farms from conventional to organic system productionon greenhouse gas emissions. The emissions of methane (CH4) from enteric fermentation and of CH4 and nitrous oxide(N2O) from manure handling were evaluated.A total of 4,754 farm records were considered: 3,282 conventional and 54 organic dairy farms, and 1,291 conventionaland 127 organic cow-calf farms. Single farm demographic structure (cows, heifers and calves consistencies) was obtainedfrom the National Bovine Registry. Milk yield data were provided by the National Agricultural Paying Agency. Datawere referred to the years 2009-2011. Additional data were taken by the International Panel on Climate Change(IPCC), the Italian National Inventory Report (NIR) and by interviews carried out on a selected number of farms.Greenhouse gases emitted were estimated using a Tier 2 approach as suggested in the guidelines provided by the IPCCand in accordance with NIR. The CH4 and N2O emissions were expressed as kg CO2 equivalent (CH4, kg x 25; N2O,kg x 310) to account for the Global Warming Potential (GWP). The GWP (mean ± standard deviation) were referredto Livestock Unit (LSU equivalent to 600 kg live mass) or to kg of milk (the latter only for the dairy sector). TheGWP for dairy farms were 3,618±304 and 3,427±425 kg CO2 eq. LSU year−1 for conventional and organic systems,respectively. The GWP referred to milk yield were 0.84±0.3 and 0.99±0.3 kg CO2 eq. kg milk−1 for conventional andorganic system, respectively. The GWP for cow-calf farms were 2,550±427 and 2,368±192 kg CO2 eq. LSU year−1

for conventional and organic systems, respectively. Enteric CH4 was the greater source of GWP and it accounted for75% and 88% in dairy and cow-calf sector, respectively.The total LSU raised in organic system contributed to save 961,527 and 802,422 kg CO2 eq. year-1 for dairy andcow-calf sector, respectively. The measure 214 contributed to reduce GWP when considering LSU, but not whenconsidering milk yield. Further studies are necessary to identify appropriate mitigation options to be implemented infuture agro-environmental policies.



Excellent Dairy Farming Profile

M. Zucali, L. Bava, M. Guerci, A. Tamburini and A. Sandrucci

Universita degli Studi di Milan, via Celoria 2, 20133 Milano, [email protected]

In recent years, dairy farmers are expected to achieve a sustainable profit to continue their activity and to pay attentionto environmental quality. The objectives of this research were to identify and describe intensive dairy farms with anexcellent profile in term of environmental and economic sustainability and milk nutritive value. The research involved28 dairy farms located in the North of Italy, members of a cheese factory, which produces Grana Padano cheese O.P.D.Through personal interviews with the farmers, a questionnaire was addressed to obtain information about the cropsystems, fuel consumption, animal management, housing systems, feeding strategies, purchased feeds, fertilizers andpesticides. Environmental impacts of milk production were assessed through a cradle-to-farm-gate Life Cycle Assess-ment considering global warming, eutrophication, acidification, land use and energy use; the functional unit was 1 kgFat Protein Corrected Milk (FPCM). To estimate farm economic sustainability, gross margin and income over feed cost(IOFC) were calculated; milk quality was defined by fat and protein percentages. The environmental impacts and theeconomic and milk quality parameters of each farms were indexed from 1 to 3 (bad to good), based on distance fromthe average values of the group of farms. From the juncture of the five environmental indices, a global sustainabilityindex was calculated. Farms were classified on the basis of dairy efficiency (DE=kg FPCM/kg DMI).High efficiency herds (DE≥1.4) performed better in terms of for global warming, energy use and eutrophication showinghigher indices than the herds with low efficient cows (DE=<1.2). This result is explained by the characteristics of thehigh efficient herds: high milk production (31.0±2.88 kg FPCM/cow day), medium feed self-sufficiency (60.3±14.0%), balanced cow diet (1.35±0.41 forage/concentrate). These herds produced high quantities of milk with less feed,reducing the environmental impacts related to feed production. As manure and enteric emissions weigh a lot on globalwarming potential, achieving high production levels with fewer animals allows to mitigate the climate impact per milkunit. Eutrophication is mainly due to crop production activities on-farm; as a consequence farms with high feed self-sufficiency, that produced most of their feed on-farm, have high eutrophication impact. They tend to administer highforage diets that negatively affect milk production, increasing impacts per unit of product.In conclusion the excellent farms were the farms with high dairy efficiency, they showed the best performances interms of both milk quality, economic results and environmental sustainability.


Tues. 11:15 Medici I Parallel session 3a: The farm scale

Mitigation Options in Perspective of Greenhouse Gas Emissions and Production on European DairyFarms

M. Stienezena, D. O’brienb, E. Cutullicc, P. Faverdinc, J.-L. Fiorellid, G. Holshofa, N.J. Hutchingse, J.E. Olesene, H.Perdokf , L. Shalloob and C.F.E. Toppg

aDLO WUR Livestock Research, Postbus 65, 8200 AB Lelystad, Netherlands; bTeagasc, Moorepark, Animal &Grassland Research and Innovation Centre, Co. Cork Fermoy, Ireland; cINRA, UMR1348 PEGASE, 35590 St-Gilles,France; dINRA-SAD / Unite ASTER, 662 avenue Louis Buffet, F- 88500 Mirecourt, France; eAarhus University,Department of Agroecology, Blichers Alle, DK-8830 Tjele, Denmark; fCargill Animal Nutrition, Cargill Innovation

Center, 5334 LD Velddriel, Netherlands; gSRUC, West Mains Road, EH9 3JG Edinburgh, [email protected]

The AnimalChange project aims at giving AN Integration of Mitigation and Adaptation options for sustainableLivestock production under climate CHANGE. For this we focused on the effects of mitigation options on greenhousegas (GHG) emissions and production on European dairy farms.Data are available from several farm types: ”Maritime mixed dairy”, ”Maritime grassland dairy”, ”Continental mixeddairy”, ”Continental grassland dairy” and ”Mediterranean mixed dairy”. Data are provided from virtual farms andreal farms. The virtual farms are created by combining estimated data and information based on regional productionsystems and national statistics. Real-life data are collected on real farms. ”Maritime mixed dairy” is represented bya Dutch virtual farm, a Dutch real farm and a Scottish organic real farm. ”Maritime grassland dairy” is representedby two Irish virtual farms and one Irish real farm. ”Continental mixed dairy” is represented by a French virtual farm.”Continental grassland dairy” is represented by one French real organic farm and ”Mediterranean mixed dairy” isrepresented by an Italian virtual farm.Local experts identified the five best mitigation options for their farm(s). From the total number of identified mitigationoptions the six most common options were selected; fertilisation rate, grass-legume swards, legumes in the rotation,improving pastures, reducing replacement rate, genetic improvement in dairy cattle. These six mitigation options arefurther specified to be able to simulate the effects on GHG emissions and farm production from the farms mentionedabove. FarmAC, a simplified carbon and nitrogen flow-based model for assessing GHG emissions from livestockfarming, is used. The effects of mitigation options are simulated one at a time presuming that other factors remainthe same. Direct and indirect GHG emissions are calculated within the farm boundary; off farm emissions from theproduction of imported inputs are not taken into account.Mitigation is assessed both on a per ha and per unit of production basis. Production is expressed in kg milk producedor kg meat produced.Acknowledgement: The research leading to these results has been conducted as part of the AnimalChange projectwhich received funding from the European Community’s Seventh Framework Programme (FP7/ 2007-2013) under thegrant agreement n◦ 266018.



A Sequential Participatory Design Approach to adapt Grassland-based Livestock Systems to ClimateChange

M. Sautiera, M. Piqueta, M. Durua and R. Martin-Clouaireb

aINRA, UMR 1248 AGIR, 24 Chemin de Borde Rouge, F-31326 Castanet Tolosan, France; bINRA, UR 875 MIAT,24 Chemin de Borde Rouge, F-31326 Castanet Tolosan, France

[email protected]

Livestock systems are and will increasingly be impacted by climate change, primarily because the feed supply producedon the farm (pastures, forage crops) highly depends on the climatic conditions experienced. To adapt grassland-basedlivestock systems to climate change, some transformational redesign of the farming system may be required. Redesignis basically a matter of reconfiguration of land-use for feed production and of management practices set up to copewith weather variability.We present a participatory method to design systems adapted to new conditions. It is based on a pre-existing game-likeplatform (Forage Rummy) in which various year-round forage production and animal feeding requirements have to beassembled by participants with the support of a computerized support system. The considered weather scenario isconveyed by dedicated intermediary objects (e.g. herbage growth profile, rainfall bar chart) that are fully shown beforethe design process starts. The elaborated solutions are then evaluated according to criteria of biophysical performance,organizational feasibility, and feeding shortage risks. The method consists in a sequence of three workshops (W) forwhich the Forage Rummy was adapted. It keeps the complexity of the design problem manageable by progressivelyintroducing the difficulties to deal with. W1 aims at producing a configuration that satisfies average weather scenarioof the future. W2 refines or possibly revises the previous configuration by taking into consideration the between-yearsvariability and the induced requirement of anticipatory cautiousness of the generated solutions. W3 explicitly takesinto account the weather uncertainty. The weather scenarios considered in W1-2, conveyed by dedicated intermediaryobjects, are fully shown before the design process starts. In contrast, the weather is revealed month by month in W3.Experimental results of the use of the method with farmers are analysed and further enhancements of the method areoutlined.



Adoption of Farm-level Adaptation Strategies in Africa: a Review of recent Research and an AdoptionIndex

S. Garcia De Jalon and A. Iglesias

Technical University of Madrid, Avda. Complutense s/n, Ciudad U, Department of Agricultural Economics, 28220Madrid, Spain

[email protected]

In light of growing concerns over facilitating policy prescriptions to augment adoption of actions against climate changemany studies have been devoted to assess the drivers behind adoption of adaptation strategies.This study presents a composite index of adoption of farm-level adaptation strategies in Africa based on past research.We review and synthesize 42 case studies published in peer- review journals in order to identify those independentvariables that regularly explain adoption, and thereby can be used to develop a composite index of adaptation adoptionmeasures. We find that these commonly used independent variables can be grouped in seven categories in terms ofhuman capital, financial resources, infrastructure and technology, social interaction and governance, food security,dependence on agriculture, and attitudes towards the environment. Using national-level indicators of these sevencategories we provide a robust composite index of adaptation adoption in Africa. Validation of indicators is basedon the past research synthesis, and the sensitivity of subsequent adaptation adoption assessments to different sets ofweightings are explored using three weighting schemes, equal weights, proportional weights and random weights.The results show that the highest adoption rate of farm-level adaptation strategies is in Northern African countriessuch as Tunisia, Egypt, Algeria, and Morocco. On the contrary, they indicate that the lowest rate of adoption issituated in nations of the Sahel and Horn of Africa and in nations that have recently experienced conflict. Weconclude that adoption of farm-level adaptation strategies is associated predominantly with governance, civil rights,financial resources, and education.



Ex-ante Farm-Scale Analysis of the Impacts of Livestock Intensification on Greenhouse Gas Emissionsof Mixed Millet- Groundnut-Beef Cattle Systems in Senegal

C. Birnholza, J. Vayssieresb,a, N.J. Hutchingsc and P. Lecomted,e

aCIRAD - Umr Selmet, Campus ISRA/IRD de Bel Air, Route des hydrocarbures BP 1386, 18524 Dakar, Senegal;bCIRAD, 37 av. Jean XXIII, Dakar Etoile, BP 6189 Dakar, Senegal; cAarhus University, Department of

Agroecology, Blichers Alle, DK-8830 Tjele, Denmark; dCIRAD - UMR Selmet, Campus International Baillarguet,34398 Montpellier Cedex 5, France; eINRA SupAgro, Cirad Campus international, 34700 Montpellier, France

[email protected]

Smallholder farming is the backbone of Sub-Sahara African agriculture and food security. As farmers move awayfrom a more traditional form of farming because of demographic and environmental pressures, they engage in moreintensive forms of livestock production. Simulations of farming systems by models allow ex-ante evaluation of theimpacts of changing cultural and livestock practices on the sustainability of the farm. The objective of this study is touse an existing farm-scale model 1) to investigate new farming systems and their consequences on C and N cycles atfarm-scale, and 2) to evaluate greenhouse gas (GHG) mitigation strategies for West African Senegalese mixed farmingsystems.The model used, FarmAC, is a simple stock-flow model that offers an environmental sustainability evaluation as itdescribes the C and N cycles and calculates GHG balances. The GHG balance considers both on-farm direct emissionsand indirect emissions (from NH3 emission and NO4 leaching). Emission factors from the IPCC and specific parameterssuch as those of local cattle race and local feedstuff were integrated in the model. Parameters from the literature forrelevant farming systems and for study sites with similar semi-arid agro- climatic conditions were used when available.Three ”typical” farming systems were defined on the basis of extensive agronomic and livestock research carriedout in the groundnut basin region of Senegal by ISRA and CIRAD: i) a traditional extensive farm with fallow andcommunal grazing (system 1), ii) an intensive farm where manure is collected from cattle fattening (system 2), andiii) an improved intensive farm similar to system 2 but implementing further nutrient conservation measures such asurine collection, covered manure heap, in-soil manure and crop residues incorporation, and introducing legumes in therotation (system 3).These farming systems are compared on the basis of simulations. Livestock intensification (systems 2 and 3) appearsto be a relevant strategy to mitigate direct emissions at farm scale by improving roughage quality (less enteric methaneemissions), and improving both animal and crop productivity (more protein and N available along the cycle). Thisstrategy is even more relevant when biomass, carbon and nutrients are further conserved (system 3).As livestock production intensification is mainly based on the use of concentrate feed, further studies integratingindirect emissions occurring along the whole life cycle are needed to conclude on the effectiveness of this strategy tomitigate GHG emissions of Sub-Sahara African agriculture.


Tues. 11:15 Medici II&III Parallel session 3b: The landscape and regional scale

Adaptation to Climate Change in the global Livestock Sector and Mitigation Co-benefits

J. Heinkea, S. Silvestria and A. Mottetb

aILRI, P.O. Box 30709, 00100 Nairobi, Kenya; bFAO, Viale delle Terme di Caracalla, 00153 Rome, [email protected]

Targeting adaptation to climate change in the livestock sector requires an understanding of the expected impactof climate change on livestock production, especially at animal and feed production level. Recommendations andinterventions to help farmers to prepare for these impacts should be based on a selection of options specific to speciesand production systems. A problem with these targeted options to anticipated climate change is that the costsassociated with their implementation represent a barrier to their adoption. Adaptation options that provide a co-benefit in terms of mitigation of greenhouse gas (GHG) emissions are thus particularly attractive as their adoptionare supported by appropriated mitigation policies.This paper aims at identifying adaptation options and associated mitigation co-benefits at regional scale. In a firststep we estimate the degree by which global livestock production is affected by climate change and where adaptationis required. Projections of local temperature change and local change in aridity and drought frequency from multipleGCMs from the CMIP5 archive are combined with maps of livestock production from FAO’s Global Livestock En-vironment Assessment Model (GLEAM). Based on the type of impact and the type of production (livestock speciesand production system), application domains for a range of adaptation options are estimated. In a second step, theGHG emissions from livestock production from different sources (e.g. soil, digestion) in the application domains areestimated using estimates from maps of GHG emissions form GLEAM. In combination with the effect of differentadaptation options on GHGs emissions from these different sources, the potential co-benefits of their adoption formitigation are highlighted.



The Greenhouse Gas Mitigation Potential of the World’s Grazinglands

A. Falcuccia, B. Hendersona, R. Conantb, T. Hilinskib, D. Ojimab, M. Salvatorea and P. Gerbera

aFAO, Viale delle Terme di Caracalla, 00153 Rome, Italy; bColorado State University, Natural Resource EcologyLab, Fort Collins, 80523-1499, USA

[email protected]

There is widespread enthusiasm for harnessing the large potential of grazinglands to offset global greenhouse gasemissions, owing to their vast land area, history of degradation, and capacity for soil carbon storage. This study seeksto add to the growing body of evidence about the large potential of mitigation practices in the world’s grazinglands,and it marks an advance in two ways. First, we have applied mechanistic models - the Century and Daycent models- that can represent the effects of a variety of management practices on C and N cycling in agroecosystems. Thisis an improvement over the usual approach of extrapolation from field studies, because these models are capable ofmore-accurately representing the variety of agroecological conditions observed in the grazinglands. Second, by usingobservations of past and current management we confined our assessment to areas where livestock production is presentand where practice changes are likely to be effective.Three mitigation practices are tested, namely, improved grazing management, legume sowing, and N fertilization. Forthe first we ran the Century model for a set of grazing offtake scenarios to explore the soil C and forage benefits thatproducers might realize by shifting from current forage offtake rates to rates that maximize forage production. Forthe second and third options we employed the Daycent model to simulate changes in soil C-stocks, N2O emissionsand forage production, associated with legume sowing and N fertilization. We estimate that adjustments in grazingpressure lead to the annual sequestration of 148 Tg CO2 yr−1 in grazinglands worldwide. The amount of sequestrationvaried substantially between regions, mostly due to differences in grazingland area rather than variations in regionalsequestration rates. The soil C sequestration potential of 203 Tg CO2 yr−1 for legume sowing was higher than forimproved grazing management, despite being effective in a much smaller total area. However, legume sowing wasestimated to increase N2O emissions by 57 Tg CO2-eq yr−1, offsetting 26% of its global C sequestration benefits.Conversely, N fertilization was found to be ineffective as a mitigation option, because it led to increases in N2Oemissions which always exceeded soil C sequestration in CO2 equivalent terms, for all N fertilization rates in allregions. Our estimate for increasing C-stocks though in grazinglands is substantially less than earlier world-wideestimates, and this is mainly attributable to the much smaller land area over which we estimate mitigation practicesto be effective.



Assessment of Uncertainties in Greenhouse Gas Emission Profiles of Livestock Sectors in Europe, LatinAmerica and Africa

H. Kros, B. Zhu, J.P. Lesschen, P. Kuikman and W. De Vries

Alterra Wageningen UR, P.O. Box 47, Droevendaalssteeg 4, 6700 AA Wageningen, [email protected]

The global animal food chain, including land use change, generates 14.5% of global greenhouse gas (GHG) emissions.However, the contribution of livestock production to GHG emissions varies highly across livestock sectors and regionsacross the world. To assess the regional variations in dairy, beef, pork, poultry and egg production, and relatedGHG (i.e. CH4, N2O and CO2) emissions the MITERRA-Global model has been developed. This model includessimple process-based descriptions and empirical relationships and uses detailed statistical agricultural and GIS-basedenvironmental data in combination with various downscaling methods.The aim of this study is to analyse the propagation of uncertainties in model inputs and model parameters to modeloutputs, using a Monte Carlo analysis. Uncertain model inputs and parameters were represented by probabilitydistributions, partly defined by using expert judgement and partly derived from global datasets. Spatial correlationwas taken into account by assigning correlation coefficients at various spatial regionalization levels. The uncertaintypropagation was analysed for GHG emission profiles of livestock sectors in Europe, Latin America and Africa. Wequantified the main sources of uncertainty contributing to the output uncertainty in GHG emissions of livestock sectorsin the various regions and distinguished the emission sources enteric fermentation, manure management, direct andindirect N2O soil emissions, fossil fuel use and fertilizer production. This allows the agricultural sector to providemore accurate and robust GHG emission profiles. This could lead to the adoption of current mitigation packages withmeasures that are most (cost) effective.



Mitigation of GHG Emissions in Livestock Production Systems: assessing Potential from ModelingPackages of Options at regional Level

A. Mottet, B. Henderson, C. Opio, A. Falcucci, G. Tempio and P. Gerber

FAO, Viale delle Terme di Caracalla, 00153 Rome, [email protected]

The livestock sector needs to mitigate its GHG emissions while responding to growing demand for its products.Significant reductions can be achieved.This analysis explores the technical potential for reducing GHG emissions from different livestock production systemsat regional scale. It is based on a life cycle assessment approach using the Global Livestock Environmental AssessmentModel (GLEAM) developed by FAO, which produces dis-aggregated estimates of GHG emissions for the main livestockcommodities, farming systems and world regions. GLEAM quantifies emissions for defined spatial units and relies ongeographical patterns of soil quality, climate, land use and livestock systems and distribution. The mitigation optionsassessed were selected according to their effectiveness and their feasibility of adoption by farmers, for each region andproduction system. They focus on packages of available mitigation options that have proven to be effective over theshort to medium term.The results demonstrate that these packages can yield large environmental benefits, and decrease emissions by between14 and 41% in the different systems and regions explored in the analysis. High mitigation potentials were estimatedfor the ruminant systems in Latin America and Africa, mainly through improvements in forage quality, animal healthand husbandry, and grazing management. Significant emission reductions can also be attained in dairy systems withalready high levels of productivity, as demonstrated by the case study in EU countries, with feasible adoption ofimproved manure management systems, feed supplementation and energy saving equipment. Some of the assessedmitigation options can lead to a concomitant reduction of emissions and increase in production, and thereby contributeto food security.


Plenary session 4: Framing the options: the national/regionalscales


Tues. 13:15 Medici Plenary session 4: Framing the options: the national/regional scales

Ambitions versus Constraints: Some further Economic Issues relevant to sustainable Intensification ofAgriculture.

D. Moran

SRUC, West Mains Road, EH93JG Edinburgh, [email protected]

The basic economic attributes of efficient emissions mitigation and adaptation are by now well-known in agriculture;specifically the need to seek cost-effective reduction of carbon dioxide equivalents and the prioritisation of low cost orno- regrets adaptation measures. These objectives may not always be consistent but are both generally located within abroader agenda of sustainable intensification, which emphasises consumption, as well as production objectives, and theneed to develop better metrics of resource use efficiency. But advancement of this agenda faces formidable challengesin terms of both behavioural and policy change to create favourable conditions for the development of relevant (i.e.efficient) technologies and innovations that are fundamental for low carbon growth. This means the development of”climate-friendly” technologies that reduce emissions per unit of output beyond the reductions created by improvedefficiency in input alone.This paper considers the implications of sustainable intensification in agriculture and offers some challenges for therealisation of both mitigation and adaptation agendas. It focuses on both policy and market constraints that arecurrently hindering ”climate-friendly” technologies that reduce emissions per unit of output beyond that created byimproved efficiency in input. It argues that consumption side and (therefore behavioural change) measures are likelyto play an important role in sector emissions transformation; but that the consumption agenda is likely to be muchmore intractable then some more conspicuous production-side policy options that urgently need to be exploited.



Barriers and Opportunities influencing the Implementation of Climate Changes Adaptation and Miti-gation Measures in Agriculture

A. Iglesias

Technical University of Madrid, Avda. Complutense s/n, Ciudad U, Department of Agricultural Economics, 28220Madrid, Spain

[email protected]

In this paper, we present a methodology to understand what social, institutional and behavioural barriers could preventthe effective implementation of adaptation and mitigation methods, thus hindering if not precluding the much covetedsustainable future. Core behavioural theories on farm decision making in relation to climate change mitigation andadaptation will be developed by surveying farmers’ behaviours, attitudes and adoption intentions.To execute such an evaluation, we will define current practice; then in place of simply considering the financialimplications and barriers to implementing adaptation and mitigation measures, we propose to further examine possiblefuture farming behaviour. We will employ a behavioural economical analysis to examine distinct future actions ofthe farming community and consider, why, even in the case where it is fiscally advantageous to implement certainadaptation and mitigation measures, some farmers may choose not to. Be it for habits, morality or fear of the unknown,individuals do not necessarily act ”rationally” and we will aim to assess the full effect of this in the livestock sectorand how much of an impediment it will impose on ultimately reducing greenhouse gases.The results presented here summarise some barriers and opportunities - social, institutional and behavioural - forimplementing mitigation and adaptation practices. From previous examples, we conclude that the evaluation of adap-tation and mitigation practices does not have an ultimately unambiguous result and we propose that this evaluationneeds to be established as a public discourse that considers the three pillars of sustainability (environmental, socialand economic), their interaction and the process.



How to shorten Livestock Shadows? Practice and Opportunities of Policy Instruments in Latin America

A. Jenet

CATIE (Tropical Agriculture Research and Higher Education Center), Ganaderıa y Manejo del Medio Ambiente(GAMMA), 7170 Cartago, 30501 Turrialba, Costa Rica

[email protected]

The IPCC predicts that GHG emissions will increase by 90% between 2000 and 2030 if no additional climate changemitigation policies are implemented. As a result, under ”business as usual” scenarios, temperatures could increase by1.7◦C by 2050 and 4.0◦C by 2100. Thus, action from all sector stakeholders is urgently required to ensure that strategiesare implemented and to ”hold the increase in global temperature below 2◦C”. According to Gerber et al. (2013) theSouth American beef sector produces 31% of the global meat and emits about 1 Gt CO2e per year, thus contributing54% to emissions from global beef production and 15% to emissions from the global livestock sector. These emissionsmainly result from 3 sources: land-use change (40%); feed production, primarily from manure deposited on pasture(23%); and enteric fermentation (30%). The emission intensities of the specialized beef production supply chain areestimated at 100 kg CO2e/kg carcass weight, thus 47% higher than the global average. Furthermore, nitrous oxide,methane and carbon dioxide emissions are losses in the nutrient cycle of nitrogen, energy and organic matter thatundermine efficiency and productivity. Therefore, general policy interventions that aim at emission reduction shall,in the end, improve production efficiency at animal and herd levels. With feasible improvements such as fertilizationplanning, rotational grazing management, pasture quality and enhanced use of silvopastoralism, emissions could bereduced by 18 to 30% of baseline emissions, or 700 - 800 Mt CO2e in Latin America. Gerber et al. (2013) estimated30% reduction of GHG emissions would be possible, for example, if producers adopted low emission technologies andpractices which are used at the moment by the 10% of producers in the region.Various policies have been tested such as subsidies for renewable energy, promotion of energy efficiency and CO2emission trading schemes. Though most policies are targeting carbon dioxide in the transport sector as the largestemitter, carbon dioxide from agricultural land-use changes, energy use at farms and fertilizer production and methaneand nitrous oxide from agriculture represent some 25-30% of global GHG emissions (IPCC 2007), thus, a widerinclusion of non-CO2 gases in climate policies would have implications particularly for agriculture in Latin America,since that sector is responsible for about 60% of global non-CO2 emissions.Overall, policy makers have the choice between a number of approaches, such as regulatory instruments (e.g. performance-, environmental- and target standards), voluntary agreements (e.g. labelling schemes), information provision (e.g.R&D, campaigns, agricultural support services, advocacy) and market-based instruments in which either ’beneficiarypays’ (abatement subsidies, deposit-refund systems) or ’polluter pays’ (emissions tax, tradable permits, licenses andenvironmental labeling laws).A number of these instruments applied in Latin American context will be highlighted, their effectiveness on three levels(national, local, economic) reflected and their interrelation with National Strategies for Climate Change (NSCC), LowEmission Development Strategies (LEDS) and Nationally Appropriate Mitigation Actions (NAMA) discussed.In conclusion, the effectiveness of mitigation policies will depend very much on the appropriate socially acceptablepolicy mix, local bio-physical conditions and the barriers to proper implementation, which include investment andother adoption costs, human capacity constraints and economic risks.



Livestock Production: Vulnerability to Population Growth and Climate Change

O. Godber and R. Wall

University of Bristol, School of Biological Sciences, Woodland Road, BS8 1UG Bristol, [email protected]

Livestock production is an important contributor to sustainable food security for many nations, particularly in lowincome areas and marginal habitats that are unsuitable for crop production. Vulnerability analysis has been widelyused in global change science to predict impacts on food security and famine. It is a particularly useful tool forpredicting the sensitivity of coupled human- environment systems and can be used to inform policy decision-makingand direct the targeting of interventions.Using a range of indicators derived from FAOSTAT and World Bank statistics, the relative vulnerability of nationsare modelled at the global scale to predicted climate and population changes which are likely to impact on their useof grazing livestock for food. The model shows that sub- Saharan Africa, particularly in the Sahel region, and someAsian nations are the most vulnerable. Livestock-based food security is already compromised in many areas on thesecontinents and suffers constraints from current climate in addition to the lack of economic and technical supportallowing mitigation of predicted climate change impacts. Governance is shown to be a highly influential factor and,paradoxically, current self-sufficiency is shown to increase future potential vulnerability because trade networks arepoorly developed. The latter may be mitigated through freer trade of food products, which is also associated withimproved governance.The study suggests that policy decisions, support and interventions will need to be targeted at the most vulnerablenations but, given the strong influence of governance, effective implementation will require considerable care in themanagement of underlying structural reform.



Sustainable Food Production Chain for sustainable Ecosystems

M. Yossifov

Institute of Animal Science, St.’Pochivka’, 2232 Kostibrod, Bulgariam [email protected]

Alternative options to sustainably maintain livestock production systems are based on efficient management of agri-cultural resources. Eco-efficiency could be gained by managing nutrient cycles and energy flows, in a sustainableagro- ecosystem. Environmental conditions and vulnerability of the ecosystem affect its sustainability, and could beovercome through additive effects, e.g. of biodiversity (intra- and interspecific diversity of pasture plants, feed crops,animals), etc.Combination of multispecies pasture and grazing management might modify environmental stress and economic sus-tainability of the ecosystem. Simultaneously, reducing costs of nitrogen (N) fertilizer inputs will restrict total reactivenitrogen (N) emissions utilization from farms (soluble nitrate, NO3

−), volatile ammonia (NH3) and nitrous oxide(N2O), etc. losses to the environment. In this respect, options can be combined : i) Plant- available nitrogen (N)through biological nitrogen fixation in grazed grassland systems, ii) regionally applied options to reduce greenhousegases (GHGs) emissions from pasture and dried distillers’ grains with soluble (DDGS) feeding systems, and iii) benefitsof DDGS as a feed-back / feed- forward regulatory network: animal performance - manure content, would be a goalat pasture- and roughage- based dairy and feedlot production systems.Local animal food production chain and traditional food specialities could be used as a goal and impact assessmentmodel in eco-agro-socio-economic performance of rural regions. The emphasis has been placed on tradition extensivefamily farming and its redesign for highest eco-agro-socio-economic performance of rural regions. Farmer’s attentionis required on different methods to gain sustainable livestock systems by means of modest intensification solutions,increasing efficiency, precision feeding by alternative and non-traditional industrial by- products and local renewableresources, bio-diversifying feedstuffs (especially protein and energy), optimal management of manure and GHG-semissions.For animal production security and safety - cheaper, safer, healthier and more efficient agricultural products andfoodstuffs as traditional specialities could be promoted.



Greenhouse Gas Emissions from a Chinese Dairy Farm based on LCA

X. Wanga, D. Lianb and X. Wangb

aAarhus University, Dept. of Agroecology, Blichers Alle 20, Postboks 50, DK-8830 Tjele, 8830 Tjele, Denmark;bNorthwest A&F University, Taicheng road 3, 712100 Yangling, China

[email protected]

Greenhouse gases (GHGs) from Dairy sector cause approximately 4% of the global anthropogenic emissions, in whichmilk production, processing and transport contributes 67.5% to total GHGs emissions from global Dairy sector. Chinais the third highest milk yield country in the world. It is important to estimate GHG emissions from dairy farmingsystems accurately in China for choosing effective mitigation measures and leading dairy farming systems to low carbondevelopment.This study used life cycle principle to estimate GHGs emissions of a typical large-scale dairy farming system in China.The system boundary was from feed crop planting to farm gate. GHG emissions of the system were from nitrogen-fertilizer production, feed crop planting, feed process, enteric methane, manure storage and spreading in field, andenergy consumption in the dairy farm and from transport. GHG emissions were allocated to milk and meat accordingto financial contribution. The productivity data were from a large-scale dairy farm at the suburb in Xi’an city inChina.The results show that large emission sources were enteric fermentation, feed production and processing, waste storage,accounting for 48.86%, 18.97% and 16.39% of the total emissions respectively. The main greenhouse gases were CH4,N2O, accounting for 55.56% and 26.9% of the entire system. The emissions, per kg of raw milk corrected by proteinand fat (FPCM), were 1.52kgCO2-eq, which is lower than the average global emissions from mixed feeding systems,but higher than European countries’. Hence, there was big potential to mitigate emissions. Emissions from individualsources could be reduced by improving the feed, manure management, field management and other measures, but thecontribution to emission reduction of the entire system should be evaluated based on LCA. It is suggested to evaluatemitigation measures based on LCA to obtain more effective emission reduction measures for the system.



Farmer Understanding of environmental Risks from outwintered Cattle Systems

B. Andrewa, H. McCalmanb and S. Buckinghamb

aSRUC, West Mains Road, Edinburgh, Eh9 3JG Edinburgh, UK; bIBERS, Penglais, SY23 3FL Aberystwyth, [email protected]

Livestock production has significant impacts on the environment as a consequence of greenhouse gas production,nutrient and pathogen release to stream water and impacts on soil and plant communities. The way in which live-stock are managed within farming systems can have important implications for the magnitude of these impacts. Amanagement strategy that has grown in popularity recently in temperate regions of Europe, predominantly driven byincreasing economic pressures, is wintering cattle on grassland. This obviates the need for high capital investment inhousing, but may have consequences for the farming system in which it operates. This paper presents results relatedto farmers’ attitudes and perceptions with respect to outwintering of cattle, and ways in which environmental harmcan be mitigated.The main drivers behind outwintering are the reduction in capital and labour costs, alongside the belief that cattlehealth is maintained within the outwintered system. The main risk factor, deemed by these farmers, was the weather,followed by having to repair the ground after the outwintering practice. Four main risks could identified with thesefarmers, namely i) economic, related to loss of subsidy from a cross-compliance breach, ii) environmental, focusedon soil quality issues, iii) social, both related to animal welfare but public perceptions towards cows within a muddyfield, iv) production risks. In terms of frequency of these topics both economic and social risks were deemed the mostimportant.Outwintering on grasslands entwines farm system research with future government ambitions related to adaptationof the farming sector, as it reflect response to economic pressures from global farming and support systems. We findthat critical factors in managing these risks are choice of field and choice of system. These are, in turn, determinedby topographical and historical factors. Nevertheless, it provides a significant barrier to mitigating environmentalimpacts as farmers are constrained by the lack of choice of appropriate field. We argue that the farmer-led nature ofoutwintering and the development of a wide range of systems is evidence of outwintering being a system-innovation.We therefore conclude that there is a role for intervention through the provision of information related to clarify therelationships between outwintering activity and cross-compliance breaches.



Environmental Competences for Sustainability of small Ruminant Systems in Northern Spain

I. Batallaa, M. Pintob, P. Eguinoac, J.M. Intxaurrandietac, J.M. Mangadoc and O. Del Hierrob

aNEIKER-Tecnalia, Berreaga 1 P.812, 48160 Derio, Spain; bNEIKER-Tecnalia, Berreaga 1 P.812, Parcela 812.,48160 Derio, Spain; cINTIA, Avda. Serapio Huici, 22, 31610 Villava, Spain

[email protected]

Agriculture sector has become a major issue in climate change debates. Climate change mitigation has been oneof the main objectives in our society for the past years. In addition, it has become one the three challenges in theconstruction of last modifications to the Common Agriculture Policy in the UE. In this way, apart from climatechange, other environmental competences of agriculture have been pointed out, especially the role of this activity andits potentials towards sustainable development. The main objective of this study is to find and describe environmentalimpacts of sheep farms in ecosystems of the Basque Country and Navarra, focusing on the close relationship betweenagricultural activity and nature.The study has been made through a set of 42 indicators in 17 farms in Northern Spain. Energy, nutrient balance,waste analysis, GHG emissions, natural elements and diversity, land use and management, livestock census and land,have been the dimensions analyzed as key factors on environmental competences of farming systems. These indicatorshave been combined into a single index of environmental sustainability (numerical integration from 0 to 10) to everydimension, to present them together into a diagram (visual integration).First results of this study highlight strengths and weaknesses of the environmental impacts of these productions. Forexample higher carbon footprint per kg of milk produced in less intensive farms, but on the other hand, it shows positiverelations that appear between this kind of animal production, and its relation with rural and nature areas dependingon different intensification grades and management practices relative to landscape maintenance and conservation ofnatural elements and biodiversity with the more traditional farms. A wide vision on environmental impact of livestockproduction is needed to set-up and implement strategies on mitigation and adaptation to challenges of the primarysector on climate change issues. Social and economic aspects should be included in this kind of analysis to get aholistic vision of farms to progress towards sustainable development.



The Opportunities and Challenges in the Implementation of Beef Sector Policy in Indonesia

S. Gayatri and M. Vaarst

Aarhus University, Blichers Alle 20, Foulum, 8830 T, 8830 Viborg, [email protected]

Indonesia, like many other Asian countries, is predominantly a rural society. For this purpose, a variety of developmentprograms are being implemented in rural areas, and a sizable amount of government resources is being invested. TheBeef Self Sufficiency Program (BSSP) aimed at improving the socio-economics which tended to be initiated, designed,and implemented based on top-down approach by the government, without consultation and involvement of theintended beneficiaries.The study explores the difficulties and challenges in the implementation of the Beef Self Sufficiency Program inIndonesia based on farmers’ perception. The research used ethnographic methods to understand the actual needs ofdifferent actors in the field of beef production in Indonesia. Quantitative and qualitative analysis was used to processdata. To bridge the gap between national supply and demand of beef products, the Indonesian government resortsto imports of live cattle from Australia. The beef self-sufficiency program has been implemented since 2005. Theaim of the beef self-sufficiency program is to reduce imports of beef cattle to 10% of total demand by 2014, andto achieve long-term food security based on local cattle to meet the increasing population’s demand for beef. Sincethe Indonesian government further tightened beef import policy, prices have grown dramatically. This lack of policyconcern has created opportunities for corruption scandals. Several political leaders are suspected of having benefitedfrom local importers who wanted to increase their import quota, meanwhile traders, consumers, and farmers aresuffering and want prices to decrease.The study shows that the farmers were not aware of the existing policies like the beef self-sufficiency program eventhough the government stimulate local farming. Not enough local cows are on the market and local cow productionis not ready yet to supply national demand on beef product. There is a need for Livestock and Fishery Office toinvolve local government in the implementation of the beef self-sufficiency program and improve ways to disseminateknowledge and information about BSSP. The interviews also revealed that the implemented import policy is not agood solution until the country really is self- sufficient. Improving the breeding sector is mandatory for Indonesia tobecome self-sufficient on beef.



Legumes: Cost-Effective Greenhouse Gas Abatement in European Regions

V. Eorya, B. Dequiedtb, J. Mairea, C.F.E. Toppa, R.M. Reesa, P. Zanderc, M. Recklingc and N. Shlaefkec

aSRUC, West Mains Road, EH9 3JG Edinburgh, UK; bClimate Economics Chair, Palais Brongniart, 4th floor, 28place de la Bourse, 75002 Paris, France; cZALF, Eberswalder Straße 84, 15374 Muncheberg, Germany

[email protected]

Representing 10.1 % of EU-27 greenhouse gas (GHG) emissions, one of the main challenges of agriculture is to reduceits emissions while increasing crop and livestock production. The cultivation of leguminous crops in crop rotationsand grasslands can contribute to achieving these goals via their ability of biological nitrogen fixation (BNF). BNFdiminishes the need for synthetic nitrogen (N) for the leguminous crop and also provides additional N to the followingcrops or the other crops in the mixture. Despite of the environmental benefits, an increasing demand for plant-derivedprotein and a corresponding increase in global legume production, the European legume production has been decliningin the past decades.This paper assessed the GHG abatement cost via an increase in the share of rotations with legumes in five Euro-pean NUTS2 regions (Eastern Scotland, Vastsverige, Brandenburg, Sud-Muntenia and Calabria). The analysis usedmarginal abatement cost curves (MACC), which contrast marginal GHG abatement cost and the potential emissionabatement. 13 site classes were characterised in the five NUTS2 regions, and based on the agronomic practices possiblerotations were generated (in total of more than 129 000 rotations) with their annual average gross margin and soilN2O emissions calculated (IPCC 2006 Tier 1). Two agronomic scenarios were examined, assuming that the pre-cropeffect either causes an increase in the following crop’s yield with no change in the fertilisation practice, or a reductionin the N fertiliser use for the following crops with no change in their yield.Results show potential win-win solutions (i.e. changes to rotations which provide both financial and GHG benefits)in every region. The aggregated ”win-win” abatement potential for the five regions is 11-16% (0.5-0.7 Mt CO2e) ofthe baseline soil N2O emissions on the 4 M ha arable area. Cost-effective abatement (up to 45 /t CO2e) is 16-20%.The cost-effective abatement is linked with a 15% increase in production, 4.2-4.9 M t DM increase in fodder and grainlegume production combined and a 25% reduction in the cereal area.



Quantifying the Greenhouse Gas Mitigation Effect of intervening against bovine Trypanosomosis inEastern Africa

M. Macleoda, T. Robinsonb, W. Wintc and A. Shawd

aSRUC, West Mains Road, EH9 3JG Edinburgh, UK; bILRI, P.O. Box 30709, 00100 Nairobi, Kenya; cUniversity ofOxford, Department of Zoology, South Park Rd, OX1 3PS Oxford, UK; dAP Consultants, 22 Walworth Enterprise

Centre, SP10 5AP Andover, [email protected]

Endemic animal diseases such as tsetse-transmitted trypanosomosis are a constant drain on the financial resourcesof African livestock keepers and on the productivity of their livestock. A previous study mapped the benefits ofremoving trypanosomosis from cattle in Eastern Africa (Shaw et al. in press). The present study builds on this workby quantifying the effects of disease removal on the greenhouse gas emissions arising from the cattle systems.The emissions are quantified for each cattle system using an excel version of GLEAM, FAO’s Global Livestock En-vironmental Assessment Model. The results indicate that for 11 of the 12 systems, (meat and milk) protein outputincreases by more than the GHG emissions when the disease is removed, leading to a reduction in the emissionsintensity per unit of protein produced of between 2% and 8%.One of the main challenges in this study has been reconciling two different models: the model used to undertake theoriginal analysis of the disease impacts(the MTB model) and GLEAM. These models have fundamental differences:MTB is an dynamic economic model that quantifies herd growth over 20 years while GLEAM is essentially static, andquantifies the output and GHG emissions at a point in time. They are also differences in terms of ways in which theherds are divided into separate cohorts and in terms of and meaning of key parameters.This paper will outline the process by which the models were harmonised, and draw some broader lessons about theways in which the effects of disease treatment on emissions can be predicted.



Sustainable Intensification of Crop Production in agro- sylvo-pastoral Territories through the Expan-sion of Cattle Herds in Western Africa

A. Vigana, J. Vayssieresb,c, D. Massed, R. Manlaye, M. Sissokhof and P. Lecomteg,h

aCIRAD - UMR Selmet, Campus International Baillarguet, 34398 Montpellier, France; bCIRAD, 37 av. Jean XXIII,Dakar Etoile, BP 6189 Dakar, Senegal; cCIRAD - Umr Selmet, Campus ISRA/IRD de Bel Air, Route des

hydrocarbures BP 1386, 18524 Dakar, Senegal; dIRD - UMR Eco&Sols, Campus ISRA/IRD de Bel Air, Route desHydrocarbures, BP 1386, 18524 Dakar, Senegal; eAgroParisTech - GEEFT, 648 rue J-F Breton BP 7355, 34086

Montpellier Cedex 4, France; fISRA, CRZ Kolda, BP 53 Kolda, Senegal; gCIRAD - UMR Selmet, CampusInternational Baillarguet, 34398 Montpellier Cedex 5, France; hINRA SupAgro, Cirad Campus international, 34700

Montpellier, [email protected]

In agro-sylvo-pastoral villages of West Africa, biomass management ensures the sustainability of mixed-farming systemsespecially in maintaining soil fertility. Traditionally, agriculture and livestock activities are strongly linked. Cattleherds’ mobility leads to a positive nutrient and carbon transfer from rangelands to individual cultivated fields. Insome regions, demographic growth and subsequent decline in rangelands lead to herd depletion, a phenomenon thatdisturbs the traditional system and threatens food security.The village of Sare Yero Bana is located in sub-humid area, region of High Casamance in Senegal. The aim of thisstudy was to assess the sustainability at village level by comparing the changes in farm functioning and the nitrogenbalance between the years 1997 and 2012. In 1997, it was based on measurements of all biomass flows (including theweight and nitrogen content analysis) and in 2012, it was updated on the basis of an exhaustive farm survey.Total increase in cultivated areas (+35%) from 1997 to 2012 did not significantly affect rangeland available for herds,with more than 200ha still available for 485 tropical livestock units. Total animals increased by +17% over the sameperiod. In both years, crop fields’ nitrogen inputs were mainly ensured by manure. Fertility transfers from rangelandsto cultivated fields increased; this partially explains a +36% crop production growth. In a context of a relativelystable village population and the development of staple crop market, nitrogen exports via harvest showed an increaseof +20% (groundnut principally). These remained globally balanced by important nitrogen inputs correspondingto an increase of fertility transfers by the herds (+9.6 kgN.ha−1.yr−1), and to the recent use of mineral fertilizers(+6.4 kgN.ha−1.yr−1). The village nitrogen balance remains stable and close to equilibrium (respectively -4 and -2kgN.ha−1.yr−1 in 1997 and in 2012).This study stresses the important role that cattle herds can play towards food security in regions of Western Africawhere rangelands still remain. Moreover, in Sub-Saharan Africa, livestock contributes significantly to climate changevia greenhouse gas emissions. Thus, the study also underlines the importance of taking into account the indirectpositive effects of livestock on other agricultural productions in greenhouse gas balances, such as the input of organicfertilizer.



Implementation of Mitigation and Adaptation Measures in the Farm-scale Model FarmAC

N.J. Hutchings, M. Jørgensen and J. Vejlin

Aarhus University, Department of Agroecology, Blichers Alle, DK-8830 Tjele, [email protected]

The farm-scale model FarmAC was developed in the AnimalChange project to simulate the greenhouse gas emissionsfrom livestock farms in a range of locations across the world, and to assess the effectiveness of a range of mitigationand adaptation measures. The model represents a compromise between the conflicting needs for the model to operatein data-poor environments while incorporating sufficient mechanisms to describe the response to the implementationof management measures and technologies. The model simulates the flows and transformations of carbon and nitrogenthrough livestock, animal housing, manure storage, crops and soils. Emissions and other losses are simulated usingstatic modelling. However, the changes in soil carbon and nitrogen storage are simulated dynamically. This combina-tion of static and dynamic modelling creates both scientific and technical challenges; the static modelling uses the yearas a basis for calculation whereas the soil model simulates for a minimum period of 10 years. The solution adopted isto simulate both crops and soils dynamically and to then average the crop production over the years simulated. Thelivestock then have access to this average supply of feed.Mitigation measures currently incorporated include management measures; modifying feed rations (addition of fat ornitrate), changing crop rotations, cessation of crop residue burning and adjusting nitrogen fertilisation with mineralfertiliser or manure, and technical measures; covering manure storage, acidification of slurry in housing, manure storageor at time of application and anaerobic digestion of slurry. Adaptation measures include changes to feed rations andcrop rotations, and the use of irrigation.This study will illustrate the flow of information through FarmAC, the mitigation and adaptation measures available,the point within the farming system where the measures operate and the direct and indirect consequences to beexpected from their use.



Global Assessment of marginal Costs for the Abatement of Ruminant GHG Emissions

B. Henderson, A. Falcucci, A. Mottet and P. Gerber

FAO, Viale delle Terme di Caracalla, 00153 Rome, [email protected]

In this study the marginal costs and potentials of a selection of GHG abatement practices are assessed for the ruminantsector, globally. This study marks an advance on previous global and regional assessments by using spatial data toaccount for the distribution of costs and benefits, among groups of producers, of adopting abatement practices. Thesedistributions provide far greater insight about the likely rates of abatement at different carbon prices than the averageabatement costs/benefits that are more commonly reported in the literature.Among the various practices available for lowering ruminant emissions, the most promising were selected for thisassessment, based on agreement among experts and the literature about their effectiveness and feasibility in differentproduction systems and regions. Improved grazing management and legume planting are the main practices assessedin grazing systems, and the alkaline treatment of crop straws is the main practice applied in mixed crop-livestocksystems in developing countries, while the feeding of dietary lipids and nitrates are assessed in confined productionsystems. Economic data, Century and Daycent model outputs are used within the framework of the Global LivestockEnvironmental Assessment Model (GLEAM) to estimate the costs and benefits of abatement.Overall, a sizeable share the technical abatement potential within the sector can be achieved at relatively low costor at carbon price levels commonly observed in carbon markets. Abatement practices that raise productivity suchas improved grazing management, legume planting and straw treatment, are estimated to be profitable for someproducers. Whereas practices with little or no productivity benefits such as dietary oils and nitrate feeding, aregenerally much more costly.



Sustainable Livelihoods in Range Management: adaptive Livelihood Strategies for Food Security

H. Khedri Gharibvand, H. Azadi and F. Witlox

Ghent University, Krijgslaan 281, S8, Belgium, 9000 Ghent, [email protected]

Prior to the 1950s, traditional systems of range management (RM) and adaptive livelihood strategies were sustainablein most countries. At that period, due to low human population, there existed a dynamic equilibrium between human,rangelands and livestock. Climate change was not an issue, livelihoods were sustainable and rangeland degradation dueto gazing pressure caused by humans in response to world’s population growth did not exist. However, socioeconomic,ecological, and climate changes accompanied by changes in traditional systems and development interventions haveconsiderably disrupted these well-adapted strategies.Nowadays, lack of attention to well-developed strategies in RM policies, has resulted in more pressure on pastoralismas a way of living that makes it vulnerable. Moreover, RM as a source of employment is no longer able to meetbasic requirements of pastoralists and it has led to a significant reduction in the value of rangelands. The mostcritical consequences of devaluation of pastoralism and rangelands have affected pastoralists’ livelihoods through foodinsecurity which has recently been the major challenge of range managers and pastoralists around the world. Achievingfood security in the face of the world’s fast growing population has been recognized as one of the intended outcomesof sustainable livelihoods’ (SLs) approach and one of the main targets of the Millennium Development Goals (MDGs).Regarding the importance of food security; increasing livestock productivity, preventing rangeland degradation andcreating equilibrium between rangeland and livestock remains crucial.Furthermore, women’s role as change agents in world’s rangelands and food security has been recognized in thesymposium of the 66 Annual Meeting of the Society for Range Management in 2013. Therefore, the recognition ofthe need to improve food security with emphasis on women’s empowerment and their role in rangeland and livestockproductivity has been acknowledged.This paper first addresses women’s role in the RM and food security. Given that RM is not just livestock grazing forkeeping, consuming, and selling, afterwards, it discusses a set of livelihood strategies including livestock-based liveli-hoods, resource-based livelihoods and supportive strategies that are crucial for creating SLs in RM. Accordingly, thisstudy argues that in the interest of well-developed strategies, ”livelihoods diversification and alternative livelihoods”must be markedly considered. This will reduce population pressure on rangelands, thereby ensuring an increase inincome per person for people who remain in the rangeland-based livestock sector. Consequently, sustainable range-land management that is the balance between rangeland and livestock will properly be achieved and will effectivelycontribute to food security.



The Importance of economical Analysis to Studies that foresee the Measurement of Greenhouse GasesEffects in Cattle-Raising in the Pampa Biome in Brazil

J.L.S.D. Santos and M.A.K. Lucas

EMBRAPA, BR 153 KM 603 Caixa Postal 242, 96401-970 Bage, [email protected]

Cattle-raising is an important economic activity for agribusiness in the southernmost state in Brazil, Rio Grande doSul, which owns a total of 12 million animals (6,4% of the national herd in 2012). Most of this herd is on farmsin the Southern part of the state, in which the Pampa biome, one of the Brazilian biomes, is located. This activitythere is closely related to the historical process of settlement in this southern part of the country, going back to thecenturies 17th and 18th, involving disputes between Portugal and Spain, which culminated in the definition of theborders between Brazil, Uruguay and Argentina only in the 20th century. As a traditional activity, cattle-raising isrun based on many arrangements in terms of styles of management and the combination of the factors used by theagents (land, labor, technologies and knowledge, among others), resulting in a big difference in terms of economicalresults obtained end of impacts on the ecosystems.Because of this situation, and in order to analyse the economic aspects of gases in cattle-raising in the Pampa biome,under the Rede PECUS project coordinated by the Brazilian Agricultural Research Corporation (Embrapa) and incharge of producing knowledge about emission of gases in the biomes, the researchers from the Economics group ofthis Rede, organised on the 26th of December 2012 a panel with cattle raisers, technicians and researchers at EmbrapaSouthern Animal Husbandry, in the city of Bage, to characterize a typical rural business to represent a mainstreamproduction unit. Then, a consensus has been reached, indicating as a model a farm of complete cattle-raising cycle,having an area of 1.200 ha, being 960 ha reserved for exploration (from these, 96 ha with agriculture, in the winterand summer), and a herd of 1.368 animals, being only 8% artificial pastures, with 0,7 AU/ha/year, and the naturalpastures having low support capacity.Besides, there is the fact that the reproductive and sanitary management are deficient, which contributes to a lowreproductive efficiency. Knowledge of this kind of management and the aspects concerned in the decision making seemessential for an economic analysis that supports the measurements from the cattle-raising activity which are beingdone in the same biome by Rede PECUS. With this goal, economic analyses have been integrated to Rede PECUS.



New Policies for Adaptation to Climate Change of Livestock on Grasslands in Uruguay

D. Sancho and W. Oyhantcabal

Ministry of Agriculture, Livest, Constituyente 1476, 11200 Montevideo, [email protected]

In 2010 the Ministry of Agriculture of Uruguay defined adaptation to climate change as a strategic priority thatmust be addressed with a transversal approach within the Department of State and to the extended agriculturalinstitutions. The task of identifying, evaluating and proposing policies related to adaptation to climate variability isa responsibility of the Agricultural Climate Change Unit of the Office of Agricultural Planning and Policy (OPYPA)the MGAP. The MGAP has managed two ambitious projects related to climate adaptation: the project ”Developmentand Adaptation to Climate Change” (DACC) with a loan from the World Bank and the project ”Family Livestockand Climate Change” (supported by the Adaptation Fund Kyoto Protocol).Planned adaptation to climate change is a relatively new subject in Uruguay and its better development needs to beassisted by science. Adaptation requirements unavoidably raise a key question: how to build resilience?Uruguay presents a great opportunity to promote processes of ecological intensification of livestock on natural pastureswith environmental co-benefits.Both the experimental data and the results of projects in landscapes show that applying process technologies, with low-cost and high- productive impact, enables a more sustainable management of natural resources, increasing productivity,efficiency, improving the income of families and promoting the conservation of grassland’s ecosystem services.These technologies focus on two groups. The first relates to improving the spatiotemporal management of pastureforage supply, basically taking it to values consistent with the requirements of animals. Another large group iscomposed by herd management technologies such as differential category management and control techniques ofsuckling. There is an opportunity to increase productivity and also to give back the value to the country’s grasslands,avoid undesired land use changes, increase carbon sequestration and reduce GHG emissions per unit of output.Recent studies of a MGAP project with FAO1 reinforce the possibility of improving farmer’s income while improvingadaptation to climate change. In this way Uruguay has a great opportunity to reconcile rural development withwin-win options between economic growth and conservation ecosystems services.1http://www.fao.org/climatechange/80141/es/



Comparing the Cost Effectiveness of GHG Mitigation Options on different Scottish Dairy Farm Groups

S. Shrestha, V. Eory and M. Macleod

SRUC, West Mains Road, EH9 3JG Edinburgh, [email protected]

Greenhouse gas (GHG) mitigation is one of the main challenges facing agriculture, exacerbated by the increasingdemand for food, in particular for livestock products. Production expansion needs to be accompanied by reductions inthe GHG emission intensity of agricultural products, if significant increases in emissions are to be avoided. However,any uptakes of mitigation options by the farmers depend on the cost-effectiveness of adopting such options. A highlyeffective mitigation option might not be practical for a farmer if the costs associated with that option are high. Inaddition to that, farms might find different options suitable for them based on the farm characteristics. A list ofmitigation option implemented on different farm types with their cost effectiveness on farms would therefore be veryuseful for farmers as well as for policy makers to make a decision.This paper aims to explore the use of three GHG mitigation options on different dairy farm groups in Scotland anddetermine the cost effectiveness of each of the options in those farm groups. The mitigation options considered forthis paper are; i) use of sexed semen to increase female calf number, ii) installing and using anaerobic digester to treatanimal waste and iii) increasing the share of concentrate diet in animal feed.Farm level data from the Scottish Farm Accountancy dataset (FAS) was used in this paper. A cluster analysiswas carried out on the farm level data for FAS dairy farms to identified different dairy farm groups with similarcharacteristics. The potential reduction of GHG emission per farm, including emissions arising from inputs usedon the farm, under each of the option was then calculated using the GLEAM life cycle assessment model and fromliterature data. An optimising farm level model, ScotFarm, was used on each of the farm groups to determine theoptimum farm net margins under a baseline situation (with no options implemented) and three mitigation scenarios.The cost-effectiveness of all three mitigation options were then determined based on reduction in GHG emission perfarm and change in farm net margins under those options.Initial results for the sexed semen scenario suggest that this option can be cost effective for both large dairy farms (-£6.26/tCO2e) and medium dairy farms (- £12.56/tCO2e), if the avoided emissions from the additional beef productionare considered.



Conserving indigenous Livestock Breeds for Adaptation to Climate Change and Food Security of thesmall Holders in the Hindu Kush Mountains of Northern Pakistan

I.U. Rahima, H. Rueffb,c and D. Masellid

aFoundation for Research and Socio-Ecological Harmony, House 41, Street 32, Sector D-17/2, Margalla ViewHousing Society, 44000 Islamabad, Pakistan; bUniversity of Oxford, School of Geography and the Environment,

South Parks Road, OX1 3QY Oxford, UK; cUniversity of Bern, Centre for Development and Environment,Hallerstrasse 10, 3012 Bern, Switzerland; dSwiss Agency for Development and Cooperation SDC, Global Prog.

Climate Change, Corporate Domain Global Cooperation, Federal Department of Foreign Affairs FDFA,Freiburgstrasse 130, 3003 Bem, Switzerland

[email protected]

The Hindu Kush Mountain in northwestern Pakistan are likely to suffer stronger warming than the global average withcorresponding increase in frequency of extreme climate events. This will pose a high risk to the food security of theresident small holder communities. The extreme climate events may include frequent flood disasters, frequent longerdroughts, increasing crop uncertainty and increasing drought stress on the rangeland vegetation. This will increasethe dependency of resident small holders on extensive livestock production for food security.The resident small holder communities are keeping a variety of indigenous livestock breeds, which have evolved tobetter tolerate the climate extremes of these mountain valleys. These breeds are adapted to the scarce forages andpoor quality roughages available on the rugged mountainous terrain. These are more resistant to prevailing livestockdiseases and are well-suited to cater the multiple needs of the smallholder communities. The small body size of thesebreeds keeps the maintenance requirement low and insures easy movement along the rugged terrain. At the sametime these breeds have high reproductive rates and a high milk production to body weight ratio compared to highlyproductive breeds adapted to the plain territories in the South of the country. In comparison, the exotic and crossbredheavy milk cattle breeds, being promoted by local authorities, require quality rations, are more vulnerable to locallyprevailing diseases and weather extremes, and can hardly adapt to rugged mountain terrain grazing.The three documented indigenous livestock breeds include Achai cattle, which weigh 40% less than the Sahiwal andRed-Sindhi dairy breeds of the plain territory, but only produce 25% less milk and a significantly higher number ofoffspring in comparison. Leg constitution of Achai cattle enables it to travel long distances during seasonal tran-shumance, thus ensuring efficient use of scarce and patchy grazing resources at uplands and lowlands. The browncoat colour of Azikheli buffalo enables it to extend its grazing habitat to mountain slopes and reduce its dependenceon swamps. Achai cattle and Azikheli buffalo have significantly higher first service conception rate (71% and 64%respectively) than the other cattle and buffalo breeds of Pakistan. The fine wool Kari sheep breed weighs only 15-20kg and ensures efficient use of scarce forages. The breed has shorter gestation period of 3 months and hence can lambthrice a year.These low-input low-output breeds can thus help smallholders cope in a better way with the consequences of extremeclimate events and ensure their food security. However, indiscriminate breeding practices of the custodian communities,cross-breeding promotion through the formal breed improvement services, and inbreeding due to continuous use ofmales for breeding in the same herd are the constant threats to the dilution of the adaptive traits of the indigenousbreeds. This warrants conservation measures to check further dilution and imbalance of the adaptive traits.


Tues. 15:45 Medici I Parallel session 4a: Policy and economics

Bioeconomic Assessment of Climate Change Impacts on Agrifood Markets: a global Approach with aFocus on the EU

M. Blancoa, F. Ramosb, B. Van Doorslaerc, D. Fumagallib and F.J. Fernandezd

aTechnical University of Madrid, ETSI Agronomos, Avda. Complutense 3, 28040 Madrid, Spain; bEU Joint ResearchCentre, JRC-IES, 21027 Ispra, Italy; cEU Joint Research Centre, JRC-IPTS, 41092 Sevilla, Spain; dTechnical

University of Madrid, ETSI Agronomos, 28040 Madrid, [email protected]

Medium and long-term projections for world food production and prices play a crucial role in evaluating and tacklingfuture food security challenges. Understanding how these projections will be affected by climate change is the mainobjective of this study. We assess the economic impacts of climate change on agrifood markets by 2030, providingboth a global analysis and a regionalised evaluation within the EU. A bioeconomic approach is used to jointly assessbiophysical and socio-economic effects.Future crop yield developments are subject to considerable uncertainty, particularly with regards to climate projectionsand the degree of carbon fertilization. To account for such uncertainties, we analyse the IPCC emission scenario A1bunder several simulation scenarios that differ in (1) the climate projection, Hadley realization (warm) or Echamrealization (mild); and (2) the influence of carbon fertilization.For each simulation scenario, WOFOST simulations performed at 25km grid resolution provide changes in bothpotential and water-limited yields for nine of the most widely grown crops in the EU, showing that yield effects varywidely across regions and crops. The magnitude of the carbon fertilization effect strongly influences the direction ofeffects and, in most cases, yield effects are more positive in the Echam realization compared to the Hadley. Furthermore,results suggest less positive (or more negative) yield effects across EU regions compared to the world average, in linewith findings from other studies.Economic simulations with the global CAPRI model highlight that positive yield effects will be counterbalanced bycrop price decreases and vice versa, emphasizing the need of using price endogenous models to assess productionimpacts of climate change. Under full carbon fertilization, yield effects are positive at the global level, leading to amoderate increase in production compared to the baseline. Without CO2 effects, in contrast, global production isexpected to decrease.Increase (decrease) in productivity will drive prices down (up). Under carbon fertilization, global production increasesin the range of 0.5-4.5% result in global price decreases in the range of 1-20%. Stronger production increases in theEcham realization (compared to the Hadley) result in higher price decreases. Simulation results indicate that agrifoodmarket projections to 2030 are very sensitive to climate change uncertainties. Uneven biophysical effects of climatechange across world regions lead to interregional adjustments in production, consumption and bilateral trade flows.Particularly for internationally traded products, regional self-sufficiency rates - an indicator of import dependency -will be affected.



Preparing Australian Dairy Businesses for extreme and more variable Climates - a Research Projectintegrating economic, biophysical and social Aspects

G. Haymana, M. Harrisonb, B. Cullenc, M. Ayrec, D. Armstrongd, W. Masona, R. Rawnsleyb, R. Nettlec, R. Beilinc,S. Wallerc and C. Phelpsa

aDairy Australia, Level 5, IBM Centre, 60 City Rd, 3006 Melbourne, Australia; bTasmanian Institute of Agriculture,Post Office Box 3523, 7320 Burnie, Australia; cUniversity of Melbourne, Melbourne School Land & Environ, 3010

Melbourne, Australia; dD-ARM Consulting, 260 Old Telegraph Rd, 3818 Jindivick, [email protected]

The Australian dairy industry has put significant effort into exploring the potential impacts of climate change, howeverfour key limitations remain:1. Climate change is only one of many drivers that influence the dairy business, other economic and social driversmust also be considered in any system analysis.2. Current (rather than future) farming systems have been etested’ using predicted future climates.3. Average predicted changes in temperature and rainfall is the focus of most research. The challenge to farmingbusinesses is the impact of extremes, increased variability, the sequencing of climate events and the emergence oftipping points and/or unexpected vulnerabilities.4. Strategies to reduce emissions and adapt to climate change have not been cross matched to understand the trade-offsand impacts on other business risks within the whole farm system.To inform future investment it is critical that the Australian dairy industry fully explores the impacts of climateextremes and a more variable climate. Using three dairy businesses in differing regions, a range of farm developmentoptions will be explored - some options will push the boundaries of current farming practice, but all will retain economicand social reality. Biophysical and economic modelling, social research and farmer engagement will assist to identifyfarm management responses that make economic sense and build human and biophysical capability to manage a morechallenging future.The project examines:1. Trade-offs between profitability, risk, social impacts, and greenhouse gas emissions associated with realistic farmdevelopment options across farming systems.2. Potential impacts of climate variability and extreme events on economic, biophysical and social aspects of farmdevelopment options.3. Management options that provide the most effective adaptation and mitigation outcomes.4. Skills and industry support systems required to build capacity to respond, considering the reduced decision makingcapacity that accompanies increased uncertainty.Preliminary research demonstrates that increased periods of drought as well as more intense rainfall events will reducemedian pasture production by up to 31% in Southern Australia, whereas more frequent exposure to heat waves willreduce pasture and milk production by as much as 28% and 20%, respectively. The combined effect of extended periodsof drought, more intense rainfall events, longer heat waves and increased frequencies of hot days will reduce pastureproduction by up to 36%. Future work will examine how these impacts influence the temporal sequence of annualfarm revenue and possible social consequences of risk perception and farm adaptation to extreme climatic events.



Climate Change systemic Adaptation and financial Value across the southern Australian LivestockIndustry

A. Ghahramani, A. Moore, S. Crimp and M. Howden

CSIRO, Black Mountain Laboratories, Black Mountain, ACT, Clunies Ross Street, 2601 Canberra, [email protected]

The GRAZPLAN biophysical models were used to simulate the dynamics of coupled climate-soil-grassland-livestocksystems at 25 representative farms across Australia’s extensive grazing region under historical and a range of projectedclimates (4 GCMs at 2030, 2050 and 2070 under SRES A2 scenario). The modelling analysis suggests that primaryproduction of grasslands and livestock are likely to decrease across most of southern Australia’s grazing lands underfuture climate. By including changes in on-farm management in our models we were able to evaluate the effectivenessof certain adaptation options.Options considered individually were not always effective but a combination of Incremental grassland management andanimal genetic improvement options (currently available to graziers) was able to offset productivity declines at cross-regional scale. Through implementation of the optimal combination of adaptation options, profitability across southernAustralia was shown to increase by +69%, +84% and +116% in 2030, 2050, and 2070, compared to no adaptation.Optimal systemic adaptation could make addition of $A 2.00 billion in 2030, $A 2.10 billion in 2050, and $A 2.12billion in 2070 to industry with current farm management. In comparison with historical production, adaptationvalue to industry would be $A 1.51 billion in 2030, $A 1.51 billion in 2050, and $A 1.12 billion in 2070 (all for a fulladaption). If the most-profitable combination of adaptations is used at the baseline instead of the current-practice,then the optimal combinations of grassland adaptations would provide a further increase in operating profitability at28%, 28%, and 16% of sites in 2030, 2050, and 2070. If the livestock genetic adaptations -cannot be adopted at thepresent for lack of seed stock - are also included, the optimal systemic adaptations would be more profitable than thealternative baseline including grassland management options at 60%, 56%, and 48% of the locations in 2030, 2050,and 2070.We discuss 3 conceptual issues which arose during our study: (i) how to estimate impact when current management isenvironmentally infeasible under future climates; (ii) estimating the effectiveness of combinations of adaptations, onlysome of which are currently available to graziers; and (iii) dealing with the tension between modelling best-practicesystems, so that present and future can be compared, versus modelling typical practice for economic valuation.



Potential Effects of Climate Change on the European Grassland Production : Impact Assessment offar Future

P. Aghajanzadeh-Darzia, S. Lapercheb, R. Martinb and P.-A. Jayeta

aINRA-Economie publique, Avenue Lucien Bretignieres, 78850 Thiverval Grignon, 78850 Thiverval Grignon, France;bINRA - UR0874, Grassland Ecosystem Research, 5 chemin de Beaulieu, 63039 Clermont-Ferrand, Cedex 2, France

[email protected]

Forage systems and more widely grasslands are highly complex and missing basic information on market prices andproductivity which is subject to large variability; it will thus be more difficult to estimate their economic value. Thiswork is intended to estimate the economic value of grass production and to assess the impact of climatic variationson the European grassland-livestock production systems, taking into account the various environmental and climaticfactors.This work is based on a real innovation in terms of calculation which aims at estimating grass production in quantityand in monetary value although it is mostly used on-farm as animal feed and hence no market prices are availableto reflect its economic value. To do so, the grassland bio-geochemical model PaSim has been used to simulate grassyield responses to nitrogen input and then has been coupled with the economic farm type supply model AROPAj,with aims at estimating the monetary value for grass. This methodology allowed us to better predict and identify theeffects of climatic variability on grassland and farm systems as well. This approach has been used at the Europeanscale (EU-15) and for two extreme SRES-IPCC-AR4 climate scenarios (A2 and B1) of far future time slice (2071 to2100).Results show a significant increase in grassland cover over time, when taking grass simulated production functionsinto account. Accordingly, due to decreases in feed expenses, farmers have the possibility to increase their livestocknumbers, which affects negatively the overall greenhouse gas emissions for all climate change scenarios considered.


Tues. 15:45 Medici II&III Parallel session 4b: Social and behavioral changes

Intensification of Grassland and Forage Use; Driving Forces and Constraints

O. Oenemaa, P. Kuikmana, C. Dekleinb and M. Alfaroc

aAlterra Wageningen UR, P.O. Box 47, Droevendaalssteeg 4, 6700 AA Wageningen, Netherlands; bAgResearchInvermay, Private Bag 50034, 9053 Mosgiel, New Zealand; cInstitute for Agricultural Research, Casilla 24-O, 24-O

Osorno, [email protected]

The increasing demand for safe and nutritional dairy and beef products in a globalizing world, together with theneed to increase resource use efficiency and to protect biodiversity, provide strong incentives for intensification ofgrassland and forage use. This paper addresses the question ”Does intensification of grassland and forage use lead toefficient, profitable and sustainable ecosystems?” Firstly, we present some notions about ’intensification of agriculturalproduction’. Secondly, we discuss the intensification of grassland-based dairy production in The Netherlands (NL),Chile and New Zealand (NZ). Finally, we arrive at some conclusions.External driving forces and ’the law of the optimum’ provide strong incentives for intensification, i.e. for increasingthe output per unit surface area and labour. The three country cases illustrate that intensification of grasslanduse is a global phenomenon, with winners and losers. Winners are farmers who are able to achieve a high returnon investments. Losers are small farmers, who drop-out of business, unless they broaden their income-base. Therelationship between intensification and environmental impact is complex. Within certain ranges, intensification leadsto increased emissions of nutrients and greenhouse gases to air and water per unit surface area, but to decreasedemissions when expressed per unit of produce. The sustainability of a grassland-based ecosystem is ultimately definedby the societal appreciation of that system and by biophysical and socio-economic constraints.In conclusion: intensification may lead to more efficient and profitable, and thereby more sustainable grassland ecosys-tems. This holds especially for those current systems that are not sustainable because they are extensively managed,under-utilized, low-productive, over-exploited and/or unregulated, and as long as the adapted and future systems domeet societal and ecological constraints.



Reduction of GHG Emissions by regional specific reduced Livestock Production resulting from dietaryChanges in the EU

J.P. Lesschena, P. Kuikmana, N. Sikiricaa, H. Westhoekb and O. Oenemaa

aAlterra Wageningen UR, P.O. Box 47, Droevendaalssteeg 4, 6700 AA Wageningen, Netherlands; bPBL, P.O. Box 1,3720BA Bilthoven, Netherlands

The contribution of livestock production in the European Union (EU) to GHG emissions is well established. Varioustechnical options are available to reduce GHG from livestock production and clearly these options have their limits.An alternative pathway to reduce GHG emissions and other environmental effects is through dietary changes andsubsequent changes in production levels. Current EU diets are relatively rich in animal protein compared to WHOrecommendations and GHG emissions might be significantly reduced when animal protein is replaced by plant-basedalternatives.We present an integrated approach for the EU27 in which we assessed GHG emissions for alternative diets, in whichthe consumption of meat, dairy and eggs is lowered by 50% and replaced by plant based food. Two contrasting landuse change scenarios were examined; i) a high-prices scenario with maximum cereal production, and ii) a greeningscenario with extensification of grassland use and production of perennial bio-energy crops on excess arable land.Our first conclusion is that a 50% reduction in the livestock component of EU diets, with corresponding changesin agriculture, will lead to substantial GHG reductions, of which the impact is generally larger than the estimatedmitigation potentials from technical mitigation measures. In this analysis, we have assumed that the reduction inconsumption of livestock products is followed by a parallel reduction of livestock production in the EU.However, it is unlikely that such a parallel reduction in livestock production relative to the current production levelswill take place accross EU. It is more likely that specific EU regions that are most vulnerable to climate change will seetheir production levels affected more or differently than less vulnerable regions. And also that reduction of livestockproduction would preferably take place in those regions where production efficiencies in terms of GHG emissions arerelatively low. Such changes will likely be driven by economics of livestock production. On the basis of a set of simpleassumptions we present GHG emissions for these 2 scenarios where differentiated responses across EU are accountedfor.The second approach might result in more effective mitigation of GHG emissions in the EU as a whole and will makerelatively more land available for other agricultural production or land use and increase the production efficiencyacross EU. This analysis allows for the design of differentiated and effective policy support to achieve targets on bothmitigation and adaptive livestock production.Acknowledgement: AnimalChange (FP7-266018) and Ministry Economic Affairs NL, KB12



What drives Pastoralists’ Vulnerability to global environmental Change? A qualitative Meta-Analysis

F. Lopez-I-Gelatsa and M.G. Rivera-Ferreb

aCenter Agro-food Economy Develop, Parc Mediterrani de la Tecnologia, C/ Esteve Terrades, 8, 08860 Castelldefels(barcelona), Spain; bUniv of Vic - Univ. Central Cataluna, C/la Laura, 13, 08500 Vic (barcelona), Spain

[email protected]

Pastoralism is a natural resource management system widespread all over the world, essentially in drylands, mountainsand cold regions. In its multiple forms it is practiced on 25% of the global land. Pastoralism is an important activity infeeding a growing world population, through its capacity to make use of marginal lands; but it also provides multipleadditional goods and services, such as animal draft power, household fuel, manure, social status or cultural identity.However, due to multiple reasons, such as large dependence on environmental conditions, political neglect and risingcompetition with other economic activities, there is wide consensus on acknowledging that the vulnerability of pastoralcommunities to climate change is increasing.To better characterise this vulnerability, we compiled and analysed the existing scientific knowledge about the trans-formations pastoralism is undergoing worldwide, taking into consideration hazards (both climate- and non-climate-related), their impacts, and how pastoral communities are adapting to these transformations. We conducted a com-bination of systematic review and qualitative meta-analysis. In so doing, we examined patterns and trends across theliterature, which are not apparent in results of individual studies. Either called conceptual meta-analysis, qualitativecomparative analysis, research synthesis or qualitative meta-analysis, this is a methodology which is being increasinglyused to study different aspects of the global environmental change, such as tropical deforestation, adaptation to climatechange, food insecurity, and desertification.The methodology revealed itself as particularly appropriate to expose the underlying complexity of the pastoralvulnerability and to identify some areas with missing research. A total of 170 case studies were initially selectedthrough reading of the abstract. This selection was further reduced to 75 case studies after complete reading of thepublications. Finally, six different combinations of drivers of transformation, both climate-related and non-climate-related, impacts of these transformations and adaptation strategies were identified as taking place at the same time.That is, six different dynamics of vulnerability and adaptation to global change have been categorized, namely:Encroachment, Re-greening, Customary, Polarization, Communal and Undiversification.



A Framework for targeting and scaling out Adaptation and Mitigation Measures in agricultural Systems

A. Notenbaerta, M. Herrerob, S. Silvestric and C. Pfeiferc

aCIAT, Kasarani Road, 00100 Nairobi, Kenya; bCSIRO, Box 2583, 4001 Brisbane, Australia; cILRI, P.O. Box 30709,00100 Nairobi, [email protected]

As a result of population growth, urbanization and climate change agricultural systems around the world will faceenormous pressures on the use of resources. There is thus a pressing need for well-targeted research and wide-scaleinnovation leading to development that improves the livelihoods of farmers while at the same time addresses naturalresource constraints. Much work has been done and promising interventions identified. One of the main problems isthat wide-scale adoption of technology remains too low for a large number of potentially beneficial practices.The suitability and adoption of interventions depends on a variety of bio-physical and socio-economic factors. Whiletheir impacts -when adopted and out-scaled- are likely to be highly heterogeneous. This heterogeneity expresses itselfnot only spatially and temporally but also in terms of the stakeholders affected. A mechanism that can facilitate asystematic, holistic assessment of the likely spread and consequential impact of potential interventions is one way ofimproving the selection and targeting of such options.In this paper we provide generic guidelines for evaluating and prioritising potential interventions. This entails an itera-tive process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Throughexamples we demonstrate each of the steps and how they are interlinked. We illustrate how priority setting of inter-vention packages and policies for adapting to, and mitigating climate change can be supported. The first component isunderstanding the out-scaling potential of different packages of interventions (across landscapes, production systemsand others). The second component addresses the quantification of the impacts of different interventions on differentdimensions. It is thereby important to include the assessment of trade-offs between different impact dimensions.The framework is applicable in many different forms and settings. The steps can be gone through qualitatively in amulti-stakeholder setting while the process can also be done quantitatively. It has a wide applicability beyond theexamples presented in this paper.


Tues. 18:00 Medici Plenary round table: addressing options and policies

The Economics of Resilience to Climate Change in Sub-Saharan Africa

C. De Haan

World Bank Consultant, Middenweg14, 7214EN Epse, [email protected]

Not only will the majority of the increase in demand and supply of red meat and milk, and the largest share of livestockproduction related Green House Gas (GHG) emission originate in the developing world, but climate change affectsalso the majority of the people involved in livestock sector. There a more than one billion rural people, of which aboutthe majority are poor who depend, at least in part of their livelihood on livestock. In particular in Africa, the largemajority of these livestock keeping live in the dryland regions, where mitigation options are constrained by structuralinstitutional constraints, and the lack of economically justified technologies.The focus in these drylands will therefore have to be on adaptation, with major attention to enhancing the resilienceof the livestock keeping population. In the dry areas, resilience is defined as the capacity not only to absorb shocks,but also to recover and adapt in a sustainable manner. The few economic studies now available are clear: (a)overall, funding for internationally and nationally provided human food aid over the last decade for drought victims inAfrica by far exceeded the amount needed to significant increase the resilience of livestock keepers; and (b) individualinterventions, such as early destocking to reduce drought induced mortality, show a highly favorable cost/benefit ratio.An on-going World Bank/FAO/ILRI/CIRAD study reviews the technology and policy options to reduce vulnerabilityand enhance the resilience to shocks of livestock dependent dryland populations. Vulnerability depends on threedeterminants: (a) the level of exposure which can be reduced by mobility and number and diversity of livestock assets;(b) the degree of sensitivity, which can be reduced by income diversification; and (c) the capacity to cope, which canbe enhanced by insurance and credit facilities. The feed balance will be the critical underlying factor defining thesethree determinants of vulnerability.The study uses several modeling tools to estimate the impact of several climate change and alternative developmentscenarios on the feed balance and the economic and social implications of these scenarios. Preliminary results showthe need for innovative approaches in increasing alternative sources of income and employment including payment forenvironmental services to enhance the resilience of the pastoralist and agro-pastoralist populations. This might beeconomically and socially more justified than permanent food aid dependency. The presentation at the conference willprovide more detailed results.

Round table

Adressing Options and Policies

Moderator: Cledwyn Thomas, EAAP, Italy Antonia Andúgar, COPA-COGECA, Europe Cees de Haan, World Bank Anne Mottet, FAO, AGAL Marina Piatto, Imaflora, Brasil Jean-François Soussana, INRA, France


AUTHOR INDEX

A. Fernandes, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77Aad, Pauline Y. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Abaigar, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Abdel Nour, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Abi Saab, Saab . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Aghajanzadeh-Darzi, Parisa . . . . . . . . . . . . . . . . . . . . . . . . 138Aguilar Ramirez, Maite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Alberdi, Oier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Alfaro, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139Almeida, Maxwell Mercon Tezolin Barros Almeida . . 24Alves, Teresa C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Amaral, Glaucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Andrade, Caroline Vasconcelos . . . . . . . . . . . . . . . . . . . . . . 36Andrew, Barnes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122Antezana, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Araujo, Barbara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Araujo, Leandro Coelho . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Archimede, Harry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Armstrong, Dan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Arriaga, Haritz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 47, 90Ash, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Assouma, Mohamed Habibou . . . . . . . . . . . . . . . . . . . . . . . 18Audouin, Elise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68Augusti, Angela . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Ayre, Margaret . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Azadi, Hossein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130Baccouche, Asma . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61Bahn, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Balogh, Janos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Banik, Bidhyut . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Bannink, Andre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27, 91Barbosa, Fabiano Alvim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Barioni, Luis Gustavo . 24, 27, 34, 36, 37, 74, 77, 96, 101Barradas, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Barreto Mass, Leonardo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Barth Neto, Armindo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Bartley, Dave J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Batalla, Inmaculada . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Bava, Luciana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 106Bayer, Cimelio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33, 48, 75Beccaccia, Amanda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Beilin, Ruth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Bellocchi, Gianni . . . . . . . . . . . . . . . . . . . . . . . . . 43, 64, 91, 92Ben Touhami, Haythem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92Bendahan, Amaury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Benoit, Marc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Benot, Marie-Lise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Bernabucci, Umberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Berndt, Alexandre . . . . . . . . . . . . . . . . 33, 36, 37, 48, 74, 75Bernoux, Martial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Bertocchi, Luigi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62Birnholz, Celine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110Blanc, Lilian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Blanco, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Blanfort, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70, 81Bois, Berenice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 61Bonal, Damien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Bonnet, Olivier Jean F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Boonyanuwat, Kalaya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22Botai, Joel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94, 97, 104Bouquet, Peggy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Bousseboua, Hacene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Boyle, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Brask, Maike . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45, 46Brennan, P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102Brown, Barbara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95Buchmann, Nina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56Buckingham, Susan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122Calvet, Salvador . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 59Cambra-Lopez, Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Carabano, Maria J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Cardozo Vieira, Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75Carvalho, Paulo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Caslenani Freua, Mateus . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Cederberg, Christel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Cerisuelo, Alba . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Cesar De Faccio Carvalho, Paulo . . . . . . . . . . . . . . . . . . . . 33Cespedes, M.A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Cezimbra, Ian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Chabbi, Abad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Chang, Jinfeng . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Chesterman, Sabrina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Christie, Karen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Colombini, Stefania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Coltri, Priscila Pereira . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Conant, Rich . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87, 112Connolly, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Cordovin, Lucia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Cortez, Luis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Costa Junior, Ciniro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37


Crespo, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71Crimp, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Cristina Moraes Genro, Teresa . . . . . . . . . . . . . . . . . . . 33, 75Cserhalmi, Dora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Cullen, Brendan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 136Cutullic, Erwan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Da Silva, Marco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Dalgaard, Tommy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43De Araujo Silva, Barbara . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75De Blas, Carlos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59De Faccio Carvalho, Paulo Cesar . . . . . . . . . . . . . . . . . . . . 75De Haan, Cees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143De Oliveira Silva, Rafael . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77De Vries, Wim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Debusho, Legesse Kassa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97Decrem, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Deklein, Cecile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139Del Hierro, Oscar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Dequiedt, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Descheemaeker, Katrien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Diaz, Clara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Dieme, Ibrahima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Diene, Mamadou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Diop, Tamsir . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 61, 72Diriba, Tadele Akeba . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97, 98Dittrich, Ruth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58Dong, Hongmin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39, 40Doreau, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 61, 63Duclos, Anne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Dupard, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Durmic, Zoey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19, 23, 32Duru, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108Dutilly, Celine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Eckard, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99Eguinoa, Paola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Eory, Vera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77, 125, 133Erskine, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Escape, Christophe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Eseverri, M.P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Estelles, Fernando . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 59Eugene, Maguy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Falcimagne, Robert . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70Falcucci, Alessandra . . . . . . . . . . . . . . . . . . 85, 112, 114, 129Faria, Bruna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Fasiaben, Maria Do Carmo Ramos . . . . . . . . . . . . . 24, 101Faulkner, Catherine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30, 38Faverdin, Philippe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Feltrin, Geovani Bertochi . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37Fernandez, Francisco J. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Ferrer, Pablo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Fialho Heguaburu, Arturu . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Finn, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56, 78Fiorelli, Jean-Louis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Foley, Jonathan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Fontaine, Sebastien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70, 81Foti, Szilvia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Fragoso, Rita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Freua, Mateus Castelani . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Freycon, Vincent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Friend, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84Fumagalli, Davide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Fushai, Felix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Garcia De Jalon, Silvestre . . . . . . . . . . . . . . . . . . . . . . . . . . 109Garcia-Rebollar, Paloma . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Garcia-Rodriguez, Aser . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 35Garnett, Tara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13Gayatri, Siwi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124Gemeda, Belete Shenkute . . . . . . . . . . . . . . . . . . . . . . . . 65, 84Gemiyo, Deribe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60Genestoux, Lucette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61, 63Gengler, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Genro, Teresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Geraldo De Lima, Jacqueline . . . . . . . . . . . . . . . . . . . . . . . . 27Gerber, James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Gerber, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112, 114, 129Ghahramani, Afshin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Giller, Ken . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Godber, Olivia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Gomes, Rodrigo Da Costa . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Grise, Marcia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81Guerci, Matteo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106Guerouali, Abdelhai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28Guimaraes Junior, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . 34Hammami, Hedi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Haque, Md Najmul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Harrison, Matthew . . . . . . . . . . . . . . . . . . . . . . . . . 42, 99, 136Hart, Kenton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30, 38Hassen, Abubeker . . . . . . . . . . . . 60, 64, 65, 84, 94, 97, 104Haughey, Eamon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56Havlik, Petr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14, 87Hayman, Gillian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Heinke, Jens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85, 103, 111Hellwing, Anne Louise F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Henderson, Benjamin . . . . . . . . . . . . . . . . . . . . . 112, 114, 129Hermann, Janice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95Herrero, Mario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14, 87, 142Hidy, Dora . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Hiernaux, Pierre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Hietala, Pauliina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Hilinski, Thomas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112


Hoeksma, Paul . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Hoekstra, Nyncke . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56Hofer, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56Hojberg, Ole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Holshof, Gertjan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Homann-Kee Tui, Sabin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Howden, Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16, 137Huang, Wenqiang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Humphreys, James . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66, 102Humphries, Alan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Hutchings, Nicholas J. . . . . . . . . . . . . 43, 91, 107, 110, 128Ickowicz, Alexandre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 61Iglesias, Ana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109, 117Intxaurrandieta, Juan Manuel . . . . . . . . . . . . . . . . . . . . . . 123Jayet, Pierre-Alain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Jenet, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118Jørgensen, Margit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128Joy, Margalida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32, 67Juanes, Xavier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Juga, Jarmo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31Khanal, Prabhat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Khedri Gharibvand, Hojatollah . . . . . . . . . . . . . . . . . . . . . 130Kipling, Richard P . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Kirwan, Laura . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Klumpp, Katja . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70, 80, 81Koncz, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Kros, Hans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Kuikman, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . 113, 139, 140Lacetera, Nicola . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62, 105Lahoud, Imad . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73Lalor, Stan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Landais, Damien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Lanigan, Gary . . . . . . . . . . . . . . . . . . . . . . . . . . . 66, 88, 90, 91Laperche, Sylvain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Lasseur, Jacques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Leclere, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Lecomte, Philippe . . . 18, 21, 61, 68, 69, 70, 81, 110, 127Ledgard, Stewart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Legua, M.A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Lemes, Amanda P. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Lesschen, Jan Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . 113, 140Li, Tong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Lian, Dongli . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Lister, Cliff . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30Liu, Chong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40Lo Presti, Stefano . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105Lobon, Sandra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Logar, Betka . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Loges, Ralph . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Lopez, Diana Maria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Lopez-I-Gelats, F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141Loyon, Laurence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Lucas, Marco Antonio Karam . . . . . . . . . . . . . . . . . . . . . . 131Lund, Kirrin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23Lund, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45, 46Luscher, Andreas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56, 78Lynd, Lee . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Machado Cezimbra, Ian . . . . . . . . . . . . . . . . . . . . . . . . . 33, 75Maciel, Giovana De Alcantara . . . . . . . . . . . . . . . . . . . . . . . 34Macleod, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126, 133Madsen, Jørgen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Maia, Alexandre Gori . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Maire, Juliette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Mandaluniz, Nerea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 35Mandarino, Raphael Amazonas . . . . . . . . . . . . . . . . . . . . . . 34Mangado, Jesus Marıa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Manlay, Raphael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127Marie-Magdeleine, Carine . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Marinho Tres Schons, Radael . . . . . . . . . . . . . . . . . . . . . . . . 75Marino, Carolina Tobias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36Martha, Geraldo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Martin, Raphael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138Martin-Clouaire, Roger . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108Masafu, M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Maselli, Daniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134Masikati, Patricia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Mason, Warren . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Masse, Dominique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68, 127McCalman, Heather . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122Medeiros, Roberto Dantas . . . . . . . . . . . . . . . . . . . . . . . . . . . 93Mei, Kai . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Melse, Roland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Menezes Santos, Patricia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27Merino, Pilar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17, 47, 90Meuret, Michel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Molano, German . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Molino, F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67Moller, Henrik Bjarne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Moorby, Jon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Moore, Andrew . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137Moran, Dominic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77, 116Moreira Santana, Marcela . . . . . . . . . . . . . . . . . . . . . . . 33, 75Moreira, Jose Mauro Magalhaes Avila Paz . . . . . . . . . 101Morgavi, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21, 61, 63Morishige, Ashley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Moset Hernandez, Veronica . . . . . . . . . . . . . . . . . . . . . . . . . 45Mosquera Losada, Julio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Mottet, Anne . . . . . . . . . . . . . . . . . . . . . . . . . 85, 111, 114, 129Mouillot, Florent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100Moura Kohmann, Marta . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33


Mueller, Nathaniel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Muetzel, Stefan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Nagy, Zoltan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Nardone, Alessandro . . . . . . . . . . . . . . . . . . . . . . . . . . . 62, 105Ndao, Sega . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69Ndiaye, Ousmane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Nettle, Ruth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Newbold, Jamie . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30, 38Newbold, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Nherera, Cfv . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Ni Choncubhair, Orlaith . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66Nielsen, Mette Olaf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29Norris, David . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Notenbaert, An . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87, 142O Mara, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88O’brien, Donal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102, 107Obersteiner, Michael . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Odru, Mariana . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68Oenema, Oene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139, 140Ojima, Dennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Olesen, Jørgen E. . . . . . . . . . . . . . . . . . . . . . . . . . . . 82, 88, 107Oliveira, Aryeverton Fortes . . . . . . . . . . . . . . . . . . . . . . . . 101Oliveira, Octavio Costa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Oliveira, Patricia A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Oosting, Simon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89Opio, Carolyn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114Oyhantcabal, Walter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132Pahl, Ole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90Papp, Marianna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Pedroso, Andre De F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Perdok, Hink . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38, 107Pereira, Luiz Gustavo Ribeiro . . . . . . . . . . . . . . . . . . . . . . . 34Persson, Martin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51Petersen, Soren O. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Pezzopanne, Jose Ricardo . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Pfeifer, Catherine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142Phelps, Catherine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Picon-Cochard, Catherine . . . . . . . . . . . . . . . . . . . . 70, 76, 81Piel, Clement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Piketty, Marie-Gabrielle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93Pineda-Quiroga, Carolina . . . . . . . . . . . . . . . . . . . . . . . . 26, 35Pinter, Krisztina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79Pinto, Miriam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123Piquet, Mathilde . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108Poccard-Chapuis, Rene . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93Poulsen, Morten . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Rahim, Inam Ur . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134Rakgase, M . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55Ramos, Fabien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Raposo De Medeiros, Sergio . . . . . . . . . . . . . . . . . . . . . 36, 37

Ravel, Olivier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Rawnsley, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . 42, 99, 136Reckling, Moritz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Rees, Robert M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Reisinger, Andy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44Revell, Clinton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Rira, Moufida . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63Ritzel Tischler, Marcelo . . . . . . . . . . . . . . . . . . . . . . . . . 33, 75Rivera-Ferre, Marta G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141Robinson, Tim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126Rocha, Jansle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Rolinski, Susanne . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103Roy, Jacques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Ruane, E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102Rueff, Henri . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134Ruget, Francoise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64Ruiz, Roberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26, 35Saetnan, Eli R . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Sakamoto, Leandro S. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74Salvatore, Mirella . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112Sancho, Diego . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132Sandrucci, Anna . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 106Santos, Darliane Castro . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Santos, Jorge Luiz Sant’Anna Dos . . . . . . . . . . . . . . . . . . 131Santos, Patrıcia Menezes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Sanz-Cobena, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . 47, 59Sautier, Marion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108Savian, Jean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48Schipani, Teresa Maria Iolanda . . . . . . . . . . . . . . . . . . . . . 105Schmid, Erwin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Scollan, Nigel D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43Sebastia, Theresa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78Shalloo, Laurence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102, 107Shaw, Alex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126Sheehan, Evan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Sheehan, John . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Shlaefke, Nicole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Shrestha, Shailesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133Siebrits, F. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Sikirica, Natasa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140Silva Dutra, Vinıcius . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Silva, Rafael De Oliveira . . . . . . . . . . . . . . . . . . . . . . . . . . . 101Silvestri, Silvia . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85, 111, 142Sissokho, Mohamadou . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127Smith, Pete . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50Soussana, Jean-Francois . . . . . . . 14, 16, 53, 70, 76, 80, 81Stahl, Clement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70, 81Stienezen, Marcia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107Suter, Matthias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56, 78Talore, Deribe Gemiyu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84


Tamburini, Alberto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 106Tasfamariam, E. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94Tekere, M. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25Tempio, Giuseppe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114Tesfamariam, Eyob . . . . . . . . . . . . . . . . . . . . . 60, 64, 84, 104Thornton, Philip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Topp, Cairistiona F.E. . . . . . . . . . . . . . . . . . 77, 82, 107, 125Toure, Ibra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72Tourrand, Jean Francois . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93Vaarst, Mettte . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124Vadhanabhuti, Joy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23, 32Valin, Hugo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14Vallejo, Antonio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Van Den Pol Van Dasselaar, Agnes . . . . . . . 27, 43, 88, 91Van Doorslaer, Benjamin . . . . . . . . . . . . . . . . . . . . . . . . . . . 135Vanrobays, Marie-Laure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83Vayssieres, Jonathan . . . . . . . . . . . . . . . . . . . 18, 68, 110, 127Vejlin, Jonas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128Veneman, Jolien . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38Vercoe, Philip . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19, 23, 32Verdoes, Nico . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Victor Savian, Jean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33, 75Vigan, Aurore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100, 127Vigne, Mathieu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69, 93Viguria Salazar, Maialen . . . . . . . . . . . . . . . . . . . . . 17, 47, 90

Vilela, Lourival . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34Viovy, Nicolas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96Vitali, Andrea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62, 105Volaire, Florence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Wall, Richard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119Waller, Steven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136Wang, Xiaoqin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Wang, Xuedong . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121Wang, Yue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Weindl, Isabelle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103Weisbjerg, Martin Riis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45West, Charles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Westhoek, Henk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140Wilburn, Sarah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95Wint, William . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126Witlox, Frank . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130Xin, Hongwei . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39Yossifov, Marin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120Zander, Peter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125Zanett Albertini, Tiago . . . . . . . . . . . . . . . . . . . . . . 36, 37, 77Zhu, Biqing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113Zhu, Zhigang . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46Zhu, Zhiping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39, 40Zucali, Maddalena . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20, 106

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