Future Land Cover Change and Forests - Global Challenges - Bioenergy versus Deforestation
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Transcript of Future Land Cover Change and Forests - Global Challenges - Bioenergy versus Deforestation
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Future Land Cover Change and Forests
- Global Challenges - Bioenergy versus Deforestation
Florian KraxnerE.-M. Nordström, P. Havlík, M. Obersteiner, et al.
+>30 collaborators
Ecosystems Services and Management Program (ESM) @International Institute for Applied Systems Analysis (IIASA), Austria
The 3rd Global Forest Carbon Working Group Meeting“Future of Global Forests”
27-29 May 2013IIASA, Austria
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Sustainable bioenergy feedstock- global scenarios and outlook
Florian Kraxner, E.-M. Nordström, P. Havlík, M. Obersteiner, et al.
Ecosystems Services and Management Program, IIASA
Bio-energy and CCS (BECCS): Options for Brazil,
13-14 June 2013, Sao Paulo, Brazil
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ESM’s Organizational Structure
Earth Observation Systems (EOS) (Fritz/See)
Environmental Resources and Development
(ERD)(Havlik/ Mosnier/Valin)
Met
hods
for E
cono
mic
Dec
isio
n–M
akin
g un
der
Unc
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inty
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) (K
haba
rov/
Fuss
)Policy and Science Interface (PSI)
(Kraxner/Boettcher)
ESM Lead / Management (MGT)(Obersteiner/Kraxner)
Agro-Environmental Systems (AES) (v.d.Velde/Balkovic)
Forest Ecosystems
Management (FEM) (Forsell)
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ESM’s Integrated Modeling Cluster
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Modeling Biomass Supply at Global Scale – An Integrated Modeling Approach
Source: IIASA (2011)
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G4M
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Biophysical forest model G4M
7, date
• Forest parameters from G4M– Provides annual harvestable wood (for sawn wood and
other wood)– Afforestation/Deforestation (NPV)– Forest management (rot/spec)– Forest Carbon stock
• Downscaling FAO country level information on above ground carbon in forests (FRA 2005) to 30 min grid (Kinderman et al., 2008)
– Harvesting costs– Forest area change– Spatially explicit
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• NPP• Population Density• Land cover• Agricultural suitability• Forest Biomass• Price level• Discount rate• Corruption• Product use
Source: Kindermann (2010)
Input Data Sets for the Global Forestry Model (G4M)
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Forest Area Development A2r (2000 – 2035)
Source: IIASA, G4M (2008)
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Deforestation 2050 under BAU
• Losses under BAU by 2050 will be 300-500 mio ha
• Tropical deforestation is considered the second largest source of anthropogenic greenhouse gas emissions (IPCC, 2007) and is expected to remain a major emission source for the foreseeable future (MEA, 2005)
• the net effect of all deforestation is basically almost an increase of 20 per cent additional emissions from human activity going into the atmosphere and feeding into climate change.
• deforestation is to blame for about one and a half billion tons of carbon dioxide being released into the atmosphere every year for the past 15 years (GCP).
• To the left we see the picture of tropical Africa now and in 2100 under BAU (the more red the less tropical forest, www.geo-bene.eu/?q=node/1653)
Source: Kindermann et al. 2006
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EPIC
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EPIC
Rain, Snow, Chemicals
Subsurface Flow
Surface Flow
Below Root Zone
Evaporation and
Transpiration
• Weather• Hydrology• Erosion• Carbon sequestration• Crop growth• Crop rotations• Fertilization• Tillage• Irrigation• Drainage• Pesticide• Grazing• Manure
Processes
Major outputs:Crop yields, Environmental effects (e.g. soil carbon, )
20 crops (>75% of harvested area)4 management systems: High input, Low input, Irrigated, Subsistence
Cropland - EPICThe Biophysical Agriculture Model EPIC
Source: Schmid (2008)
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SOC
increase SOC0.18 t/ha/year
Crop Yield
DM Crop Yield -0.30 t/ha, or -7.9%
Source: INSEA, Schmid (2006)
EPIC – Management Change (conventional minimum tillage)
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Source: Data: Tyndall, Afi Scenario, simulation model: EPIC (2011)
EPIC - Relative Difference in Means (2050/2100) in Wheat Yields
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GLOBIOM
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Model general structure
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• Partial equilibrium model on land use at global scale (endogenous prices balance supply and demand)– Agriculture: major agricultural crops and livestock products– Forestry: managed forests for sawnwood, and pulp and
paper production– Bioenergy: conventional crops and dedicated forest
plantations• Optimization of the social welfare (producer + consumer
surplus)• Base year 2000, recursively dynamic (10 year periods)• Supply defined at the grid cell resolution• Demand defined at the level of 52 world regions• Main data source: FAOSTAT, complemented with bottom-up
sectoral models for production parameters
GLOBIOM
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GLOBIOM - Supply chain
Natural Forests
Managed Forests
Short Rotation Tree Plantations
Cropland
Grassland
Other natural land
BioenergyBioethanol Biodiesel MethanolHeatElectricityBiogas
Wood products
Sawn woodPulp
Livestock productsBeefLambPorkPoultryEggsMilk
CropsCornWheatCassavaPotatoesRapeseedetc…
LAN
D U
SE C
HA
NG
E
Wood Processing
Bioenergy- Processing
Livestock Feeding
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World partitioned in 52 regions
28 regions represented on the map+ Sub-saharan Africa split in Western Africa, Eastern Africa and Southern Africa (Congo Basin and South Africa already separated)
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GLOBIOM: Typical applications
• Agricultural prospective– Schneider et al. (2011) Impacts of population growth, economic development, and technical
change on global food production and consumption. Agricultural Systems– Smith et al. (2010) Competition for land, Philosophical transactions– Applied scenarios such as Eastern Africa with CCAFS
• Deforestation– Mosnier et al. (2010) Modeling impacts of development trajectories on forest cover in
the Congo Basin– Living Forest Report – WWF (2011)
• Climate change mitigation– Valin et al. (2010) Climate change mitigation and food consumption patterns
• Biofuels– Fuss et al. (2011) A stochastic analysis of biofuel policies– Havlik et al. (2010) Global land-use implications of first and second generation biofuel targets.
Energy Policy– Mosnier et al. (2010) Direct and indirect trade effects of EU biofuel targets on global GHG
emissions• Trade and trade-off assessments• Direct and indirect water demand of feedstock/livestock production systems
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Globally Consistent Assessment of Forest Development and Bioenergy…
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Background
Global Future Energy Portfolios, 2000 – 2100 Source: modified after Azar et al., 2010
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Cumulative biomass production (EJ/grid) for bioenergy between 2000 and 2100 at the energy price supplied by MESSAGE based on the revised IPCC SRES A2r scenario (country investment risk excluded).
Source: Rokityanskiy et al. 2006
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Forest Area Development A2r (2000 – 2035)
Source: IIASA, G4M (2008)
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Source: compiled from FAO 2005, 2001; CIESIN 2007, ATFS 2008; FSC 2008; PEFC 2008.
Kraxner et al., 2008
Certified area relative to managed forest area by countries
Forest Management Certification (Potentials)
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Global BE Feedstock Scenarios – Definitions & Objectives
WWF, 2011
Objectives:a) to achieve a global perspective using an integrated
modeling approach; b) to frame the boundaries for lower scale assessments;
and c) to identify potential trade-offs to be considered in
future research.
Zero Net Deforestation and Degradation (ZNDD) means no net forest loss through deforestation and no net decline in forest quality through degradation.
Scenario name Description BAU ”Business as usual”: Projection of future development
in line with historical trends BE2010 As BAU but the production of bioenergy fixed at the
level in 2010 BEPlus Projection of bioenergy demand by 2050 as in the
100 per cent renewable energy vision by the Ecofys Energy Model
BEPlusRED As BEPlus but with target ”no net deforestation” (RED=Reducing Emissons from Deforestation)
BiodivRED Stricter biodiversity protection combined with target ‘no net deforestation’
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Cumulative deforestation 2000-2050 caused by land-use change according to the different scenarios.
Global Deforestation Trends
• BEPlus similar to BAU• BE2010 on same high level because of unrestricted deforestation• RED keeps deforestation at present level
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• most of the loss of unmanaged forest takes place in the tropical areas of South America, Africa and Asia
Loss of pristine (unmanaged) forest as a proxy for BE production on Biodiversity
Cumulative loss of area of unmanaged forest 2000-2050 in different regions under the BAU scenario
Cumulative loss of area of unmanaged forest 2000-2050 in different regions under the BEPlus RED scenario
• the loss of unmanaged forest is not only considerably smaller but also more evenly distributed from a global perspective
Regional Effects by Adding BE, Biodiv, RED - Unmanaged Forest rel to BAU
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GHG emissions from total land use 2000-2050 under the different scenarios
GHG Emissions by Scenarios
• Under the BE2010 scenario, the bioenergy use is small compared to the other scenarios, and the GHG emissions are the highest, 8,091 Mt CO2/year. The GHG emissions are lower under the BAU and BEPlus scenarios, where the bioenergy use is more extensive.
• Lowest GHG emissions can be achieved under the RED scenarios
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Water consumption for agriculture 2000-2050 under the different scenarios
Agricultural Water Demand by Scenarios
• All scenarios show increased demand• Lowest restriction on forest and biodiversity conservation show less water need• Higher restriction implies less land available for eg food production = intensification
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• The demand for bioenergy will be high and will increase competition for land• Bioenergy production is a significant but not the major driver of forest loss • Avoiding large-scale deforestation is possible, even under expanded bioenergy
production. • Unmanaged forest will be lost under all scenarios but under the RED scenarios
the loss is only half of the loss under the BAU scenario• GHG emissions may be substantially reduced by minimizing deforestation• Minimization of deforestation may have negative impacts on other natural
ecosystems• The more forest and biodiversity one would like to be conserved, the less land
will be available for food production• The more conservation and protection, the higher the need for optimization and
intensification• Various policy areas must be coordinated to ensure sustainable use of
resources• Future studies need to go into the details identified here
Summary & Discussion & Conclusions
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High hopes…
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Contact
Florian Kraxner
Ecosystem Services and Management ProgramInternational Institute for Applied Systems Analysis, IIASA Laxenburg, [email protected]://www.iiasa.ac.at
Paper contribuion:Florian Kraxner; Eva-Maria Nordström; et al. (2013). Global Bioenergy Scenarios - Future Forest Development, Land-Use Implications, and Trade-Offs. Biomass and Bioenergy (in press)