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Shifting cultivation in the upland secondary forests of the Philippines:
Biodiversity and carbon stock assessment, and ecosystem services trade-offs in
land-use decisions
Sharif Ahmed Mukul
BSc (Hons I), MSc in Forestry, Shahjalal University of Science and Technology
MSc in Tropical Forestry and Management, Technische Universität Dresden
MSc in Agricultural Development, University of Copenhagen
A thesis submitted for the degree of Doctor of Philosophy at
The University of Queensland in 2015
School of Agriculture and Food Sciences
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Abstract
Secondary forest comprises a large area in the tropical region, and it has increasingly
believed that the future of tropical forests depends on the effective management of such second
growth forests largely modified by human activity. In tropical secondary forests, shifting
cultivation, swidden or slash-and-burn is a major land-use that has been attributed to causing large
scale deforestation and forest degradation. This view has been embedded in many policy
documents, although there are conflicting views within the literature as to the impact of shifting
cultivation on secondary forest dynamics. This is largely due to the complex nature of this land-use
that makes any generalisation difficult.
In the Philippines – a country overwhelmed with rich biodiversity and species endemism,
shifting cultivation is locally known as kaingin and represents a dominant land-use in upland rural
areas. Although not officially recognised, it has a major contribution to the livelihoods and food
security of smallholder rural farmers. After post–logging secondary forests, post–kaingin secondary
forests also form the largest group of secondary forests in the Philippines. This thesis based on an
empirical study where secondary forest dynamics after shifting cultivation were investigated in an
upland area in the Leyte Island, the Philippines.
Chapter 2 of my thesis is a synthesis that reports, spatial and temporal distribution of
research on shifting cultivation using a systematic literature search protocol, and the key findings of
research in conservation biology, plant ecology, soil nutrients and chemistry, and soil physics and
hydrology. A bias towards research on anthropology and/or human ecology was found with most
research reported from tropical Asia-Pacific region. A great variation in findings on selected
forest/environmental parameters was also evident.
In Chapter 3, I report a field study where tree diversity, species composition and forest
structure and their recovery in secondary forests after shifting cultivation was investigated along a
fallow/shifting cultivation land-use gradient. Twenty-five individual sites representing four different
fallow categories and old-growth forest as control were surveyed. Tree species richness was
significantly higher in the oldest fallow sites while other diversity and forest structure indices were
higher in the old-growth forest sites. A homogeneous species composition was found in older
fallow sites and in old-growth forest. It was found that secondary forests disturbed by shifting
cultivation recovers rapidly in terms of species richness and abundance, and that patch size is a
strong predictor of this recovery.
Uncertainties in the aboveground biomass carbon in degraded secondary forests after
shifting cultivation are one of the main issues hindering its inclusion in the current REDD+
negotiations. In Chapter 4, the distribution and recovery of biomass carbon along a fallow gradient
were reported from my study sites. It was found that aboveground total biomass carbon and living
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woody biomass carbon was significantly higher in the old-growth forest sites while coarse dead
wood biomass carbon was high in the new fallow sites. The high level of dead wood biomass
carbon in new fallow sites was due mainly to high levels of coarse dead wood remaining as an
artefact of clearing. Relatively higher biomass carbon recovery in oldest fallow sites than other
fallow category with patch size again as an influential factor in explaining the variation in biomass
carbon recovery in regenerating secondary forests after shifting cultivation was evident.
Shifting cultivation has been linked to an adverse impact on soil carbon and nutrients in the
tropical region, albeit different conclusions from the studies. In Chapter 5, the distributions and
recovery of soil organic carbon, soil nitrogen, phosphorus and potassium in relation to shifting
cultivation use in regenerating secondary forests were examined. Limited influence of shifting
cultivation on soil carbon, nitrogen and phosphorus were found, although soil K recovery was low
across the sites. Multivariate analysis revealed patch size together with slope and fallow age
important in explaining the variation in soil carbon and nutrient recovery in different site categories
and soil depths.
It has commonly believed that tropical landscapes after shifting cultivation are not suitable
for biodiversity and carbon benefits. Drawing on my present study in the Philippines in Chapter 6, I
demonstrate that regenerating secondary forests following shifting cultivation have the potential for
inclusion in programs on forest conservation under REDD+ and CDM. I argue that regenerating
secondary forests after shifting cultivation can be a cost-effective conservation, restoration and
forest management option not only in the Philippines but also in other countries where shifting
cultivation is prevalent.
Overall, my thesis highlights the key biophysical and some policy aspects of shifting
cultivation on tropical secondary forest dynamics. My results indicate that regenerating forests after
shifting cultivation can act as a low-cost refuge for biodiversity conservation and an important
source and sink of carbon that increases with abandonment age. A better understanding of the forest
dynamics associated with shifting cultivation land-use, however, is important for the future of
tropical forest management and conservation.
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Declaration by author
This thesis is composed of my original work, and contains no material previously published or
written by another person except where due reference has been made in the text. I have clearly
stated the contribution by others to jointly-authored works that I have included in my thesis.
I have clearly stated the contribution of others to my thesis as a whole, including statistical
assistance, survey design, data analysis, significant technical procedures, professional editorial
advice, and any other original research work used or reported in my thesis. The content of my thesis
is the result of work I have carried out since the commencement of my research higher degree
candidature and does not include a substantial part of work that has been submitted to qualify for
the award of any other degree or diploma in any university or other tertiary institution. I have
clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.
I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,
subject to the policy and procedures of The University of Queensland, the thesis be made available
for research and study in accordance with the Copyright Act 1968 unless a period of embargo has
been approved by the Dean of the Graduate School.
I acknowledge that copyright of all material contained in my thesis resides with the copyright
holder(s) of that material. Where appropriate I have obtained copyright permission from the
copyright holder to reproduce material in this thesis.
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Publications during candidature
Peer reviewed papers – lead author
Mukul, S.A., Herbohn, J., Firn, J. (in review) High resilience of tropical forest diversity and
structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science.
Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. (in review) Soil carbon and nutrients
status in relation to shifting cultivation in regenerating secondary forests in the Philippines
uplands. Land Degradation & Development.
Mukul, S.A., Herbohn, J., Firn, J. (in press) Co-benefits of biodiversity and carbon from
regenerating secondary forests in the Philippines uplands: Implications for forest landscape
restoration. Biotropica.
Mukul, S.A., Herbohn, J., Firn, J. (2016) Tropical secondary forests regenerating after shifting
cultivation in the Philippines uplands are important carbon sinks. Scientific Reports 6: 22483.
Mukul, S.A., Herbohn, J. (2016) The impacts of shifting cultivation on secondary forests dynamics
in tropics: a synthesis of the key findings and spatio temporal distribution of research.
Environmental Science & Policy 55: 167-177.
Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B., Khan, N.A. (2015) Role of non-timber forest
products in sustaining forest-based livelihoods and rural households’ resilience capacity in
and around protected area: a Bangladesh study. Journal of Environmental Planning and
Management DOI: 10.1080/09640568.2015.1035774.
Mukul, S.A., Herbohn, J., Rashid, A.Z.M.M., Uddin, M.B. (2014) Comparing the effectiveness of
forest law enforcement and economic incentive to prevent illegal logging in Bangladesh.
International Forestry Review 16: 363-375.
Mukul, S.A., Biswas, S.R., Rashid, A.Z.M.M., Miah, M.D., Uddin, M.B., Kabir, M.E., Khan, N.A.,
Alamgir, M., Sohel, M.S.I., Chowdhury, M.S.H., Rana, M.P., Khan, M.A.S.A., Rahman,
S.A., Hoque, M.A. (2014) A new estimate of carbon in Bangladesh forest ecosystems, with
their spatial distribution and REDD+ implication. International Journal of Research on Land-
use Sustainability 1: 33-40.
Mukul, S.A., Tito, M.R., Munim, S.A. (2014) Can homegardens help save forests in Bangladesh?
Domestic biomass fuel consumption patterns and implications for forest conservation in
south-central Bangladesh. International Journal of Research on Land-use Sustainability 1:
18-25.
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Mukul, S.A., Rana, M.P. (2013) The trade of Bamboo (Graminae) and its secondary products in a
regional market of southern Bangladesh: status and socio-economic significance.
International Journal of Biodiversity Science, Ecosystem Services & Management 9: 146-154.
Mukul, S.A., Rashid, A.Z.M.M., Quazi, S.A., Uddin, M.B., Fox, J. (2012) Local peoples' response
to co-management in protected areas: A case study from Satchari National Park, Bangladesh.
Forests, Trees and Livelihoods 21: 16-29.
Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B. (2012) The role of spiritual beliefs in conserving
wildlife species in religious shrines of Bangladesh. Biodiversity 13: 108-114.
Peer reviewed papers – co-author
Pavel, M.A.A., Mukul, S.A.*, Uddin, M.B., Harada, K., Khan, M.A.S.A. (in press) Effects of stand
characteristics on tree species richness in and around a conservation area of northeast
Bangladesh. Journal of Mountain Science DOI: 10.1007/s11629-015-3501-2.
Sohel, M.S.I., Mukul, S.A., Burkhard, B. (2015) Landscape’s capacities to supply ecosystem
services in Bangladesh: A mapping assessment for Lawachara National Park. Ecosystem
Services 12: 128-135.
Alamgir, M., Mukul, S.A.*, Turton, S. (2015) Modelling spatial distribution of critically
endangered Asian elephant and Hoolock gibbon in Bangladesh forest ecosystems under a
changing climate. Applied Geography 60: 10-19.
Sohel, M.S.I., Mukul, S.A., Chicharo, L. (2015) A new ecohydrological approach for ecosystem
service provisions and sustainable management of aquatic ecosystems in Bangladesh.
Ecohydrology & Hydrobiology 15: 1-12.
Chowdhury, M.S.H., Gudmundsson, C., Izumiyama, S., Koike, M., Nazia, N., Rana, M.P., Mukul,
S.A., Muhammed, N., Redowan, M. (2014) Community attitudes toward forest conservation
programs through collaborative protected area management in Bangladesh. Environment,
Development and Sustainability 16: 1235-1252.
Rashid, A.Z.M.M., Tunon, H., Khan, N.A., Mukul, S.A. (2014) Commercial cultivation by farmers
of medicinal plants in northern Bangladesh. European Journal of Environmental Sciences 4:
60-68.
Uddin, M.B., Steinbauer, M.J., Jentsch, A., Mukul, S.A.*, Beierkuhnlein, C. (2013) Do
environmental attributes, disturbances, and protection regimes determine the distribution of
exotic plant species in Bangladesh forest ecosystem? Forest Ecology and Management 303:
72-80.
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Rashid, A.Z.M.M., Craig, D., Mukul, S.A., Khan, N.A. (2013) A journey towards shared
governance: status and prospects of collaborative management in the protected areas of
Bangladesh. Journal of Forestry Research 24: 599 -605.
Al-Mamun, M., Poostforush, M., Mukul, S.A., Parvez, M.K., Subhan, M.A. (2013) Biosorption of
As(III) from aqueous solution by Acacia auriculiformis leaves. Scientia Iranica 20: 1871-
1880.
Al-Mamun, M., Poostforush, M., Mukul, S.A., Subhan, M.A. (2013) Isotherm and Kinetics of
As(III) Uptake from Aqueous Solution by Cinnamomum zeylanicum. Research Journal of
Chemical Sciences 3: 34-41.
Uddin, M.B., Mukul, S.A.*, Hossain, M.K. (2012) Effects of organic manure on seedling growth
and nodulation capabilities of five popular leguminous agroforestry tree components of
Bangladesh. Journal of Forest Science 28: 212 -219.
Uddin, M.B., Mukul, S.A.* (2012) Ethnomedicianl knowledge of Khasia tribe in Sylhet region,
Bangladesh. Indian Journal of Tropical Biodiversity 20: 69-76.
* where corresponding author.
Book chapters
Mukul, S.A., Byg, A., Herbohn, J. (in press) Shifting away from swidden? Factors affecting
swidden transition in central hill districts of Nepal. In: Cairns, M. (ed) Shifting cultivation
policy: trying to get it right, Routledge, London.
Mukul, S.A. (2014) Biodiversity conservation and ecosystem functions of traditional agroforestry
systems: case study from three tribal communities in and around Lawachara National Park.
In: Chowdhury, M.S.H. (ed) Forest conservation in protected areas of Bangladesh: policy
and community development perspectives (World Forests Series, Vol. 20), Springer,
Switzerland, pp. 171-179.
Conference abstracts
Mukul, S.A., Herbohn, J. (2015) A novel carbon payment scheme for improved livelihoods and
better management of swidden fallow secondary forests in the developing tropics, (oral
presentation), 1st Annual FLARE (Forests & Livelihoods: Assessment, Research, and
Engagement) Network Conference, 27-30 November, Paris, France.
Mukul, S.A., Herbohn, J., Firn, J. (2015) Co-benefits of biodiversity and carbon from degraded
secondary forests following shifting cultivation in the Philippines: implications for forest
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restoration and community development, (oral presentation), Small-scale and community
forestry and changing nature of forest landscapes, 11-15 October 2015, Sunshine Coast.
Mukul, S.A., Herbohn, J. (2015) Divergent estimates of biomass carbon in Southeast Asian rain
forests: a Philippines study, (oral presentation), ATBC 2015: resilience of island systems in
context of climate change, 12-16 July 2015, Hawaii, USA.
Mukul, S.A., Herbohn, J., Firn, J. (2015) Rapid recovery of tree diversity over forest structure in
post-kaingin secondary forests in the Philippines, (poster presentation), Student Conference
on Conservation Science 2015 (SCCS - Australia), 19-29 January 2015, Brisbane.
Mukul, S.A., Herbohn, J. (2014) Biodiversity and ecosystem carbon budget in the upland
landscapes following shifting cultivation by small-holder kaingin farmers in the Philippines,
(oral presentation), 2014 IUFRO World Congress - sustaining forests, sustaining people, the
role of research, 5-11 October 2014, Salt Lake City, USA.
Mukul, S.A., Herbohn, J., Firn, J. (2014) Neglecting conservation value of degraded tropical
landscapes? tree diversity following shifting cultivation in the upland Philippines (oral
presentation), ATBC 2014 - the future of tropical biology and conservation, 20-24 July 2014,
Cairns.
Mukul, S.A., Herbohn, J. (2013) The future of reforestation programs in the tropical developing
countries: insights from the Philippines, (oral presentation), American Geophysical Union
Fall Meeting, 9-13 December 2013, San Francisco, USA.
Mukul, S.A., Gregorio, N., Baynes, J., Herbohn, J. (2013) The future of reforestation programs in
tropical developing countries: insights from the Philippines, (oral presentation), The Australia
New Zealand Society for Ecological Economics (ANZSEE) Conference: opportunities for the
critical decade, enhancing well-being within planetary boundaries, 11-14 November 2013,
Canberra.
Mukul, S.A., Rashid, A.Z.M.M., Uddin, M.B., Herbohn, J. (2013) Efficacy of forest law
enforcement and incentive based conservation to prevent illegal logging in developing
countries: experience from Bangladesh, (oral presentation), Earth System Governance Tokyo
Conference: complex architectures, multiple agents, 28-31 January 2013, Tokyo, Japan.
Mukul, S.A., Herbohn, J. (2012) Linking ethics, ecology and the economics in land-use decisions:
towards and integrated approach for global sustainability, (oral presentation), World
Conference on Natural Resource Modelling, 9-12 July 2012, Brisbane.
Mukul, S.A., Byg, A. (2012) Swidden cultivation in the central hills of Nepal: local perceptions
and factors affecting change, (poster presentation), Planet under Pressure – new knowledge
towards solutions, 26-29 March 2012, London, UK.
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Publications included in this thesis
I have chosen to incorporate five publications into my thesis as per UQ policy (PPL 4.60.07
Alternative Thesis Format Options). This section details each publication, where it appears in the
thesis and contributions to the authorship as per the requirements in the UQ Authorship Policy (PPL
4.20.04 Authorship).
Mukul, S.A., Herbohn, J. (2016) The impacts of shifting cultivation on secondary forests dynamics
in tropics: a synthesis of the key findings and spatio temporal distribution of research.
Environmental Science & Policy 55: 167-177.
– incorporated as Chapter 2.
Contributor Statement of contribution
Author SA Mukul (Candidate) Conceptualised the framework (90%), and wrote
and edited the paper (80%)
Author J Herbohn Conceptualised the framework (10%), and wrote
and edited the paper (20%)
Mukul, S.A., Herbohn, J., Firn, J. (in review) High resilience of tropical forest diversity and
structure after shifting cultivation in the Philippines uplands. Applied Vegetation Science.
– incorporated as Chapter 3.
Contributor Statement of contribution
Author SA Mukul (Candidate) Conceptualised the study (90%), designed and
conducted the fieldwork (100%), wrote and
edited the paper (80%)
Author J Herbohn Conceptualised the framework (5%), and wrote
and edited the paper (10%)
Author J Firn Conceptualised the framework (5%), and wrote
and edited the paper (10%)
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Mukul, S.A., Herbohn, J., Firn, J. (2016) Tropical secondary forests regenerating after shifting
cultivation in the Philippines uplands are important carbon sinks. Scientific Reports 6: 22483.
– incorporated as Chapter 4.
Contributor Statement of contribution
Author SA Mukul (Candidate) Conceptualised the study (90%), designed and
conducted the fieldwork (100%), wrote and
edited the paper (80%)
Author J Herbohn Conceptualised the framework (5%), and wrote
and edited the paper (10%)
Author J Firn Conceptualised the framework (5%), and wrote
and edited the paper (10%)
Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. (in review) Soil carbon and nutrients
status in relation to shifting cultivation in regenerating secondary forests in the Philippines uplands.
Land Degradation & Development.
– incorporated as Chapter 5.
Contributor Statement of contribution
Author SA Mukul (Candidate) Conceptualised the framework (90%), study
design and analyse (100%), wrote and edited the
paper (80%)
Author J Herbohn Conceptualised the framework (5%), and wrote
and edited the paper (5%)
Author J Firn Conceptualised the framework (5%), and wrote
and edited the paper (5%)
Author A Almendras-Ferraren Wrote and edited the paper (5%)
Author R Congdon Wrote and edited the paper (5%)
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Mukul, S.A., Herbohn, J., Firn, J. (in press) Co-benefits of biodiversity and carbon from
regenerating secondary forests in the Philippines uplands: Implications for forest landscape
restoration. Biotropica.
– incorporated as Chapter 6.
Contributor Statement of contribution
Author SA Mukul (Candidate) Conceptualised the framework (90%), study
design and analyse (90%), wrote and edited the
paper (80%)
Author J Herbohn Conceptualised the framework (5%), study
design and analyse (10%), and wrote and edited
the paper (10%)
Author J Firn Conceptualised the framework (5%), and wrote
and edited the paper (10%)
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Contributions by others to the thesis
Along with my principal supervisor Professor John Herbohn and co-supervisor Associate Professor
Jennifer Firn, Professor Angela Ferraren and Dr Robert Congdon provided inputs in the Chapter 6.
Dr Jefferson Fox provided thoughtful comments on an earlier draft of the Chapter 2, and Professors
Robin Chazdon and David Lamb provided comments on earlier drafts of the Chapter 3 and 4 of this
thesis.
Chapter 1and 7, the overall thesis introduction and overall conclusion, were written by myself with
editorial input from my principal supervisor, Professor John Herbohn.
All other significant contribution and inputs by others are provided above for each published,
accepted and submitted papers that are currently under consideration for publication.
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Statement of parts of the thesis submitted to qualify for the award of another degree
None.
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Acknowledgements
I am very much grateful to my principal advisor, Professor John Herbohn (UQ/USC) and co-
advisor, Associate Professor Jennifer Firn (QUT) for their valuable guidance, feedback and
suggestions which made this work possible. I would also like to thank Drs Nestor Gregorio (USC),
Arturo Pasa (VSU) and VSU-ACIAR field staffs in the Philippines, particularly – Nayar Adanarg,
Val Solano, Jun Ray and Cris Solano for their heartiest cooperation during my fieldwork in the
Philippines. Thanks also due to Professors Angela Ferraen (VSU) and Robert Congdon (JCU) for
the lab facility in the Philippines, and Ofelia Manarnguit, Jertz Escala for assistance in laboratory
analysis. The valuable suggestions and feedback provided by Professors Robin Chazdon (UConn),
David Lamb (UQ/USC), L.A. Bruinjeel (VU Amsterdam), Susanne Schimdt (UQ), Vera Lex Engel
(UNESP), Stephen Harrison (UQ/USC), Jerry Vanclay (SCU), Associate Professors Wolfram
Dressler (U Melbourne), Drs Jefferson Fox (EWC), Jack Baynes (USC), Paul Dargusch (UQ), John
Meadows (USC) at different stages of this project was very helpful.
During my several visits and stay in the Philippines from 2012 (June) and 2013 (February,
June-October) several co-workers, including – Jun Zhang, Jarrah Wills and Chloe Gudmundsson
who were working at the same time for their graduate projects made my stay and work there very
enjoyable, together with other VSU-ACIAR project staffs – Ian Kim Gahoy, Mayet Avela, Rogelio
Tripoli, Nova Parcia and Jufamar Fernandez. Thanks also to Shawkat Sohel for his help in part of
thesis formatting.
Throughout my doctoral training and study period at UQ my parents and younger brother
inspired and motivated me a lot to reach my desired destination.
This work is being made possible by a scholarship support (International Postgraduate
Research Scholarship) from the Australian Government, with additional funding towards field
activity from the Australian Centre for International Agricultural Research (ACIAR-
ASEM/2010/50).
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Dedication
This thesis is dedicated to the memory of my father Mostaque Ahmed (1955-2016) who left
us on January 17, 2016.
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Keywords
tropical forest, kaingin, deforestation, biodiversity conservation, forest carbon stock, land-use
change, REDD+, reforestation, Southeast Asia
Australian and New Zealand Standard Research Classifications (ANZSRC)
ANZSRC code: 050205, Environmental Management, 60%
ANZSRC code: 050209, Natural Resource Management, 20%
ANZSRC code: 070504, Forestry Management and Environment, 20%
Fields of Research (FoR) Classification
FoR code: 0502, Environmental Science and Management, 90%
FoR code: 1605, Policy and Administration, 10%
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Table of Contents
Chapter 1. Introduction 1
1.1 Background 1
1.2 Research problem and the research questions 3
1.3 Justification of this research 6
1.4 Methodology 8
1.5 Limitations and challenges 10
1.6 Overview of this thesis 10
1.7 References 11
Chapter 2. The impacts of shifting cultivation on secondary forests dynamics in tropics:
a synthesis of the key findings and spatio temporal distribution of research
16
2.1 Abstract 16
2.2 Introduction 17
2.3 Methodology 18
2.3.1 Document search for systematic map 18
2.3.2 Document characterization 19
2.3.3 Document selection for meta-analysis 19
2.3.4 Data interpretation and analysis 20
2.4 Results and discussions 20
2.4.1 Spatio-temporal dynamics of research on shifting cultivation 20
i. Spatial distribution of research on shifting cultivation 20
ii. Temporal pattern of research on shifting cultivation 22
2.4.2 Impacts of shifting cultivation on tropical forest dynamics 22
i. Plant ecology 26
ii. Conservation biology 27
iii. Soil nutrients and chemistry 28
iv. Soil physics and hydrology 29
2.5 Conclusions 29
2.6 Additional information 30
2.7 References 30
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Chapter 3. High resilience of tropical forest diversity and structure after shifting
cultivation in the Philippines uplands
43
3.1 Abstract 43
3.2 Introduction 43
3.3 Materials and methods 45
3.3.1 Study area 45
3.3.2 Site selection criteria 47
3.3.3 Sampling protocol and vegetation survey 47
3.3.4 Site environmental parameters
3.3.5 Diversity and forest structure indices
48
49
3.3.6 Species composition and similarities 49
3.3.7 Recovery of tree species diversity and forest structure 50
3.3.8 Data analysis 50
3.4 Results 51
3.4.1 Species and characteristics 51
3.4.2 Biodiversity and forest structure in regenerating secondary forests 52
3.4.3 Species composition in regenerating secondary forests after shifting cultivation 53
3.4.4 Tree diversity and forest structure recovery along a shifting cultivation fallow
gradient
55
3.4.5 Environmental controls on the recovery of secondary forest diversity and structure 56
3.5 Discussion 58
3.5.1 Biodiversity conservation and secondary forest development after shifting
cultivation
58
3.5.2 Controls of site environmental conditions in forest recovery after shifting cultivation 60
3.5.3 Implications for conservation and forest landscape management 61
3.6 Conclusions 61
3.7 Additional information 62
3.8 References 62
Chapter 4. Tropical secondary forests regenerating after shifting cultivation in the
Philippines uplands are important carbon sinks
76
4.1 Abstract 76
4.2 Introduction 76
4.3 Methods 78
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4.3.1 Study area 78
4.3.2 Site selection 79
4.3.3 Biomass inventory 80
4.3.4 Biomass calculation in forest ecosystems 81
4.3.5 Estimating carbon in aboveground forest biomass 82
4.3.6 Estimating the recovery of biomass carbon in forests 83
4.3.7 Statistical analysis 83
4.4 Results 84
4.4.1 Distribution of biomass carbon in fallow secondary forests 84
4.4.2 Recovery of biomass carbon in fallow secondary forests 88
4.4.3 Factors influencing the recovery of aboveground biomass carbon in fallow secondary
forests
89
4.5 Discussion 91
4.5.1 Biomass carbon distribution in tropical fallow secondary forests 91
4.5.2 Factors influencing the biomass carbon recovery in fallow secondary forests 92
4.5.3 Forest management and landscape restoration implications 94
4.6 Conclusions 94
4.7 Additional information 95
4.8 References 95
Chapter 5. Soil carbon and nutrients status in relation to shifting cultivation in
regenerating secondary forests in the Philippines uplands
102
5.1 Abstract 102
5.2 Introduction 102
5.3 Materials and methods 104
5.3.1 Study location 104
5.3.2 Site selection and characteristics 104
5.3.3 Soil sample collection 106
5.3.4 Soil sample processing 105
5.3.5 Statistical analysis 107
5.4 Results 108
5.4.1 Soil carbon and nutrients concentrations across a fallow gradient 108
5.4.2 Availability of soil carbon and nutrients along a fallow age gradient 110
5.4.3 Environmental controls on soil carbon and nutrients in fallow sites 112
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5.5 Discussion
5.5.1 Variability in soil carbon and nutrients in fallow secondary forests
5.5.2 Influence of site environmental factors on soil carbon and nutrients
114
114
114
5.6 Conclusions 115
5.7 Additional information 116
5.8 References 116
Chapter 6. Co-benefits of biodiversity and carbon from regenerating secondary forests
in the Philippines uplands: implications for forest landscape restoration
123
6.1 Abstract 123
6.2 Introduction 123
6.3 Methods
6.3.1 Background of the area
6.3.2 Study site selection
6.3.3 Data collection
6.3.4 Data interpretation and analysis
125
125
127
127
127
6.4 Results 128
6.4.1 Biodiversity and carbon co-benefits from regenerating secondary forests 128
6.4.2 Biodiversity and carbon trade-offs in the upland land-use of Philippines 129
6.5 Discussion and implications 130
6.6 References 132
Chapter 7. General conclusions 138
7.1 The context 138
7.2 A synthesis of the impacts of shifting cultivation on tropical forests dynamics 138
7.3 The impact of shifting cultivation on biodiversity, species composition and forest
structure
139
7.4 Aboveground biomass carbon dynamics in regenerating tropical secondary forests 139
7.5 Soil carbon and nutrients in regenerating secondary forests after shifting cultivation 140
7.6 Opportunities for biodiversity and carbon benefits from fallow secondary forests 140
7.7 Implications of this research 140
7.8 References 141
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Annexes
Annex 2.1. Summary of studies used in meta-analysis on impacts of shifting cultivation on
forest dynamics.
39
Annex 3.1. List of tree species recorded from the sites in Gaas on Leyte Island, the
Philippines.
71
Annex 4.1. Summary of aboveground biomass carbon distribution in our study sites on
Leyte Island, the Philippines.
101
Appendices
143
Supplmentary Figure 2.1. Country-wise distribution of research on shifting cultivation. 143
Supplementary Table 3.1. Different measures for diversity and forest structure used in
the present study.
144
Supplementary Table 3.2. Pearson correlation between site environmental attributes. 145
Supplementary Figure 3.1. Importance value of species across the sites of different
fallow categories and in control old-growth forest.
146
Supplementary Figure 3.2. nMDS of richness and abundance of species of global
conservation concern using Bray-Curtis distance.
147
Supplementary Figure 3.3. nMDS of richness and abundance of species of local
conservation concern using Bray-Curtis distance.
148
Supplementary Table 4.1. Site environmental attributes. 149
Supplementary Table 4.2. Wood density and characteristics of species recorded from the
sites on Leyte Island, the Philippines.
150
Supplementary Table 4.3. Organic carbon contents in litter and undergrowth samples
from the study sites on Leyte island, the Philippines.
154
Supplementary Table 4.4. Organic carbon contents in dead wood samples from the study
sites in Leyte Island, the Philippines.
155
Supplementary Table 4.5. Pearson correlation between site environmental attributes. 156
Supplementary Table 4.6. Biomass carbon distribution in living woody species in our
study sites on Leyte island, the Philippines.
157
Supplementary Figure 4.1. Relative contribution of living stems of different diameter
class in living woody biomass carbon (LWBC).
162
Supplementary Figure 4.2. Relative contribution of living stems of different height class
in living woody biomass carbon (LWBC).
163
Supplementary Table 5.1. Pearson’s correlation between site environmental attributes. 164
xxii
Supplementary Figure 5.1. Percentage concentrations of soil organic carbon and soil
nutrients on Leyte Island, the Philippines.
165
xxiii
List of Figures
Figure 1.1. Conceptual framework of this thesis project.
4
Figure 1.2. The background, importance and potential implications of this project. 7
Figure 1.3. Outline of the chapters in this thesis. 11
Figure 2.1. Summary of literature used for systematic map and meta-analysis. 21
Figure 2.2. Geographical distribution of the studies on shifting cultivation by country. 23
Figure 2.3. Temporal changes in research focus between 1950-2014. 24
Figure 2.4. Reported effect of shifting cultivation on (a) major forest characteristics; (b)
selected wildlife selected taxa, (c) major soil nutrients and (d) soil physical and hydraulic
properties.
25
Figure 3.1. Map showing location of the study area on Leyte Island, and the study sites
plotted in a Google Earth map showing the location of the 25 sites.
46
Figure 3.2. Distribution and characteristics of species in different fallow categories and in
old-growth forest on Leyte Island, the Philippines.
Figure 3.3. Within and between variations of tree diversity and forest structure indices across
the sites on Leyte Island, the Philippines.
51
52
Figure 3.4. nMDS of species richness and abundance using Bray-Curtis distance. 55
Figure 3.5. Recovery of tree diversity and forest structure in relation to old-growth forest on
Leyte Island, the Philippines.
56
Figure 4.1. Map of the Philippines, with location map of Barangay Gaas on Leyte Island and
our study sites in Gaas.
Figure 4.2. Distribution of aboveground biomass carbon in our study sites on Leyte Island,
the Philippines.
79
85
Figure 4.3. Relative contribution of different source to the total aboveground biomass carbon
stock in our sites on Leyte Island, the Philippines.
86
Figure 4.4. Relative importance of different successional species groups in living woody
biomass carbon (LWBC); and species of different origin in LWBC.
87
Figure 4.5. Relative importance of coarse dead wood of different stand form in coarse dead
wood biomass carbon (CDWBC); and dead woods of different degradation status in CDWBC.
87
Figure 4.6. Distribution of aboveground biomass carbon in fallow secondary forest sites in
relation to the old-growth forests on Leyte Island, the Philippines.
89
Figure 5.1. Location map of the study area on Leyte Island, and the study sites plotted on a 105
xxiv
Google earthTM map.
Figure 5.2. The relative contribution of soil organic carbon and nutrients at different soil
depths in our sites on Leyte Island, the Philippines.
110
Figure 5.3. Soil carbon and nutrients in relation to control old-growth forests at our study
sites on Leyte Island, the Philippines.
111
Figure 6.1. Major land-use/land-cover in the Philippines with the location of Leyte Island
indicated, and some common land-use in the upland areas after shifting cultivation use.
125
Figure 6.2. Tree biodiversity in regenerating forest after shifting cultivation in the Philippines
uplands.
Figure 6.3. Above ground biomass carbon in regenerating forest following shifting
cultivation in the upland Philippines.
128
128
xxv
List of Tables
Table 1.1. Summary of the samples and measurements taken from the study sites in the
Philippines.
8
Table 1.2. Research matrix used for this project. 9
Table 2.1. Example of documents under different subject focus. 19
Table 3.1. Environmental attributes of our fallow sites and old-growth forest on Leyte Island,
the Philippines.
49
Table 3.2. Top ten species with highest importance value in sites of different fallow
categories and in old-growth forest on Leyte Island, the Philippines.
53
Table 3.3. Summary of mixed effect models obtained using package MuMin. 57
Table 3.4. The relative importance of site environmental attributes in the final LMEM. 58
Table 4.1. Summary of LMEM between site biomass recovery with environmental attributes
obtained using the package MuMin.
90
Table 4.2. The relative importance of site environmental attributes in the final LMEM. 90
Table 5.1. Environmental attributes of the study sites on Leyte Island, the Philippines. 106
Table 5.2. Concentrations of soil organic carbon and nutrients across the sites of different
fallow categories and old-growth forest on Leyte Island, the Philippines.
109
Table 5.3. Summary of LMEM between soil carbon and nutrient recovery with
environmental attributes obtained using the package.
112
Table 5.4. The relative importance of site environmental attributes in the final LMEM. 113
Table 6.1. Biodiversity and aboveground carbon stocks in common upland land-cover/use in
the Philippines uplands.
131
xxvi
List of Abbreviations
AGB Aboveground Biomass
CBNRM Community Based Natural Resource Management
CDM Clean Development Mechanism
DENR Department of Environment and Natural Resources
IPCC Intergovernmental Panel on Climate Change
IUCN International Union for Conservation of Nature
NGP National Greening Program
REDD+ Reducing Emissions from Deforestation and Forest Degradation
SOC Soil Organic Carbon
1
CHAPTER 1: INTRODUCTION
1.1 Background
Tropical forests provide services that are essential for society and human wellbeing,
including biodiversity, timber, water, and carbon sequestration (Lewis et al., 2015). The future
capability of forests to provide these ecosystem services is determined by changes in land-use,
socio-economic context, biodiversity and climate (Trumbore et al., 2015; Malhi et al., 2014;
Metzger et al., 2006). In tropical secondary forests, shifting cultivation, also termed as swidden or
slash-and-burn agriculture, is one of the dominant land-uses in upland areas, and has long been
considered as one of the main drivers of deforestation and forest degradation (Ziegler et al., 2011;
Mertz et al., 2009; Fox et al., 2000). Shifting cultivation was the dominant form of agriculture in
most tropical areas until the end of the 20th
century, when the political and economic integration at
many geographic locations promoted more intensive agriculture (Lawrence et al., 2010; Fox et al.,
2009). A large proportion of tropical secondary forests have been subjected to shifting cultivation
(Angelsen, 1995), and in many parts of the tropics this practice is now evolving into other more
intensive land-uses like rubber, oil palm plantations and sedentary agriculture etc. (see Mukul and
Herbohn, 2016; Fox et al., 2014; van Vliet et al., 2012; Padoch et al., 2007; Mertz et al., 2009). In
recent years, while shifting cultivation has declined, in many developing countries, it still remains a
major means of livelihoods and food security of poorest people living in rural remote landscapes
(Parrota et al., 2012; van Vliet et al., 2012; Cramb et al., 2009).
Shifting cultivation typically involves the clearing of the forest by a combination of cutting and
subsequent burning of vegetation; the cleared area is then used for cultivation of agricultural crops
which was formerly forested land for two to three years (Cairns, 2015). Shifting cultivation farmers
then move to another piece of land allowing former land a fallow period to regenerate naturally
(Fox et al., 2000). In mountainous areas in many countries of mainland Southeast Asia, shifting
cultivation system is still essential for livelihoods and food security (Ziegler et al., 2012; Brunn et
al., 2009). Without sufficient empirically based evidence, for decades policy makers and some
scientists have believed that shifting cultivation is environmentally unsustainable and one of the
major reasons of land degradation (Mertz et al., 2012, 2009; Ziegler et al., 2011; Bruun et al., 2009;
Fox et al., 2009).
The Philippines have experienced one of the highest rates of deforestation in Southeast Asia (Lasco
and Pullhin, 2009; Chokkalingam et al., 2006). The Philippines is also one of the first countries to
2
introduce massive reforestation programs to restore its degraded forests, landscapes and associated
environmental parameters in upland areas (Chokkalingam et al., 2006). The country is one of the
‘hottest of the biodiversity hotspots’, endowed with a vast variety of endemic flora and fauna, many
of which are currently under different level of threats (Sodhi et al., 2010; Suarez and Sajise, 2010;
Posa et al., 2008). Until the early colonizers arrived in the country in the 16th
century, about 90
percent of the Philippines were covered with dipterocarp rich rainforests, which have now reduced
to less than 24 percent (Lasco and Pullhin, 2000). Characteristically, upland rural areas in the
Philippines are less developed, inhabited by smallholder poor farmers who rely on neighbouring
forests for sustaining livelihoods (Herbohn et al., 2014; Le et al., 2014). The majority of the
smallholder farmers in rural, remote upland areas practice shifting cultivation, locally termed as
kaingin (Lawrence, 1997; Kummer, 1992). Since the Spanish colonial period (i.e. AD1565-AD
1898) major forestry policies in the Philippines tried to impose restriction on this land use practice,
assuming a negative impact on upland forests and environment (Suarez and Sajise, 2010). Major
reforestation projects in the Philippines also ignored this major land-use, with still very limited
understanding the consequences of kaingin on the local environment (Suarez and Sajise, 2010). In
upland areas, smallholder kaingin farmers are also vulnerable to environmental changes due to their
dependence on forests with very limited access to other natural resources, and kaingin will continue
to form an important land-use in the country until greater access to state regulated forestry and other
land-use programs, and economic development will take place (Mukul and Herbohn, 2013;
Harrison et al., 2004).
Lack of knowledge on biodiversity and biomass carbon and their recovery in shifting cultivation
landscapes is one of the major constraints to incorporating this land-use in global voluntary carbon
markets under REDD+ (Reducing Emissions from Deforestation and Forest Degradation) and CDM
(Clean Development Mechanism) (Parrota et al., 2012; Mertz et al., 2012, Mertz, 2009; Ziegler et
al., 2012). Recently, Martin et al. (2013) and Bonner et al. (2013) in their meta-analyses found that
secondary forests after disturbances can act as a low-cost measure for conserving biodiversity and
forest biomass carbon and hold great potentials for tropical forest restoration. In the Philippines,
post-kaingin secondary forests, due to their vast area also have the potentials for carbon /
biodiversity offset projects under REDD+ and CDM, and to attract funds to protect and conserve
country’s forests with greater community involvement (Lasco and Pulhin, 2003; Lasco et al., 2001).
Such project and activities however require better understanding of the biodiversity and carbon
dynamics associated with related land-use(s) (Budiharta et al., 2014; Niels et al., 2002).
3
In case of the shifting cultivation there has been a great variability among findings from studies
focusing on ecology and successional development of forests, with studies finding different fallow
lengths are required for forest to return its earlier condition, with also different level of impacts on
forests and related environmental parameters (Mukul and Herbohn, 2016; Bruun et al., 2009).
Against theses backdrops, my thesis sheds light on secondary forest dynamics after shifting
cultivation in the Philippines uplands, with this research having important implications for land-use
policy and development in the country.
1.2 Research problem and the research questions
I hypothesized that secondary forests after shifting cultivation involves major trade-offs in
biodiversity and carbon storage when considering potential competing land-uses like natural
regeneration, reforestation (native vs. exotic, single vs. mixed species, etc.), invasion by grasslands
or conversion to sedentary agricultural field. The conceptual framework of this hypothesis is
outlined in Figure 1.1. In my thesis I only considered natural regeneration due to time constraints.
To test the hypothesis and to address the existing gaps and inconsistency in research findings (on
shifting cultivation) the following research problem was developed.
Since shifting cultivation is not only a dominant land-use in the tropics, but also a survival strategy
for millions of marginal and rural people dwelling in either upland hilly or mountainous areas (van
Vliet et al., 2012), the research problem has implications not only in the Philippines but in other
developing countries where shifting cultivation is common. Again, in the upland Philippines, a
large-scale donor funded reforestation programs known as – National Greening Program (NGP)
currently being implemented, which has the objective to restore 1.5 million hectares of degraded
upland forests by 2016 (Le et al., 2014).
Understanding biodiversity and carbon stock and any recognized pattern in recovery after kaingin is
important to realize any opportunities the large amount of secondary forests in the upland areas may
Research problem:
To what extent do tree diversity, species composition, forest structure, biomass carbon and
soil nutrients recover following shifting cultivation, and what are the implications for land-
use policy development?
4
Figure 1.1. Conceptual framework of this thesis project.
Traditional Shifting Cultivation
Slash-and-burn/
Forest degradation
Fallow Land
Secondary Forest Grass Land Agricultural Crop Field Planted Forest
Disturbance/
Invasion Natural
succession
Reforestation/ Restoration
Settlement
Biodiversity / Carbon Trade-offs
Bio
div
ersi
ty /
Carb
on
Loss
Long fallow period Fallow cycle
Intensive Shifting Cultivation
Fallow Land
Short fallow period Fallow cycle
Features
*Remote area
*Indigenous communities
*Low population pressure
*Emigration for better livelihood
Features
*Proper area/closer to road networks
*Immigration/Migrants from lowlands
*High population pressure
*Land scarcity
Whole landscape
Intact forest
Disturbed forest patches Degraded landscape/forests
Intact forest patches
Primary Forest
5
have for REDD+ or other CDM, which may also complement or boost the current NGP or any other
projects in the future on upland secondary forests.
Other than the literature review, synthesis and gap analysis that comprise the second chapter of this
thesis, four research questions were constructed to address the research problem stated above. The
first research question aimed to examine the conservation value of secondary forests regenerating
after shifting cultivation in the Philippines upland.
General background and context of this research question is discussed in later part of this thesis.
The second research question investigated the aboveground carbon stock in secondary forests
regenerating after shifting cultivation and the patterns and determinants of biomass recovery.
The third research question concerned with soil carbon and nutrients in relation to kaingin land-use
and to see how these may recover in regenerating secondary forests. The question was:
For research question 4, I performed a biodiversity and carbon trade-off analysis using data from
this study and information available from literatures on biodiversity and carbon dynamics in other
land-use(s) that may replace fallow areas after kaingin in the upland Philippines. The study has
implications for land-use policy, forest restoration and community development through REDD+
and other possible CDM projects in the Philippines uplands.
Research question 1:
To what extent regenerating kaingin fallow forests complement the old-growth forest in
terms of biodiversity and forest structure?
Research question 2:
What are the aboveground carbon stocks in secondary forests after shifting cultivation, and
how is biomass carbon is allocated in different forest biomass components?
Research question 3:
What is the status of soil carbon and nutrients in regenerating secondary forests after
kaingin, and how do different environmental attributes affect soil carbon and nutrients
recovery?
6
1.3 Justification of this research
This study provides a better understanding of the biodiversity, aboveground forest biomass
carbon, soil carbon and nutrient stocks in fallow forests and their recovery in relation to old-growth
forests that never been used for shifting cultivation or logging. These are important for forest
management, restoration and conservation not only in the Philippines but in other countries where
shifting cultivation is common.
Forest structure and composition in the tropics change persistently as a result of human use,
disturbances, and as a natural pathway of succession (Chazdon, 2014, 2003; Gardner et al., 2009).
In tropical regions, secondary forests formed following shifting cultivation and other disturbances
are rapidly becoming a dominant forest type (Chazdon, 2014; Chokkalingam and Perera, 2001;
Hughes et al., 1999). Although controversial, shifting cultivation is still a dominant land-use in the
tropical forest-agriculture frontier (van Vliet et al., 2012; Piotto et al., 2009). Lack of reliable
information regarding biodiversity and carbon dynamics associated with shifting cultivation land-
use is however hindering its inclusion in ongoing REDD+ and CDM negotiations (Mertz et al.,
2012; Ziegler et al., 2012). It is however clear that in tropical region regenerating secondary forests
after shifting is important carbon sinks (Mukul et al., 2016).
In the Philippines, shifting cultivation is blamed for majority of country’s deforestation, in the
upland areas (Kummer, 1992) with limited ecological studies (see Kellman, 1970). In most of the
previous and ongoing reforestation programs (e.g. NGP) this traditional land-use, however, has
simply been overlooked without any further attempt to understand the ecological and/or socio-
economic dimensions associated with it. The current study will provide information to help explain
some of the important aspects of this ‘black-box’, and the findings have potential application by
policy makers and reforestation agencies to better recognize this land-use. Figure 1.2 below
summarizes the background, importance and implications of this thesis project.
Research question 4:
What is the possible ecosystem service benefits and trade-offs associated with regenerating
secondary forests after kaingin when compared with other competing land-use(s), and what
implications it has on land-use and policy development in the Philippines?
7
Figure 1.2. The background, importance and potential implications of this project.
CONTEXT
Socio-economic and policy related 1. a common upland land-use practice;
2. connected to food-security;
3. controversial land-use/ sustainability;
4. with potentials for REDD+/carbon forestry
Scientific 1. biomass and carbon recovery issues;
2. suitable fallow length/cycles;
APPROACHES 1. empirical evidence from a case study area;
2. vegetation survey for biodiversity, above
ground biomass and carbon;
3. soil samples and below ground organic
carbon
OUTCOMES 1. state of art and knowledge about one of the
most common land-use in the upland
Philippines;
2. biomass and carbon stocks in relation to
land- use history/ intensity of use;
3. recovery of biomass and carbon stock in
relation to land- use history and intensity
IMPLICAIONS
Scientific 5. knowledge on biomass and carbon stock in fallow
kaingin/shifting cultivation areas in upland Philippines;
6. recovery rate of biomass and carbon after severe
disturbance by kaingin practice;
7. determining an optimal fallow length;
Policy related 1. framing policy based on field evidence;
2. scenario-development/comparison with existing plantation
focused forestry;
3. search for potential carbon-forestry/reward packages to
ensure long term sustainability and financing of upland
development programs.
8
1.4 Methodology
This thesis is based on an empirical study from Leyte Island, Visayas region, the
Philippines. Vegetation survey, biomass inventory and soil sampling was undertaken in post-
kaingin secondary forests and in old-growth forests with no prior history of kaingin use. Altogether
100 transects (50 m x 5 m size) established in 25 sites belonging to four fallow categories (e.g.
fallow for less than 5 years, fallow between 6-10 years, fallow between 11-20 years, 21-30 years
old fallow) and control old-growth forest sites was used. Table 1.1 shows the samples and/or
measurements taken from each site/transects other than site environmental information (e.g.
elevation, slope, leaf area index, distance from nearest control forest site etc.) collected during this
doctoral thesis project. Table1.2 presents the research matrix with brief summary of methodology
against each research objective/question. Further details of the area, methodology and instruments
used for sample collection and analysis are described in the following chapters of this thesis.
Table 1.1. Summary of the samples and measurements taken from the study sites in the Philippines.
Sample/Item Number (N) Measurement/Analysis/Data Remark
Standing live tree 2918 dbh, height, species identity (≥5 cm dbh)
Tree fern 184 dbh, height
Abaca (Musa textilis) 124
Dead tree 1281 dbh, height/length, degradation
status
(≥5 cm dbh)
Tree wood core sample 844 Wood density Not used here
Dead wood sample 20
(4 category x 5
replicates)
Organic Carbon (OC %)
Undergrowth biomass
sample (fresh)
100 Dry biomass
Organic Carbon (OC %)
Litter and woody debris
sample
100 Dry biomass
Organic Carbon (OC %)
Soil core sample (5 cm3)
(3 soil depth – 0-5 cm, 6-
15 cm, 16-30 cm);
(3 transect position –
outer edge, centre, inner
edge)
900
(3 position x 3
depth x 100
transect)
Soil Organic Carbon (SOC)
Soil Nitrogen (N)
Soil Phosphorus (P)
Soil Potassium (K)
Fine root biomass and OC%
Soil pH
Soil moisture content
Soil bulk density
Incomplete
(samples are
being
processed)
9
Table 1.2. Research matrix used for this project.
Specific objective Research question Data required Data collection method
To measure tree diversity
and forest structure in
fallow shifting cultivation
landscape
To what extent regenerating kaingin
fallow forests complement old-growth
forest in terms of biodiversity and forest
structure?
- tree (≥5 cm) dbh;
- tree (≥5 cm) height;
- tree (≥5 cm) identity;
- site characters;
- site leaf area index
Vegetation survey in 25 sites
covering 100 transects in both
fallow shifting cultivation area
and in control old-growth forest.
To measure aboveground
biomass carbon stocks in
fallow shifting cultivation
area and in control old-
growth forest.
What are the aboveground carbon stocks
in regenerating secondary forests after
shifting cultivation, and how is biomass
carbon is allocated in different forest
biomass components?
- live tree (≥5 cm) dbh and height;
- dead tree (≥5 cm)
dbh/circumference and
height/length; wood samples;
- dbh and height of tree ferns and
Abaca (≥5 cm);
- undergrowths, leaf litter and
woody debris biomass;
Biomass inventory and
application of appropriate
allometric models.
To understand the status of
soil carbon and nutrients in
relation to shifting
cultivation in regenerating
secondary forests.
What is the status of soil carbon and
nutrients in regenerating secondary
forests after kaingin, and how do
different environmental attributes affect
the recovery of soil carbon and
nutrients?
- soil organic carbon;
- soil nitrogen;
- soil phosphorus;
- soil potassium;
- site characteristics;
Soil sample collection from
different depths and laboratory
analysis in VSU-ACIAR
Analytical Chemistry Laboratory.
To understand the potential
biodiversity and carbon
trade-offs associated with
regenerating forests after
shifting cultivation and
other possible land-uses.
What is the possible ecosystem service
benefits and trade-offs associated with
regenerating secondary forests after
kaingin when compared with other
competing land-use(s), and what
implications it has on land-use and
policy development?
- land-use type;
- tree biodiversity;
- aboveground carbon stock;
- carbon sequestration potential.
Primary and secondary data from
present project and available
secondary data from peer-
reviewed publications.
10
1.5 Limitations and challenges
Against the hypothesis presented in the Figure 1.1, this project was limited to only the
traditional less intensive shifting cultivation landscapes that represent the general shifting
cultivation systems common in much of the tropics. Time and resources limited the extension of the
study to include other land-use(s) that may also replace shifting cultivation area. A major challenge
was to adjust to a new environment and get acquainted with local culture and systems. Security
issues related to unauthorized militant groups in the upland area also influenced my study at least
once. Heavy rainfall and extreme weather also restricted my access to the study sites on several
occasions. Since shifting cultivation still an unrecognised land-use in the Philippines, it was
difficult to get the trust of the local smallholders and landowners regarding land-use and history.
Species identification was another challenge but greatly facilitated by local botanists. The enormity
of the field samples and the subsequent processing and analysis was challenging. The analysis of
samples was further affected by typhoon Haiyan which devastated the Leyte Island in November
2013, the area where I worked and based at until October 2013. Visayas State University (VSU),
where my samples were stored was severely damaged and lost power for over 3 months, and the
laboratory (VSU-ACIAR Analytical Chemistry Laboratory) where my samples were being
analaysed was out of operation for more than four months. This resulted in a substantial delay in the
analysis of my soil and plant samples. Finally, due to time limitations it was also not possible to
analyse and use some of the field data that I collected (e.g. own wood density data, fine root
biomass etc.), and include few others manuscripts from this project that are currently on the very
early stage of development.
1.6 Overview of this thesis
This thesis comprises 7 chapters. Throughout this thesis kaingin and shifting cultivation has
been used simultaneously and synonymously. Chapter 2 is a synthesis that reports, spatial and
temporal distribution of previous research on shifting cultivation using a systematic literature search
protocol, and the key findings of research on some of the selected aspects. Chapter 3 reports a
vegetation survey where tree diversity, species composition and forest structure and their recovery
in secondary forests after shifting cultivation was investigated along a fallow/shifting cultivation
land-use gradient. In Chapter 4, the distribution and recovery of biomass carbon along a fallow
gradient were reported. In Chapter 5, the status of soil organic carbon, nitrogen, phosphorus and
potassium in relation to shifting cultivation land-use and their recovery of were investigated.
Drawing on the previous chapters and present study in Chapter 6, I demonstrate that regenerating
secondary forests following shifting cultivation have the potential for inclusion in programs on
11
forest conservation under REDD+ and CDM. Chapter 7 is the general conclusions. Figure 1.3
below provides the outline of this thesis.
Figure 1.3. Outline of the chapters in this thesis.
1.7 References
Angelsen, A., 1995. Shifting cultivation and “deforestation”: a study from Indonesia. World
Development, 23, 1713-1729.
CHAPTER 1:
General Introduction and background
CHAPTER 4:
Aboveground carbon
Distribution and
recovery of AGB
carbon in the case
study sites, with
environmental and site
factors that influence
the recovery
CHAPTER 3: Biodiversity
Tree species diversity,
composition, forest
structure, and their
recovery along a fallow
age and environmental
gradient.
CHAPTER 5: Soil carbon & nutrients
Soil organic carbon, soil
nitrogen, phosphorus
and potassium
distribution up to 30 cm
soil depth and their
recovery along a fallow
gradient.
CHAPTER 2:
Systematic map and literature synthesis
CHAPTER 6:
Broader study implication using the empirical case study.
CHAPTER 7: General conclusions
Summary conclusions of all the thesis chapters with implications and priorities for
future research.
12
Bonner, M.T.L., Schmidt, S., Shoo, L.P., 2013. A meta-analytical global comparison of
aboveground biomass accumulation between tropical secondary forests and monoculture
plantations. Forest Ecology and Management, 291, 73-86.
Bruun, T.B., de Neergard, A., Lawrence, D., Ziegler, A.D., 2009. Environmental consequences of
the demise in swidden cultivation in Southeast Asia: carbon storage and soil quality. Human
Ecology, 37, 375-388.
Budiharta, S., Meijaard, E., Erskine, P.D., Rondinini, C., Pacifici, M., Wilson, K.A., 2014.
Restoring degraded tropical forests for carbon and biodiversity. Environmental Research
Letters, 9, 114020.
Carins, M.F. (ed.), 2015. Shifting cultivation and environmental change – indigenous people,
agriculture and forest conservation. Earthscan, London.
Chazdon, R.L., 2003. Tropical forest recovery: legacies of human impact and natural disturbances.
Perspectives in Plant Ecology, Evolution and Systematics, 6, 51-71.
Chazdon, R.L., 2014. Second growth: The promise of tropical forest regeneration in an age of
deforestation. University of Chicago Press, Chicago, IL.
Chokkalingam, U., Carandang, A.P., Pulhin, J.M., Lasco, R.D., Peras, R.J.J., Toma, T. (eds), 2006.
One century of forest rehabilitation in the Philippines: Approaches, outcomes and lessons.
Centre for International Forestry Research (CIFOR), Bogor, Indonesia.
Chokkalingam, U.W.U., Perera, G.A.D., 2001. The evolution of swidden fallow secondary forests
in Asia. Journal of Tropical Forest Science, 13, 800–815.
Cramb, R.A., Colfer, C.J.P., Dressler, W., Laungaramsri, P., Le, Q.T., Mulyoutami, E., Peluso,
N.L., Wadley, R.L., 2009. Swidden transformations and rural livelihoods in Southeast Asia.
Human Ecology, 37, 323-346.
Fox, J., Castella, J.C., Ziegler, A.D., 2014. Swidden, rubber and carbon: Can REDD+ work for
people and the environment in Montane Mainland Southeast Asia. Global Environmental
Change, 29, 318-326.
Fox, J., Fujita, Y., Ngidang, D., Peluso, N.L., Potter, L., Sakuntaladewi, N., Sturgeon, J., Thomas,
D., 2009. Policies, political economy and swidden in Southeast Asia. Human Ecology, 37,
305–322.
Fox, J., Truong, D.M., Rambo, A.T., Tuyen, N.P., Cuc, L.T., Leisz, S., 2000. Shifting cultivation: A
new old paradigm for managing tropical forests. BioScience, 50, 521-528.
Gardner, T.A., Barlow, J., Chazdon, R.L., Ewers, R., Harvey, C.A., Peres, C.A., Sodhi, N., 2009.
Prospects for tropical forest biodiversity in a human-modified world. Ecology Letters, 12,
561-582.
13
Harrison, S., Emtage, N.F., Nasayao, E.E., 2004. Past and present forestry support programs in the
Philippines, and lessons for the future. Small-scale Forest Economics, Management and
Policy, 3, 303-317.
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16
CHAPTER 2: THE IMPACTS OF SHIFTING CULTIVATION ON SECONDARY
FORESTS DYNAMICS IN TROPICS: A SYNTHESIS OF THE KEY FINDINGS
AND SPATIO TEMPORAL DISTRIBUTION OF RESEARCH
May cite as – Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary
forests dynamics in tropics: a synthesis of the key findings and spatio temporal distribution of
research. Environmental Science & Policy, 55, 167–177.
2.1 Abstract
Shifting cultivation has been attributed to causing large-scale deforestation and forest degradation in
tropical forest-agriculture frontiers. This view has been embedded in many policy documents in the
tropics, although, there are conflicting views within the literature as to the impacts of shifting
cultivation. In part, this may be due to the complex nature of this land use making generalisations
challenging. Here we provided a systematic map of research conducted on shifting cultivation in the
tropics. We first developed a literature search protocol using ISI Web of Science that identified 401
documents which met the search criteria. The spatial and temporal distribution of research related to
shifting cultivation was mapped according to research focus. We then conducted a meta-analysis of
studies (n = 73) that focused on forest dynamics following shifting cultivation. A bias in research on
anthropology/ human ecology was evident, with most research reported from the tropical Asia
Pacific region (215 studies). Other key research foci were – soil nutrients and chemistry (72
studies), plant ecology (62 studies), agricultural production/ management (57 studies), agroforestry
(35 studies), geography/land-use transitions (26 studies). Our meta-analysis revealed a great
variability in findings on selected forest and environmental parameters from the studies examined.
Studies on ecology were mainly concentrated on plant diversity and successional development,
while conservation biology related studies were focused on birds. Limited impacts of shifting
cultivation on some soil essential nutrients were also apparent. Apart from the intensity of past
usage site spatial attributes seems critical for the successful development fallow landscapes to
secondary forests. It is clear that further research is needed to help ascertain the environmental
consequences of this traditional land-use on tropical forests. Scientists and policy makers also need
to be cautious when making generalisations about the impacts of shifting cultivation and to the both
the social and environmental context in which shifting cultivation is being undertaken.
Key-words: deforestation; secondary forest; agriculture; environmental consequence; conservation.
17
2.2 Introduction
Shifting cultivation, swidden or slash-and-burn is a widespread land-use common in the
tropical forest agriculture frontier, and has formed the basis of land uses, livelihoods and customs in
upland areas for centuries (Dressler et al., 2015; van Vliet et al., 2012; Mertz et al., 2009a; Metzger,
2003). While reliable information on the number of people who engaged in shifting cultivation is
unavailable, Mertz et al. (2009b) has estimated about 14-34 million people alone from tropical Asia
depend on shifting cultivation. In tropical regions, it has also been estimated that shifting cultivation
is responsible for as much as 60 percent of the total deforestation and is considered as a prominent
source of greenhouse gas emissions (Davidson et al., 2008; Geist and Lambin, 2002). At the same
time, however, this traditional land-use practice remains central to the livelihoods, culture and food
security of millions of people in tropical region (Dalle et al., 2011). In tropical developing
countries, the practice of shifting cultivation is sometimes synonymous with poverty and low
productivity of land (Schroth et al., 2004). In recent years, the extent of land under shifting
cultivation and the people who depend on it for livelihoods and food security has been declining
due to rapid urbanization and economic development in some countries (van Vliet et al., 2012;
Mertz et al., 2009a). In many parts of South and Southeast Asia, local and regional land-use and
development policies have been developed to reduce shifting cultivation due to a perceived negative
impact on environment (van Vliet et al., 2012; Fox et al., 2009). There is, however, growing
recognition from scientists of the importance of this traditional land-use to smallholder’s livelihoods
and food security (Fox et al., 2009; Mertz et al., 2009b; Ziegler et al., 2011). At the same time,
controversies still persist among policy makers and the scientific community on the suitability of
this traditional land-use from environmental and conservation perspectives (Bruun et al., 2009;
Lawrence et al., 2010).
Shifting cultivation is still a dominant land-use/practice in countries rich in biodiversity and forest
cover, and many of these countries also has some of the highest rates of deforestation (Baccini et
al., 2012). Understanding shifting cultivation is therefore critical for sustainable forest management,
biodiversity conservation, and proper land-use and development planning in tropical regions
(DeFries and Rosenzweig, 2010). The issues associated with shifting cultivation however, are
complex, and involve the intersection of socio-economic, environmental and policy issues. In recent
years evidence-based science has been embraced by scientific communities as a desirable approach
to design appropriate environmental policies (Lele and Kurien, 2011). In this paper, we review and
analyze empirical research on shifting cultivation following a protocol. Our focus was on the spatio-
temporal patterns of research on shifting cultivation across the tropics in order to identify research
trends and gaps in research. We then performed a meta-analysis of literature that focused on forest
18
dynamics following shifting cultivation with emphasis on the effect of shifting cultivation on key
forest and environmental parameters including - plant ecology, conservation biology, soil nutrients
and chemistry, and soil physics and hydrology. We finally presented a meta analysis where selected
environmental attributes were compared with primary forests and/or other tree based land-
use/cover. The drivers of change of shifting cultivation in tropics, with related livelihoods and
environmental consequences have been reviewed by van Vliet et al. (2012) based on an analysis of
the literature between 2000 and 2010. We extend that analysis to include papers published from
1950 to 2014. Importantly, our study builds on van Vliet et al. (2012) by providing more detailed
analysis of the dynamics of tropical secondary forests after shifting cultivation, and factors that may
influence the recovery of such landscapes. Our paper provides a general overview of the research on
shifting cultivation, gaps in research and secondary forest dynamics after shifting cultivation.
Uncovering such issues with greater certainty is useful for both conservation and management of
declining tropical forests.
2.3 Methodology
2.3.1 Document search for systematic map
We searched the relevant literature using the ISI Web of Science (WoS, Thomson Reuters)
database (Web of Science, 2014). WoS was selected as it is one of the most powerful,
comprehensive, and widely used search engine for the analysis of interdisciplinary and peer-
reviewed literature (Jasco, 2005). There are many terms that have been used locally to explain
shifting cultivation (e.g. jhum in Bangladesh and parts of India, kaingin in the Philippines, bhasme
in Nepal, ladang in Indonesia, conuco in Venezuela, tavy in Madagascar etc). However, shifting
cultivation, swidden and slash-and-burn are the most commonly used and generally accepted terms
that have been used to delineate this land-use (Mertz et al., 2009a). In our literature search we used
a combination of those keywords using the search term - (shifting cultivation or swidden or (‘slash-
and- burn’) in the title. Our review was limited to peer-reviewed articles published between January
1950 to January 2014.
Our search initially yielded 551 documents of which 460 were relevant to our study (Supplementary
material 1). All 460 retrieved documents were then reviewed based on their title and abstract to
evaluate their suitability for inclusion in the final review. We considered only the articles that
reported empirical studies from tropical countries. We then excluded any review, meta-analysis,
methodological paper, and paper from outside the tropics (Figure 2.1). This resulted in a list of 401
articles that met our final selection criteria.
19
2.3.2 Document characterzization
We classified the documents according to their main research subject focus (Table 2.1) as
interpreted through their title, abstract and corresponding journal title and classification. Documents
were classified into the following subject categories: (i) agricultural production/management; (ii)
agroforestry; (iii) anthropology/human ecology; (iv) conservation biology; (v) geography/land-use
transitions; (vi) plant ecology; (vii) soil nutrients and chemistry; (viii) soil physics and hydrology;
and (ix) others. The year of the publication and geographic location of the research (i.e.
country/region) were noted for each document.
Table 2.1. Example of documents under different subject focus.
Subject/Topic Example
Agricultural production/
Management
agricultural crop yield, weed management etc.
Agroforestry
agro-biodiversity, cultural management, non-timber forest
products (NTFPs), and NTFPs domestication
Anthropology/ Human ecology socio-political issues related to shifting cultivation,
indigenous knowledge, history, perceptions and attitudes
on shifting cultivation etc.
Conservation biology wildlife diversity and assemblage in shifting cultivation
landscapes.
Geography/ Land-use transitions spatial land-use/cover change analysis, land-use change
dynamics etc.
Plant ecology
plant biodiversity, plant succession, biomass and species
recovery, soil seed bank etc.
Soil nutrients and chemistry soil nutrients, soil organic carbon, and other chemical
properties of soil.
Soil physics and hydrology soil erosion, soil infiltration capacity, soil particle stability
etc.
Others
documents other than the above research focus, e.g. trace
gas emissions from shifting cultivation.
2.3.3 Document selection for meta-analysis
The main emphasis of our meta-analysis was on the secondary forest dynamics following
shifting cultivation and the impacts of shifting cultivation on forest characteristics considering
primary or undisturbed forest as control. Therefore, articles from subject foci – plant ecology,
conservation biology, soil nutrients and chemistry, and soil physics and hydrology have been
included. Since we focused on forest dynamics following shifting cultivation we restricted our
20
analysis only to articles that presented a comparison of the related parameters with undisturbed
forests (i.e. primary or secondary forest without prior history of shifting cultivation). Seventy three
articles met our final selection criteria for that meta-analysis, comprising 34 studies on plant
ecology, 14 studies on conservation biology, 17 studies on soil nutrients and chemistry, and 8
studies on soil physics and hydrology.
2.3.4 Data interpretation and analysis
For our systematic map we compared the number of research studies on different subjects,
conducted in different time span as well as in different geographic regions. We performed Student’s
t-tests with p-value (one-tailed) to see any significant difference in number of research studies on
shifting cultivation during different time period as well as in different tropical regions. All statistical
analyses were implemented using MS Excel and R statistical package (version 3.1.0; R
Development Core Team, 2012). For mapping spatial distribution of research on shifting
cultivation, we used the package ‘rworldmap’ (South, 2011).
2.4 Results and discussions
2.4.1 Spatio-temporal dynamics of research on shifting cultivation
i. Spatial distribution of research on shifting cultivation
Our study revealed spatial heterogeneity and biases in research focus, as well as a high degree of
variability in the number of research studies across tropical countries and regions. Altogether 412
studies from 45 countries representing three tropical regions (i.e. tropical Asia and the Pacific;
Africa and tropical America) were covered by the retrieved documents (n = 401). The geographic
distributions of the studies are shown in Figure 2. Of these studies, 215 (52.2%) were from tropical
Asia and the Pacific, 131 (31.8%) from tropical America and the Caribbean, and 66 (16%) were
from Africa. A small number of articles (n=9) reported empirical studies from more than one
country. The largest number of studies was reported from India (n=58, 14%), followed by Brazil
(n=43, 10.4%), Mexico (n=38, 9.2%), Indonesia, and Lao PDR (n=32, 7.8%) (see - Supplementary
Figure 2.1) and coincide within tropical countries where deforestation rates are relatively high (see
Baccini et al., 2012).
When considering the geographic focus, most research took place in tropical Asia and the Pacific
region (t = 3.18; p < 0.05). Significantly more research was conducted on anthropology and human
ecology issues (t = 4.35; p ≤ 0.01) with the majority of these studies being conducted in the Asia
and the Pacific region (56 studies, 26%) region and in tropical America (32 studies, 24.4%). Plant
ecology related studies were the most common in Africa (n=16, 24.2%) and in tropical America
21
Figure 2.1. Summary of literature used for systematic map and meta-analysis.
ISI Web of Science
search
Search term: (shifting cultivation or swidden or (slash and burn)) Range: January 1950 to January 2014 Document type: Peer reviewed article
Not relevant
551 Documents
Included (n = 460)
Review/Meta-analysis/Methods Case study (n = 401)
Anthropology/Human ecology (n = 101)
Agricultural production/Management
management (n = 57)
Geography/Land-use transition (n = 26)
Conservation biology (n = 24)
Agroforestry (n = 35)
Plant ecology (n = 62)
Soil physics & hydrology (n = 20)
Soil nutrients & chemistry (n = 72)
Others (n = 4)
Excluded (n = 91)
Excluded (n = 59)
Conservation biology (n = 14)
Plant ecology (n =34)
Soil physics & hydrology (n = 8)
Soil nutrients & chemistry (n = 17)
Systematic map Meta-analysis
22
(n=25, 19%). Research on soil nutrients and chemistry was prominent (n=46, 21.4%) in the Asia-
Pacific region (Figure 2.2).
ii. Temporal pattern of research on shifting cultivation
The majority of research related to shifting cultivation has been published since 2001 (t = 2.1; p =
0.52), with the major foci being on anthropology/human ecology (22%), plant ecology (20.7%), and
soil nutrients and chemistry (14.2%). The majority of the research was on soil physics and
hydrology (80%), geography/land-use transitions (73%) and plant ecology (72.6%) has occurred
since 2001. Figure 2.3 illustrates the changes in research focus in the retrieved documents between
1950 and 2014.
Research on anthropology and human ecology was prominent (n = 101) throughout almost the
entire period except during 1981-1990. Research on agricultural production/management (n = 17)
and soil nutrients and chemistry (n=16) was also prominent after anthropology/ human ecology
during 1981–1990. During 1991–2000 soil nutrients and chemistry was a major focus of the
researchers (n=23). In recent years, research on the environmental impacts of shifting cultivation
(e.g. soil physics and hydrology, plant ecology etc) have received more attention.
A similar pattern is also common in case of geography and land-use transition research which may
be attributed to the rapid advancement and access to spatial information technologies (for example:
satellite imagery and advanced methods to monitor changes in shifting cultivation landscapes).
2.4.2 Impacts of shifting cultivation on tropical forest dynamics
In tropical forested landscapes shifting cultivation has long been considered environmentally
harmful and unsustainable (see - van Vilet et al., 2012; Ziegler et al., 2011, 2009; Bruun et al.,
2009). However, what is often overlooked is that in many cases alternative land-uses to shifting
cultivation fallow forests may have potentially greater negative impacts (Dressler et al., 2015;
Vongvisouk et al., 2014). However, there are only a few studies that have investigated the change in
environmental values of these alternative land-uses that may replace fallow secondary forests. From
these studies, there is a growing evidence that the expansion of monoculture tree crops like rubber
and oil palm in many parts of tropical Asia, which has replaced traditional shifting cultivations
systems, has resulted in increased deforestation, biodiversity loss and deterioration of other related
environmental parameters (Ahrends et al., 2015; Bruun et al., 2013; van Vliet et al., 2012).
23
Figure 2.2. Geogrpahical distribution of the studies on shifting cultivation by country.
24
Figure 2.3. Temporal changes in research focus between 1950-2014
(top: percentage; below: number)
Our meta-analysis revealed that there is a high degree of variability with respect to the impacts that
shifting cultivation has on forest characteristics, wildlife, soil nutrients, and soil physical and
2 17
14 24 1
0
5
11 18
7
6 16
24
48
0
0
2 5
19
1
3 6
14
10 7 45
2 16
23 31
0 1 3 16
1 3
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1950-1970 1971-1980 1981-1990 1991-2000 2001-2014
Agricultural production/ Management AgroforestryAnthroplogy/ Human ecology Geography/ Land-use transitionsConservation biology Plant ecologySoil nutrients and chemistry Soil physics and hydrologyOthers
17 14 24 1
5 11
18
7 6
16 24
48
2 5
19
3
6
14
10
7
45
2
16
23
31
1
3
16
0
50
100
150
200
250
1950-1970 1971-1980 1981-1990 1991-2000 2001-2014Agricultural production/ Management AgroforestryAnthroplogy/ Human ecology Geography/ Land-use transitionsConservation biology Plant ecologySoil nutrients and chemistry Soil physics and hydrologyOthers
Nu
mb
er o
f st
ud
ies
25
hydraulic properties (Annex 2.1). Interestingly, most of the studies used a chrnosequence approach
for monitoring change in different forest attributes in secondary fallow forest following the shifting
cultivation (Annex 2.1). Figure 2.4 presents the key insights of the retrieved documents with
quantitative data (n=73). Albeit a diverse research focus, a contrasting effect of shifting cultivation
in forest characteristics is evident from the literature. It is important to notice here that our
comparison was limited to only fallow forests and primary or old-growth forests without any history
of shifting cultivation. Due to limited data we were unable to include other possible land-use/cover
changes that may also replace fallow shifting cultivation landscape in tropics with potentially
greater harmful effects. Details of the changes in forest characteristics, and their recovery pattern
and determinants are discussed hereafter as per subject foci.
Figure 2.4. Reported effect of shifting cultivation on (a) major forest characteristics; (b) selected
wildlife selected taxa, (c) major soil nutrients and (d) soil physical and hydraulic properties.
(Note: this is based on comparison with primary or old-growth secondary forests without any
history of shifting cultivation, and doesn’t not include other possible potentially more harmful land-
use/cover changes that may also replace fallow shifting cultivation landscapes).
26
i. Plant ecology
Our meta-analysis of studies on plant ecology revealed a general negative impact of shifting
cultivation on plant diversity and species composition (see Ding et al., 2012; Do et al., 2011;
Castro-Luna et al., 2011; Figure 2.4a). Interestingly, studies that focused on early successional stage
following shifting cultivation found minor effect of shifting cultivation on plant diversity indices
(e.g. Phongoudome et al., 2013; d'Oliveira et al., 2011; Raharimalala et al., 2010). A conspicuous
negative impact of shifting cultivation on plant diversity compared to undisturbed forest was
reported by Ding et al. (2012), Wilde et al. (2012), Do et al. (2011) and Castro-Luna et al. (2011)
respectively from tropical China, Madagascar, Vietnam and Mexico. Species richness, however, did
not differ significantly between undisturbed forests and secondary forests that have been subjected
to shifting cultivation (Klanderud et al., 2010). Some studies found traditional forest management
practices like logging less harmful than shifting cultivation when considering species diversity and
composition (e.g. Ding et al., 2012).
Both fallow age and intensity of previous use influence the recovery of species composition and
diversity after shifting cultivation (Ding et al., 2012; Schmook, 2010; N’Dja and Decocq, 2008).
Young fallow areas have less diversity of species, but that diversity recovers quickly (Schmook,
2010). Similarly, it was found that, plant diversity recovered rapidly following shifting cultivation
in Mexico, with continuous accumulation with age (Read and Lawrence, 2003). In Madagascar
woody species become prominent in fallow secondary forests after about ten years (Rahamiralala et
al., 2010; Klanderud et al., 2010). In such circumstances, an active management strategy may be
necessary to restore mature-forest species in fallow secondary forest (Bonilla-Moheno et al., 2010).
It may however take around 60 years to achieve biodiversity of an old growth forest in such
landscape (Do et al., 2010). Interestingly, when considering the factors that influences species
diversity and composition, it was found that, soil type did not influence species diversity in the
fallow secondary forests (N’Dja and Decocq, 2008).
Compared to species diversity, forest structure is slow to recover following shifting cultivation. For
example, Piotto et al. (2009), found that it may take as long as 40 years to recover the structure of
an old-growth forest after they have been used for shifting cultivation in Brazil. It has also been
found in Cameroon that forest structure is much slower to recover in fallow secondary forests
following shifting cultivation compared with logged forests i.e. 30 to 60 years compared to five to
14 years respectively (Gemerden et al., 2003) However, recovery of some specific stand structure
parameters, such as stand density, can be rapid in young fallow areas (Phongoudome et al., 2013).
27
Biomass recovery follows a similar trend to the recovery of species diversity, with a rapid initial
recovery phase which subsequently slows. Biomass accumulation increases with abandonment age
(Raharimalala et al., 2012). Both above and below ground biomass recovers rapidly at early
successional stage with an estimated accumulation rate between 7.5 to 15.0 Mg ha−1
year−1
(Kenzo
et al., 2010). Similarly, Gehring et al. (2005) found that biomass recovery is rapid in the early
successional stages, with about 50 percent of the biomass recovering within 25 years after last use.
Read and Lawrence (2003) from Mexico reported that recovery of biomass may take as long as 55
to 95 years after shifting cultivation. Similarly, Do et al. (2010) found in Vietnam that it may take
about 60 years to achieve 80 percent biomass of an undisturbed forest. Substantial recovery of
biomass has been found in Brazil following repeated fire events, with recovery to pre-fire
aboveground biomass level within 30 years (d’Oliveira et al., 2011).
Burning following initial clearing has been found to have a positive influence on biomass
accumulation in fallow secondary forests in the early successional stage (d’Oliveira et al., 2011;
Kenzo et al., 2010; Tschakert et al., 2007). The rate of recovery of biomass is also affected by
intensity and number of prior shifting cultivation cycles. For example, Lawrence (2005) found that
the rate of biomass accumulation declines by about 10 percent with each subsequent shifting
cultivation cycle.
In fallow secondary forests seed is crucial for species recovery and regeneration (Vieira and
Proctor, 2007), and distance from intact forests or from forests that provide regular seed sources
can also influence the recovery of species diversity (Sovu et al., 2009; Wangpakapattanawong et al.,
2010). Lawrence et al. (2005), for instance, reported that seed rain declined with increasing distance
from the undisturbed forest. Interestingly, the largest seed banks were found in young fallow areas
in the Brazilian Amazon (Vieira and Proctor, 2007).
ii. Conservation biology
Most studies on conservation biology reported a negative impact of shifting cultivation on selected
animal taxa (Figure 2.4b). Our analysis however does not include exotic or monoculture
planatations established in fallow secondary forests that have sometimes been found more harmful
for local fauna (Ahrends et al., 2015). The majority of the studies (n=7) were, limited to bird
diversity and abundance in fallow secondary forests. In India, it has been found that bird diversity
and abundance increase with an increase in the fallow age (Raman et al., 1998), although
undisturbed forests remain as the main habitat of specialized forest birds (Raman, 2001; Bowman et
al., 1990). Intensity of past shifting cultivation use greatly influences the diversity of birds in fallow
28
secondary forest in tropical China (Zhijuna and Young, 2003). The diversity and abundance of large
frugivores (i.e. birds that feed on large fruits) also increases with the increase in fallow age (Schulze
et al., 2000).
Shifting cultivation also been found to have a negative (but minor) impact on small mammal
diversity and abundance in Peru (Naughton-Treves et al., 2003), and Zaire (Wilkie and Finn, 1990),
with hunting intensity having a much greater influence (Naughton-Treves et al., 2003). Other lower
taxa animal appear to recover quickly after shifting cultivation, with their composition and richness
being greatly influenced by the alteration of forest structure (Yoshima et al., 2013).
iii. Soil nutrients and chemistry
Studies on soil nutrients and chemistry have reported a mixed effect of shifting cultivation on
associated soil parameters (Figure 2.4c). Generally, shifting cultivation involves burning of forest
vegetation, and it is quite likely that it increases the amount of organic matter in soil via ash
(Tanaka et al., 2001; Giardina et al., 2000; Adedeji, 1984). Soil nutrient losses can be potentially
higher following shifting cultivation due increased soil run-off associated with forest clearing and
site spatial characteristics like slope (Rodenburg et al., 2003; Brand and Pfund, 1998). In Mexico,
Giardina et al. (2000) found that, apart from ash, heating of soil during the burning of forests also
acts as an important mechanism of nutrient release in the soil. Interestingly, Osman et al. (2013)
found that, soil organic carbon (SOC) was greater in fallow secondary forests than in adjacent
natural forests in Bangladesh. In Thailand, Tanaka et al. (2001) found that, while burning increases
(SOC), it also results in a decrease in microbial biomass C in soil. In contrast, a 32% decrease in
SOC due to combustion has been reported in Mexico (Garcia-Oliva et al., 1999). Some other land-
uses like oil palm plantations may have however even more detrimental effect than shifting
cultivation when considering soil C (Brunn et al., 2013).
Other nutrients, including soil available nitrogen (N), phosphorus (P) and potassium (K) also
exhibit mixed effects following shifting cultivation. For instance, in China, Yang et al. (2003) found
that fire reduced the total N and P in soil by about 20% and 10% respectively, while K was
increased. Similarly, Brand and Pfund (1998) have reported a positive effect of shifting cultivation
on soil available P and K in a 5 year old fallow secondary forest, but negative impact on Ca and Mg
available in soil. In contrast, in Nigeria, Adedeji (1984) found that, soil K and N decreased rapidly
after clearing for shifting cultivation, and in a 6 year old fallow forest the soil nutrient levels were
still far below those found in in a nearby undisturbed forest.
29
A long fallow period appears to be important to restore the essential soil nutrients (Funakawa et al.,
2009). For instance, in Madagascar, Rahamiralala et al. (2010) found that it may take about 20 years
to restore soil nutrients after shifting cultivation. Intensity of past use (i.e. number of fallow cycles)
does not appear to influence soil P, at least in Indonesia (Lawrence and Schlesinger, 2001).
iv. Soil physics and hydrology
Studies on soil physics and hydrology reported mostly negative impacts of shifting cultivation on
associated soil attributes in fallow secondary forests (Figure 2.4d). In most cases, subsequent fire
resulted in disruption to soil physical and hydraulic properties (Hattori et al., 2005; Garcia-Oliva et
al., 1999). Clearing and burning of forest at the initial stage of shifting cultivation cause increased
soil run-off (Rodenburg et al., 2003). Dung et al. (2008) found significant increases in soil erosion
and runoff compared to undisturbed forest in Vietnam. Gafur et al. (2003, 2004) also found a
considerable amount of soil loss (3 Mg ha−1
y−1
) through runoff due to shifting cultivation in forests
of Bangladesh. In contrast, Osman et al. (2013) however, did not found any considerable effect of
shifting cultivation on soil physical properties including – water holding capacity, bulk density,
moisture content and particle density.
In Malaysia (Hattori et al., 2005) and Thailand (Grange and Kansuntisukmongkol, 2004) it has
been found that shifting cultivation accelerates soil erosion and deteriorates soil hydrological
properties in regenerating fallow secondary forests. Soil loss decreased exponentially from burned
to early stage of secondary forest development following the shifting cultivation (Thomaz, 2013).
However, Grange and Kansuntisukmongkol (2003) did not find any detrimental effect of fallow
length on soil physical attributes after shifting cultivation.
2.5 Conclusions
In tropical forested landscapes shifting cultivation is still a dominant land-use, although in
recent years, both the intensity and extent of shifting cultivation have changed in many countries
(van Vliet et al. 2012, 2013). Our systematic map revealed a large spatio-temporal variability and
gaps in research on shifting cultivation across the tropics. There is great variability in the numbers
and focus of research studies dealing with various aspects of shifting cultivation. Most research has
been on anthropology and human ecology issues. In contrast, research on environmental
consequences is still limited, and only gaining wider attention from researchers in the recent years.
Due to its complex nature, diverse focus, and differences in the context, it is difficult to generalize
the findings of research on shifting cultivation systems. Our meta-analysis on the impacts of
30
shifting cultivation on forest dynamics and related bio-physical and environmental parameters
revealed great variability in research findings. There were a relatively large number of studies on
plant ecology and fewer studies on soil physics and hydrology. A limited number of studies on
environmental consequences of other land use/covers that are common after shifting cultivation in
tropics was also evident. Plant diversity and composition was the most common aspects of plant
ecology research while conservation biology related research were mainly focused on bird diversity.
A limited impact of shifting cultivation on some soil essential nutrients were also evident from our
meta-analysis. Apart from fallow length and intensity of previous use, site spatial attributes like
slope, nearness to natural forests and permanent seed/dispersal source also seems critical for
successful development of fallow secondary forests.
The sustainability of shifting cultivation systems continues to be debated in many tropical countries,
and it is clear that this traditional practice will reamain an important land-use and subsistence
strategy in those countries many years ahead (Lawrence et al., 2010; Neergard et al., 2008). In
developing tropical countries, shifting cultivation is still seen as a threat to the natural forest (Hett et
al., 2013), and has been widely promoted as a practice having a detrimental impact to the
environment (Neergard et al., 2008; Fox et al., 2000). However, when discussing shifting
cultivation, scientists and policy makers should also consider alternative land-uses with potentially
greater negative impacts, like sedentary agriculture, commercially driven large scale plantations or
monocultures (Dressler et al., 2015). Policy makers also need be cautious while designing policies,
with careful consideration to the small-holder farmers to whom shifting cultivation is still the
mainstay of livelihoods and food security.
2.6 Additional information
Supplementary Figure 2.1 related to this chapter/manuscript is provided at the end of this
thesis under the section – Appendices.
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Yang, Y., Guo, J.F., Chen, G.S., He, Z.M., Xie, J.S., 2003. Effect of slash burning on nutrient
removal and soil fertility in Chinese fir and evergreen broadleaved forests of mid-subtropical
China. Pedosphere, 13, 87-96.
Yoshima, M., Takematsu, Y., Yoneyama, A., Nakagawa, M., 2013. Recovery of litter and soil
invertebrate communities following swidden cultivation in Sarawak, Malaysia. The Raffles
Bulletin of Zoology, 61, 767–777.
Zhijuna, W., Young, S.S., 2003. Differences in bird diversity between two swidden agricultural
sites in mountainous terrain, Xishuangbanna, Yunnan, China. Biological Conservation, 110,
231–243.
Ziegler, A.D., Fox, J.M. Webb, E.L., Padoch, C., Leisz, S., Cramb, R.A., Mertz, O., Bruun, T.T.,
Vien, T.D., 2011. Recognizing contemporary roles of swidden agriculture in transforming
landscapes of Southeast Asia. Conservation Biology, 25, 846‐848.
Ziegler, A.D., Bruun, T.B., Guardiola-Claramonte, M. , Giambelluca, T.W., Lawrence, D., Lam,
N.T., 2009. Environmental consequences of the demise in swidden cultivation in Montane
Mainland Southeast Asia: hydrology and geomorphology. Human Ecology, 37, 361–373.
39
Annex 2.1. Summary of studies used in meta-analysis on impacts of shifting cultivation on forest dynamics.
Primary area Source Country Forest type Study approach* Specific focus Environmental
consequence**
Reference land-
use***
Conservation
biology/zoology
(n=14)
Yoshima et al., 2013 Malaysia Humid forest Comparison Invertebrate diversity Minor Undisturbed
forest****
Matsumoto et al., 2009 Malaysia Humid forest Chronosequnce, 2-
20 yr
Ant diversity Negative Undisturbed forest
Borges, 2007 Brazil Humid forest Chronosequnce, 4-
35 yr
Bird diversity Negative Undisturbed forest
Gathrone-Hardy et al.,
2006
Indonesia Humid forest Chronosequence, 2-
60 yr
Termites activity Negative Undisturbed forest
Naugton-Treves et al.,
2003
Peru Humid forest Comparison Mammalian diversity Minor Undisturbed forest
Zhijuna and Young,
2003
China Comparison Bird diversity Negative Undisturbed forest
Anderson, 2001 Honduras Humid forest Comparison Bird diversity Negative Undisturbed forest
Raman, 2001 India Dry forest Chronosequnce, 1-
100 yr
Bird diversity Negative Undisturbed forest
Schulze et al., 2000 Guatemala Humid forest Comparison Bat diversity Negative Undisturbed forest
Raman et al., 1998 India Dry forest Chronosequnce, 1-
100 yr
Bird diversity Negative Undisturbed forest
Raman, 1996 India Dry forest Comparison Primate/squirrel
abundance
Negative Undisturbed forest
Bowman et al., 1990 Papua New
Guinea
Humid forest Chronosequence Bird/butterflies/reptile
diversity
Negative Undisturbed forest
Wilkie and Finn, 1990 Zaire Humid forest Comparison Mammalian diversity Minor Undisturbed forest
Mishra and
Ramakrishnan, 1988
India Dry forest Chronosequnce, 1-
15 yr
Nematode abundance Negative Undisturbed forest
Plant ecology
(n=34)
Phongoudome et al.,
2013
Lao PDR Humid forest Chronosequence Plant diversity, forest
structure
Minor Undisturbed forest,
Logged forest
Raharimalala et al.,
2012
Madagascar Humid forest Chronosequence Forest biomass Negative Undisturbed forest
Wilde et al., 2012 Madagascar Humid forest Chronosequence Plant diversity Negative Undisturbed forest
Ding et al., 2012 China Humid forest Chronosequence Plant diversity Negative Undisturbed forest,
Logged forest
d’Oliveira et al., 2011 Brazil Humid forest Long term
monitoring
Forest biomass Minor Undisturbed forest
Do et al., 2011 Vietnam Humid forest Chronosequence Plant diversity Negative Undisturbed forest
Castro-Luna et al.,
2011
Mexico Dry forest Chronosequence Plant diversity Negative Undisturbed forest,
Logged forest
40
Bonilla-Moheno et al.,
2010
Mexico Dry forest Chronosequence
5-15 yr
Seedling survival Negative Undisturbed forest
Rahamiralala et al.,
2010
Madagascar Humid forest Chronosequence,
upto 40 years
Plant diversity Minor Undisturbed forest
Wangpakapattanawong
et al., 2010
Thailand Humid forest Chronosequence, 1-
6 yr
Plant diversity/
succession
Minor Undisturbed forest
Schmook, 2010 Mexico Dry forest Chronosequence Plant diversity/
succession
Negative Undisturbed forest
Kenzo et al., 2010 Malaysia Humid forest Long term
monitoring
Forest biomass Positive Undisturbed forest
Do et al., 2010 Vietnam Humid forest Chronosequence, 1-
26 yr
Plant diversity, Forest
biomass
Negative Undisturbed forest
Klanderud et al., 2010 Madagascar Humid forest Chronosequence Plant diversity Negative Undisturbed forest
Lawrence et al., 2010 Mexico/Indonesia Dry/Humid
forest
Long term
monitoring
Forest biomass Negative Undisturbed forest
Piotto et al., 2009 Brazil Humid forest Chronosequence,
10-40 yr
Plant diversity, Forest
structure
Minor Undisturbed forest
Sovu et al., 2009 Lao PDR Humid forest Chronosequence, 1-
20 yr
Species diversity,
Forest structure
Negative Undisturbed forest
Eaton and Lawrence,
2009
Mexico Dry forest Chronosequence, 2-
25 yr
Forest biomass Negative Undisturbed forest
N’Dja and Decocq,
2008
Ivory Coast Humid forest Chronosequence, 1-
30 yr
Plant diversity Minor Undisturbed forest,
Logged forest
Gehring et al., 2008 Brazil Humid forest Chronosequence, 2-
25 yr
Plant diversity Negative Undisturbed forest
Ochoa-Gaona et al.,
2007
Mexico Dry forest Chronosequence Plant diversity Negative Undisturbed forest
Vieira and Proctor,
2007
Brazil Humid forest Chronosequence, 5-
20 yr
Soil seed
bank/succession
Positive Undisturbed forest
Lawrence et al., 2005 Indonesia Humid forest Chronosequence, 9-
12 yr
Plant diversity Negative Undisturbed forest
Gehring et al., 2005 Brazil Humid forest Chronosequence, 2-
25 yr
Plant diversity, Forest
biomass
Negative Undisturbed forest
Lawrence, 2005 Indonesia Humid forest 10-200 yrs Forest biomass Negative Undisturbed forest
Lawrence, 2004 Indonesia Humid forest 9-12 Plant diversity Negative Undisturbed forest
Kupfer et al., 2004 Belize Dry forest Chronosequence, 1-
10 yr
Plant diversity/
Succession
Negative Undisturbed forest
Metzger, 2003 Brazil Humid forest Chronosequence, 4-
10 yr
Plant diversity/
Succession
Negative Undisturbed forest
Gemerden et al., 2003 Cameroon Humid forest Chronosequence, Plant diversity Negative Undisturbed forest,
41
10-60 yr Logged forest
Read and Lawrence,
2003
Mexico Dry forest Chronosequence, 2-
25
Forest biomass Negative Undisturbed forest
Lawrence and Foster,
2002
Mexico Dry forest Chronosequence, 2-
25
Forest biomass Negative Undisturbed forest
Miller and Kauffman,
1998a
Mexico Dry forest Chronosequence; 2-
19 yr
Plant diversity/
Succession
Negative Undisturbed forest
Miller and Kauffman,
1998b
Mexico Dry forest Comparison Plant diversity Negative Undisturbed forest
Kotto-Same et al., 1998 Cameroon Chronosequence, 4-
70 yr
Forest biomass/
carbon
Negative Undisturbed forest,
Cacao plantation
Soil nutrient and
chemistry
(n=17)
Bruun et al., 2013 Malaysia Humid forest Comparison SOC Negative Undisturbed forest,
Oil palm plantation
Osman et al., 2013 Bangladesh Humid forest Chronosequence, 1-
3 yr
SOC, N, P, K SOC (+)
Negative
Undisturbed forest
Lima et al., 2011 Brazil Humid forest Chronosequence SOC, N Negative Undisturbed forest,
Agroforests
Rahamiralala et al.,
2010
Madagascar Humid forest Chronosequence SOC, N Minor Undisturbed forest
Eaton and Lawrence,
2009
Mexico Dry forest Chronosequence, 2-
25 yr
SOC Negative Undisturbed forest
Funakawa et al., 2009 Indonesia Humid forest Comparison SOC Negative Undisturbed forest
Neergaard et al., 2008 Malaysia Humid forest Comparison SOC Minor Undisturbed forest,
Pepper plantation
Rodenburg et al., 2003 Indonesia Humid forest Comparison P Negative Rubber agroforest
Gafur et al., 2003 Bangladesh Humid forest Comparison SOM Negative Agroforests
Borggaard et al., 2003 Bangladesh Humid forest Comparison SOC, N, K Negative Agroforests
Yang et al., 2003 China Comparison N, P, K Negative Undisturbed forest
Lawrence and
Schlesinger, 2001
Indonesia Humid forest Chronosequence,
200 yr
P Minor Undisturbed forest
Giardina et al., 2000 Mexico Dry forest Comparison N, P, K Positive Undisturbed forest
Garcia-Oliva et al.,
1999
Mexico Dry forest Chronosequence, 1-
10 yr
SOC Negative Undisturbed forest
Brand and Pfund, 1998 Madagascar Humid forest Comparison P, K, Ca, Mg Mixed
(P,K+)
Undisturbed forest
Salcedo et al., 1997 Brazil Humid forest Comparison SOC Minor Undisturbed forest
Adedeji, 1984 Nigeria Chronosequence, 16
yr
N, P, K Negative Undisturbed forest
Soil physics and
hydrology
(n=8)
Thomaz, 2013 Brazil Humid forest na Soil erosion Negative Undisturbed forest
Osman et al., 2013 Bangladesh Humid forest Comparison Bulk density, water
holding capacity
Negative Undisturbed forest
42
Lestrelin et al., 2012 Lao PDR Humid forest na Soil erosion Negative Undisturbed forest
Dung et al., 2008 Vietnam Humid forest na Soil erosion Negative Undisturbed forest
Neergaard et al., 2008 Malaysia Humid forest Comparison Soil erosion Minor Undisturbed forest,
Pepper plantation
Hattori et al., 2005 Malaysia Humid forest Comparison Soil structure Negative Undisturbed forest
Gafur et al., 2004 Bangladesh Humid forest Comparison Soil structure Negative Undisturbed forest
Grange and
Kansuntisumkmongkol,
2003
Thailand Humid forest Chronosequence, 10
yr
Soil structure, water
holding capacity
Minor Undisturbed forest
*where, chronsequence studies used secondary forests of different ages that have been previously used for shifting cultivation (and abandoned); comparison studies
used only one age (specified or unspecified) of secondary forests (abandoned after shifting cultivation), and long term monitoring studies used the same fallow
secondary forest sites for subesequnt investigation over a long period of time;
**when refering e to a environmental consequence we consider the specific focus of that study and used undisturbed forests for any comparison;
***our reference land-use for the comparisons were primarily based on forests, either logged or unlogged, and/or other tree based land-uses when available, e.g.
cacao/rubber agroforests; we did not include any agricultural land-use in the analysis;
**** undisturbed forests includes primary or secondary forests that has never been used for shifting cutivation.
43
CHAPTER 3: HIGH RESILIENCE OF TROPICAL FOREST DIVERSITY AND
STRUCTURE AFTER SHIFTING CULTIVATION IN THE PHILIPPINES
UPLANDS
May cite as – Mukul, S.A., Herbohn, J., Firn, J. In review. High resilience of tropical forest
diversity and structure after shifting cultivation in the Philippines uplands. Applied Vegetation
Science.
3.1 Abstract
Shifting cultivation is a widespread land-use in the tropics that is considered a major threat to rain
forests diversity and structure. Despite its extent in the tropical region and critical role in forest
quality, few studies have attempted to quantify the resilience or recovery capacity of fallow
secondary forests after shifting cultivation. We investigated the impact of shifting cultivation on
secondary forest dynamics in an upland area of the Philippines - a global biodiversity hot spot and
megadiverse country. Species diversity and forests structure parameters were measured at 25 sites
along a fallow gradient. Species composition and reassembly pattern in relation to the old-growth
forest was also examined. Our study finds high conservation values of secondary forests after
shifting cultivation in the area. Species richness was significantly higher in the oldest fallow sites,
while Shannon’s diversity index, species evenness, stem number, basal area and leaf area index
were higher in the old-growth forest followed by oldest fallow sites. A homogeneous species
composition pattern was found in our fallow secondary forests and control old-growth forest. Our
results indicate that regenerating secondary forests disturbed by shifting cultivation can exhibit high
resilience and may recover rapidly after five years and that patch size is a strong predictor of this
recovery. Although recovery of forest structure was not as rapid as tree diversity, our older fallow
sites demonstrated comparable numbers of species as the old-growth forest which are either
endemic to the Philippines or entails special conservation needs. Our findings suggest that novel
and emerging ecosystems like regenerating tropical fallow secondary forests are of high
conservation significance with their important role as a refuge for threatened tropical forest
biodiversity.
Key-words: forest conservation; kaingin; Southeast Asia; reforestation; forest restoration.
3.2 Introduction
A large area of tropical forests has been modified by human activity, mainly logging and
shifting cultivation, and the future of forest management in this region relies on the effective
44
management of such human-modified landscapes (Ghazoul et al., 2015; Putz and Romero, 2014;
Gardner et al., 2009; Chazdon, 2008). In this region, secondary or second growth forests have
become a key concern of the scientists and policy makers in recent years due to their potentials to
offset the unprecedented loss of tropical forest biodiversity (Chazdon, 2014, 2003; Pichancourt et
al., 2014; Laurance, 2007; Brook et al., 2006; Wright and Muller-Landau, 2006). It is also
increasingly acknowledged that regenerating secondary forests in tropics can provide as much
environmental benefit as the primary forests although the role they have played in biodiversity
conservation remained still largely unexplored (Bonner et al., 2013; Sang et al., 2013; Chazdon et
al., 2009; Norden et al., 2009; Erskine et al., 2006).
In Southeast Asia, shifting cultivation or slash-and-burn agriculture has been considered as a
primary agent of forest degradation and deforestation for many years (Ziegler et al., 2011; Achard
et al., 2002; Geist and Lambin, 2002; Angelsen, 1995). Shifting cultivation is a dominant land-use
in this region with deforestation rate remains still amongst highest in the tropics (Dalle et al., 2011;
Sodhi et al., 2010; Achard et al., 2002). In recent years, although the extent of land under shifting
cultivation has declined in many countries (van Vliet et al., 2012), this traditional land-use still form
a central part of the livelihoods of millions of upland rural people in Southeast Asia (Dalle et al.,
2011). At the same time, large controversies persist among policy makers and scientific community
on the impact of shifting cultivation on forest dynamics both from management and conservation
perspectives (Ziegler et al., 2011; Lawrence et al., 2010; Bruun et al., 2009).
The general negative view of shifting cultivation on forest diversity and structure is mainly due to
its comparison with primary or less disturbed forests (see - Ding et al., 2012; Do et al., 2011;
Castro-Luna et al., 2011; Klanderud et al., 2010). Such comparison is unrealistic for some other
land-uses that are currently replacing the tropical rainforests, like oil palm or rubber plantation is
environmentally more detrimental than shifting cultivation (Fox et al., 2014; Bruun et al., 2013).
Recovering fallow secondary forests after shifting cultivation in this region also never gained as
attention as the logged tropical forests here, although together they are the largest contributor of
forest degradation (Houghton et al., 2012; Houghton, 2012). Due to the dynamic nature of fallow
landscapes, differences in management and site spatial heterogeneity, research on the impact of
shifting cultivation in secondary forest dynamics has always been challenging (Mukul and Herbohn,
2016). The intensity of past usage consistently found important in determining the capacity of
degraded tropical to recover in terms of species diversity and forest structure, although a large
variation exists in the recovery of different forest attributes and time required for their recovery
(Lawrence et al., 2010; Lawrence, 2004). It took, at least, ten years to woody species become
45
prominent in secondary forests following shifting cultivation (Raharimalala et al., 2010) and 60
years to achieve biodiversity of an old-growth forest (Do et al., 2010). Recovery of specific stand
structure indices, such as stand density, can be rapid in young fallow areas (Phongoudome et al.,
2013) although recovery of the other forest structure parameter may take as long as 40 years (Piotto
et al., 2009). In both cases an active forest management strategy found useful to restore forest tree
diversity and structure (Bonilla-Moheno and Hol, 2010).
The resilience of forest ecosystems depends on the rate at which they recover from disturbances
both biotic and abiotic (Isbell et al., 2015; Wilson et al., 2015). We investigated the recovery of
species diversity, composition and forest structure along a shifting cultivation-fallow gradient in an
upland secondary forest in the Philippines – a global biodiversity hotspot and a megadiversity
country (Posa et al., 2008; Myers et al., 2000). We also examined the factors that may expedite the
recovery process in such altered ecosystems. The Philippines maintain about 5% of the world’s
plant diversity with high level of species endemism (Lasco et al., 2013; Sodhi et al., 2010; Kummer
and Turner, 1994). The forest cover in the country has declined from 50% in 1950 to 24% in 2004
(Lasco and Pullhin, 2009), with the majority of the remaining forests severely degraded
(Chokkalingam et al., 2006). Shifting cultivation, locally known as kaingin, is a common, yet
controversial land-use in the country (Saurez and Sajise, 2010). Kaingin has also been blamed for
much of the country’s deforestation and forest degradation, and not a recognized land-use in
government policies (Lasco et al., 2013, 2009; Kummer, 1992). After post logging secondary forest,
post-kaingin secondary forest, however, represents the second largest group of secondary forests in
the Philippines (Lasco et al., 2001).
While shifting cultivation is declining in many Southeast Asian countries (see - van Vliet et al.,
2012; Mertz et al., 2009), secondary forests regenerating after shifting cultivation becoming more
common in this region (Mertz et al., 2009; Chokkalingam and Perera, 2001). Understanding
biodiversity patterns in such landscape is, therefore, essential for the establishment of science -
based conservation strategies that could potentially support policy-making for better forest and
landscape management and restoration (Trimble and van Aarde, 2012; Schroth et al., 2004). Our
study, hence useful not only to recognize the resilience capacity of tropical secondary forests after
shifting cultivation but also to fully understand the future potential of tropical forests to support
biodiversity and aid forest restoration and management.
3.3 Materials and methods
3.3.1 Study area
46
We conducted our study in Barangay1 Gaas in Ormoc city – located in the west part of the
Leyte Island in the Philippines. The island is eighth largest in the country with an area nearly about
800,000 ha. Geographically, Leyte is situated between 124017
/ and 125
018
/ East longitude and
between 9055
/ and 11
048
/ North latitude (Figure 3.1). Forest cover on the island is about 10%,
although the once dipterocarp rich rainforests of the island are now represented by patches of old-
growth and secondary forests intermixed with coconut (Cocos nucifera) and abaca (Musa textilis)
plantations (Asio et al., 1998). The relatively flat lowlands of the island are used for agricultural
production, mainly corn (Zea mays), rice (Oryza sativa) and sweet potato (Ipomea batatas) (Asio et
al., 1998). There have been many attempts at to support reforestation in Leyte and there are
numerous smallholder and community forests scattered across the island, including ‘rainforestation
plantings’ designed to reduced kaingin activity in the Philippines (see - Herbohn et al., 2014;
Nguyen et al., 2014).
Figure 3.1. Map showing location of the study area on Leyte Island (left), and the study sites (right)
plotted in a Google Earth map showing the location of the 25 sites.
1 Barangay (Brgy. in short) is the smallest administrative unit in the Philippines and is the native
Filipino term for a village.
47
Leyte has a ‘type IV’ climate based on the Coronas Classification of Climate (Navarrete et al.,
2013). According to Aurelio (2000) the whole island is formed from tectonic movement and plate
convergence that started during the Tertiary and Quaternary age (Asio et al., 1998). The island
enjoys relatively even distribution of rainfall throughout the year with an annual rainfall of about
4,000 mm (Jahn and Asio, 2001). Although there is no distinct dry season, between March and May
the area experiences its lowest monthly rainfall (Jahn and Asio, 2001). Mean annual temperature is
280C which remains relatively constant throughout the year (Navarrete et al., 2013). Relative
humidity ranges between 75 to 80 percent during the dry and the wettest months (Kolb, 2003).
3.3.2 Site selection criteria
Olofson (1980) has categorized the kaingin systems in the Philippines into three distinct
types based on the sites where they have been practiced, these are: i) the tubigan system, ii) the
katihan system and iii) the dahilig system. The tubigan and katihan systems take place in lower
elevation or in gently sloping land with limited facilities of irrigation, whereas the dahilig system is
widely practiced in profoundly forested areas and in steeper slopes (Olofson, 1980). For the present
study, we sampled only from the dahilig system as it is comparable to the most common form of
shifting cultivation available in Southeast Asian rain forests.
We purposively chose Brgy. Gaas (hereafter Gaas only) for our study. It is situated in a relatively
higher elevational range with low population density and high vegetation cover which is essentials
for the regeneration of kaingin fallow secondary forests (Chokkalingam et al., 2006). Smallholder
farmers living in the area usually grow abaca or coconut in their kaingin fallow land in order to
receive some cash benefits during the time of abandonment. Our study was, however, confined to
the areas where farmers planted only abaca since coconut plantations generally lead more intensive
land-management and as such secondary regrowth generally does not result.
3.3.3 Sampling protocol and vegetation survey
Chronosequence studies (i.e. space for time) are popular as an alternative to long-term
ecological research and have widely been used to investigate successional trends in tropical forests
(Norden et al., 2015; Pickett, 1989). We categorized our sites into four different fallow categories;
i.e. fallow less than (or equal to) 5 year old (SA0-5), hereafter referred to as new, 6-10 year old
fallow (SA6-10) hereafter referred to as young, 11-20 year old fallow (SA11-20) hereafter referred
to as middle-aged, and 21-30 year old fallow (SA21-30), hereafter referred to as oldest.
Additionally, old-growth forest (SF) without any history of major disturbances (i.e kaingin and
logging) located close to the fallow sites was sampled as our control. Our control old-growth forest
48
sites may have experienced little anthropogenic disturbance like much of the tropical forest, e.g.
source of wild edible fruits and game for meat, therefore for the clarity of the discussion were not
considered as the intact or primary forest.
Vegetation survey was undertaken from May to October 2013. We established 25 sites (5 categories
x 5 sites) in fallow areas and in old-growth forest representing a total sample area of 2.5 ha. In the
case of fallow secondary forests, we sampled from the sites that were at least 1 ha in size (Piotto et
al., 2009). We followed a modified Gentry plot approach for our vegetation survey (Gentry, 1982),
as it is the most efficient method of providing accurate estimates of tree diversity at the landscape
level (Baraloto et al., 2103). Four transects of 50 m x 5 m size (parallel to each other and with a
minimum of 5 m distance from each other) were established at each of our 25 sites. We recorded
diameter of each tree ≥5 cm at diameter at breast height (dbh) using a diameter tape. There were no
standing trees in two of our new fallow sites.
All trees were identified to the species level and named with the help of a local expert from Visyas
State University (VSU). Drawing upon the description in published literature and from the web,
additional information like the biogeographic origin (endemic, native or exotic), successional guild
(pioneer, secondary, and climax), and conservation status of the species as per the World
Conservation Union (IUCN, 2013) and local lists maintained by Philippines’ Department of
Environment and Natural Resources (DENR, 2007) were noted. For botanical description of species
we followed Roskov et al. (2013). In the case of unknown species we used the most common
Filipino name of that species.
3.3.4 Site environmental parameters
Both fallow age and fallow cycles are known to influence vegetation and soil parameters
and their recovery (Klanderud et al., 2010; Lawrence, 2005). Here we are only able to consider
fallow age and not fallow cycles because reliable information was not available from the
landowner. Other site attributes collected were - geographic position and altitude of the site,
distance from the nearest control old-growth forest, patch size, slope and soil organic carbon (SOC
%). We used a digital plant canopy imager (Model: CID Bio-Science, CI-110/120) for leaf area
index (LAI) measurement and a hand-held global positioning system (Model: Garmin eTrex) for
site altitude. Table 3.1 shows the summary of attributes recorded.
49
Table 3.1. Environmental attributes of our fallow sites and old-growth forest on Leyte Island, the
Philippines.
Site
attributes
Fallow category Old-growth
forest
0-5 year
F -value
6-10 year ≤5 year 6-10 year 11-20 year 21-30 year
Elevation
(m asl)
600.8
±22.19
549.0
±72.41
567.2
±49.24
574.8
±35.35
512.4
±54.77
2.18
Slope
(degree)
33 ±5.7 32.4 ±9.4 32.6 ±9.2 38.2 ±7.98 36.4 ±9.71 0.47
Patch area
(ha)
1.16 ±0.21 1.14 ±0.13 1.34 ±0.24 1.14 ±0.22 na -
Distance
(m)
290 ±74.16 540 ±114.01 162 ±198.17 256 ±153.88 0 11.97*
SOCǂ (%) 6.17 ±0.68 6.54 ±2.05 5.21 ±0.69 6.79 ±1.92 4.77 ±1.11 1.87
*F-value significant at p <0.01 level as indicated from ANOVA
ǂSource: Mukul et al. (in review).
3.3.5 Diversity and forest structure indices
Species diversity was described in terms of species richness (S), Shannon-Wiener’s diversity
index (H) and species evenness index (J). Shannon’s diversity index and species evenness index
were calculated as described in Magurran (2004) while species richness was the number of unique
tree species per site (see also – Supplementary Table 3.1). We used stem number (N), basal area
(B), and LAI as the measure of forest structure. Both, stem number and basal area (m2) were
expressed per site (0.1 ha) basis. Stem density or number was the number of tree individuals (≥5 cm
dbh) per site while basal area (m2) was the total cross-sectional area of all stems (≥5 cm dbh) in
each site. LAI was measured as the ratio between total leaf area and ground area as described in
Watson (1947).
3.3.6 Species composition and similarities
We used importance value (IV) index to compare tree species dominance pattern in each
fallow secondary forests and in control old-growth forest (Newton, 2007). IV was the sum of
relative density, relative dominance, and relative frequency of species (Curtis and Cottam, 1962).
Permutational multivariate analysis of variance (PERMANOVA) was also performed to test
whether species composition differed among different site categories, and a non-metric multi
dimensional scaling (nNMDS) to check species compositional similarities between different fallow
categories and old-growth forest.
50
3.3.7 Recovery of tree species diversity and forest structure
Recovery of the tree species diversity and forest structure were compared with the old-
growth forest. Our recovery represents how efficiently secondary forests may complement the old-
growth control forest. We, therefore, calculated recovery as the percentage of tree diversity and
forest structure relative to old-growth forest using the following equation.
R =( Xfallow / Xs) × 100
where is the measure of a diversity and/or forest structure parameter of fallow site, and Xs is
the mean of corresponding biodiversity and/or forest structure parameter in control old-growth
forest sites.
3.3.8 Data analysis
Statistical analysis was performed using ‘R’ Statistical package (version 3.0.1; R
Development Core Team, 2014). Analysis of variance (ANOVA) and Tukey’s post-hoc test was
performed to test for significant differences between the variables. We used ‘Biodiversity R’
(version 2.4-1; Kindt and Coe, 2005) and ‘vegan’ (version 2.0-10; Oksanen et al., 2010) for
calculating species richness and other biodiversity indices. For PERMANOVA and nMDS we used
Bray-Curtis similarity metric with 1000 iterations, starting with a random configuration (Valencia et
al., 2014), using the package ‘vegan’ (Oksanen et al., 2010).
Linear mixed-effect models (hereafter refer to as LMEM) were developed to examine the effect of
fallow age and site environmental attributes (see Table 3.1) on tree diversity and forest structure
recovery, using the package ‘nlme’ (Pinheiro et al., 2011). In our LMEM, fallow age (FA), slope
(SL), distance from nearest old-growth forest (DIS), patch size (PS) and soil organic carbon (SOC)
were used as explanatory variables (i.e. fixed factors), and site diversity (i.e. species richness,
Shannon’s index, Species evenness) and forest structure indices (i.e. stem number, basal area, LAI)
was the response variable. We used sites nested in fallow categories as the random effect in our
models. Due to its collinearity with other explanatory variable ‘elevation’ was excluded from final
LMEM (Supplementary Table 3.2). We considered Akaike Information Criterion corrected for
small sample sizes (AICc) for the selection of our top models, where the best models had the lowest
AICc scores (Johnson and Omland, 2004). For our model selection and to evaluate the contribution
different fixed effects had on explaining the variation in the response variables we used R-package
‘MuMin’ (Bartoń, 2011). We considered models within four AICc units to be competing models
(Grueber et al., 2011).
51
3.4 Results
3.4.1 Species and characteristics
Altogether, we censused 2918 tree individuals belonging to 131 species, 86 genera and 46
families in our 25 sites on Leyte Island, the Philippines (Annex 3.1). There were six species that
were unidentified comprising 0.02% of total individuals. Among the species, 14 belonged to the
family Moraceae, followed by Dipterocarpaceae (10 species), Phyllanthaceae (8 species), Fabaceae
(6 species), Euphorbiaceae, Lamiaceae (5 species) and Rubiaceae (5 species). At the landscape
level, 106 species were recorded alone from our oldest fallow sites, followed by 11-20 years old
fallow sites (95 species), and 79 species from the old-growth forest. We found 40 species that were
endemic to the Philippines. The highest number (37) of endemic species was recorded from the
oldest fallow sites, followed by in 11-20 year old fallow sites (30 species), young fallow sites (29
species) and in old-growth forest (27 species). Six exotic species were also recorded from the sites,
although there were no exotic species in the old-growth forest and in young fallow secondary forest.
The highest number of pioneer (49), secondary (46) and climax (11) species were recorded from the
oldest fallow sites (Figure 3.2). We found nine tree species that are critically endangered globally
(as per IUCN Red List) in our oldest fallow sites, and eight species in young fallow sites and our
middle-aged secondary forest sites (Figure 3.2).
Figure 3.2. Distribution and characteristics of species in different fallow categories and in old-
growth forest on Leyte Island, the Philippines.
52
3.4.2 Biodiversity and forest structure in regenerating secondary forests
Tree diversity and forest structure were varied significantly across our sites on Leyte Island,
the Philippines. This was the case whether these attributes were measured as species richness
(F4=30.79, p<0.01), Shannon’s diversity index (F4=12.39, p<0.01), species evenness (F4=1.66,
p<0.05), stem number (F4=54.1, p<0.01), basal area (F4=12.51, p<0.01) and in LAI (F4=26.48,
p<0.01). Post-hoc analysis using Tukey’s HSD showed species richness significantly higher
(p<0.01) in oldest fallow secondary forest followed by old-growth forest (45.2 ±4.21) and in the
middle-aged forest (39.2 ±9.52) (Figure 3.3). Both Shannon’s diversity index (3.37±0.11), species
evenness (0.88±0.02), stem number (145.8 ±16.53), tree basal area (7.81±2.23), and LAI were
significantly (p<0.001) higher in the old-growth forest.
Figure 3.3. Within and between variations of tree diversity (left) and forest structure (right) indices
across the sites on Leyte Island, the Philippines. Note the differences in scale on Y axes.
53
3.4.3 Species composition in regenerating secondary forests after shifting cultivation
Climax species had the highest IV in all fallow categories and in the old-growth forest
except in the case of young fallow sites (Table 3.2). Shorea polysperma showed the highest IV
(44.34) in new fallow sites, where in young fallow secondary forest Lithocarpus llanosil had the
highest IV (15.4). Parashorea malannoan had the highest IV both in old-growth forest (53.07),
middle-aged secondary forest (22.90) and in the oldest fallow secondary forest (24.63)
(Supplementary Figure 3.1).
We found a homogeneous pattern of species richness and abundance in our ordination. In nMDS,
species richness and abundance in secondary forests were clustered against our old-growth forest.
There was no distinct pattern in secondary fallow forests and control old-growth forest as in our
ordination all sites were spread out (Figure 3.4). The stress value of nMDS using species richness
and abundance was respectively 12.16 and 13.61. It was the same case for the species of global and
local conservation concerns (Supplementary Figure 3.2, 3.3). PERMANOVA using site category as
our main effect, however, showed a significant difference (F4 = 1.88; p < 0.001) in species
composition across our sites. Tukey’s HSD also confirmed significantly different species
composition between old-growth forest with new fallow (p < 0.001), young fallow (p < 0.05) and
middle-aged fallow secondary forest sites (p < 0.05).
Table 3.2. Top ten species with highest importance value in sites of different fallow categories and
in old-growth forest on Leyte Island, the Philippines.
Site
category
Species Relative
density
Relative
frequency
Relative
dominanc
e
IV
New fallow Shorea polysperma 3.71 3.33 37.30 44.34
Parashorea malaanonan* 7.41 3.33 23.30 34.04
Pterocarpus indicus 14.82 6.67 8.47 29.95
Calophyllum lancifolium 3.71 3.33 7.34 14.37
Siyao 1.85 3.33 9.12 14.30
Polyscias nodosa** 3.71 6.67 0.65 11.02
Ficus minahassae 7.41 3.33 0.23 10.97
Lithocarpus llanosii** 3.71 3.33 3.17 10.20
Shorea contorta 3.71 3.33 2.85 9.88
Piper anduncum 5.56 3.33 0.16 9.05
Young
fallow
Lithocarpus llanosii** 2.39 1.56 11.39 15.34
Polyscias nodosa** 7.15 2.08 3.90 13.13
Caryota cumingii*** 6.03 1.56 4.30 11.89
54
Ficus gul 5.75 2.61 3.23 11.58
Radermachera pinnate 3.93 2.08 4.50 10.51
Leucosyke capitellata 6.45 1.56 2.12 10.13
Ormosia calavensis 4.77 1.56 3.29 9.62
Parashorea malaanonan* 1.54 2.61 4.85 8.10
Horsfieldia costulata** 4.63 2.08 1.80 8.51
Bischofia javanica** 3.37 2.08 2.93 8.38
Middle-aged
fallow
Parashorea malaanonan* 2.70 2.04 18.16 22.90
Polyscias nodosa** 11.79 2.55 4.33 18.67
Shorea contorta 2.27 2.04 9.47 13.78
Leucosyke capitellata 8.52 2.55 1.78 12.85
Lithocarpus llanosii** 3.98 2.04 6.43 12.45
Bischofia javanica** 2.84 1.02 6.34 10.20
Horsfieldia costulata** 5.12 2.04 2.19 9.34
Ficus balete 1.42 1.02 6.68 9.12
Ficus minahassae 2.13 1.53 5.17 8.83
Radermachera pinnate 3.41 2.04 2.30 7.75
Oldest fallow Parashorea malaanonan* 4.46 2.18 17.99 24.63
Polyscias nodosa** 13.51 2.18 5.80 21.50
Shorea polysperma 1.95 1.31 10.03 13.29
Calophyllum blancoi 3.07 2.18 7.97 13.22
Lithocarpus llanosii** 3.76 1.75 5.74 11.25
Bischofia javanica** 3.62 1.75 4.47 9.84
Ficus gul 4.46 1.75 1.43 7.63
Horsfieldia costulata** 3.62 2.18 1.51 7.31
Caryota cumingii *** 3.62 1.75 1.42 6.78
Ormosia calavensis 2.65 1.75 1.67 6.07
Old-growth
forest
Parashorea malaanonan* 8.37 2.21 42.49 53.07
Bischofia javanica** 7.96 2.21 5.96 16.13
Caryota cumingii*** 11.39 2.21 1.50 15.10
Shorea guiso 4.25 2.21 2.85 9.32
Horsfieldia costulata** 5.21 2.21 1.74 9.16
Ficus balete 0.55 0.89 5.83 7.27
Petersianthus quadrialatus 1.10 1.33 4.61 7.04
Calophyllum blancoi 1.24 1.77 3.99 7.00
Canarium luzonicum 3.84 2.21 0.79 6.85
Palaquium luzoniense 2.20 2.21 2.19 6.60
Where: * - species common across all site categories, ** - species common across at least four site
categories, and *** - species common acroos at least three site categories.
55
Figure 3.4. nMDS of species richness (stress=12.16) and abundance (stress=13.61) using Bray-
Curtis distance.
3.4.4 Tree diversity and forest structure recovery along a shifting cultivation fallow gradient
The recovery of tree diversity and forest structure with respect to the old-growth forest were
significantly different across our secondary forest sites as measured by species richness (F3 = 17.39;
p < 0.00), Shannon’s index (F3 = 9.52; p < 0.001), stem number (F3 = 36.06; p < 0.00) and LAI (F3
= 16.28; p < 0.00). There were, however, no significant differences in the recovery of species
evenness (F3 = 2.43; p = 0.10) and basal area (F3 = 2.34; p < 0.11) across our sites (Figure 3.5).
Recovery of tree diversity in terms of species richness (101.33±13.13) and Shannon’s diversity
index (98.87±4.78) was highest in the 21-30 year old fallow sites. Recovery of forest structure
parameters, including stem number (98.49±3.05) and basal area (50.15±17.80) was also highest in
the oldest fallow sites. Our post-hoc analysis using Tukey’s HSD revealed significantly low (p <
0.05) recovery of species richness, Shannon’s index, stem number and LAI in the new fallow sites
compared to sites of other fallow categories.
56
Figure 3.5. Recovery of tree diversity (left) and forest structure (right) in relation to old-growth
forest on Leyte Island, the Philippines. Note the differences in scales on Y axes.
3.4.5 Environmental controls on the recovery of secondary forest diversity and structure
Our multiple candidates LMEM models explained the differences in species diversity and
forest structure recovery in tropical secondary forests after shifting cultivation (Table 3.3). For all
response variables, models that included patch size explained as much variation as other more
complex models that included interactions (as all models within ∆AICc= 4 were considered
equivalent) (Table 3.4). Other than patch size, soil organic carbon and fallow age were also found to
57
explain variation in the recovery of different biodiversity and forest structure parameters. Distance
from old-growth control forest was not retained in any of the best-fit candidate models.
Table 3.3. Summary of mixed effect models (within ∆ AICc = 4) obtained using package MuMin
(Bartoń, 2011). Where, S= species richness, H= Shannon’s index, J= species evenness, N= stem
number, BA= basal area, LAI= leaf area index, FA = fallow age, DIS= distance from the nearest
control forest, SL= slope, PS= patch size, SOC= soil organic carbon.
Response variables Site environmental attribute DF LL
AICc ∆ AICc
Weight
FA DIS SL PS SOC
S
X X 6 -69.93 159.50 0.0 0.36
X 5 -72.59 160.19 0.69 0.26
X X 6 -70.52 160.68 1.18 0.20
X X X 7 -67.85 160.9 1.4 0.18
H
X 5 -65.48 145.96 0.0 0.39
X X 6 -63.67 146.97 1.02 0.23
X X 6 -63.68 146.99 1.03 0.23
X X X 7 -61.84 148.89 2.93 0.09
X X 6 -64.98 149.6 3.64 0.06
J
X X 6 -49.31 118.26 0.0 0.57
X 5 -51.9 118.8 0.55 0.43
N
X X 6 -68.1 155.83 0.0 0.29
X X X 7 -65.69 156.58 0.76 0.2
X X 6 -68.83 156.91 1.08 0.17
X 5 -71.06 157.12 1.3 0.15
X X 6 -69.53 158.7 2.87 0.07
X 5 -71.94 158.89 3.06 0.06
X X 6 -69.69 159.01 3.19 0.06
BA
X X 6 -69.76 159.17 0.0 0.18
X 5 -72.27 159.53 0.37 0.15
X X 6 -70.05 159.73 0.56 0.14
X X X 7 -67.37 159.94 0.77 0.12
X X X 7 -67.39 159.99 0.82 0.12
X X 6 -70.36 160.35 1.19 0.1
X X X 7 -68.22 161.65 2.48 0.05
X X 6 -71.26 162.16 2.99 0.04
X X 6 -71.47 162.57 3.41 0.03
X X X X 8 -65.3 162.6 3.43 0.03
X 5 -73.91 162.82 3.65 0.03
LAI
X 5 -70.67 156.35 0.0 0.35
X X 6 -68.72 157.07 0.72 0.25
X X 6 -68.72 157.08 0.74 0.24
X X X 7 -66.76 158.71 2.37 0.11
X X 6 -70.31 160.25 3.9 0.05
58
*DF- degree of freedom, LL- log likelihood, AICc - Akaike information criterion corrected for small
sample size.
Table 3.4. The relative importance of site environmental attributes in the final LMEM.
Where, S= species richness, H= Shannon’s index, J= species evenness, N= stem number, BA= basal
area, LAI= leaf area index, FA= fallow age, PS=patch size, SL= slope, DIS= distance from the
nearest control forest, SOC= soil organic carbon.
Site indices Site environmental attribute* Number
of models FA PS DIS SL SOC
S 0.54 (2) 1.0 (4) - - 0.38 (2) 4
H 0.32 (2) 1.0 (5) - 0.06 (1) 0.32 (2) 5
J - 1.0 (2) - - 0.57 (1) 2
N 0.44 (3) 0.87 (5) - 0.06 (1) 0.62 (4) 7
BA 0.49 (6) 0.9 (8) - 0.35 (5) 0.45 (6) 11
LAI 0.35 (2) 1.0 (5) - 0.05 (1) 0.35 (2) 5
*values in the parenthesis indicates the number of models containing respective explanatory
variable.
3.5 Discussion
3.5.1 Biodiversity conservation and secondary forest development after shifting cultivation
Our study revealed rapid recovery and high resilience of regenerating secondary forests after
disturbed by shifting cultivation and their importance in species conservation at the landscape level.
Recovery of tree diversity was more rapid than forest structure in the area. Although, there was a
substantial decrease in biodiversity in the first five years, but our older fallow sites exhibited similar
levels of biodiversity and were similar to old-growth forest. The measures of biodiversity we used
(species richness, Shannon’s index and species evenness) and chronosequence approach have been
widely used to investigate the successional development of forests after disturbances (Mukul and
Herbohn, 2016; Norden et al., 2015; Baraloto et al., 2013). We found that Shannon’s index and
species evenness index were higher in old-growth forest and species richness was higher in the
oldest fallow sites. Recently abandoned fallow areas represented by our new fallow sites
demonstrated a very distinct pattern of species diversity compared to the other much older fallow
categories in our study. A similar observation was made by Klanderud et al. (2010) in Madagascar
who found subsequent shrub dominance after the abandonment of shifting cultivation inhibiting tree
diversity in the area. Young fallow areas have less diversity of adult tree species (Schmook, 2010;
Miller and Kaffman, 1998), and woody species become prominent in secondary fallow forests after
about ten years (Klanderud et al., 2010; Rahamiralala et al., 2010; Gemerden et al., 2003). Some
59
studies suggest that secondary forest, for example, after selective logging, can exhibit better forest
structure in terms of basal area than undisturbed forest (e.g. Ding et al., 2012; Castro-Luna et al.,
2011), although the conservation value of such landscapes are not always high when considering
the diversity of forest specialist species (Mo et al., 2011; Fredericksen and Mostacedo, 2000). In our
study, however, we found a reasonably greater forest structure in the old-growth forest. Despite the
comparable species richness and abundance in older fallow sites and in old-growth forest, tree basal
area was significantly higher in the old-growth forest which may be attributed by the presence of
large diameter and canopy trees in relatively undisturbed forests (Mo et al., 2011).
Despite a relatively homogeneous species composition our new fallow sites showed limited
overlaps in species composition within the old-growth forest and older fallow secondary forests.
Species composition and reassembly regarded as key aspects of forest recovery study after
disturbances (Valencia et al., 2014; Slik et al., 2008), and several studies reported that similarity
between undisturbed forests and fallow regenerating fallow forests increase with an increase in the
abandonment age (see – Norden et al., 2009; Piotto et al., 2009; Lawrence, 2004). In our nMDS
ordination, two of the new fallow sites were wholly spread out, which may be a consequence of the
intensity of past usage represented by fallow cycles that were not incorporated in our analysis.
Interestingly, when considering IV of species on our sites, some dipterocarp species (e.g.
Parashorea malaanoan) were found dominant across all sites which may be also attributed to
remnant large canopy trees not interfering during agricultural use of the sites (Hager et al., 2014;
Dawson et al., 2013).
Recovery of species richness and Shannon’s index was rapid in older fallow sites, although there
was no significant difference in the recovery of species evenness. Recovery of stem density
increased gradually with the fallow age. Recovery of stand basal area was distinct across the sites
and was more inclined to our older fallow sites, an indication of more large and mature trees in
those sites. In tropical forests the degree to which a forest recovered after disturbance is uncertain
(Ding et al., 2012), although it is acknowledged that tropical forests after disturbances can recover
in terms of species richness and stand structure (see – Letcher and Chazdon, 2009; Cannon et al.,
1998). Unlike Martin et al., (2013), Letcher and Chazdon (2009) and Slik et al., (2008), who found
rapid recovery of forest structure parameters over diversity during secondary forest succession, we
found rapid recovery of forest tree diversity in our study sites.
60
3.5.2 Controls of site environmental conditions in forest recovery after shifting cultivation
Patch size influences the recovery of species diversity and composition in our sites, and
patch size on its own was found to have similar explanatory power for recovery of forest diversity
and structure to more complicated models that include interactions of fallow age, slope and soil
organic carbon. Echeverría et al. (2007) also found patch size as the single most important factor
influencing both species composition and stand structure in terms of basal area and stem density.
Both fallow age and fallow cycles influence the intensity of past forest use (Schmook, 2010;
Lawrence, 2004), although, in our analysis, we only included the fallow age (as the cycle was not
known). Biodiversity recovery in tropical disturbed secondary forests may depend on the remaining
forest cover (Arroyo-Rodriguez et al., 2008), although the intensity of past use is a stronger
predictor of forest recovery than edaphic environmental variables, highlighting the importance of
humans in shaping tropical forest dynamics (Mukul et al., 2016; Ding et al., 2012; Castro-Luna et
al., 2011; Klanderud et al., 2010).
While our study was limited to only soil organic carbon, which is an important indicator of soil
fertility, our findings support those of Paoli et al. (2008) who found soil nutrients positively
influence the recovery of forest structure parameters like basal area. We, however, found no
significant effect of distance from the nearest old-growth forest on the recovery of any of the
parameters studied in this study. Studies on secondary forest dynamics have demonstrated that
diversity of woody species increases gradually with time, although the rate of recovery differs
depending on site geographic location and associated environmental parameters (see - Ehrlen and
Morris, 2015; Chazdon, 2014; Martin et al., 2013; Uddin et al., 2013; Klanderud et al., 2010;
Lawrence et al., 2010; Piotto et al., 2009; Sovu et al., 2009; Read and Lawrence, 2003; Thompson
et al., 2002). Previous studies (e.g. Ding et al., 2012; Schmook, 2010; N’Dja and Decocq, 2008)
have reported that secondary forests may require different durations to attain the diversity and
structure of an undisturbed forest after they have been abandoned. Fallow age however, did not
affect the recovery of forest diversity measures when a common species pool occurs across the sites
(Sovu et al., 2009). Slope of the stand was found to influence the stem number where highest stem
density can be found in the down-slope and vice versa (Ding et al., 2006). Connectivity to primary
forests increases forest regeneration by influencing natural processes like pollination and seed
dispersal (Hager et al., 2014; Echeverria et al., 2007) although in our study it was not important. A
declining trend in species richness with increasing distance to primary forest edge, however, may
found (Sovu et al., 2009).
61
3.5.3 Implications for conservation and forest landscape management
Our study confirms that regenerating tropical forests have the ability to recover after shifting
cultivation, although site factors (patch size in our case) may be important during this recovery
process. Throughout the tropics, secondary forests are expanding dramatically, and in many
countries, they have already exceeded the total area covered by remaining primary or old-growth
forests (McNamara et al., 2012; FAO, 2005; Chazdon et al., 2003). Those forests emerged after
deliberate human use, and interventions are increasingly considered as a novel and/or emerging
ecosystem with a different structure and species composition than previous land-use/cover (Hobbs
et al., 2009; 2006). The successful maintenance of tree diversity in such novel ecosystems offers
important synergies for conservation, as high plant diversity is associated with higher wildlife
diversity (Koh and Ghazoul, 2010; Chazdon et al., 2009). In the case of the Philippines, secondary
forest covers a large area and represent a highly dynamic ecosystem, making biodiversity
conservation a daunting challenge in the country (Posa et al., 2008; Lasco et al., 2001).
We found that old kaingin fallow areas can also support relatively high numbers of rare and
endangered species and thus can play an important role in their conservation. This is contrary to
previous views that fallow landscapes are unfavorable for the maintenance forest biodiversity (see -
Mo et al., 2011; Gemerden et al., 2003). The population status of rare and endemic species are
highly relevant to the prioritization of conservation efforts globally (Peque and Holscher, 2014;
Kier et al., 2009). Tropical forest-agriculture frontiers also provide important clues for conservation
in complex, heterogeneous landscapes (Kumaraswamy and Kunte, 2013). We found that the
number of endemics, climax and red-listed species was greater in relatively oldest fallow secondary
forests. A number of dipeterocarp species, including Hopea philippinensis, Shorea polysperma,
Shorea contorta – that are equally important for conservation both globally and locally, were shared
among secondary forests of different fallow categories and in old-growth forest, indicates high
conservation potential of such landscapes.
3.6 Conclusions
It is clear that regenerating forests after shifting cultivation have the potentials to offset the
tropical forests and biodiversity loss and have high resilience or recovering capacity. In the study
species composition in secondary forests with fallow age more than five years were similar to the
less disturbed old-growth forest, indicating a continious accumulation of species richness and
abundance with fallow age. Recovery of tree diversity was rapid compared to the forest structure,
and in all cases, young fallow secondary forest showed a divergent pattern of forest structure and
diversity than that of our older fallow secondary forest categories. Although shifting cultivation has
62
a negative reputation for degradation and loss of tropical rainforests, little attention has been paid to
study secondary forest dynamics in such complex landscapes. Our study indicates that novel
ecosystems such as tropical fallow secondary forests that arise after deliberate human intervention
exhibits high resilience and can act as a low-cost refuge for biodiversity conservation. Such
landscape can also serve as a low restoration measure in tropical developing countries where
shifting cultivation is common.
3.7 Additional information
Supplementary Tables 3.1, 3.2, and Supplementary Figures 3.1, 3.2, 3.3, related to this
chapter/manuscript is provided at the end of this thesis under the section – Appendices.
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Annex 3.1. List of tree species recorded from the sites in Gaas on Leyte Island, the Philippines.
Family Botanical name1 Local name Abundance Origin2 Conservation status Successional
guild5 ≤ 5 year
fallow
6-10 year
fallow
11-20 year
fallow
21-30 year
fallow
Old-growth
forest
IUCN3 DENR4
Alangiaceae Alangium javanicum (Bl.) Wang Putian - 4 3 3 5 Native LR NA Secondary
Anacardiaceae
Dracontomelon dao (Blanco) Merr. &
Rolfe
Dao
- 2
3 1 2 Native
NA
V Secondary
Dracontomelon edule (Blanco) Skeels. Lamio
- 2 1 1 Native
NA
V Secondary
Annonaceae
Cananga odorata (Lam.) Hook. f. &
Thomson
Ilang-ilang
- 1
- - - Native
NA
NA Secondary
Polyalthia oblongifolia Burck Lapnisan - 6 2 6 1 Native NA NA Secondary
Polyalthia flava Yellow
lanutan
- 7 4 1 8 Endemic NA NA Secondary
Apocynaceae
Alstonia macrophylla G. Don Batino - 5 4 5 - Native LR NA Pioneer Alstonia parvifolia Merr. Batino-liitan - - 3 - - Endemic NA NA Pioneer
Wrightia pubescens R.Br. Lanete 1 9 13 9 2 Native NA NA Pioneer
Kibatalia gitingensis (Elmer) Woodson Laneteng-gubat
- 1 1 17 8 Endemic
V
CE Secondary
Araliaceae
Arthrophyllum cenabrei Merr. Bingliu - - 9 - - Endemic NA NA Pioneer
Polyscias nodosa (Blume) Seem. Malapapaya 2 51 83 97 14 Native NA NA Pioneer
Arecaceae
Areca cathecu L Bunga - - 5 8 - Native NA NA Secondary Cocos nucifera L. Coconut - - - 5 - Native NA NA Pioneer
Caryota cumingii Lodd. ex Mart. Pugahan - 43 25 26 83 Native NA NA Pioneer
Heterospathe elata Scheff. Sagisi - 6 6 2 15 Native NA NA Pioneer
Bignoniaceae
Radermachera pinnate (Blanco) Seem. Banai-Banai
2 28 24 11 2 Native
NA
NA Secondary
Burseraceae
Canarium hirsutum Milipili - - 2 6 1 Native NA NA Secondary
Canarium calophyllum Perkins. Pagsahingin-
bulog
1 11 10 8 12 Native
NA
NA
Secondary
Canarium luzonicum (Blume) A.Gray Piling-liitan - 2 3 6 28 Endemic
V
NA Pioneer
Calophyllaceae Calophyllum lancifolium Elmer. Bitanghol-
sibat
2 3 - 2 - Native NA NA Secondary
Cannabaceae
Trema orientalis (L.) Bl. Anabiong 1 - - - 2 Native NA NA Pioneer Celtis philippensis Blanco Malaikmo - - - 1 4 Native NA NA Secondary
Casuarinaceae
Casuarina equisetifolia L. Agoho 1 - 1 - - Exotic NA NA Pioneer
Gymnostoma rumphianum (Miq.) L.A.S. Johnson
Mountain agoho
1 - - 1 - Native NA NA Secondary
Clusiaceae
Calophyllum blancoi Planch. & Triana Bitanghol
- 7 7 22 9 Native
NA
NA Secondary
Combretaceae Terminalia microcarpa Decne. Kalumpit - - 2 - - Native NA NA Secondary
Cycadaceae Cycas circinalis L. Pitogo - - 1 - - Native E NA Pioneer
Datiscaceae Octomeles sumatrana Miq. Binuang - - - 1 - Native LR NA Secondary
Dilleniaceae
Dillenia indica L. Handapara - 2 - 4 - Native NA NA Secondary
Dillenia philippinensis Rolfe Katmon - 2 6 5 6 Endemic V NA Secondary
Dipterocarpaceae
Shorea almon Foxw. Almon - 2 - 3 Endemic CE V Climax Parashorea malaanonan (Blanco)
Merr.
Bagtikan
4 11 19 32 61 Native
NA
NA Climax
72
Dipterocarpus eurynchus Miq. Basilanapiton
g
- - 1 - - Endemic CE E Secondary
Hopea philippinensis Dyer Gisok-gisok - 7 3 2 20 Endemic CE CE Pioneer
Shorea guiso (Blanco) Blume Guijo - 15 8 4 31 Native CE NA Pioneer Shorea palosapis (Blanco) Merr. Mayapis - 3 9 5 12 Endemic CE NA Climax
Anisoptera thurifera Palosapis - - - 1 - Native NA NA Secondary
Shorea polysperma (Blanco) Merr. Tangile 2 6 8 14 5 Endemic CE V Climax Shorea contorta Vidal White lauan 2 5 16 6 4 Endemic CE V Climax
Hopea malibato Yakal-kaliot - - - 1 - Native CE CE Climax
Ebenaceae
Diospyros pilosanthera Blanco Bolong-eta - 1 4 9 3 Native NA E Secondary
Diospyros blancoi A.DC. Kamagong - 1 3 - 1 Native V CE Climax
Euphorbiaceae
Neotrewia cumingii (Müll.Arg.) Pax & K.Hoffm.
Apanang
- 3 3 2 4 Native
NA
NA
Pioneer
Mallotus philippensis (Lam.) Müll.Arg. Banato
- 2 - - - Native
NA
NA
Secondary
Macaranga tanarius (L.) Müll.Arg. Binunga - 5 4 2 7 Native NA NA Pioneer
Macaranga bicolor Muell. -Arg. Hamindang - 9 1 8 5 Endemic V NA Pioneer
Mallotus ricinoides (Pers.) Müll.Arg. Hinlaumo
1
5
12 5 - Native NA NA Pioneer
Fabaceae
Ormosia calavensis Blanco Bahai - 34 3 19 2 Endemic NA NA Climax
Albizia falcataria (L.) Fosberg. Falcata - 5 6 - Exotic NA NA Secondary Leucaena leucaephala (Lam.) de Wit. Ipil-ipil
- - 7 3 - Exotic
NA
NA
Pioneer
Pterocarpus indicus Willd. Narra 8 - - - - Native V NA Secondary Albizia saponaria(Lour.) Blume ex
Miq.
Salingkugi
- 4 - 3 8 Native
NA
NA
Secondary
Senna siamea (Lam.) Irwin et Barneby Thailand shower
- - 2 1 - Native
NA
NA
Secondary
Fagaceae Lithocarpus llanosii (A.DC.) Rehder Ulaian 2 17 28 27 16 Native NA NA Pioneer
Hypericaceae Cratoxylum celebicum Bl. Paguriagon - 4 2 11 4 Native NA NA Secondary
Lamiaceae
Vitex quinata (Lour.) F. N. Williams Kalipapa
- - 1 - 10 Native
NA
NA
Pioneer
Vitex turczaninowii (Turcz.) Merr. Lingo-lingo - - - - 1 Endemic NA NA Secondary
Premna cumingiana Schauer Magilik 1 - - - 2 Native NA NA Secondary
Tectona grandis L. f. Teak - - - 1 - Exotic NA NA Pioneer Callicarpa elegans Hayek Tigau-ganda - - - 2 - Endemic NA NA Pioneer
Lauraceae
Cinnamomum cebuense Kostermans Kaningag - 2 2 2 - Endemic CE NA Pioneer
Litsea perrottetii (Bl.) Villar. Marang - 5 2 8 4 Native NA NA Secondary Neolitsea vidalii Merr. Puso-puso - 7 3 6 Endemic V NA Secondary
Lecythidaceae
Barringtonia racemosa Spreng. Putat - 3 4 6 11 Native NA NA Pioneer
Petersianthus quadrialatus (Merr.) Merr.
Toog
- - - 1 8 Endemic
NA
NA
Pioneer
Malvaceae
Diplodiscus paniculatus Turcz. Balobo - 9 5 7 5 Endemic V NA Secondary
Pterospermum obliquum Blanco Kulatingan - - - 1 2 Endemic NA NA Pioneer
Melastomataceae Astronia cumingiana S.Vidal Badling - 4 8 7 3 Native CE NA Pioneer
Meliaceae
Dysoxylum decandrum Merrill. Igyo - 2 3 2 6 Native NA NA Pioneer Toona philippinensis Elmer. Lanigpa - 1 3 5 4 Native NA NA Pioneer
Dysoxylum cumingianum C. DC. Tara-tara - 4 6 13 10 Native NA NA Pioneer
Moraceae
Artocarpus blancoi (Elmer) Merr. Antipolo 1 6 5 4 7 Endemic V NA Pioneer Artocarpus ovatus Blanco Anubing - - - 2 - Endemic NA NA Pioneer
73
Ficus irisana Elmer. Aplas - 5 9 7 1 Native NA NA Pioneer
Ficus balete Merr. Balete 1 9 10 - 4 Native NA NA Pioneer
Ficus gul K. Schum. & Lauterb. Butli 3 41 19 32 18 Native NA NA Secondary
Ficus minahassae (Teijsm. & De Vriese) Miq.
Hagimit
4 19 15 4 4 Native
NA
NA
Secondary
Ficus septica Burm. f. Hauili 2 3 18 - Native NA NA Secondary
Ficus ulmifolia Lam. Is-is - 3 1 2 1 Endemic V NA Pioneer Ficus callosa Willd. Kalukoi - - 2 1 - Native NA NA Pioneer
Ficus magnoliifolia Blume Kanapai - 6 2 1 - Native NA NA Secondary
Ficus odorata (Blanco) Merr. Pakiling - 1 1 5 - Endemic NA NA Climax Ficus vrieseana Miq. Tagitig - - - 1 1 Native NA NA Secondary
Ficus nota Merr. Tibig 1 21 17 2 7 Native NA NA Pioneer
Ficus ampelas Burm. f Upling-gubat 12 1 - 6 Native NA NA Pioneer
Myricaceae Myrica javanica Reinw. ex Bl. Hindang 1 - - - 3 Native NA NA Secondary
Myristicaceae
Knema mindanaensis (Warb.) comb.
nov.
Bunod
- 1
3 5 - Endemic
NA
NA
Secondary
Parartocarpus venenosus (Zoll. &
Morr.) Becc. ssp. papuanus (Becc.) Jarr.
Malanangka
1 2 2 2 4 Native
NA
NA Pioneer
Horsfieldia costulata (Miq.) Warb. Yabnob - 33 36 26 38 Native NA NA Pioneer
Myrsinaceae
Ardisia pyramidalis (Cav.) Pers. ex A. DC.
Aunasin
- 8 6 4 12 Native
NA
NA
Secondary
Myrtaceae
Syzygium surigaense (Merr.) Merr. Kagagko - - - 2 3 Endemic NA NA Secondary
Syzygium crassilimbum (Merr.) Merr. Kaitatanag
- 1 1 2 - Endemic
NA
NA
Secondary
Syzygium gigantifolium (Merr.) Merr. Malatalisai
- 4 4 4 Endemic
NA
NA
Secondary
Syzygium hutchinsonii (C.B.Robinson) Merr.
Malatambis
1 10 11 12 5 Endemic
NA
NA
Secondary
Xanthostemon verdugonianus Naves Mangkono
- - - 2 2 Endemic
V
NA
Pioneer
Olacaceae
Strombosia philippinensis (Baill.) Rolfe Tamayuan
- 12 14 14 16 Endemic
NA
NA
Secondary
Pandanaceae
Pandanus radicans Blanco
Ulangong-
ugatan
- - - 2 - Endemic
NA
NA
Pioneer
Phyllanthaceae
Securinega fIexuosa (Muell. -Arg.) Anislag - 6 4 6 - Endemic NA NA Pioneer
Antidesma ghaesembilla Gaertn. Binayuyu - 13 - 3 3 Native NA NA Climax
Glochidion camiguinense Merr. Bunot-Bunot - 8 3 10 2 Endemic NA NA Pioneer Glochidion album (Blanco) Boerl. Malabagang - 1 1 2 3 Native NA NA Pioneer
Breynia rhamnoides Müll.Arg. Matang-hipon - 3 2 2 - Native NA NA Pioneer
Cleistanthus venosus C.B. Rob. Sarimisim - 2 1 - Endemic NA NA Secondary Bridelia penangiana Hook.f.Bridelia
insulana Hance
Subiang
- 3 1 1 8 Native
NA
NA
Secondary
Bischofia javanica Blume Tuai - 24 20 26 58 Native NA NA Secondary
Piperaceae Piper anduncum L. Spiked pepper 3 - 3 1 5 Native NA NA Pioneer
Rhizophoraceae Carallia brachiata (Lour.) Merr. Bakauan-
gubat
- 4 2 1 1 Native NA NA Secondary
Rubiaceae
Neonauclea formicaria (Elmer) Merr. Hambabalud
- 6
7 7 2 Endemic
NA
NA
Pioneer
74
Mussaenda philippica A.Rich. Kahoi-dalaga 1 1 - - - Native NA E Secondary
Neonauclea bartlingii (DC.) Merr. Lisak - 1 6 4 5 Endemic NA NA Secondary
Canthium fenicis (Merr.) Merr. Mapugahan - 2 - 4 - Endemic NA NA Pioneer
Canthium monstrosum (A. Rich.) Merr. Tadiang-anuang
- 4 1 1 - Native
NA
NA
Pioneer
Rutaceae Melicope triphylla (Lam.) Merr. Matang-arau - 4 4 3 1 Endemic NA NA Pioneer
Sapindaceae Nephelium lappaceum Rambutan - - 1 - - Native LR NA Pioneer
Sapotaceae
Planchonella nitida (Blume) Dubard. Duklitan
- - 1 9 - Exotic
NA
NA
Secondary
Palaquium luzoniense (Fern.-Vill.)
Vidal
Nato
- 11 2 8 16 Endemic
V
V
Secondary
Sterculiaceae Pterospermum diversifolium Bl. Bayok - - 4 1 1 Native NA NA Pioneer
Tiliaceae
Trichospermum involucratum (Merr.)
Elmer
Langosig
- - 1 - - Endemic
NA
NA
Pioneer
Urticaceae
Leucosyke capitellata (Pair.) Wedd. Alagasi 3 46 60 5 7 Native NA NA Pioneer
Pipturus arborescens (Link) C. B. Rob. Dalunot
-
-
1 8 - Native
NA
NA
Pioneer
Dendrocnide stimulans (L. f) Chew Lingaton - - - 1 - Native NA NA Pioneer
Verbenaceae
Premna odorata Blanco Alagau 1 - 2 - - Native NA NA Secondary Premna stellate Merr. Manaba - - 1 - - Native NA NA Secondary
Vitaceae Leea aculeata Bl. Amamali - 1 3 - 5 Native NA NA Pioneer
Unknown
Anungo - 8 2 4 18 - - Secondary
Nandamai - - - 1 - - - Pioneer Pandukaki - - - 1 - - - Pioneer
Pegonngon - - - 1 - - - Secondary
Poelig - 13 1 1 - - Pioneer Siyao 1 - - - - - Pioneer
1whenever possible species name was followed as per Species 2000 & ITIS Catalogue of Life, 2014 Annual Checklist (available online at:
www.catalogueoflife.org/annual-checklist/2014/). 2where Endemic - refers to a species found only in the Philippines, Native – refers to a species naturally occurring in the Philippines and Exotic – refers to a species
that has been introduced in the Philippines. 3as per IUCN Red List of Threatened Species (available online at: http://www.iucnredlist.org), where:
CE or Critically endangered – refers to a species or subspecies facing extremely high risk of extinction in the wild in the immediate future.
Endangered - refers to a species or subspecies that is not critically endangered but whose survival in the wild is unlikely if the causal factors continue
operating.
V or Vulnerable - refers to a species or subspecies that is not critically endangered nor endangered but is under threat from adverse factors throughout its range
and is likely to move to the endangered category in the future.
LR or Lower risk – refers to a species that has been evaluated, but does not satisfy the criteria for any of the categories Critically Endangered, Endangered or
Vulnerable.
NA or Not available/Not assessed – refers to a species that has not yet been assessed against the criteria. 4as per DENR Adminsitrative Order No. 2007.01, where:
75
CE or Critically endangered - refers to a species or subspecies facing extremely high risk of extinction in the wild in the immediate future. This shall include
varieties, I formae or other infraspecific categories;
E or Endangered - refers to a species or subspecies that is not critically endangered but whose survival in the wild is unlikely if the causal factors continue
operating. This shall include varieties, formag or other infraspecific categories;
V or Vulnerable - refers to a species or subspecies that is not critically endangered nor endangered but is under threat from adverse factors throughout its range
and is likely to move to the endangered category in the future. This shall include varieties, formae or other infraspecific categories; 5based on experts opinion from the Philippines.
76
CHAPTER 4: TROPICAL SECONDARY FORESTS REGENERATING AFTER
SHIFTING CULTIVATION IN THE PHILIPPINES UPLANDS ARE IMPORTANT
CARBON SINKS
May cite as – Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after
shifting cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6,
22483.
4.1 Abstract
In the tropics, shifting cultivation has long been attributed to large scale forest degradation, and
remains a major source of uncertainty in forest carbon accounting. In the Philippines, shifting
cultivation, locally known as kaingin, is a major land-use in upland areas. We measured the
distribution and recovery of aboveground biomass carbon along a fallow gradient in post-kaingin
secondary forests in an upland area in the Philippines. We found significantly higher carbon in the
aboveground total biomass and living woody biomass in old-growth forest, while coarse dead wood
biomass carbon was higher in the young fallow secondary forest. Aboveground total biomass
carbon in our new, young, moderately aged and oldest fallow sites were 160.3 Mg ha-1
, 101.09 Mg
ha-1
, 122.41 Mg ha-1
, and 132.54 Mg ha-1
respectively compared to 321.29 Mg ha-1
in old-growth
forest. The high level of aboveground biomass carbon in new fallow sites was due mainly to high
levels of coarse dead wood remaining as an artefact of clearing. For young through to the oldest
fallow sites, there was a progressive recovery of biomass carbon evident. Multivariate analysis
indicates patch size as an influential factor in explaining the variation in biomass carbon recovery in
secondary forests after shifting cultivation. Our study indicates secondary forests after shifting
cultivation are substantial carbon sinks and that this capacity to store carbon increases with
abandonment age. Large trees contribute most to aboveground biomass, with one species,
Parashorea malaanonan, contributing 33.2% to the overall living wood biomass across the sites. A
better understanding of the relative contribution of different biomass sources in aboveground total
forest biomass, however, is necessary to fully capture the value of such landscapes from forest
management, restoration and conservation perspectives.
Key-words: biomass carbon; regenarating forest; shifting agriculture; REDD+; Southeast Asia.
4.2 Introduction
Secondary forests comprise more than half of the total forest area in tropical regions and are
the dominant forest type (FAO, 2010). In the tropics, secondary forests also represent a major
77
global carbon sink that rapidly accumulates carbon in aboveground biomass (Pan etal., 2011; Eaton
and Lawrence, 2009; Malhi et al., 2006). Because they cover a large area in the tropics, accurate
estimates of carbon in secondary forests are critical for quantifying the global carbon balance as
well as for the successful implementation of climate change mitigation projects (Chave et al., 2014).
However, there remains a high level of uncertainty in tropical forest carbon accounting, firstly due
to the unknown amount of deforestation and forest degradation (Malhi, 2010), and secondly due to
a limited number of field studies that have estimated standing biomass in secondary forests (Chave
et al., 2005). In fact, globally tropical deforestation and forest degradation accounts for
approximately 15-35% of anthropogenic carbon emissions (DeFries et al., 2002), and reversing this
trend has a clearly recognized potential for recovering the stocks of forest biomass carbon and for
other forest conservation outcomes (Houghton, 2012).
Shifting cultivation or ‘slash-and-burn agriculture’ is a traditional land-use practice in tropical
forested landscapes, and is a dominant land-use in rural upland areas in the developing countries
(Mertz et al., 2009). In the tropics, shifting cultivation has also been seen as the primary source of
deforestation and forest degradation for many years (Lawrence et al., 2010; Fox et al., 2009).
Historically, shifting cultivation has been viewed negatively as contributing to many forms of
environmental degradation, including loss of biodiversity and biomass carbon in forests (van Vliet
et al., 2012). Accordingly, throughout much of the tropics, governments have developed policies to
control or reduce the practice of shifting cultivation by smallholder rural farmers (Fox et al., 2009).
In Southeast Asia, secondary forests constitute around 63% of the total forest area (Koh, 2007), with
an estimated 14-34 million people dependent on shifting cultivation for their livelihoods (Mertz et
al., 2009). The extent of land under shifting cultivation however has declined in recent years due to
government policies restricting shifting cultivaton and economic factors that promoted other land-
use systems (van Vliet et al., 2012; Fox et al., 2009). Consequently, in many parts of this region
regenerating secondary forests following shifting cultivation are becoming prominent (Pelletier et
al., 2012; Lawrence et al., 2010; Mertz et al., 2009). Due to the dynamic nature of the landscape,
shifting cultivation and its changes over time have been very difficult to delineate using satellite
based earth observation systems (Houghton, 2012; Pelletier et al., 2012). In Southeast Asia there is
also a lack of spatially explicit knowledge of the forest biomass carbon stocks and carbon dynamics
associated with shifting cultivation landscapes. This has limited the inclusion of these landscapes in
current negotiations on Reducing Emissions from Deforestation and Forest Degradation (REDD+)
in the region to achieve the dual objectives of community development and forest conservation
(Ziegler et al., 2012).
78
In this paper, we report aboveground biomass carbon distribution along a fallow gradient in an
upland secondary forest of the Philippines after shifting cultivation. The Philippines, is both a
mega-diverse country and a global biodiversity hotspot, placing it amongst the top priority countries
for global conservation (Posa et al., 2008; Myers et al., 2000). As in other parts of the developing
tropics, shifting cultivation, known as kaingin in the Philippines, is a common and controversial
land-use in the country (Saurez and Sajise, 2010). In fact, secondary forests developed after shifting
cultivation forms the second largest group of forest in the country after post logging secondary
forests (Lasco et al., 2001). In this paper we also investigate the determinants of biomass carbon
recovery in fallow secondary forests, which remain largely overlooked throughout the tropics
(Taylor et al., 2015; Malhi et al., 2006). We believe the present study helps address the existing
gaps in knowledge on biomass carbon changes and recovery after forest degradation in Southeast
Asia which is still largely biased towards the neotropics (see - Ngo et al., 2013, Saner et al., 2012,
Kenzo et al., 2010 for example). The study is one of the first attempts to systematically assess the
carbon in secondary forests associated with slash-and-burn fallows; and will thus substantially
improve our understanding of the role that such landscapes play as a sink of atmospheric carbon for
both the Philippnes and other tropical developing countries.
4.3 Methods
4.3.1 Study area
The study was conducted in Barangay (the smallest administrative unit and native Filipino
term for village) Gaas on Leyte Island, the Philippines (Figure 4.1). Leyte is the eighth largest
island in the Philippines, and our study site was located on the western side of the island.
Geographically, Leyte is located between 124017
/ and 125
018
/ East longitude and between 9
055
/ and
11048
/ North latitude, and covers an area of about 800,000 ha. Forest cover on the island is about
10%, although the once dipterocarp-rich rainforests now comprise mainly patches of old-growth
and primary forests, and coconut (Cocos nucifera) and Abaca (Musa textilis) plantations (Asio et
al., 1998). The relatively flat lowlands of the island are being used for agricultural crop production,
especially rice (Oryza sativa) and corn (Zea mays) (Asio et al., 1998).
79
Figure 4.1. Map of the Philippines (a), with location map of Barangay Gaas on Leyte Island (b) and
our study sites in Gaas (c). Spatial position of the site locations were plotted in global geo-political
boundary available from Esri (http://www.arcgis.com/) using ArcMap (version 10.3) software.
Leyte Island was formed from tectonic movement and plate convergence which started during the
tertiary and quaternary age (Aurelio, 2000; Asio et al., 1998). Based on the Coronas Classification
of Climate, Leyte has a ‘type IV’ climate with two distinct season (Navarrete et al., 2013). The area
enjoys a relatively even distribution of rainfall throughout the year with annual rainfall totalling
approximately 4,000 mm (Jahn and Asio et al., 2001). Mean annual temperature is 280C which
remains constant throughout the year (Navarrete et al., 2013). Relative humidity ranges between 75
to 80 percent during the dry and the wettest months (Kolb, 2003). The soil in our study area in Gaas
was an Andisol type which possesses a markedly higher soil organic carbon content than rest of the
islands (Navarrete et al., 2013).
4.3.2 Site selection
We chose Barangy Gaas (also refer to as Gaas) purposively. This area of Leyte is situated in
a comparatively high altitudinal range and compared to other parts of the island it has a relatively
greater extent of undisturbed forests. It also has a low population density. These critieria are
prerequisites for the kaingin fallow to regrow as secondary forests (Chokkalingam et al., 2006). For
80
our study we consider only the dahilig kaingin system which is identical to the most common
practice of shifting cultivation in the tropics (see Olofson (1980) for details of the Philippines
kaingin systems). Smallholder farmers living in the area usually grow Abaca or coconut in their
fallow kaingin area in order to receive financial benefits during the time of abandonment. Our study
was however confined to the areas where farmers cultivated only Abaca since coconut plantations
generally involve more intensified land-management during the fallow periods and this is not
conducive for secondary forest development.
4.3.3 Biomass Inventory
A series of extensive field surveys were undertaken at the sites between May and October
2013. For the biomass inventory we followed a modified Gentry plot approach (Gentry, 1982). This
method has been reported as the most efficient for monitoring secondary forest development in
tropical regions (Baraloto et al., 2013). We categorized our sites into four different fallow
categories; i.e. less than 5 year old fallow (SA0-5), also referred to as new, 6-10 year old fallow
(SA6-10) also referred to as young, 11-20 year old fallow (SA11-20) also referred to as middle-
aged, and 21-30 year old fallow (SA21-30) also refered to as oldest. We limited our study to fallow
forest sites that were at least 1 ha in size (Piotto et al., 2009). Additionally, we sampled old-growth
forest (SF) as control forest sites. These forests had no history of kaingin and logging and were
located close to our fallow sites. Our control forest sites were structurally and floristically similar to
primary forests although they may have undergone a limited level of anthropogenic use (e.g. source
of firewood, wild fruits etc.) like most of the forest in the tropical forest-agriculture frontiers.
We identified a total of 25 sites (four fallow categories + old-growth forest x five replicates). Both
the fallow age and fallow cycles have been reported to influence the biomass dynamics in
secondary forests (Eaton and Lawrence, 2009). In our study we were only able to consider the
fallow age and not the fallow cycles due to a lack of reliable information about past site history. At
each site, four transects of 50 m x 5 m were established parallel to each other and with a minimum
of 5 m distance between transects, representing a total area of 0.1 ha per site. For standing live trees
and palms ≥5 cm diameter at breast height (dbh) we recorded diameter and height of each
individuals at 1.3 m from the ground or above stem abnormalities (e.g. buttresses, stilt roots etc.).
All individuals were identified to the species level and named with the help of a local expert from
Visyas State University (VSU). In the case of unknown species we used the most common Filipino
name for that species. We also measured all tree ferns and Abaca ≥5 cm dbh in our transects as
other living biomass because they represent a major component of secondary forest succession in
post-kaingin secondary forests in the Philippines (Suarez and Sajise, 2010). Lianas were not
81
included in our study. For measuring the dbh of individual tree stems we used diameter tapes. We
used a hypsometer for tree height measurements, although the closely-structured canopy in tropical
forests sometimes made it difficult to measure tree heights with a high reliability.
Since slashing and burning is a common practice in shifting cultivation landscapes, coarse dead
wood biomass in the form of felled, degraded and burnt trees comprise a significant part of the total
aboveground biomass in such areas (Pelletier et al., 2012; Mertz et al., 2009). Consequently we
censused all dead, cut and burnt trees ≥5 cm at dbh that fell within in our transects. For each
individual stem, we recorded whether it was standing or downed (i.e. fallen), and the degradation
staus, categorized as – freshly cut, moderately decomposed, highly decomposed and burnt (Ngo et
al., 2013). For litter and undergrowth (i.e. seedlings, saplings, shrubs and herbaceous plants) we
followed a destructive sampling approach. A 1 m x 1 m rectangular plot was laid in the centre of
each of our 100 transects distributed in 25 sites, and all litter and undergrowth samples were
collected and weighed in the plot using a measuring balance.
Additionally, for each site we recorded the site geographic position, elevation (E), distance from the
nearest control forest (D), patch size (PS), slope (SL), leaf area index (LAI) and soil organic carbon
(SOC) as a percentage. We used a digital plant canopy imager (Model: CID Bio-Science, CI-
110/120) for measuring leaf area index and a hand-held global positioning system (Model: Garmin
eTrex) for elevation (Supplementary Table 4.1).
4.3.4 Biomass calculation in forest ecosystems
There is no allometric equation which is specifically developed for the secondary forests in
the Philippines (Lasco et al., 2004), Consequently we used the generic allometric model develeoped
by Chave et al. (2014).
AGB = 0.0673 x (ρD2H)
0.976
Where, AGB or aboveground dry biomass is in kg, D is the dbh in cm, H is the height of the tree
and/or palm in m and ρ is the species specific wood density (g cm-3
). This model performed better
than the widely accepted previous model by Chave et al., (2005), and performed well across all
forest types and bioclimatic conditions (Chave et al., 2014). The inclusion of tree height in this
model provides more reliable estimates of biomass, compared to the pervious models that used only
diameter in the model (Chave et al., 2014; Hunter et al., 2013). Moreover, this model is based on 58
global sites distributed across the tropics where the previous model was based on 27 global sites
82
(Chave et al., 2014, 2005). For species specific wood density we used the World Agroforestry
Centre’s wood density database where wood density was the ratio of dry mass to the green volume
(World Agroforestry Centre, 2014) (Supplementary Table 4.2). In the case of unknown species or
where wood density was not available, we took the mean wood density of the genus as a substitute
(Saner et al., 2012).
For tree ferns and Abaca we used the following allometric models developed by Stanley et al.
(2010) and Armecin and Coseco (2012) respectively.
AGB = 1135.3D - 4814.5
AGB = 5.1164 / (1+1343.02e-0.1550D
)
where AGB for ferns and Abaca is respectively in g and kg, and D is the diameter of individuals in
cm.
The volume of coarse woody debris per area was calculated from transect data, and we used the
following equation to obtain the volume of individual stems that fell within or intersected our
transects.
V = π2D
2 / 8L
Where, V is the volume per stem, L is the total length of the stem (of coarse woody debris) that fell
within or intersected our transects in m and D is the diameter of coarse woody debris. Wood density
was determined locally by the water displacement method taking representative samples (n = 5) for
each of the four wood degradation status (i.e. freshly cut, moderately decomposed, highly
decomposed and burnt), and were 0.48 g cm-3
, 0.35 g cm-3
, 0.25 g cm-3
and 0.19 g cm-3
respectively
for our freshly cut, moderately decomposed, highly decomposed and burnt wood samples (Delaney
et al., 1998). All biomass measurements were first made at the site level (Mg), and then converted
to a per hectare (ha) value after correcting plot size or transect length for the slope (Pelletier et al.,
2012).
4.3.5 Estimating carbon in aboveground forest biomass
In our study total aboveground biomass carbon (AGTBC) is the sum of aboveground living
woody (tree and palms) biomass carbon (LWBC), other living biomass carbon (OLBC) measured for
tree ferns and Abaca, coarse dead wood biomass carbon (CDWBC), undergrowth biomass carbon
83
(UBC), and litter biomass carbon (LBC). To convert the aboveground biomass of trees we assumed
that 50% of the dry mass was carbon (Brown, 1997). Studies at nearby sites with similar forest
types have found average carbon content close to 50% (Saner et al., 2012; Kenzo et al., 2010; Lasco
et al., 2004). For tree ferns and Abaca, carbon content was assumed to be 50% and 47.3%
respectively by total dry biomass after Armecin and Coseco (2012) and Beets et al. (2012).
Measuring of the dry biomass litter and undergrowth samples was undertaken in the VSU-ACIAR
Analytical Chemistry Laboratory. The samples were air dried at room temperature and then grinded
using an electric grinder. The samples were then oven dried at 70oC for 24 hours and weighed. A
representative subsample from each of the litter and undergrowth samples was analysed for
estimating the carbon content (% C‐Heanes) (Supplementary Table 4.3). In the case of coarse
woody debris we took 5 subsamples from each of the degradation states as mentioned earlier, and
the carbon content was measured locally in the laboratory (Supplementary Table 4.4).
4.3.6 Estimating the recovery of biomass carbon in forests
We compared the recovery of biomass carbon in different aboveground components with
that of the control old-growth forests. We combined both tree fern and Abaca as other living
biomass carbon (OLBC) during the analysis due to their relatively low contribution to AGTBC.
Recovery (R) was expressed as a percentage (%) of biomass carbon using the following equation.
R =( Xfallow / Xs) × 100
where 𝑋fallow is the measure of biomass carbon in a fallow site, and 𝑋s is the mean of corresponding
biomass carbon in a similar ecosystem in the control old-growth forest.
4.3.7 Statistical analysis
We performed both the analysis of variance (ANOVA) and Tukey’s post-hoc test to test any
significant difference between the variables. We developed linear mixed-effect models (also refered
to as LMEM) to examine the effect of fallow age and selected site attributes (see Supplementary
Table 4.1) on recovery of biomass carbon, using the package ‘nlme’. In our LMEM, fallow age
(FA), slope (SL), distance from the nearest control forest (DIS), patch size (PS), leaf area index
(LAI) and soil organic carbon (SOC) were used as explanatory variables (i.e. fixed factors), and
biomass carbon in different forest strata was the response variable. We used sites nested in fallow
categories as the random effect in our models. Due to their high collinearity with other explanatory
variables, ‘elevation’ and ‘LAI’ were excluded from the final LMEM (Supplementary Table 4.5).
84
All analyses were performed using ‘R’ Statistical package (version 3.0.1). We considered Akaike
Information Criterion corrected for small sample sizes (AICc) for the selection of our top models,
where the best models had the lowest AICc scores. We used the R-package ‘MuMin’for our model
selection, to evaluate the contribution different fixed effects had on explaining the variabiont in the
response variables (Bartoń, 2011). We considered models within four AICc units to be equivalent
models (Grueber et al., 2011).
4.4 Results
4.4.1 Distribution of biomass carbon in fallow secondary forests
We measured the biomass of 2918 living tree stems (representing 131 species), 184 tree
ferns and 124 Abaca plants (Musa textilis, a species of banana native to the Philippines) in our study
sites covering a total sample area of 2.5 ha. Tree ferns and Abaca are characteristic species in fallow
secondary forests in the area and we include them due to their common occurrence in our study
sites. Within our transects we also encountered 1281 pieces of dead woody debris that met the
criteria for inclusion for biomass measurement. Using existing allometric models our study thus
across all sites finds 328.2 Mg C in the living woody biomass (LWBC), 1.18 Mg C in other living
biomass (OLBC; i.e. tree fern and Abaca), 88.83 Mg C in coarse dead wood biomass (CDWBC) and
0.02 Mg C in undergrowth (UBC) and litter biomass (LBC). Aboveground total biomass carbon
(AGTBC) was significantly (F4 = 6.07, p < 0.01) higher in old-growth forest than the secondary
forests of all fallow categories. We found that, carbon in both living woody biomass and coarse
dead wood biomass varied significantly (F4 = 9.54, p < 0.01) across the sites of different kaingin
history as expressed by their fallow age (i.e. post kaingin period) and in our control old-growth
forest (Annex 4.1). There were however no significant differences among the sites when we
considered the carbon stored in other living biomass and in undergrowth and litter biomass (Figure
4.2). Our post-hoc analysis using Tukey’s HSD revealed significantly higher (321.29 ± 130.96 Mg
C; p < 0.01) aboveground total biomass carbon in old-growth forest followed by our new (i.e. SA 0-
5) and oldest (i.e SA 21-30) kaingin fallow sites. LWBC was also significantly higher (316.96 ±
130.63 Mg C; p < 0.01) in old-growth forest sites accounting for 98.65% of the AGTBC, whilst
CDWBC was highest (126.65 ± 22.58 Mg C; p < 0.01) in our new kaingin fallow sites with an
estimated 79% contribution to the AGTBC (Figure 4.3).
85
Figure 4.2. Distribution of aboveground biomass carbon (Mg ha-1
) in our study sites on Leyte
Island, the Philippines. Each bar indicates upper, lower and median values of biomass carbon
allocation, and standard deviation of C allocation under corresponding site category. Note the
differences in the Y axis.
Parashorea malaanonan had the highest contribution (33.23%) to the overall LWBC, and had
relatively greater contribution to all of our fallow sites and old-growth forest. Other than P.
86
malaanonan, Lithocarpus llanosii, Ficus balete and Shorea contorta contributed respectively
6.39%, 5.32% and 3.89% to the overall LWBC (see Supplementary Table 4.6). In old-growth forest
Calophyllum blancoi (5.69%), Petersianthus quadrialatus (5.26%) and Bischofia javanica (4.79%)
were other major sources of biomass carbon in living woody stems. When considering species
successional guild, climax species were the highest contributers (48.93%; p < 0.01) to LWBC in
old-growth forest sites followed by the oldest kangin fallow sites (i.e. SA 21-30) (Figure 4.4).
Similarly , the contribution of native species to LWBC was also significantly higher in the old-
growth forest (80.81%; p < 0.01) (Figure 4.4). As expected, large diameter stems had the greatest
contribution to the LWBC in our fallow sites, and a significantly high contribution in the old-growth
forest (43.28%; p < 0.01) (Supplementary Figure 4.1). It was a similar case when considering stem
heights, where woody stems attaining heights between 30-50 m constituted about 30.11% of the
LWBC, which was a significantly higher (p < 0.01) contribution than other height classes
(Supplementary Figure 4.2). In the case of OLBC as measured for tree fern and Abaca, we found no
significant difference in biomass carbon allocation across the sites.
Figure 4.3. Relative contribution of different source to the total aboveground biomass carbon stock
in our sites on Leyte Island, the Philippines.
In the case of CDWBC, carbon stored in standing dead wood was significantly higher (p < 0.01) in
our new fallow sites contributing about 85.49% to the CDWBC (Figure 4.5). There were no
significant differences in the carbon stored in downed dead wood in our sites of different fallow
categories. Post hoc analysis however revealed significantly different (p < 0.05) carbon in downed
87
dead wood in new fallow sites and old-growth forest. In new fallow sites the amount of carbon
stored in the freshly cut wood was also highest (91.03%; p < 0.01), and there were no significant
differences in carbon stored in moderately decomposed, highly decomposed and burnt dead wood in
different fallow sites and in old-growth forest (Figure 4.5). Similarly, we found no significant
difference in biomass carbon in litter and undergrowth between our fallow secondary forest sites
and in old-growth forest.
Figure 4.4. Relative importance of different successional species groups in living woody biomass
carbon (LWBC) (left); and species of different origin in LWBC. Values in the bars indicate absolute
contribution (Mg C ha-1
) to LWBC of individual category.
Figure 4.5. Relative importance of coarse dead wood of different stand form in coarse dead wood
biomass carbon (CDWBC) (left); and dead woods of different degradation status in CDWBC (right).
Values in the bars indicate absolute contribution (Mg C ha-1
) to CDWBC of individual category.
88
4.4.2 Recovery of biomass carbon in fallow secondary forests
When compared with old-growth forests used as our control, overall we found that AGTBC
was highest (49.89 ±17.39) in the new (i.e. SA 0-5) fallow sites, followed by our oldest fallow sites
(41.25 ±17.76), middle-aged (i.e. SA 11-20) sites (38.10 ±23.33), and in the young (i.e. SA 6-10)
sites (31.46 ±17.42). The high amount of AGTBC in our new fallow sites was mainly driven by the
large amount of CDWBC remaining in the sites after being cleared and/or used for kaingin.
Although there was no significant difference, the recovery of LWBC was highest in the oldest
fallow sites (37.86%), followed by the middle-aged sites (35.28%), young fallow sites (23.4%) and
the new fallow sites (10.54%) (Figure 4.6). There was no significant difference in the recovery of
OLBC (in tree fern and Abaca) across our sites, except in the case of new kaingin fallow sites and
young fallow sites where it was significantly different (p < 0.05). The amount of CDWBC in
relation to that in the control old-growth forest sites was significantly different (F3 = 47.42, p <
0.01) across the fallow categories, and was significantly higher in the new kaingin fallow sites (i.e.
SA 0-5). In fallow secondary forests, woody debris is ultimately lost from the ecosystem with the
increasing fallow age but at the same time the regrowth of vegetation offsets the large loss in dead
wood in the area. There was however no significant difference in the recovery of undergrowth and
litter biomass carbon (ULBC) across our fallow sites (of different age categories) compared with the
control old-growth forest.
89
Figure 4.6. Distribution of aboveground biomass carbon in fallow secondary forest sites in relation
to the old-growth forests on Leyte Island, the Philippines. Each bar indicates upper, lower and
median values of biomass carbon recovery, and standard deviation of C recovery under
corresponding site category. Note the differences in the Y axis.
4.4.3 Factors influencing the recovery of aboveground biomass carbon in fallow secondary forests
Patch size was found to consistently explain the variation in the response variables (i.e.
percentage recovery of living woody biomass carbon, LWBC; other living biomass carbon, OLBC;
coarse dead wood biomass carbon, CDWBC; and undergrowth and litter biomass carbon, ULBC). It
also explained the similar amount of variation (models within ∆AIC = 4 are considered equivalent)
found in other complex models with more interactions among explanatory variables (Table 4.1;
Table 4.2). Soil organic carbon, fallow age and the slope of a site were also important in explaining
the variation in the recovery of different parameters investigated. Distance from the control forest
sites was not retained in any of the best fit candidate models.
90
Table 4.1. Summary of LMEM between site biomass recovery with environmental attributes
obtained using the package MuMin (Bartoń 2011). Where, LWBC = living woody biomass carbon,
OLBC = other living biomass carbon, CDWBC = coarse dead wood biomass carbon, ULBC =
undergrowth and litter biomass carbon, FA = fallow age, DIS = distance (from the nearest control
forest site), SL = slope, PS = patch size, SOC = soil organic carbon.
Parameter Explanatory variable DF LL AICc ∆ AICc Weight
FA DIS SL PS SOC
LWBC X X 6 -68.93 157.51 0.00 0.31
X 5 -71.81 158.62 1.12 0.18
X X 6 -69.88 159.40 1.90 0.12
X X X 7 -67.14 159.48 1.98 0.11
X X X 7 -67.50 160.20 2.70 0.08
X X X 7 -67.52 160.25 2.74 0.08
X X 6 -70.34 160.31 2.81 0.08
X 5 -73.04 161.07 3.57 0.05
OLBC X X X X 8 -121.09 271.28 0.00 0.47
X X X 7 -124.55 272.44 1.16 0.27
X X X 7 -124.90 273.12 1.85 0.19
X X 6 -128.31 275.08 3.80 0.07
CDWBC X X X X 8 -127.61 284.31 0.00 0.76
X X X 7 -131.62 286.57 2.26 0.24
ULBC X X X 7 -92.14 207.62 0.00 0.55
X X 6 -95.83 210.13 2.51 0.16
X X X X 8 -90.61 210.32 2.70 0.14
X X X 7 -94.08 211.50 3.89 0.08
X X 6 -96.57 211.60 3.98 0.07
*DF— Degree of Freedom, LL— Log Likelihood, AIC—Akaike Information Criterion corrected for
small sample size; **Values in the bold indicate the most influential model describing the variation
in biosmass carbon recovery.
Table 4.2. The relative importance of site environmental attributes in the final LMEM.
Where, LWBC = living woody biomass carbon, OLBC = other living biomass carbon, CDWBC =
coarse dead wood biomass carbon, ULBC = undergrowth and litter biomass carbon, FA = fallow
age, DIS = distance (from the nearest control forest site), SL = slope, PS = patch size, SOC = soil
organic carbon.
Parameter Explanatory variable* Number of
models FA DIS SL PS SOC
LWBC 0.27 (3) - 0.28 (3) 0.95 (7) 0.55 (4) 8
OLBC 0.74 (2) - 0.66 (2) 1.0 (4) 1.0 (4) 4
CDWBC 1.0 (2) - 0.76 (1) 1.0 (2) 1.0 (2) 2
ULBC 0.77 (3) - 0.22 (2) 1.0 (5) 0.93 (4) 5
*Values in the parenthesis indicate the number of models containing respective explanatory
variable.
91
4.5 Discussion
4.5.1 Biomass carbon distribution in tropical fallow secondary forests
We show that secondary forests after shifting cultivation are significant sinks for above
ground carbon. We also show the relatively greater contribution of older fallow areas over young
fallow areas as a carbon sink after being used for shifting cultivation in the upland Philippines. In
this area, carbon stored in old-growth forests, oldest fallow areas and moderately-aged fallow areas
were 321.29 (±130.96) Mg ha-1
, 132.54 (±57.07) Mg ha-1
and 122.41 (±74.95) Mg ha-1
respectively,
which is comparable to the carbon pools reported from other forests in the Philippines (Lasco and
Pulhin., 2009; Lasco et al., 2006, 2004). These studies found carbon stored in aboveground biomass
ranged between 117.9-305.5 Mg ha-1
. This estimate is also greater than the upland forests that were
selectively logged (Lasco et al., 2006).
The allometric models and sampling approach used may introduce errors in the estimates of
carbon, and thus both may have substantial influences on the results of groundbased forest carbon
estimates (see - Chave et al., 2005; Ketterings et al., 2001; Brown, 1997). Locally developed and
calibrated allometeric models have the potential to minimize this uncertainty in tropical forest
carbon accounting (Chave et al., 2005). In our study, we used the most recent allometric model
developed by Chave et al. (2014) for estimating living woody biomass in tropical forests. Studies on
biomass dynamics and forest carbon stocks are biased towards the neotropics, with very limited
systematic inventory reported so far from Southeast Asian secondary forests (e.g. Ngo et al., 2013;
Saner et al., 2012; Kenzo et al., 2010). The model developed by Chave et al. (2014) is reported to
underestimate the aboveground living biomass by 20% when observed biomass exceeded 30 Mg for
individual stems, although this trend disappears when a stem’s biomass is between 10-30 Mg
(Chave et al., 2014). We found that stem density was not the main factor in determining carbon
stored in living woody biomass, but diameter and height of individual stems had a better ability to
control biomass carbon distribution in forests which is consistent with the observations made by
Rozendaal and Chazdon (2015), Marin-Spiotta et al. (2007), Lasco et al. (2006), and Lawrence
(2005) respectively in the Costa Rica, Puerto Rico, Philippines and Indonesia. We also found that,
in old-growth forests and in older fallow secondary forests climax species contributed the most in
terms of aboveground living woody biomass carbon, which is also in accordance with the finding of
Rozendaal and Chazdon (2015). This may reflect the persistence of mature remnant trees in fallow
forest when converted from old-growth stands (Lawrence, 2005). For example, in all of our fallow
sites and old-growth forest Parashorea malaanonan consistently made the highest contribution to
living woody biomass. In contrast, McNamar et al. (2012) have found limited difference in the
occurrence of old-growth forest specialist species in secondary forests with different disturbance
92
history in Lao PDR, and argued that it may due to the high resilience capacity of certain species and
their quick resprouting ability.
In young kaingin fallow areas the ‘other living standing biomass’ (i.e. tree ferns and Abaca in the
present study) and coarse dead biomass constitute a major part of the aboveground biomass carbon.
This depicts a very different composition in landscape scale total aboveground biomass carbon than
that of old-growth forest and older kaingin fallow areas. This is largely due to the long disturbance
(and use) history and the large remaining amount of dead wood on sites after being used for shifting
cultivation (Eaton and Lawrence, 2009). However, Orihuela-Belmonte et al. (2013) have found that
in Mexico coarse dead wood biomass carbon is higher in older fallow areas and also significantly
different across sites of different fallow age. Similar to our findings, Pelletier et al. (2012) also
reported that aboveground forest biomass carbon is not very different between old-growth forest
and older fallow areas, but is different between young fallow areas and old-growth forest.
4.5.2 Factors influencing the biomass carbon recovery in fallow secondary forests
Recovery of aboveground living tree biomass carbon was highest in the oldest fallow sites
and lowest in the new kaingin fallow areas, although living tree biomass is the first pool to be
affected when forests are converted for shifting cultivation use. Coarse dead biomass carbon was
high in the new kaingin fallow sites compared to the control old-growth forest site, reflecting the
high amount of coarse dead wood in new and relatively young kaingin fallow sites remaining after
clearing these areas. Other living biomass carbon was highest in the young kaingin fallow areas
representing the dynamic nature of such landscapes, where undergrowth and litter biomass carbon is
found to increase gradually from new to oldest kaingin fallow sites. Several studies have found that
aboveground biomass carbon recovers rapidly during early successional years after abandonment,
followed by a relatively slow recovery rate after reaching a peak or intermediate stage
(Raharimalala et al., 2012; Kenzo et al., 2010; Letcher and Chazdon, 2009; Lawrence, 2005). Such
recovery may take place at a rate of between 3.75-9.4 Mg C ha−1
year−1
and may take as long as 55-
95 years (Kenzo et al., 2010; Read and Lawrence, 2003; Kotto-Same et al., 1998). In tropical old-
growth forests, annual rates of biomass carbon change are typically lower than forests that have
been subject to different levels of anthropogenic disturbance (Valencia et al., 2009), and in such
forests the biomass carbon accumulation rates also decrease with an increasing stand age after
reaching an intermediate age (Rozendaal and Chazdon, 2015; Martin-Spiotta et al., 2007).
We found that biomass carbon recovery was constrained mainly by landscape patchiness. In our
LMEM patch size showed a consistent control in determining the recovery of biomass carbon at
93
different aboveground levels. In tropical forests, environmental determinants of such recovery as
well as its magnitude are still poorly quantified (Taylor et al., 2015; Malhi et al., 2006). Changes in
biomass carbon are also driven by the growth and mortality of trees, although such changes are
difficult to monitor and require long-term monitoring (Lasky et al., 2014). It is however clear from
our study that aboveground living tree biomass is the most vulnerable carbon pool in tropical
secondary forests. A similar observation is also made by Kotto-Same et al. (1998). Other
environmental factors that also influence the variation in recovery rates are soil organic carbon,
fallow age and slope of a site. Distance from the nearest control old-growth forest was found to be
unimportant in our LMEM. In the case of other living biomass carbon and coarse dead wood
biomass carbon recovery, there was no notable pattern in the LMEM, which may be attributed to
the fact that these components have the smallest contribution to our old-growth forest total
aboveground biomass carbon.
Chronosequence studies are a widely used approach to investigate secondary forest and
successional developments after disturbances (Mukul and Herbohn, 2016; Rozendaal and Chazdon,
2015; Blanc et al., 2009). Both fallow age and fallow cycles offers an indication of previous forest
use (Lawrence, 2005), although the present study was limited to only fallow age as the number of
cycles was unknown. We found that recovery of standing living woody biomass carbon was distinct
across sites of different categories and was superior in older kaingin fallow sites. In young fallow
areas, although the number of stumps was higher, biomass carbon recovery was higher in sites with
larger diameter trees as also mentioned by Rozendaal and Chazdon (2015). Many environmental
factors influence secondary forest recovery after disturbances (Martin et al., 2013; Lawrence et al.,
2010), and studies have demonstrated different recovery rates depending on the site’s geographic
position together with biotic and abiotic attributes (Lawrence et al., 2010; Piotto et al., 2009; Read
and Lawrence, 2003).
Biomass accumulation specifies the carbon stored in aboveground biomass, and was reported to be
declining by 9.3% with each fallow cycle in Indonesia (Hulvey et al., 2013; Lawrence et al., 2010;
Lawrence, 2005). This decline was mainly driven by the density and biomass of woody stems >10
cm dbh as well as soil phosphorus availability (Lawrence, 2005). Burning also has a positive
influence on biomass carbon accumulation in fallow secondary forests (Kenzo et al., 2010;
d’Oliviera et al., 2011). Recovery may also depend on remaining forest cover in a landscape,
although intensity of past land-use rather than edaphic variables is the strongest predictor of
biomass recovery (Castro-Luna et al., 2011). Rapid biomass recovery during secondary forest
succession was also reported by Letcher and Chazdon (2015) and Martin et al. (2013).
94
4.5.3 Forest management and landscape restoration implications
In tropical forests, aboveground biomass carbon dynamics are important in net primary
productivity, and regardless their large contribution to the global carbon balance, uncertainty yet
remains regarding their quantitative contribution to the atmospheric carbon cycle (Chave et al.,
2005; Clark et al., 2001). In Southeast Asia there are large areas of secondary forest as a result of
past anthropogenic disturbances. The existing carbon measurement uncertainties create critical data
gaps that limit our understanding of the important role of these forests as sources and sinks of
terrestrial carbon (Ziegler et al., 2012). In recent years, it is also increasingly recognized that
although undervalued, tropical secondary forests can provide the same important ecosystem goods
and services as primary or old-growth forests (Bonner et al., 2013; Martin-Spiotta et al., 2007;
Chazdon, 2003). In tropical regions deforestation has been a large contributor of greenhouse gas
emissions, and reversing these trends with suitable land-use(s) has a clearly recognized potential for
recovering biomass carbon stock in forests (Budiharta et al., 2014; Houghton, 2012). Compared to
other climate mitigation options, regenerating secondary forests offers a low-cost approach to
reducing greenhouse gas emissions in the tropics, although a greater understanding of and capability
to quantify carbon dynamics in such novel and emerging ecosystems is necessary at landscape
scales (Bonner et al., 2013). For instance, in many tropical countries monocultures have been
preferred for reforestation, but our study along with others suggest that considerable net primary
productivity and carbon storage could be achieved if more species diversity is secured in tropical
landscapes (Pichancourt et al., 2014). Current remote sensing based techniques using satellite
imagery offer promise for estimation of ecosystem carbon exchange in complex forested
landscapes, although large variability exists depending on forest conditions and landscape type
(Tang et al., 2013, 2012). A combination of field-based inventory and remote sensing techniques
can be used to reduce such variability and to cover large areas of tropical forests (Pelletier et al.,
2012).
4.6 Conclusions
Our results highlight that the secondary forests regenerating following shifting cultivation
are important carbon sinks in tropical ecosystems. Allowing development of such secondary
regrowth has clear potential for carbon storage in the aboveground forest biomass. Biomass carbon
distribution differs across sites with different land-use histories, and a large amount of carbon is
stored in living woody biomass in older fallow areas indicating the dynamic nature of the landscape
and succesional development towards undisturbed forests. In young fallow areas, large amounts of
carbon are stored in coarse dead wood material which ultimately provided inputs to the soil for
95
biomass accumulation in living trees. We found that patch size is an important factor in biomass
carbon recovery together with soil organic carbon, fallow age and the slope of a site, and after
thirty years a site may achieve more than 40% of the biomass carbon found in old-growth forest
without any history of major disturbances. The extensive deforestation and forest degradation in
tropical regions caused by shifting cultivation and other land-uses is being blamed for biodiversity
loss and global warming. We found that regenerating secondary forests have the potential to
mitigate the impacts of such deforestation and forest degradation and to contribute to global carbon
sequestration. However, it remains necessary to determine exactly where in the aboveground forest
biomass the carbon is being sequestered (e.g. in the present study, we found that coarse woody
debris in new kaingin fallow sites has the highest contribution to aboveground total biomass carbon,
and in oldest kaingin fallow sites living woody biomass carbon had the highest contribution).
4.7 Additional information
Supplementary Tables 4.1, 4.2, 4.3, 4.4, 4.5,4.6, and Supplementary Figures 4.1,4.2, related
to this chapter/manuscript is provided at the end of this thesis under the section – Appendices.
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101
Annex 4.1. Summary (mean ± SE) of aboveground biomass carbon (Mg ha-1
) distribution in our study sites on Leyte Island, the Philippines. Where,
LWBC = living woody biomass carbon, OLBC = other living biomass carbon , CDWBC = coarse dead wood biomass carbon, UBC = undergrowth
biomass carbon, LBC = litter biomass carbon , AGTBC = aboveground total biomass carbon.
Parameter Fallow category Old-growth forest
≤ 5 year 6-10 year 11-20 year 21-30 year
LWBC 33.42 (±55.25) 74.18 (±54.15) 111.81 (±74.65) 120.02 (±52.05) 316.96 (±130.63)*
Pioneer 4.09 (±5.31) 37.30 (±43.85) 29.32 (±20.78) 24.57 (±6.54) 87.58 (±45.63)
Secondary 6.75 (±7.97) 20.13 (±6.28) 33.65 (±22.4) 45.03 (±18.78) 74.31 (±36.66)
Climax 22.57 (±49.0) 16.75 (±12.27) 48.85 (±55.56) 50.42 (±35.68) 155.07 (±84.03)*
Native 17.63 (±23.35) 60.32 (±42.23) 78.17 (±52.47) 75.79 (±33.68) 256.14 (±108.27)*
Endemic 15.43 (±32.71) 14.50 (±12.03) 33.24 (±28.13) 41.66 (±30.67) 60.83 (±31.7)
Exotic 0.35 (±0.79) 0 0.4 (±0.61) 2.57 (±5.14) 0
OLBC 0.09 (±0.17) 1.45 (±1.34) 0.40 (±0.27) 0.34 (±0.37) 0.21 (±0.30)
Tree fern 0.08 (±0.17) 1.41 (±1.33) 0.32 (±0.31) 0.23 (±0.25) 0.21 (±0.30)
Abaca 0.01 (±0.02) 0.04 (±0.05) 0.08 (±0.06) 0.11 (±0.14) 0
CDWBC 126.65 (±22.58)* 25.26 (±25.0) 9.95 (±4.97) 11.87 (±12.57) 3.91 (±1.17)
Standing 108.28 (±19.46)* 18.21 (±24.74) 2.53 (±1.07) 4.47 (±5.74) 0.31 (±0.25)
Downed 18.37 (±11.70) 7.05 (±5.68) 7.42 (±5.49) 7.40 (±7.33) 3.60 (±1.07)
Freshly cut 115.29 (±22.2)* 2.06 (±2.77) 0.27 (±0.28) 1.13 (±1.85) 0
Moderately degraded 7.85 (±7.69) 17.20 (±25.39) 4.69 (±3.68) 6.72 (±8.45) 0.3 (±0.21)
Highly degraded 3.04 (±3.56) 5.93 (±4.47) 4.97 (±3.76) 4.0 (±4.5) 3.57 (±1.23)
Burnt 0.47 (±1.01) 0.08 (±0.13) 0.02 (±0.05) 0.01 (±0.02) 0.04 (±0.09)
UBC 0.08 (±0.06) 0.10 (±0.03) 0.12 (±0.04) 0.15 (±0.08) 0.11 (±0.04)
LBC 0.07 (±0.04) 0.09 (±0.03) 0.13 (±0.09) 0.17 (±0.10) 0.10 (±0.02)
AGTBC 160.3 (±55.86) 101.09 (±55.98) 122.41 (±74.95) 132.54 (±57.07) 321.29 (±130.96)*
*Values are significantly different at p < 0.01 level.
102
CHAPTER 5: SOIL CARBON AND NUTRIENTS STATUS IN RELATION TO
SHIFTING CULTIVATION IN REGENERATING SECONDARY FORESTS IN
THE PHILIPPINES UPLANDS
May cite as – Mukul, S.A., Herbohn, J., Firn, J., Ferraren, A., Congdon, R. In review. Soil carbon
and nutrients status in relation to shifting cultivation in regenerating secondary forests in the
Philippines uplands. Land Degradation & Development.
5.1 Abstract
Shifting cultivation is a dominant land-use in tropical forest-agriculture frontier that is associated
with much of the environmental degradation in Southeast Asia. We examined the distribution and
availability of key soil parameters –i.e. soil organic carbon (SOC), total nitrogen (N), phosphorus
(P) and potassium (K), in relation to shifting cultivation in the upland Philippines. Soil samples
were collected along a fallow gradient from regenerating secondary forests on Leyte Island. The
effect of site environmental attributes on the availability (in relation to the old-growth forest) of soil
carbon and nutrients was investigated using linear mixed-effect models (LMEM). We found
relatively higher concentrations of soil carbon and P in the oldest fallow sites and higher N
concentration at the youngest fallow sites. Soil K was consistently lower in all of our fallow sites,
although soil C and other nutrients were relatively lower in our control old-growth forest sites. We
found no significant difference in carbon and nutrients within sites of different fallow categories
and soil depths, except in the case of soil K where it was highest in our control old-growth forest
sites. Patch size together with slope and fallow age were the most influential factors in explaining
the availability of soil carbon and nutrients in tropical secondary forests after shifting cultivation
use. Our study suggests that shifting cultivation may not be as detrimental to soil quality at least on
the soil type and climate we studied. Further studies are also required to fully understand the long-
term effect of shifting cultivation in tropical forest landscapes.
Key-words: soil quality; degradation; disturbance; resilience; restoration; kaingin.
5.2 Introduction
Shifting cultivation, swidden or slash-and-burn agriculture is a common land-use in tropical
forests and has long been a major source of forest degradation (Ziegler et al., 2011; Mertz et al.,
2009a). Generally, shifting cultivation involves slashing and burning of forest vegetation before or
at the onset of the monsoon to release nutrients locked in plant biomass; the sites are then cultivated
and harvested over several years before they are left fallow to allow growth of secondary forest
103
(Fox et al., 2000). Much of the forest in the tropics has been subjected to shifting cultivation, and
this is a major contribution to the livelihoods and food security of smallholder rural upland farmers
(Dressler et al., 2015; Chazdon, 2014; van Vliet et al., 2012). Although reliable statistics about the
extent of land under shifting cultivation are not available, Mertz et al., (2009b) reported that there
are an estimated 14–34 million people dependent on shifting cultivation in tropical Asia. In the last
few decades, a rapid transformation of shifting cultivation landscapes has taken place in Southeast
Asia, mainly driven by rapid urbanization, and the changing land-use policies and focus of
governments (van Vliet et al., 2012; Fox et al., 2009). Another threat to forest in the Southeast Asia
is posed by large-scale plantations of commercial and perennial crops including rubber and oil palm
(Ahrends et al., 2015; van Vliet et al., 2012), yet shifting cultivation regarded as a major cause of
the region’s environmental and forest degradation (Mukul and Herbohn 2016; Hett et al., 2012;
Ziegler et al., 2011).
Soil quality is one of the key environmental attributes that is influenced by shifting cultivation and
is likely to be affected by any changes in shifting cultivation practices (Paudel et al., 2015; Bruun et
al., 2013, 2009; Lawrence et al., 2010; Kotto-Same et al., 1998). Soil quality is defined here as the
capacity of the soil to support forest growth without causing degradation of the soil or to the
environment (Lal, 1997). Soil quality is also closely linked to soil resilience which refers to the
ability of the soil to restore its functions following disturbances (Estes et al., 2011; Lal, 1997). The
ecological aspects of shifting cultivation, however, are much more complex than is often presented
in the literature, and the transformations of shifting cultivation landscapes to other land-uses have a
wide range of environmental consequences, both at the local and global level (Mukul and Herbohn,
2016; van Vliet et al., 2012; Bruun et al., 2009). For instance, the transition of shifting cultivation
landscapes to sedentary agriculture will bring a substantial reduction in the above and below ground
carbon stocks compared to the transition of shifting cultivation landscapes to secondary forests
(Bruun et al., 2009).
In the tropics, the effects of anthropogenic forest disturbances, including the impacts of shifting
cultivation, on soil carbon and essential nutrients are still unclear, and characterized by data scarcity
and inconclusiveness (see – Paudel et al., 2015; Sang et al., 2013; Bruun et al., 2009; Richards et
al., 2007). Consequently, we investigate the effect of shifting cultivation on key soil quality
indicators namely – soil organic carbon (SOC), total nitrogen (N), phosphorus (P) and potassium
(K) in an upland area of the Philippines (Sharma et al., 2005). In the Philippines shifting cultivation
is locally known as kaingin and represents a dominant land-use in the upland areas (Saurej and
Sajise, 2010). After logged forests, post kaingin forests constitute the largest group of secondary
104
forests in the country (Chokkalingam et al., 2006, 2001). Our specific research objectives were to
determine the concentrations of selected soil parameters (SOC, N, P and K) in post kaingin
secondary forests of the country along a fallow gradient, and to identify the effect of site
environmental attributes on the recovery of key soil quality indicators investigated. Understanding
changes in soil carbon and nutrient availability between secondary forests after shifting cultivation
has wider implications for forest management and restoration in the tropics (Locatelli et al., 2015;
Smith et al., 2015; Bonner et al., 2013; Sang et al., 2013; Bruun et al., 2009).
5.3 Materials and methods
5.3.1 Study location
In the Philippines, 53% of the total land area is considered as forest land based on the
national land classification system. Another 47% lands are regarded as alienable and disposable
land, with slope less than 18% and are not required for forest purposes (Carating et al., 2014).
About 23% of the total land area of the country is classified as upland with altitude ranging between
100-500 m asl (Carating et al., 2014). Our study was conducted in an upland area situated on the
western side of the island of Leyte (Figure 5.1), which is the eighth largest in the country and
located between 124017
/ and 125
018
/ East longitude and between 9
055
/ and 11
048
/ North latitude.
Forests cover only about 10% of the island’s 800,000 ha area (Asio et al., 1998). The once
dipterocarp rich rainforests of the island are now dominated by patches of old-growth forest,
coconut plantations, Abaca (a fiber yielding species from the Musaceae) and fast growing timber
species (Asio et al., 1998).
Leyte has a ‘type IV’ climate, according to the Coronas Climate Classification with two distinct
seasons – monsoon and dry seasons (Navarrete et al., 2013). Annual rainfall of the study area is
about 4,000 mm with a mean annual temperature of about 280C that varies little throughout the year
(Navarrete et al., 2013; Jahn and Asio, 2001). Relative humidity ranges between 75 to 80 percent
(Kolb, 2003). The soil of our study area is an Andisol and possessed markedly higher
concentrations of organic carbon than on the other islands with the Andisol soil type (Navarrete et
al., 2013).
5.3.2 Site selection and characteristics
We purposively selected Barangay (administrative entity, similar to a village) Gaas
(hereafter Gaas only) on Leyte Island because the area has relatively low population density with
some undisturbed forests, which is the prerequisite for the development of second growth forests in
tropics (Chokkalingam et al., 2006). The kaingin system of the Philippines can be divided into three
105
distinct categories based on slope and access to irrigation facility, these are: i) the tubigan system
ii) the katihan system and iii) the dahilig system (Olofson, 1980). Both, the tubigan and katihan
systems take places in lower elevation or gently sloping areas with limited facilities for irrigation;,
whereas, the dahilig system is more common in the forested areas with steeper slopes (Olofson,
1980). We focused, however, only to the dahilig system because it is the most common form of
shifting cultivation in Southeast Asia (Olofson, 1980).
Figure 5.1. Location map of the study area on Leyte Island (left), and the study sites (right) plotted
on a Google earthTM
map.
Altogether 25 sites (5 categories x 5 replicates) were established in the area. We took samples from
four different fallow categories, i.e. less than (or equal to) 5 years old fallow (SA0-5, also referred
to as new sites), 6-10 years old fallow (SA6-10, also referred to as young sites), 11-20 years old
fallow (SA11-20, referred to as middle-aged sites), and 21-30 years old fallow (SA21-30, also
referred to as oldest sites), and from old-growth forests as our control or standard (SF). Our old-
growth forests are similar to the primary forests in terms of structure and floristic composition, ever
been used for kaingin and/or logging, however, may experience limited level of anthropogenic
disturbance like fruit or fuelwood collection. We took samples only from sites that were 1 ha or
more in size (Piotto et al., 2009). The age of the site was confirmed by asking the land-
owner/farmer (Lawrence, 2004). A detailed vegetation survey was conducted at each site and all
106
trees all trees ≥5 cm dbh were identified and measured for related parameters. To measure sites
elevation, distance from nearby control secondary forest and geographic position, we used a hand-
held global positioning system (Model: Garmin eTrex). We used a digital plant canopy imager
(Model: CID Bio-Science, CI-110/120) for measuring leaf area index. Summaries of our site
environmental attributes are presented in Table 5.1.
Table 5.1. Environmental attributes of the study sites on Leyte Island, the Philippines.
where EL= site elevation (m ASL), SL = slope (°), PS = patch size (ha), DIS = distance (from the
nearest control forest site, m), N = tree species richness (no of unique species, site-1
), A = tree
species abundance (no of individuals, site-1
), BA = tree basal area (m2 site
-1), LAI = leaf area index
(m2 site
-1) (Mukul et al. In review).
Site
category
Site environmental attribute
EL SL PS DIS N A BA LAI
SA0-5 600.8
(±22.19)
33.0
(±5.7)
1.16
(±0.21)
290.0
(±74.16)
6.0
(±7.38)
10.8
(±13.52)
0.89
(±1.32)
1.33
(±0.57)
SA6-10 549.0
(±72.41)
32.4
(±9.4)
1.14
(±0.13)
540.0
(±114.02)
38.4
(±4.83)
142.6
(±20.5)
2.8
(±0.81)
5.7
(±0.96)
SA11-20 567.2
(±49.24)
32.6
(±9.21)
1.34
(±0.24)
162.0
(±198.17)
39.2
(±9.52)
140.8
(±26.94)
3.85
(±1.86)
5.14
(±1.01)
SA21-30 574.8
(±35.35)
38.2
(±7.98)
1.14
(±0.22)
256.0
(±153.88)
45.8
(±5.93)
143.6
(±4.45)
3.92
(±1.39)
5.3
(±0.69)
SF 512.4
(±54.77)
36.4
(±9.71)
NA** NA** 45.2
(±4.21)
145.8
(±16.53)
7.81
(±2.23)
6.08
(±0.86)
*values in the parenthesis indicate standard deviation of means.
** not applicable for old-growth forest sites.
5.3.3 Soil sample collection
Four transects of 50 m x 5m were established within each of the 25 sites. Within each site,
transects were spaced at least 5 m apart, parallel to each other and running from the boundary to the
centre of the site. Along each transect soil samples were collected from the beginning (0 m), centre
(25 m) and end of transect (50 m). Samples from the top 30 cm of topsoil were obtained. Topsoil
profile is widely reported to be most affected by land use/cover change (Sang et al., 2013; Bruun et
al., 2009; Batjes, 1996); and the top 30 cm of soil is also the standard depth recognized by FAO and
approved by IPCC for the global voluntary carbon markets (FAO, 2006). We collected soil core
(5cm3) samples from three different depths, i.e. 0-5cm (also referred to as the top soil layer), 6-
15cm (the middle soil layer) and 16-30cm (the bottom soil layer) using a standard soil auger
(Manufacturer: AMS Inc., USA). Altogether 900 core samples were collected from 100 transects
distributed over the 25 sites. Samples were placed in plastic bags and labeled in the field before
further processing in the laboratory.
107
5.3.4 Soil sample processing
All analyses were performed in the VSU-ACIAR Analytical Chemistry Laboratory at
Visayas State University in the Philippines. Samples were air dried at room temperature prior to
being passed through a 2 mm sieve to remove rocks, pebbles and plant material (e.g. roots, litter).
We used a homogenized composite sample (n= 3) pooled for the same soil depth for each transect.
Altogether there were 300 composite samples from our 900 core samples that were used for
laboratory analysis to determine SOC, N, P and K. Subsamples were used for oven drying (105oC
for 48 hours) and all calculations are reported on an oven dry weight basis.
For SOC (% C‐Heanes) we oxidized the composite soil samples for each transect by heating with
H2SO4 in the presence of dichromate (Congdon, 2012). Unlike the traditional Walkley-Black
method, external heating ensures complete oxidation and more reliable estimate of SOC (Krishan et
al., 2009; Rayment and Higginson, 1992). Soil N and P were determined colorimetrically following
the single digestion method of Anderson and Ingram (1989), while soil total K was quantified using
an atomic absorption spectrophotometer. The recovery of soil parameter is expressed as the
percentage of respective soil parameter in our control old-growth forest sites.
5.3.5 Statistical analysis
We performed analysis of variance (ANOVA) and Tukey’s post-hoc analysis to test for
significant differences among variables. We developed linear mixed-effect models (hereafter refer
to as LMEM) to identify the effect of selected site environmental attributes on the availability of
SOC, N, P and K in relation to our control old-growth forests using the package ‘nlme’ (Pinheiro et
al., 2011). For LMEM along with fallow age (FA), we first considered eight environmental
variables as our explanatory variables (i.e. fixed factors) – elevation (EL), slope (SL), patch size
(PS), distance from the nearest control forest site (DIS), tree species richness (≥5 cm dbh) (N), tree
species abundance (≥5 cm dbh), basal area (≥5 cm dbh) and leaf area index (LAI) (Table 5.1). Tree
species richness, abundance, basal area and leaf area index were expressed per site (i.e. 0.1 ha area)
basis. After a Pearson’s correlation test we however, found only five site environmental variables,
i.e. fallow age, elevation, slope, patch size and leaf area index, suitable for our final LMEM
(Supplementary Table 5.1). We used sites nested in fallow categories as the random effect in our
LMEM with SOC, N, P, and K at different soil depths as the response variable. All statistical
analyses were performed using the ‘R’ Statistical Package (version 3.0.1; R Development Core
Team, 2012). We considered Akaike Information Criterion corrected for small sample sizes (AICc)
for the selection of our top models. Only models within four AICc units were considered as
108
competing models in the present study (Grueber et al., 2011). We used the package ‘MuMin’ for
our model selections and to evaluate the contribution that different fixed effects had on explaining
the variation in the response variables (Bartoń, 2011).
5.4 Results
5.4.1 Soil carbon and nutrients concentrations across a fallow gradient
We found higher SOC concentrations in all soil depths in our oldest fallow sites (SA21-30)
followed by young fallow sites (SA6-10) and in new fallow sites (SA0-5) (Table 5.2). A similar
pattern was found at all soil depths examined (i.e. 0-5 cm, 6-15 cm and 16-30 cm). The differences
in SOC distribution was not significant in the case of the top soil layer (i.e. 0-5 cm), whilst in the
middle (6-15 cm) and bottom (16-30 cm) soil layers were significantly (p<0.05) different across the
sites (Figure 2). Tukey’s post-hoc analysis also revealed significantly (p<0.05) higher SOC
concentrations in our middle and bottom soil layer in the oldest fallow sites followed by young and
new kaingin fallow sites. The relative contribution of the SOC (at the different soil depths) to total
SOC stock, however, varied varied across the sites of different fallow categories and forest, with
relatively higher SOC concentrations in the top soil layers (i.e. 0-5 cm) in our control forest sites
(49.8%) followed by the middle aged sites (48.98%) (Figure 5.3). In the case of the oldest fallow
secondary forest sites the relative contribution of SOC in the bottom layer was comparatively higher
(27.1%) than all other site categories.
Interestingly soil total N concentrations were highest in the new kaingin fallow sites and in the top
layer of the soil that we investigated (see Table 5.2). We found no significant difference in the soil
N distribution between different site categories and soil depths as indicated by ANOVA. The
relative contribution of soil N present in the top layer of soil to total N stock was higher (54.1%) in
our control forest sites followed by young fallow sites (48.4%).
Similar to SOC and N there was no significant difference in total P concentrations in our study sites
distributed across different fallow categories and secondary forest without any history of kaingin
(Supplementary Figure 5.1). The concentrations of soil P were, however, higher in the oldest fallow
sites and in the top soil layer of all our site categories although the differences were not statistically
significant using ANOVA (Table 5.2). The relative importance of soil P at different soil depths
varied across the sites, and in the secondary forest sites, soil P in the top soil layer had the highest
contribution (50.5%) to the total soil P stock identified at the three different depths (Figure 5.3).
109
Soil total K concentration was highest in old-growth forest sites at all soil depths followed by young
fallow sites and middle-aged sites (Table 5.2). We found significantly higher (F4= 3.16, p<0.05)
soil K concentrations in the top layer of soil of our old-growth forest sites using ANOVA and
Tukey’s post-hoc analysis. The difference was, however, not significant in the middle (F4= 2.15,
p=0.11) and bottom (F4= 1.73, p=0.18) soil layers.
Table 5.2. Concentrations of soil organic carbon and nutrients across the sites of different fallow
categories and old-growth forest on Leyte Island, the Philippines.
Soil parameter Soil depth Site category
SA0-5 SA6-10 SA11-20 SA21-30 SF
SOC
(mg C g-1
)
0-5 cm 61.66
(±6.82)
65.36
(±20.53)
52.06
(±6.9)
67.88
(±19.18)
47.47
(±11.09)
6-15 cm 36.81
(±6.89)
36.58
(±15.15)
29.23
(±3.6)
46.81
(±17.31)
25.44
(±5.1)
15-30 cm 29.96
(±6.66)
32.97
(±13.78)
24.99
(±3.73)
42.56
(±16.67)
22.68
(±5.38)
Total N
(mg N g-1
)
0-5 cm 4.33
(±0.77)
3.53
(±1.17)
3.46
(±1.14)
3.36
(±1.02)
3.4
(±0.5)
6-15 cm 2.67
(±1.17)
1.88
(±0.85)
2.22
(±1.6)
2.21
(±0.89)
1.68
(±0.43)
15-30 cm 2.46
(±1.28)
1.89
(±0.69)
1.51
(±1.15)
1.86
(±1.11)
1.22
(±0.53)
Total P
(mg P g-1
)
0-5 cm 0.51
(±0.09)
0.53
(±0.11)
0.49
(±0.1)
0.61
(±0.14)
0.49
(±0.13)
6-15 cm 0.34
(±0.14)
0.4
(±0.1)
0.34
(±0.09)
0.4
(±0.14)
0.28
(±0.14)
15-30 cm 0.30
(±0.13)
0.33
(±0.09)
0.23
(±0.07)
0.34
(±0.18)
0.2
(±0.12)
K
(mg K g-1
)
0-5 cm 1.02
(±0.22)
1.88
(±1.23)
1.52
(±0.99)
1.3
(±0.76)
3.18
(±1.58)
6-15 cm 0.86
(±0.26)
1.81
(±1.29)
1.51
(±1.18)
0.9
(±0.48)
2.45
(±1.35)
15-30 cm 0.89
(±0.31)
1.76
(±1.3)
1.54
(±1.24)
0.91
(±0.53)
2.3
(±1.24)
*Values in the parentheses indicate the standard deviations of means under respective categories.
110
Figure 5.2. The relative contribution of soil organic carbon and nutrients at different soil depths in
our sites on Leyte Island, the Philippines. The Y axis here indicates the percentage (%) contribution
to the total soil carbon and nutrient pools at the three soil depths studied. The values within the bars
are the mean concentrations (mg g-1
) of the soil parameters for the respective depths and site
categories.
5.4.2 Availability of soil carbon and nutrients along a fallow age gradient
We found high SOC, soil N and soil P recovery in our fallow sites when compared with the
control old-growth forests (Figure 5.3). In most cases the recovery was higher in young fallow sites
and in oldest fallow sites. Among the soil nutrients soil K recovery was lowest across all site
categories. The pattern of soil K recovery was different to soil carbon and N and P, with relatively
higher recovery in middle-aged sites. Interestingly soil K recovery was lowest in the oldest fallow
sites. Despite relatively higher variability within the sites in recovery of carbon and nutrients, there
111
was no significant difference between sites (of different fallow categories) in the recovery of
selected soil parameters.
Figure 5.3. Soil carbon and nutrients in relation to control old-growth forests at our study sites on
Leyte Island, the Philippines. Note that different scales are used on the Y axes.
112
5.4.2 Environmental controls on soil carbon and nutrients in fallow sites
We found patch size (PS) explained the highest amount of variation in soil carbon and
nutrients availability (i.e. dependent variables) in regenerating secondary forests in relation to the
control old-growth forests (Table 5.3). Other site factors important in explaining the variations were
slope (SL) and fallow age (FA). There was no influence of the distance from nearby secondary
forest (DIS) to the recovery of the soil carbon and nutrients across our sites. Patch size was found to
be consistently important in explaining the variation in recovery for all the soil parameters and soil
depths we examined (Table 5.4). In the case of soil P recovery we also found that the slope of the
sites was equally important in explaining the variation as the patch size.
Table 5.3. Summary of LMEM between soil carbon and nutrient recovery with environmental
attributes obtained using the package MuMin (Bartoń 2011). Where, FA = fallow age, DIS =
distance (from the nearest control forest site), SL = slope, PS = patch size.
Soil
parameter
Soil depth
(cm)
Explanatory
variable
DF LL AICc ∆ AICc Weight
FA DIS SL PS
SOC 0-5
X X 6 -86.12 190.71 0.0 0.47
X 5 -88.43 191.15 0.44 0.37
X X 6 -87.80 194.05 3.34 0.09
X X X 7 -85.54 194.42 3.71 0.07
6-15
X X 6 -93.6 205.65 0.0 0.44
X 5 -96.3 206.88 1.23 0.24
X X 6 -94.56 207.58 1.93 0.17
X X X 7 -92.25 207.83 2.18 0.15
16-30
X X 6 -95.67 209.79 0.0 0.42
X 5 -98.48 211.25 1.46 0.20
X X X 7 -94.01 211.36 1.57 0.19
X X 6 -96.47 211.39 1.6 0.19
Total N 0-15
X 5 -88.43 191.14 0.0 0.42
X X 6 -86.93 192.31 1.17 0.24
X X 6 -87.07 192.6 1.46 0.20
X X X 7 -85.01 193.35 2.21 0.14
6-15 X 5 -101.9 218.08 0.0 0.40
X X 6 -100.1 218.71 0.63 0.29
X X 6 -100.5 219.53 1.44 0.19
X X X 7 -98.65 220.64 2.56 0.11
16-30 X 5 -106.9 228.03 0.0 0.30
X X 6 -104.9 228.29 0.27 0.26
X X 6 -104.9 228.36 0.33 0.25
113
X X X 7 -102.8 229.0 0.97 0.18
Total P 0-5
X X 6 -80.12 178.7 0.0 0.51
X 5 -82.76 179.8 1.1 0.30
X X 6 -81.67 181.8 3.09 0.11
X X X 7 -79.55 182.42 3.72 0.08
6-15
X 5 -93.35 200.98 0.0 0.42
X X 6 -91.42 201.3 0.32 0.36
X X 6 -92.33 203.12 2.14 0.14
X X X 7 -90.51 204.35 3.37 0.08
16-30 X X 6 -98.21 214.89 0.0 0.45
X 5 -100.8 215.81 0.92 0.28
X X X 7 -96.90 217.13 2.24 0.15
X X 6 -99.47 217.41 2.52 0.13
K 0-5
X X 6 -82.95 184.37 0.0 0.76
X X X 7 -82.20 187.73 3.36 0.14
X 5 -87.04 188.36 3.99 0.10
6-15
X X 6 -88.49 195.44 0.0 0.82
X X X 7 -87.57 198.47 3.03 0.18
16-30 X X 6 -89.94 198.35 0.0 0.82
X X X 7 -89.02 201.37 3.02 0.18
*DF— Degree of Freedom, LL— Log Likelihood, AIC—Akaike Information Criterion corrected for
small sample size; **Values in the bold indicate the most influential model describing the variation
in biomass carbon recovery.
Table 5.4. The relative importance of site environmental attributes in the final LMEM.
Where, FA = fallow age, DIS = distance (from the nearest control forest site), SL = slope, PS =
patch size.
Soil
parameter
Soil depth
(cm)
Explanatory variable* Number of
models FA DIS SL PS
SOC 0-5 0.16 (2) - 0.54 (2) 1.0 (4) 4
6-15 0.32 (2) - 0.59 (2) 1.0 (4) 4
16-30 0.38 (2) - 0.61 (2) 1.0 (4) 4
Total N 0-5 0.34 (2) - 0.37 (2) 1.0 (4) 4
6-15 0.31 (2) - 0.40 (2) 1.0 (4) 4
16-30 0.45 (2) - 0.44 (2) 1.0 (4) 4
Total P 0-5 0.19 (2) - 0.59 (2) 1.0 (4) 4
6-15 0.22 (2) - 0.44 (2) 1.0 (4) 4
16-30 0.27 (2) - 0.59 (2) 1.0 (4) 4
K 0-5 0.14 (1) - 0.90 (2) 1.0 (3) 3
6-15 0.18 (1) - 1.0 (2) 1.0 (2) 2
16-30 0.18 (1) - 1.0 (2) 1.0 (2) 2
*Values in the parenthesis indicate the number of models containing respective explanatory
variable.
114
5.5 Discussion
5.5.1 Variability in soil carbon and nutrients in fallow secondary forests
We did not find a clear or consistent influence of shifting cultivation land-use on the stocks
of soil organic carbon, N, and P in regenerating secondary forests in the upland Philippines, with
relatively greater influence on soil K concentrations. The higher levels of soil organic carbon and
nutrients (i.e. N and P) in young fallow sites could be due to the initial release of carbon and
nutrients from plant materials to soil following burning (see- Tanaka et al., 2001; Giardina et al.,
2000). Heating of soil during burning acts as an important mechanism of nutrient release and the
initial burning associated with shifting cultivation is reported to increase SOC by addition of
organic matter in soil via ash (Tanaka et al., 2001). Burning can also result in losses of soil
available N due to increased volatilization, although, the losses of soil P to atmosphere due to
volatilization is relatively low (Romanyá et al., 2001; Giardina et al., 2000). In shifting cultivation
landscapes burning also results in a decrease in microbial activity and associated biomass in soil at
the initial stage that may negatively influence organic carbon in soil (Tanaka et al., 2001).
The relatively lower concentration of SOC and P at our middle-aged sites (i.e. SA11-20) could be
due to increasing nutrient uptake by regenerating vegetation during successional development.
Similarly, relatively greater concentrations of soil carbon, N, and P in our oldest fallow sites (SA21-
30) could be due to higher litterfall, litter decomposition and microbial activity in sites (Lange et al.,
2015; Paudel et al., 2015; Sayer et al., 2011). Positive effects of shifting cultivation on soil available
P and K in secondary forest have been reported by Brand and Pfund (1998). In contrast to our
findings, Garcia-Oliva et al. (1999), however, in Mexico found a 32% initial decrease in SOC stock
due to fire and combustion, and Yang et al. (2003) found a reduction in soil available N and P after
shifting cultivation use. Soil K was consistently low at all our sites and fallow categories, although
Yang et al. (2003) reported an increase in soil K after fire and shifting cultivation use at sites in
China. Other than combustion during the burning of vegetation, soil runoff associated with forest
clearing during shifting cultivation also reported to causes nutrient losses in shifting cultivation
landscape (Rodenburg et al., 2003; Brand and Pfund, 1998). Such generalisations might, however,
underestimate the fact that in the tropics, smallholder farmers usually select sites with greater soil
fertility for shifting cultivation use (Mertz et al., 2008).
5.5.2 Influence of site environmental factors on soil carbon and nutrients
We found that site environmental parameters, mainly patch size, have the greatest influence
on the recovery of SOC, soil total N and P; and we have found that the same factors influence
aboveground biomass carbon and forest structure recovery in regenerating secondary forests after
115
shifting cultivation (see Mukul et al., 2016; Mukul et al., Under review). As mentioned earlier the
higher levels of soil carbon and nutrients in our fallow sites could be also due to the initial release
of carbon and nutrients following burning, and may not represent the actual recovery in young
fallow sites. In the case of soil K, both patch size and slope were found to be equally important for
its recovery. However, patch size was found to be the most important factor as models within
∆AICc=4 are considered as equivalent and explain the same amount of variation as other more
complex models incorporating more interactions of variables (Bartoń, 2011). Due to a lack of
information about past fallow cycles, we did not take account of this in our analysis. It is thus
unclear what impact past fallow cycles may have had on the results. The effect of land-use and site
environmental attributes on soil carbon and nutrients is evident from many studies (see- Fernandez-
Romero, 2014; Parras-Alcantara et al., 2013; Hatter et al., 2010; Neill et al., 1997; van Noordwijk et
al., 1997). A long fallow period is critical to restoring essential soil nutrients, and it may take as
long as 20 years to restore soil nutrients to a level similar to a secondary forest (Rahamiralala et al.,
2010; Funakawa et al., 2009). In an Indonesian study, the number of fallow cycles did not influence
soil nutrients, like soil P, although the presence of deep and fine root systems in soil was found to
be more important than fire history in recovery of soil P (Lawrence and Schlesinger, 2001). A
similar observation was also made by Bruun et al. (2009) where they found higher growth of
pioneer species in fallows due to their shallow root systems and ability to take up nutrients from the
top layer. Forest structure and species composition may also influence the dynamics of soil carbon
and nutrients and vice-versa (Raich et al., 2014; Paoli et al., 2008; Firn et al., 2007; Lawrence et al.,
2005). Furthermore, spatial heterogeneity in soil in terms of texture, clay mineralogy and site
topography and climate may vary and can also override the effects of other environmental factors
(Nottingham et al. 2015; Bruun et al., 2006).
5.6 Conclusions
Our study finds that shifting cultivation may not be as detrimental to soil quality at least on
the soil type and climate we studied as suggested in the literature, and that geographic and site
specific conditions may be important in determining the impact that shifting cultivation has on soil
properties. The concentrations of soil carbon, N and P were significantly higher in the young fallow
secondary forests, while soil K concentration was lower compared to old-growth forest. We also
found greater availability in the soil stocks of SOC, soil N and P in tropical secondary forests
compared to old-growth forests after shifting cultivation use. In young fallow areas, this may be
attributed to the release of nutrients from slashing and burning of plant biomass available in sites.
Patch size together with the slope (of the site) and fallow age were significant explanatory factors
associated with the recovery process.
116
In tropical regions shifting cultivation is still a dominant land-use and likely to contribute to the
food security and livelihoods of smallholder farmers in upland areas for many years ahead. The
traditional view of shifting cultivation as environmentally detrimental in terms of its impacts on soil
is not well established (Murty et al., 2002). A better understanding of this issue, with systematic and
long-term studies, is important for the restoration and management of tropical secondary forests not
only after the shifting cultivation but also after other disturbances.
5.7 Additional information
Supplementary Table 5.1 and Figure 5.1, related to this chapter/manuscript are provided at
the end of this thesis under the section – Appendices.
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CHAPTER 6: CO-BENEFITS OF BIODIVERSITY AND CARBON FROM
REGENERATING SECONDARY FORESTS IN THE PHILIPPINES UPLANDS:
IMPLICATIONS FOR FOREST LANDSCAPE RESTORATION
May cite as – Mukul, S.A., Herbohn, J., Firn, J. In press. Co-benefits of biodiversity and carbon
from regenerating secondary forests in the Philippines uplands: implications for forest landscape
restoration. Biotropica.
6.1 Abstract
Shifting cultivation is a widespread land-use in tropical forested areas, and often regarded as the
major driver of forest degradation by policy makers. The secondary fallow forests regrowing after
shifting cultivation are generally not viewed as suitable targets for biodiversity conservation and
carbon retention. Drawing upon an empirical study in the Philippines and other relevant case
studies, we demonstrate that recovering secondary forests following shifting cultivation have high
potentials for biodiversity and carbon conservation in upland rural areas of the Philippines – a
global hotspot of biodiversity and deforestation. We compare the potential biodiversity and carbon
sequestration observed in regenerating forests with other land-uses that may replace the fallow areas
after shifting cultivation. We argue that regenerating tropical forests can be used as a cost-effective
management and restoration strategy in countries where they are common and where forest is an
integral part of rural people’s livelihoods. We discuss the issues and potential mechanisms through
which such dynamic land-use can be incorporated into development projects that are currently
being used for financing sustainable management, conservation and restoration of tropical forests.
Key-words: forest degradation; restoration; reforestation; community forestry; REDD+.
6.2 Introduction
Deforestation and forest degradation are among the major threats to forests and biodiversity
in Southeast Asia (Sodhi et al., 2010; Achard et al., 2002). Shifting cultivation, also known as
swidden agriculture or slash-and-burn has long been seen as the primary agents of deforestation and
forest degradation in this region (Ziegler et al., 2011; Angelsen, 1995). In this region shifting
cultivation has been practised for centuries and supports an estimated 14-34 million people
(Dressler et al., 2015; Mertz et al., 2009). As a consequence, secondary forests regrowing after
shifting cultivation are rapidly becoming a prominent forest type in Southeast Asia where secondary
forests regrowing both after shifting cultivation, logging and other disturbance constitute about 63%
124
of the total forest cover (Kettle et al., 2010, Koh, 2007; Chokkalingam et al., 2001; de Jong et al.,
2001).
The Philippines is both a biodiversity hotspot and a megadiverse country (Posa et al., 2008; Myers
et al., 2000), and is among the top priority countries for conservation (Conservation International,
2013). The country has experienced one of the highest rates of deforestation in Southeast Asia, and
was one of the first countries to introduce massive reforestation and forest restoration programs to
address the country’s rapid forest loss (Pulhin et al., 2007; Chokkalingam et al., 2006). The
National Greening Program (NGP) – the most recent reforestation initiative in the country - has an
aim to reforest 1.5 million hectares of degraded upland areas by 2016. The success of such efforts
are still uncertain, as they are likely to be influenced by many factors and past reforestation
programs in the Philippines have had only limited success (see – Le et al., 2014, 2015; Herbohn et
al., 2014, Nguyen et al., 2014).
Shifting cultivation, locally called as kaingin, contributes to the livelihoods of many marginal
upland farmers in remote rural areas in the Philippines (Lawrence, 1997; Kummer, 1992). In the
country at least three and five million people largely depend on kaingin for their subsistence (Mertz
et al., 2009). Major forestry policies in the Philippines, however, have attempted to impose
restrictions on this land-use, based on the assumption that it has detrimental environmental impacts
(Saurez and Sajise, 2010). Although, the Philippines is one of the pioneers in large-scale restoration
and reforestation activities, access by smallholder and subsistence farmers to such efforts remains
very limited (Pulhin et al., 2007, Harrison et al., 2004). It is likely that kanigin will continue to form
an important land-use in the country’s rural, remote areas until greater access to such state regulated
reforestation programs will be secured to local communities under community based forest
management (CBFM) and other participatory schemes (Pulhin et al., 2007).
Due to its dynamic nature in tropical forested region, it is always difficult to generalize the
environmental outcomes of shifting cultivation both during and after the practice (Mukul and
Herbohn, 2016). Based on an empirical study in the Philippines here we present evidence that
fallow secondary forest after shifting cultivation can provide biodiversity and carbon co-benefits,
and could potentially be used as a cost effective forest management and reforestation measure. We
also draw upon results from other relevant studies focusing on alternative land-uses, namely
plantations of fast growing timber species (Swietenia macrophylla, Acacia sp.), oil palm, and
grassland areas and agricultural production (rice) in upland areas to perform a biodiversity and
carbon trade-off analysis. We discuss how the biodiversity and carbon co-benefits from
125
regenerating fallow forests could be integrated in ongoing forest conservation measures like
Payment for Environmental Services (PES), Reducing Emissions from Deforestation and Forest
Degradation (REDD+) and Clean Development Mechanism (CDM) projects. We also emphasized
on measures that are essential for success of such efforts with an aim to forest landscape restoration
and local development.
6.3 Methods
6.3.1 Background of the area
The Philippines archipelago is comprised of 7,107 islands, with a total land area of about 30
million ha (Chokkalingam et al., 2006). The country is divided into 17 regions covering 81
provinces, 118 cities, 1,520 municipalities and 41,995 Barangay (the smallest administrative entity
in the country, similar to a village). The climate of the country is tropical humid in general
(Kummer, 1992). Based on the national land classification system the Philippines has 53% forest
lands (all areas with a slope about 18% irrespective of whether they are covered in forest) and 47%
alienable and disposable lands (i.e. lands not classified as forestland and with slopes less than 18%)
(Jahn and Asio, 2001; Figure 6.1).
Upland areas in the Philippines are important for three main reasons. Firstly, most of the remaining
forests are located in the uplands; secondly, upland areas have been subject to intensified human use
since the Second World War; and thirdly, land degradation in the uplands is severe and widespread
(Cramb, 1998). At the same time, a great deal of uncertainty exists regarding recovery of
biodiversity and carbon stocks in degraded upland secondary forests after different levels of
disturbance and human use.
Our empirical study was based in the Leyte Island, the eighth largest island in the country. Leyte
has a forest cover of about 10%, although the once extensive dipterocarp rain forests are now
mainly patches of disturbed old-growth forests. The island covers an area of about 800,000 ha, and
is located between 124017
/ and 125
018
/ East longitude and between 9
055
/ and 11
048
/ North latitude.
According to Corona’s Classification of Climate Leyte has a ‘type IV’ climate (Navarrete et al.,
2013). The Island enjoys relatively even distribution of rainfall throughout the year with annual
rainfall totalling about 4,000 mm (Jahn and Asio, 2001). Mean annual temperature is 280C, which
remains constant throughout the year (Navarrete et al., 2013).
126
Figure 6.1. Major land-use/land-cover in the Philippines (left) (Source: Manuel 2014) with the location of Leyte Island indicated, and some common
land-use in the upland areas after shifting cultivation use (clockwise from top-left: regenerating forest dominated by seedlings and undergrowth,
secondary forest dominated by tree ferns, coconut plantation in grassland, abaca (Musa textilis) field, Acacia plantation in upland forest invaded by
grassland, old coconut plantation within secondary forest) (Photo credits: S.A. Mukul).
127
6.3.2 Study site selection
The sites for our empirical study were located in Barangay Gaas. The area was selected
purposively as it is situated in the comparatively high altitudinal range (450 - 650 m asl) in the
island with relatively greater extent of undisturbed forests and with low population density. Both of
these factors favour the natural regeneration in the kaingin fallow forests (Chokkalingam et al.,
2006). Smallholder farmers living in the area usually grow abaca (Musa textillis, a species of
banana native to the Philippines and harvested for fibre) or coconut in their fallow kaingin area in
order to receive financial benefits during the time of abandonment. We confined our study to the
areas where farmers cultivated only abaca, since coconut plantations generally involve more
intensified land-management during the fallow periods and does not favour secondary forest
development.
6.3.3 Data collection
A series of extensive field surveys were undertaken in our sites in Barangay Gaas between
May and October 2013. We categorized our sites into four different fallow categories; i.e. new
fallows (i.e. less than 5 year old fallow), young fallows (i.e. 6-10 year old fallow), middle-aged
fallows (i.e. 11-20 year old fallow), and oldest fallows (21-30 year old fallow). We sampled five
sites from each category, and all sites were at least 1 ha in size. Within each site four transects of
50m x 5m were established and we identified and measured the dbh (diameter at breast height) and
height of all trees that were at least 5 cm dbh. We also quantified the biomass of dead wood and
other non woody vegetation. More information about the survey design and data collection methods
can be found at Mukul et al., (in press). Additionally, we sampled old-growth forests as our control
site. Our control old-growth forests sites were structurally and floristically similar to intact primary
forests and had never been logged or used for kaingin. As with almost all forests in the Philippines
they may however have experienced limited anthropogenic disturbances (e.g. firewood, wild fruit
collection).
6.3.4 Data interpretation and analysis
Species richness or the number of unique species in each land-use/cover was used as a
measure of diversity in the study. We used the mean species number recorded from each fallow
category and from our control old-growth forest. Above ground biomass (Mg) was calculated on a
per hectare (ha) basis. We used the generic allometric model developed by Chave et al. (2014) for
measuring biomass in standing live trees (≥ 5cm dbh).
AGB = 0.0673 × (ρD2H)
0.976
128
Where, AGB is the aboveground biomass in kg, D is the dbh, H is the height of the tree and ρ is the
species specific wood density (g cm-3
). We assume carbon content is 50% of the dry plant biomass
(Brown, 1997). For species specific wood density we used the World Agroforestry Centre’s wood
density database (World Agroforestry Centre, 2014). Others biomass in undergrowth, litter, dead
wood and in other non-woody plants was measured using standard procedures (see Mukul et al., in
press for details).
We used descriptive statistics for data interpretation and analysis. Biodiversity and carbon trade-
offs was expressed as the additionality (∆), and was calculated as below (Maron et al., 2013):
∆ Additionality = Biodiversity/Carbon in control forest sites - Biodiversity/Carbon in other
land use/cover reported from the Philippines.
Where, additionality (∆) could be either positive, where + value indicates biodiversity/carbon gain
and a negative value indicates biodiversity/carbon loss.
6.4 Results
6.4.1 Biodiversity and carbon co-benefits from regenerating secondary forests
Tree diversity in terms of species richness was higher in the oldest fallow sites in our study
area in Gaas, followed by in middle-aged sites and in young fallow sites. Other indicators of
biodiversity like the number of locally endemic species (i.e. species that are not found outside of the
Philippines) were higher in the relatively older fallow sites (Figure 6.2). The number of critically
endangered species globally as listed in the IUCN Red List, and locally endangered species listed
by the Philippines’ Department of Environment and Natural Resources (DENR) was, however
occur on all fallow sites except for the new fallow sites (see Figure 6.2). Aboveground biomass
carbon was substantially higher in the old-growth forests compared to sites of all fallow categories.
The relative contribution of biomass carbon in live trees and in other above ground biomass is
shown in Figure 6.3. Biomass in other categories composed mostly by the deadwoods which was
substantially higher in the new fallow sites and vice versa.
129
Figure 6.2. Tree biodiversity in regenerating forest after shifting cultivation in the Philippines
uplands.
Figure 6.3. Above ground biomass carbon in regenerating forest following shifting cultivation in
the upland Philippines.
6.4.2 Biodiversity and carbon trade-offs in the upland land-use of Philippines
In Table 6.1 we present the potential trade-offs between biodiversity and carbon associated
with shifting cultivation fallow secondary forests and other common upland land-use that may
replace the regenerating forest after being abandoned or if the land converted to permanent and
more intensive sedentary agricultural field or used for plantation and/or reforestation using single
species or mixed species. Our old-growth control forest always provided the highest benefits in
terms of carbon in aboveground forest biomass. The Swietenia macrophylla plantation had the
nearest carbon stock to our old-growth forest sites, followed by kaingin fallow sites. The
biodiversity and/or conservation importance of the Swietenia macrophylla plantation was however
very low compared to kaingin fallow secondary forests of different fallow age and other tree based
land-use/cover that has been examined (Table 6.1). Only fallow secondary forest had the potential
to provide relatively similar biodiversity and carbon benefits compared to our old-growth control
0
20
40
60
80
100
120
New fallows Youngfallows
Middle-agedfallows
Oldestfallows
Old-growthforest
Number of species Endemic species
0
1
2
3
4
5
6
7
8
9
10
New fallows Youngfallows
Middle-agedfallows
Oldestfallows
Old-growthforest
Critically endangered (Global) Critically endangered (Local)
0
50
100
150
200
250
300
350
New fallows Young fallows Middle-agedfallows
Oldest fallows Old-growthforest
AGB (live tree) AGB (others)
Mg
ha-1
130
forests. As expected, agricultural use (e.g. rice paddy in this case) and plantations of commercially
important species such as oil palm and fast growing exotic Acacia species had also the lowest
conservation and carbon importance in the upland Philippines when compared with secondary
forests or fallow secondary forests after shifting cultivation (Table 6.1).
6.5 Discussion and implications
Our results clearly show that secondary forest regrowing after shifting cultivation can
support both substantial biodiversity and carbon benefits when compared with the old-growth
forest. While other land-uses may also have greater value in terms of carbon storage and
sequestration in tropical countries (see - Chazdon, 2014; Erskine et al., 2006), the conservation
value of such land-use is not always comparable to the old-growth forests or to the regenerating
fallow sites used in our study. Moreover, the costs and labour involved in plantation establishment
and management are also prerequisites for the long term success and continuation of these projects
(Gregorio et al., 2015). Our findings are consistent with the findings of Evans et al. (2015) and
Gilroy et al. (2014) that show the high potential of post-agricultural forest regeneration for
providing biodiversity and carbon co-benefits. We also find that, natural regeneration of shifting
cultivation fallows is a highly cost effective restoration measure when considering the costs of
plantation establishment and management in degraded landscapes in the area.
The extensive deforestation and degradation of tropical forests is a significant contributor to the loss
of biodiversity and to carbon emissions that cause global warming (Budiharta et al., 2014). In
tropical regions, uncertainties in biomass carbon, their distribution and recovery are one of the main
constraints in inclusion of secondary forests degraded by shifting cultivation to emerging global
voluntary carbon market (Ziegler et al., 2012; Mertz, 2009). Here we consider the potential of
alternative land-use(s) that may also replace fallow shifting cultivation landscapes in the tropics.
Presently, global forest carbon credits are valued at over US$100 billion/year, and are an emerging,
growing sector (Petrokofsky et al., 2011). In 2012, the price of sequestered carbon in the
internationally recognized market was averaged US$9.20 per tonne (i.e. Mg), although in recent
years there has been a decline in that price (US$3.8 per tonne in 2014) mainly due to fail in
legislation to ratify another phase of the Kyoto Protocol (Hamrick, 2015; Peters-Stanley and Yin,
2013). The prospect of inclusion of regenerating secondary forests in emerging global carbon
markets, however largely depends on the reliable estimates of carbon together with biodiversity
benefits of a particular land-use (Evans et al., 2015; Law et al., 2015; Maron et al., 2013).
131
Table 6.1. Biodiversity and aboveground carbon stocks in common upland land-cover/use in the Philippines uplands.
Land-use Biodiversity1 Carbon
2
(Mg ha-1
)
Additionality3(∆) Age
4 C sequestration
(Mg ha-1
)
Source
∆ Biodiversity ∆ Carbon
Old-growth forest 79 321.3 - - - NA Mukul et al. (2016),
Mukul et al. (In
review)
As above
As above
As above
As above
Post-kangin forest
New fallow 28 160.3 -51 -160.9 5 -
Young fallow 84 101.1 +5 -220.2 10 -
Middle-aged 95 122.4 +16 -198.9 20 -
Oldest fallow 106 132.5 +27 -188.8 30 -
Dipterocarp forest NA 221 - -100.3 NA - Lasco & Pulhin
(2009)
Grasslands -
Imperata sp. 0 8.5 -79 -312.8 1 0* Lasco & Pulhin
(2009)
Sacharrum sp. 0 13.1 -79 -308.2 1 0 * Lasco & Pulhin
(2009)
Plantations -
Swietenia
macrophylla
1 264 -78 -57.3 NA - Racelis et al. (2008)
Acacia sp. 1 81 -78 -240.3 NA - Lasco & Pulhin
(2009)
Oil palm 1 55 -78 -266.3 9 6.1 Pulhin et al. (2014)
Rice paddy 0 3.1 -79 -318.2 1 0* Lasco & Pulhin
(2009) 1 here we only consider the main and/or characteristics plant diversity of a particular land-use;
2 aboveground carbon in forest biomass;
3 the difference, either positive or negative between control old-growth forest and respective land-use;
4 stand age;
*no sequestration due to regular harvest;
NA – not available.
132
Globally policy makers recently collectively committed to the Bonn Challenge, an initiative to
restore 150 million hectares of degraded forests by 2020 and 350 million hectares by 2030
(Locatelli et al., 2015). Our trade-off analysis found that regenerating secondary forests after
shifting cultivation can be a cost-effective restoration approach in the Philippines, and are likely to
play a similar role in other tropical developing countries with comparatively similar socio-political
and environmental contexts. Due to limited information and data available on belowground
biomass/carbon we did not include belowground carbon in our comparisons. A recent study
suggested that carbon estimates without belowground biomass in tropical fallow secondary forests
may underestimate the carbon content by up to 30% (McNicol et al., 2015).
Deforestation in tropics is a large contributor to the global CO2 emissions, and reversing this trend
therefore has an obvious potential for recovering carbon, biodiversity and mitigate climate change
(Gibbs et al., 2007; Houghton, 2012). Because of diverse stakeholder needs, managing tropical
forest is complex and challenging (Yasmi et al., 2012). In tropical forest regions, particularly in
South and Southeast Asia, involving local communities offers potential benefits for forest
conservation (Robinson et al., 2014, Bowler et al., 2012, Balooni and Inoue, 2007). Globally, PES
programs like REDD+ and CDM are increasingly gaining wider recognition for their prospects for
protecting tropical forest and improving the standards of living of smallholders by giving them
access to forest management, monitoring and benefits from carbon trading. The number of CDM
projects with afforestation and/or reforestation objectives however remains still very limited
(Thomas et al., 2010).
Forest conservation in the Philippines has clearly visible benefits to local livelihoods and climate
change mitigation (see Lasco et al., 2013, 2011, Sheeran, 2006). Due to their extent and
distribution, regeneration in shifting cultivation fallows in the Philippines offers great prospects for
REDD+ and CDM. It is however critical to involve local community members in such activities
with clearly defined rights and responsibilities. Improvement of environmental governance by legal
and regulatory reform, better land tenure, land allocation and management, law enforcement and
monitoring however, crucial for the successful implementation and involvement of local people in
forest management in the country (see – Mukul et al., 2014; Chazdon, 2013; Grabowski and
Chazdon, 2012).
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138
CHAPTER 7: GENERAL CONCLUSIONS
7.1 The context
In tropical regions regenerating secondary forests are expanding dramatically, and in many
countries, they have already exceeded the total area covered by remaining primary forests (Chazdon
2014; McNamara et al., 2012). Much of these secondary forests emerged after different levels of
human interventions and use (Lawrence and Vandecar, 2015), and is increasingly considered as a
novel or emerging ecosystem with characteristics that are not common elsewhere (Chazdon, 2014;
Hobbs et al., 2009). Successful restoration and management of such novel ecosystems offer
important synergies for conservation and development (Locatelli et al., 2015; Chazdon et al., 2009).
In the upland Philippines, secondary forests comprise a large area with ecosystems that are highly
dynamic, making forest management and conservation challenging (Posa et al., 2008; Lasco et al.,
2001). Shifting cultivation or kaingin has been around a long time in the country (Kummer, 1992)
with perceived negative impacts on forests and environment, and no or limited conservation
significance in the country (Suarez and Sajise, 2010). The various chapters contained within this
thesis addressed the impacts of shifting cultivation in the Philippines uplands. The results are
important for understanding the impact of this land use in the Philippines and more broadly in the
tropics, and also have important policy implications. The key conclusions from this study are
discussed hereafter.
7.2 A synthesis of the impacts of shifting cultivation on tropical forests dynamics
Chapter 2 in this thesis presented a synthesis paper based on systematic literature review
(see also - Mukul and Herbohn, 2016). Emphasis was given on identifying any geographical and/or
subject/research focus bias that exists in research on shifting cultivation, with forest and
environmental aspects in secondary forests after shifting cultivation. The purpose of this study was
to better understand the ecological factors that may influence the recovery of such complex
landscape into secondary forest with environmental values similar to secondary or undisturbed
forest that never used for shifting cultivation. There was a bias towards research on anthropology
and/or human ecology with most research reported from tropical Asia Pacific region was evident.
There was also a great variation in the findings on selected environmental research aspects related
to secondary forest dynamics including conservation biology, plant ecology, soil nutrients and
chemistry and soil physics and hydrology.
139
7.3 The impact of shifting cultivation on biodiversity, species composition and forest
structure
The empirical part of this thesis study suggests that tropical secondary forests have the
ability to recover after shifting cultivation, although site factors matter during the recovery process.
It was found that old kaingin fallow areas can support relatively high numbers of rare and
endangered species and thus also play an important role in conservation. A number of dipterocarp
species, including endemic Hopea philippinensis, Shorea polysperma, Shorea contorta, were shared
across the fallow sites of different categories and in control old-growth forest. It was found that
initially there is a substantial decrease in biodiversity in the first five years, but the older fallow sites
can exhibit similar levels of biodiversity as to the old-growth forest without any history of major
disturbance. It was found that biodiversity indices used in the study, including –Shannon’s index
and species evenness index were higher in the old-growth forest while species richness was higher
in the oldest fallow sites. Recently abandoned new fallow areas demonstrated a very distinct pattern
of species diversity compared to the other older fallow categories in our study. A homogeneous
species composition between the older fallow sites/categories and old-growth forest was also
evident. Recovery of species richness and Shannon’s index in older fallow sites were rapid,
although there was no significant difference in the recovery of species evenness across the sites.
Recovery of stem density also increased gradually with fallow age. Recovery of stand basal area
was distinct across the sites and was higher in the relatively older fallow sites indicating the
presence of larger and mature trees in those sites. Patch size was found to influence the recovery of
species diversity, composition, and forest structure in regenerating secondary forests after shifting
cultivation.
7.4 Aboveground biomass carbon dynamics in regenerating tropical secondary forests
Overall, it was found that, tropical regenerating forests after shifting cultivation contribute
significant amounts to aboveground carbon. A relatively larger contribution of older fallow areas
compared to that of young fallow areas was found in the upland Philippines forests (see also –
Mukul et al., 2016). Carbon stored in control old-growth forest, oldest fallow areas and moderately-
aged fallow areas were 321.3 (±130.9) Mg ha-1
, 132.5 (±57.1) Mg ha-1
, 122.4 (±74.9) Mg ha-1
respectively. In young kaingin fallow areas, other living standing biomass (represented here by tree
ferns and Abaca, a relative of the banana) and coarse dead wood biomass constitute a major part of
the aboveground biomass carbon, depicting a different composition in landscape level total
aboveground biomass carbon storage in the area. Recovery of aboveground living woody biomass
carbon was highest in the oldest fallow sites and lowest in the new kaingin fallow sites. In new
140
kaingin fallow areas, the high level of aboveground biomass carbon was mainly due to high levels
of coarse dead wood remaining as an artefact of forest clearing. Carbon stored in other living
biomass was highest in young kaingin fallow areas, where undergrowth and litter biomass carbon
was found to increase gradually from new to old kaingin fallow sites. It was again found that
biomass carbon recovery was constrained mainly by landscape patchiness, with patch size
exhibiting a significant influence on the recovery of biomass carbon at different aboveground
carbon pool.
7.5 Soil carbon and nutrients in regenerating secondary forests after shifting cultivation
The study found limited influence of shifting cultivation on soil organic carbon, soil
nitrogen, and phosphorus availability in regenerating secondary forests. A reduced stock of soil
available potassium was however found. Site environmental factors like patch size, had the greatest
control on the recovery of the pool of soil carbon, soil nitrogen and soil phosphorus. In case of soil
potassium in middle (i.e. 6-15 cm) and bottom (i.e. 16-30 cm) soil layer, slope was also found
equally important together with patch size in the recovery of potassium in the soil.
7.6 Opportunities for biodiversity and carbon benefits from fallow secondary forests
Uncertainties in the biodiversity and carbon dynamics associated with shifting cultivation-
fallow secondary forests are one of the main issues hindering its inclusion in major developments in
tropical forest conservation using REDD+ and other CDM options. Drawing on the empirical
finding from the Philippines upland it was demonstrated that regenerating secondary forests after
shifting cultivation have the potentials for inclusion in programs on forest conservation like REDD+
and CDM (see also- Mukul et al., in press).
7.7 Implications of this research
The challenge of translating science into policy is a common problem for many applied
disciplines including forestry and environmental science (Cook et al., 2013; Bilotta et al., 2014).
Evidence-based science provides scientific and other relevant communities like policy makers, an
overview of relevant and trustworthy guidelines that are pertinent to informed decision making
(Pullin and Knight, 2009). The finding of this research emphasized the importance of Southeast
Asian rainforests after major anthropogenic disturbances like shifting cultivation in the context of
biodiversity conservation, and carbon and soil quality management. The results conclude that
regenerating secondary forests after shifting cultivation can act as a cost-effective conservation,
restoration, and forest management option not only in the Philippines but also in other developing
141
countries where the practice of shifting cultivation is common among smallholder rural and upland
farmers.
7.8 References
Bilotta, G.S., Milner, A.M., Boyd, I., 2014. On the use of systematic reviews to inform
environmental policies. Environmental Science & Policy, 42, 67-77.
Budiharta, S., Meijaard, E., Erskine, P.D., Rondinini, C., Pacifici, M., Wilson, K.A., 2014.
Restoring degraded tropical forests for carbon and biodiversity. Environmental Research
Letters, 9, 114020.
Chazdon, R.L., 2014. Second growth: The promise of tropical forest regeneration in an age of
deforestation. University of Chicago Press, Chicago, IL.
Chazdon, R.L., Peres, C.A., Dent, D., Sheil, D., Lugo, A.E., Lamb, D., Stork, N.E., Miller, S.E.,
2009. The Potential for species conservation in tropical secondary forests. Conservation
Biology, 23, 1406–1417.
Cook, C.N., Possingham, H.P., Fuller, R.A., 2013. Contribution of systematic reviews to
management decisions. Conservation Biology, 27, 902-915.
Hobbs, R.J., Higgs, E., Harris, J.A., 2009. Novel ecosystems: implications for conservation and
restoration. Trends in Ecology and Evolution, 24, 599-605.
Kummer, D.M., 1992. Upland agriculture, the land frontier and forest decline in the
Philippines. Agroforestry Systems, 18, 31-46.
Lasco, R.D., Visco, R.G., Pulhin, J.M., 2001. Secondary forests in the Philippines: formation and
transformation in the 20th century. Journal of Tropical Forest Science, 13, 652–670.
Lawrence, D., Vandecar, K., 2015. Effects of tropical deforestation on climate and agriculture.
Nature Climate Change, 5, 27-36.
Locatelli, B., Catterall, C.P., Imbach, P., Kumar, C., Lasco, R., Marín-Spiotta, E., Mercer, B.,
Powers, J.S., Schwartz, N., Uriarte, M., 2015. Tropical reforestation and climate change:
beyond carbon. Restoration Ecology, 23, 337-343.
McNamara, S., Erskine, P.D., Lamb, D., Chantalangsy, L., Boyle, S., 2012. Primary tree species
diversity in secondary fallow forests of Laos. Forest Ecology and Management, 281, 93–99.
Mukul, S.A., Herbohn, J., Firn, J., 2016. Tropical secondary forests regenerating after shifting
cultivation in the Philippines uplands are important carbon sinks. Scientific Reports, 6, 22483.
Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics
in tropics: a synthesis of the key findings and spatio temporal distribution of research.
Environmental Science & Policy, 55, 167-177.
142
Mukul, S.A., Herbohn, J., Firn, J., In press. Co-benefits of biodiversity and carbon from
regenerating secondary forests following shifting cultivation in the upland Philippines:
implications for forest landscape restoration. Biotropica.
Posa, M.R., Diesmos, A.C., Sodhi, N.S., Brooks, T.M., 2008. Hope for threatened tropical
biodiversity: lessons from the Philippines. BioScience, 58, 231-240.
Pullin, A.S., Knight, T.M., 2009. Doing more good than harm – building and evidence-base for
conservation and environmental management. Biological Conservation, 142, 931-934.
Suarez, R.K., Sajise, P.E., 2010. Deforestation, swidden agriculture and Philippine biodiversity.
Philippine Science Letters, 3, 91-99.
143
APPENDICES
Supplmentary Figure 2.1. Country-wise distribution of research on shifting cultivation.
0 10 20 30 40 50 60 70
Bangladesh
Belize
Bhutan
Bolivia
Brazil
Burkina Faso
Cameroon
China
Colombia
Costa Rica
Ecuador
Egypt
French Guiana
Guatemala
Guinea
Honduras
India
Indonesia
Ivory Coast
Lao PDR
Liberia
Madagascar
Malaysia
Mexico
Nicaragua
Nigeria
Panama
Papua New Guinea
Paraguay
Peru
Philippines
São Tomé
Sierra Leone
Solomon Islands
South Africa
Sri Lanka
Sudan
Suriname
Tanzania
Thailand
Tonga
Venezuela
Vietnam
Zaire
Zambia
Agricultural production/ Management Agroforestry Anthroplogy/ Human ecology
Geography/ Land-use transitions Conservation biology Plant ecology
Soil nutrients and chemistry Soil physics and hydrology Others
144
Supplementary Table 3.1. Different measures for diversity and forest structure used in the present
study.
Parameter Indices Description
Biodiversity Species richness (S) Number of unique species
Shannon-Wiener’s Index (H) 𝐻 = − ∑ 𝑝ᵢ(𝑙𝑛 𝑝ᵢ) 𝑠𝑖=1 ,
Species Evenness Index (J) J= H/ln(S)
Forest structure Stem number (N) Number of individuals
Basal area (BA) 𝐵 = ∑ 0.00007854 𝑋 DBH2
Leaf Area Index (LAI) Total leaf area/ground area
*where‘S’ is the number of species; ‘N’ is the total number of trees, ‘𝑝𝑖’is the proportion of a
particular species, and DBH is the diameter at breast height of trees expressed in cm.
145
Supplementary Table 3.2. Pearson correlation between site environmnetal attributes.
Fallow age Elevation Slope Patch size Distance SOC
Fallow age 1 -0.09 0.25 0.07 -0.35 0.05
Elevation -0.09 1 0.52* -0.03 -0.117 0.53*
Slope 0.25 0.52* 1 -0.16 0.065 0.43
Patch size 0.07 -0.01 -0.16 1 -0.085 -0.33
Distance -0.35 -0.12 0.07 -0.09 1 -0.01
SOC 0.05 0.53* 0.43 -0.325 -0.005 1
* Correlations significant at p<0.05 level.
146
Supplementary Figure 3.1. Importance value of species across the sites of different fallow categories and in control old-growth
forest.
Old-growth forest
147
Supplementary Figure 3.2. nMDS of richness (stress=11.33) and abundance (stress=13.03)
of species of global (as per IUCN Red List) conservation concern using Bray-Curtis distance.
148
Supplementary Figure 3.3. nMDS of richness (stress=19.07) and abundance (stress=19.57)
of species of local (as per DENR) conservation concern using Bray-Curtis distance.
149
Supplementary Table 4.1. Site environmental attributes, mean±SE. Where, EL = elevation,
SL = slope, PS = patch size, DIS = distance (from the nearest control forest site), LAI = leaf
area index, SOC = soil organic carbon.
Site attributes
(unit)
Fallow category Old-growth
forest ≤5 year 6-10 year 11-20 year 21-30 year
EL
(masl)
600.8
(±22.19)
549.0
(±72.41)
567.2
(±49.24)
574.8
(±35.35)
512.4
(±54.77)
SL
(degree)
33
(±5.7)
32.4
(±9.4)
32.6
(±9.2)
38.2
(±7.98)
36.4
(±9.71)
PS
(ha)
1.16
(±0.21)
1.14
(±0.13)
1.34
(±0.24)
1.14
(±0.22)
na
DIS
(m)
290
(±74.16)
540
(±114.01)
162
(±198.17)
256
(±153.88)
na
LAI
(%)
1.33
(±0.57)
5.70
(±0.96)
5.14
(±1.01)
5.33
(±0.69)
6.08
(±0.86)
SOC
(%)
6.17
(±0.68)
6.54
(±2.05)
5.21
(±0.69)
6.79
(±1.92)
4.77
(±1.11)
Values in the parenthesis indicates the standarard deviation;
na – not available.
150
Supplementary Table 4.2. Wood density and characteristics of species recorded from the sites on
Leyte Island, the Philippines.
Botanical name Local name Origin1 Successional
guild2
Wood density3
(gm cm-3
)
Alangium javanicum (Bl.) Wang Putian Native Secondary 0.78
Dracontomelon dao (Blanco) Merr. &
Rolfe
Dao
Native
Secondary
0.63
Dracontomelon edule (Blanco) Skeels. Lamio Native Secondary 0.55
Cananga odorata (Lam.) Hook. f. &
Thomson
Ilang-ilang
Native
Secondary
0.35
Polyalthia oblongifolia Burck Lapnisan Native Secondary 0.56
Polyalthia flava Yellow lanutan Endemic Secondary 0.51
Alstonia macrophylla G. Don Batino Native Pioneer 0.56
Alstonia parvifolia Merr. Batino-liitan Endemic Pioneer 0.46
Wrightia pubescens R.Br. Lanete Native Pioneer 0.53
Kibatalia gitingensis (Elmer) Woodson Laneteng-gubat Endemic Secondary 0.46
Arthrophyllum cenabrei Merr. Bingliu Endemic Pioneer 0.41
Polyscias nodosa (Blume) Seem. Malapapaya Native Pioneer 0.37
Areca cathecu L Bunga Native Secondary 0.62
Cocos nucifera L. Coconut Native Pioneer 0.62
Caryota cumingii Lodd. ex Mart. Pugahan Native Pioneer 0.62
Heterospathe elata Scheff. Sagisi Native Pioneer 0.62
Radermachera pinnate (Blanco) Seem. Banai-Banai Native Secondary 0.52
Canarium hirsutum Milipili Native Secondary 0.57
Canarium calophyllum Perkins. Pagsahingin-
bulog
Native
Secondary
0.57
Canarium luzonicum (Blume) A.Gray Piling-liitan Endemic Pioneer 0.43
Calophyllum lancifolium Elmer. Bitanghol-sibat Native Secondary 0.61
Trema orientalis (L.) Bl. Anabiong Native Pioneer 0.36
Celtis philippensis Blanco Malaikmo Native Secondary 0.72
Casuarina equisetifolia L. Agoho Exotic Pioneer 0.92
Gymnostoma rumphianum (Miq.) L.A.S.
Johnson
Mountain
agoho
Native Secondary 1.0
Calophyllum blancoi Planch. & Triana Bitanghol Native Secondary 0.53
Terminalia microcarpa Decne. Kalumpit Native Secondary 0.57
Cycas circinalis L. Pitogo Native Pioneer 0.57
Octomeles sumatrana Miq. Binuang Native Secondary 0.32
Dillenia indica L. Handapara Native Secondary 0.65
Dillenia philippinensis Rolfe Katmon Endemic Secondary 0.67
Shorea almon Foxw. Almon Endemic Climax 0.44
Parashorea malaanonan (Blanco) Merr. Bagtikan Native Climax 0.47
Dipterocarpus eurynchus Miq. Basilanapitong Endemic Secondary 0.72
Hopea philippinensis Dyer Gisok-gisok Endemic Pioneer 0.75
Shorea guiso (Blanco) Blume Guijo Native Pioneer 0.77
Shorea palosapis (Blanco) Merr. Mayapis Endemic Climax 0.42
Anisoptera thurifera Palosapis Native Secondary 0.65
Shorea polysperma (Blanco) Merr. Tangile Endemic Climax 0.56
Shorea contorta Vidal White lauan Endemic Climax 0.48
Hopea malibato Yakal-kaliot Native Climax 1.0
Diospyros pilosanthera Blanco Bolong-eta Native Secondary 0.75
151
Diospyros blancoi A.DC. Kamagong Native Climax 0.9
Neotrewia cumingii (Müll.Arg.) Pax &
K.Hoffm.
Apanang
Native
Pioneer
0.55
Mallotus philippensis (Lam.) Müll.Arg. Banato Native Secondary 0.68
Macaranga tanarius (L.) Müll.Arg. Binunga Native Pioneer 0.48
Macaranga bicolor Muell. -Arg. Hamindang Endemic Pioneer 0.30
Mallotus ricinoides (Pers.) Müll.Arg. Hinlaumo Native Pioneer 0.42
Ormosia calavensis Blanco Bahai Endemic Climax 0.50
Albizia falcataria (L.) Fosberg. Falcata Exotic Secondary 0.31
Leucaena leucaephala (Lam.) de Wit. Ipil-ipil Exotic Pioneer 0.64
Pterocarpus indicus Willd. Narra Native Secondary 0.74
Albizia saponaria(Lour.) Blume ex Miq. Salingkugi Native Secondary 0.66
Senna siamea (Lam.) Irwin et Barneby Thailand
shower
Native Secondary 0.68
Lithocarpus llanosii (A.DC.) Rehder Ulaian Native Pioneer 0.71
Cratoxylum celebicum Bl. Paguriagon Native Secondary 0.60
Vitex quinata (Lour.) F. N. Williams Kalipapa Native Pioneer 0.50
Vitex turczaninowii (Turcz.) Merr. Lingo-lingo Endemic Secondary 0.64
Premna cumingiana Schauer Magilik Native Secondary 0.66
Tectona grandis L. f. Teak Exotic Pioneer 0.61
Callicarpa elegans Hayek Tigau-ganda Endemic Pioneer 0.40
Cinnamomum cebuense Kostermans Kaningag Endemic Pioneer 0.50
Litsea perrottetii (Bl.) Villar. Marang Native Secondary 0.49
Neolitsea vidalii Merr. Puso-puso Endemic Secondary 0.59
Barringtonia racemosa Spreng. Putat Native Pioneer 0.50
Petersianthus quadrialatus (Merr.) Merr. Toog Endemic Pioneer 0.59
Diplodiscus paniculatus Turcz. Balobo Endemic Secondary 0.63
Pterospermum obliquum Blanco Kulatingan Endemic Pioneer 0.52
Astronia cumingiana S.Vidal Badling Native Pioneer 0.56
Dysoxylum decandrum Merrill. Igyo Native Pioneer 0.58
Toona philippinensis Elmer. Lanigpa Native Pioneer 0.42
Dysoxylum cumingianum C. DC. Tara-tara Native Pioneer 0.64
Artocarpus blancoi (Elmer) Merr. Antipolo Endemic Pioneer 0.60
Artocarpus ovatus Blanco Anubing Endemic Pioneer 0.69
Ficus irisana Elmer. Aplas Native Pioneer 0.44
Ficus balete Merr. Balete Native Pioneer 0.65
Ficus gul K. Schum. & Lauterb. Butli Native Secondary 0.44
Ficus minahassae (Teijsm. & De Vriese)
Miq.
Hagimit
Native
Secondary
0.38
Ficus septica Burm. f. Hauili Native Secondary 0.44
Ficus ulmifolia Lam. Is-is Endemic Pioneer 0.44
Ficus callosa Willd. Kalukoi Native Pioneer 0.33
Ficus magnoliifolia Blume Kanapai Native Secondary 0.44
Ficus odorata (Blanco) Merr. Pakiling Endemic Climax 0.44
Ficus vrieseana Miq. Tagitig Native Secondary 0.44
Ficus nota Merr. Tibig Native Pioneer 0.44
Ficus ampelas Burm. f Upling-gubat Native Pioneer 0.33
Myrica javanica Reinw. ex Bl. Hindang Native Secondary 0.62
Knema mindanaensis (Warb.) comb. nov. Bunod Endemic Secondary 0.58
Parartocarpus venenosus (Zoll. & Morr.)
Becc. ssp. papuanus (Becc.) Jarr.
Malanangka
Native
Pioneer
0.42
152
Horsfieldia costulata (Miq.) Warb. Yabnob Native Pioneer 0.49
Ardisia pyramidalis (Cav.) Pers. ex A.
DC.
Aunasin Native Secondary 0.58
Syzygium surigaense (Merr.) Merr. Kagagko Endemic Secondary 0.71
Syzygium crassilimbum (Merr.) Merr. Kaitatanag Endemic Secondary 0.71
Syzygium gigantifolium (Merr.) Merr. Malatalisai Endemic Secondary 0.71
Syzygium hutchinsonii (C.B.Robinson)
Merr.
Malatambis
Endemic
Secondary
0.71
Xanthostemon verdugonianus Naves Mangkono Endemic Pioneer 1.05
Strombosia philippinensis (Baill.) Rolfe Tamayuan Endemic Secondary 0.75
Pandanus radicans Blanco Ulangong-
ugatan
Endemic Pioneer 0.33
Securinega fIexuosa (Muell. -Arg.) Anislag Endemic Pioneer 0.77
Antidesma ghaesembilla Gaertn. Binayuyu Native Climax 0.63
Glochidion camiguinense Merr. Bunot-Bunot Endemic Pioneer 0.61
Glochidion album (Blanco) Boerl. Malabagang Native Pioneer 0.61
Breynia rhamnoides Müll.Arg. Matang-hipon Native Pioneer 0.77
Cleistanthus venosus C.B. Rob. Sarimisim Endemic Secondary 0.67
Bridelia penangiana Hook.f.Bridelia
insulana Hance
Subiang
Native
Secondary
0.54
Bischofia javanica Blume Tuai Native Secondary 0.64
Piper anduncum L. Spiked pepper Native Pioneer 0.39
Carallia brachiata (Lour.) Merr. Bakauan-gubat Native Secondary 0.70
Neonauclea formicaria (Elmer) Merr. Hambabalud Endemic Pioneer 0.74
Mussaenda philippica A.Rich. Kahoi-dalaga Native Secondary 0.64
Neonauclea bartlingii (DC.) Merr. Lisak Endemic Secondary 0.74
Canthium fenicis (Merr.) Merr. Mapugahan Endemic Pioneer 0.64
Canthium monstrosum (A. Rich.) Merr. Tadiang-anuang Native Pioneer 0.43
Melicope triphylla (Lam.) Merr. Matang-arau Endemic Pioneer 0.38
Nephelium lappaceum Rambutan Native Pioneer 0.77
Planchonella nitida (Blume) Dubard. Duklitan Exotic Secondary 0.61
Palaquium luzoniense (Fern.-Vill.) Vidal Nato Endemic Secondary 0.71
Pterospermum diversifolium Bl. Bayok Native Pioneer 0.58
Trichospermum involucratum (Merr.)
Elmer
Langosig
Endemic
Pioneer
0.33
Leucosyke capitellata (Pair.) Wedd. Alagasi Native Pioneer 0.44
Pipturus arborescens (Link) C. B. Rob. Dalunot Native Pioneer 0.39
Dendrocnide stimulans (L. f) Chew Lingaton Native Pioneer 0.21
Premna odorata Blanco Alagau Native Secondary 0.66
Premna stellate Merr. Manaba Native Secondary 0.66
Leea aculeata Bl. Amamali Native Pioneer 0.57
Unknown Anungo - Secondary 0.57
Unknown Nandamai - Pioneer 0.57
Unknown Pandukaki - Pioneer 0.57
Unknown Pegonngon - Secondary 0.57
Unknown Poelig - Pioneer 0.57
Unknown Siyao - Pioneer 0.57 1where Native – refers to a species naturally occurring in the Philippines, Endemic - refers to a species found
only in the Philippines and Exotic – refers to a species that has been introduced in the Philippines.
153
2based on experts opinion from the Philippines; where pioneer species generally refers to the early colonizer
species with high light demanding and first growing nature, secondary are the intermediary group of species
with moderate light demand and growth, and climax species are the characteristics species of a forest
ecosystem that are common in the old growth forest, and are shade tolerant.
1meadian wood density value retrieved from the World Agroforestry Centre Wood Density Database on 2014
(http://www.worldagroforestry.org/regions/southeast_asia/resources/db/wd).
154
Supplementary Table 4.3. Organic carbon contents in litter and undergrowth samples from the
study sites on Leyte island, the Philippines.
Site category Carbon (%) in dry biomass*
Litter Undergrowth
SA0-5 39.56 (±2.52) 37.74 (±3.91)
SA6-10 41.17 (±5.49) 39.53 (±3.19)
SA11-20 41.46 (±2.13) 44.04 (±1.85)
SA21-30 43.45 (±2.57) 44.14 (±1.10)
SF 40.37 (±1.73) 42.57 (±1.70)
*values in the parenthesis indicate the standard deviation of means.
155
Supplementary Table 4.4. Organic carbon contents in dead wood samples from the study sites on
Leyte Island, the Philippines.
Wood degradation status Carbon (%) in dry biomass*
Freshly cut 43.60 (±0.93)
Moderately decomposed 40.54 (±2.32)
Highly decomposed 41.98 (±1.98)
Burnt 46.95 (±0.48)
*values in the parenthesis indicate the standard deviation of means.
156
Supplementary Table 4.5. Pearson correlation between site environmental attributes.
Fallow age Elevation Slope Patch
size
Distance LAI SOC
Fallow age 1 -0.09 0.25 0.07 -0.35 0.57**
0.05
Elevation -0.09 1 0.52* -0.003 -0.12 -0.41 0.53
*
Slope 0.25 0.52* 1 -0.16 0.07 0.02 0.43
Patch size 0.07 -0.003 -0.16 1 -0.09 -0.04 -0.33
Distance -0.35 -0.12 0.07 -0.09 1 0.22 -0.01
LAI 0.57**
-0.41 0.02 -0.04 0.22 1 -0.01
SOC 0.05 0.53* 0.43 -0.33 -0.01 -0.01 1
*Correlations significant at p<0.05 level;
**Correlations significant at p<0.01 level.
157
Supplementary Table 4.6. Biomass carbon (Mg C) distribution in living woody species (LWBC) in our study sites on Leyte island, the
Philippines.
Botanical name All sites Site category
SA0-5 SA6-10 SA11-20 SA21-30 SF
Alangium javanicum (Bl.) Wang 6.21 (1.95%)* 0 (0) 0.91 (2.45%) 0.97 (1.74%) 2.9 (4.83%) 1.43 (0.90%)
Albizia falcataria (L.) Fosberg. 0.08 (0.03%) 0 (0) 0 (0) 0.01(0.02%) 0.07 (0.1%2) 0 (0)
Albizia saponaria(Lour.) Blume ex Miq. 0.45 (0.14%) 0 (0) 0.02 (0.05%) 0 (0) 0.02 (0.04%) 0.41 (0.26%)
Alstonia macrophylla G. Don 0.15 (0.05%) 0 (0) 0.03 (0.07%) 0.07 (0.13%) 0.05 (0.08%) 0 (0)
Alstonia parvifolia Merr. 0.01 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0) 0 (0)
Anisoptera thurifera 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0)
Antidesma ghaesembilla Gaertn. 1.63 (0.51%) 0 (0) 1.17 (3.16%) 0 (0) 0.29 (0.48%) 0.17 (0.11%)
Ardisia pyramidalis (Cav.) Pers. ex A. DC. 1.60 (0.50%) 0 (0) 0.65 (1.76%) 0.27 (0.49%) 0.09 (0.15%) 0.58 (0.37%)
Areca cathecu L 0.15 (0.05%) 0 (0) 0 (0) 0.06 (0.11%) 0.09 (0.15%) 0 (0)
Arthrophyllum cenabrei Merr. 0.09 (0.03%) 0 (0) 0 (0) 0.09 (0.16%) 0 (0) 0 (0)
Artocarpus blancoi (Elmer) Merr. 2.09 (0.65%) 0 (0.02%) 0.18 (0.48%) 0.37 (0.65%) 0.02 (0.03%) 1.52 (0.96%)
Artocarpus ovatus Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0)
Astronia cumingiana S.Vidal 0.28 (0.09%) 0 (0) 0.02 (0.06%) 0.05 (0.09%) 0.14 (0.24%) 0.05 (0.03%)
Barringtonia racemosa Spreng. 1.55 (0.49%) 0 (0) 0.09 (0.25%) 0.20 (0.36%) 0.42 (0.70%) 0.84 (0.53%)
Bischofia javanica Blume 15.86 (4.97%) 0 (0) 1.02 (2.74%) 4.38 (7.83%) 2.86 (4.77%) 7.60 (4.79%)
Breynia rhamnoides Müll.Arg. 0.29 (0.09%) 0 (0) 0.17 (0.46%) 0.08 (0.14%) 0.04 (0.07%) 0 (0)
Bridelia penangiana Hook.f.Bridelia insulana Hance 1.05 (0.33%) 0 (0) 0.06 (0.16%) 0.01 (0.02%) 0 (0.01%) 0.98 (0.62%)
Callicarpa elegans Hayek 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0)
Calophyllum blancoi Planch. & Triana 13.53 (4.24%) 0 (0) 0.24 (0.64%) 0.84 (1.50%) 3.43 (5.72%) 9.02 (5.69%)
Calophyllum lancifolium Elmer. 1.39 (0.43%) 1.35 (8.08%) 0.01 (0.03%) 0 (0) 0.02 (0.04%) 0 (0)
Cananga odorata (Lam.) Hook. f. & Thomson 0.06 (0.02%) 0 (0) 0.06 (0.15%) 0 (0) 0 (0) 0 (0)
Canarium calophyllum Perkins. 0.81 (0.25%) 0.01 (0.06%) 0.11 (0.30%) 0.21 (0.37%) 0.13 (0.22%) 0.36 (0.23%)
Canarium hirsutum 0.09 (0.03%) 0 (0) 0 (0) 0.03 (0.05%) 0.05 (0.08%) 0.02 (0.01%)
Canarium luzonicum (Blume) A.Gray 0.62 (0.19%) 0 (0) 0.04 (0.11%) 0.03 (0.05%) 0.12 (0.20%) 0.43 (0.27%)
Canthium fenicis (Merr.) Merr. 0.31 (0.10%) 0 (0) 0.17 (0.47%) 0 (0) 0.13 (0.22%) 0 (0)
Canthium monstrosum (A. Rich.) Merr. 0.16 (0.05%) 0 (0) 0.15 (0.40%) 0.01 (0.02%) 0 (0) 0 (0)
Carallia brachiata (Lour.) Merr. 0.20 (0.06%) 0 (0) 0.06 (0.15%) 0.01 (0.02%) 0.04 (0.07%) 0.09 (0.06%)
Caryota cumingii Lodd. ex Mart. 3.03 (0.95%) 0 (0) 0.87 (2.37%) 0.43 (0.77%) 0.45 (0.74%) 1.29 (0.81%)
158
Casuarina equisetifolia L. 0.18 (0.06%) 0.18 (1.06%) 0 (0) 0.01 (0.01%) 0 (0) 0 (0)
Celtis philippensis Blanco 0.78 (0.25%) 0 (0) 0 (0) 0 (0) 0.02 (0.03%) 0.77 (0.48%)
Cinnamomum cebuense Kostermans 1.12 (0.35%) 0 (0) 0.05 (0.13%) 0.98 (1.75%) 0.09 (0.15%) 0 (0)
Cleistanthus venosus C.B. Rob. 0.02 (0.01%) 0 (0) 0.01 (0.02%) 0 (0) 0.02 (0.03%) 0 (0)
Cocos nucifera L. 0.02 (0.01%) 0 (0) 0 (0) 0 (0) 0.02 (0.04%) 0 (0)
Cratoxylum celebicum Bl. 1.24 (0.39%) 0 (0) 0.07 (0.18%) 0.01 (0.02%) 1.06 (1.77%) 0.10 (0.06%)
Cycas circinalis L. 0.06 (0.02%) 0 (0) 0 (0) 0.06 (0.10%) 0 (0) 0 (0)
Dendrocnide stimulans (L. f) Chew 0 (0) 0 (0) 0 (0) 0 (0) 0 (0.01%) 0 (0)
Dillenia indica L. 0.02 (0.01%) 0 (0) 0.01 (0.02%) 0 (0) 0.01 (0.02%) 0 (0)
Dillenia philippinensis Rolfe 0.52 (0.16%) 0 (0) 0.02 (0.06%) 0.06 (0.10%) 0.22 (0.37%) 0.22 (0.14%)
Diospyros blancoi A.DC. 1.67 (0.52%) 0 (0) 0.01 (0.02%) 1.64 (2.93%) 0 (0) 0.03 (0.02%)
Diospyros pilosanthera Blanco 1.69 (0.53%) 0 (0) 0.01 (0.02%) 1.04 (1.86%) 0.53 (0.89%) 0.11 (0.07%)
Diplodiscus paniculatus Turcz. 2.86 (0.90%) 0 (0) 1.24 (3.36%) 0.23 (0.41%) 0.81 (1.34%) 0.58 (0.36%)
Dipterocarpus eurynchus Miq. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0) 0 (0)
Dracontomelon dao (Blanco) Merr. & Rolfe 1.13 (0.36%) 0 (0) 0.01 (0.02%) 0.61 (1.08%) 0.04 (0.07%) 0.48 (0.30%)
Dracontomelon edule (Blanco) Skeels. 0.36 (0.11%) 0 (0) 0 (0) 0.02 (0.04%) 0.02 (0.03%) 0.31 (0.20%)
Dysoxylum cumingianum C. DC. 2.01 (0.63%) 0 (0) 0.15 (0.39%) 0.21 (0.37%) 0.16 (0.26%) 1.50 (0.95%)
Dysoxylum decandrum Merrill. 1.89 (0.59%) 0 (0) 0.01 (0.01%) 0.07 (0.13%) 0.16 (0.27%) 1.65 (1.04%)
Ficus ampelas Burm. f 1.11 (0.35%) 0 (0) 0.13 (0.35%) 0 (0.01%) 0 (0) 0.98 (0.62%)
Ficus balete Merr. 16.97 (5.32%) 0 (0.01%) 0.53 (1.43%) 2.75 (4.91%) 0 (0) 13.69 (8.64%)
Ficus callosa Willd. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0.01%) 0 (0)
Ficus gul K. Schum. & Lauterb. 1.03 (0.32%) 0.01 (0.03%) 0.47 (1.25%) 0.13 (0.24%) 0.27 (0.45%) 0.15 (0.10%)
Ficus irisana Elmer. 0.21 (0.06%) 0 (0) 0.07 (0.20%) 0.10 (0.18%) 0.03 (0.05%) 0 (0)
Ficus magnoliifolia Blume 0.58 (0.18%) 0 (0) 0.53 (1.44%) 0.04 (0.08%) 0.01 (0.01%) 0 (0)
Ficus minahassae (Teijsm. & De Vriese) Miq. 1.72 (0.54%) 0.01 (0.04%) 0.50 (1.34%) 1.09 (1.94%) 0.02 (0.03%) 0.11 (0.07%)
Ficus nota Merr. 0.36 (0.11%) 0 (0.01%) 0.24 (0.63%) 0.05 (0.09%) 0.01 (0.01%) 0.06 (0.04%)
Ficus odorata (Blanco) Merr. 0.11 (0.04%) 0 (0) 0.09 (0.25%) 0 (0.01%) 0.02 (0.03%) 0 (0)
Ficus septica Burm. f. 0.56 (0.18%) 0 (0.03%) 0.49 (1.33%) 0.07 (0.12%) 0 (0) 0 (0)
Ficus ulmifolia Lam. 0.12 (0.04%) 0 (0) 0.04 (0.12%) 0 (0.01%) 0.06 (0.10%) 0 (0)
Ficus vrieseana Miq. 0.15 (0.05%) 0 (0) 0 (0) 0 (0) 0 (0) 0.15 (0.09%)
Glochidion album (Blanco) Boerl. 0.26 (0.08%) 0 (0) 0.02 (0.06%) 0 (0.01%) 0.01 (0.02%) 0.22 (0.14%)
Glochidion camiguinense Merr. 1.07 (0.34%) 0 (0) 0.22 (0.59%) 0.02 (0.04%) 0.09 (0.16%) 0.74 (0.47%)
Gymnostoma rumphianum (Miq.) L.A.S. Johnson 1.18 (0.37%) 0 (0) 0.38 (1.02%) 0 (0) 0.81 (1.34%) 0 (0)
Heterospathe elata Scheff. 0.34 (0.11%) 0 (0) 0.03 (0.09%) 0.03 (0.05%) 0 (0.01%) 0.28 (0.18%)
159
Hopea malibato 0 (0) 0 (0) 0 (0) 0 (0) 0 (0.01%) 0 (0)
Hopea philippinensis Dyer 3.12 (0.98%) 0 (0) 0.43 (1.16%) 0.22 (0.40%) 0.08 (0.13%) 2.40 (1.51%)
Horsfieldia costulata (Miq.) Warb. 2.81 (0.88%) 0 (0) 0.34 (0.91%) 0.68 (1.22%) 0.50 (0.83%) 1.29 (0.82%)
Kibatalia gitingensis (Elmer) Woodson 1.87 (0.58%) 0 (0) 0.01 (0.02%) 0.74 (1.33%) 0.89 (1.47%) 0.23 (0.15%)
Knema mindanaensis (Warb.) comb. nov. 0.56 (0.18%) 0 (0) 0.07 (0.18%) 0.02 (0.03%) 0.48 (0.80%) 0 (0)
Leea aculeata Bl. 0.05 (0.02%) 0 (0) 0 (0.01%) 0.02 (0.03%) 0 (0) 0.04 (0.02%)
Leucaena leucaephala (Lam.) de Wit. 0.16 (0.05%) 0 (0) 0 (0) 0.15 (0.27%) 0.01 (0.02) % 0 (0)
Leucosyke capitellata (Pair.) Wedd. 0.69 (0.22%) 0 (0.03%) 0.30 (0.81%) 0.32 (0.57%) 0.02 (0.03%) 0.05 (0.03%)
Lithocarpus llanosii (A.DC.) Rehder 20.40 (6.39%) 0.60 (3.56%) 9.60 (25.87%) 4.62 (8.26%) 4.84 (8.06%) 0.75 (0.48%)
Litsea perrottetii (Bl.) Villar. 0.38 (0.12%) 0 (0) 0.11 (0.30%) 0.08 (0.14%) 0.18 (0.30%) 0.01 (0.01%)
Macaranga bicolor Muell. -Arg. 0.19 (0.06%) 0 (0) 0.14 (0.37%) 0 (0) 0.04 (0.06%) 0.02 (0.01%)
Macaranga tanarius (L.) Müll.Arg. 0.81 (0.25%) 0 (0) 0.63 (1.69%) 0.04 (0.07%) 0.04 (0.06%) 0.10 (0.06%)
Mallotus philippensis (Lam.) Müll.Arg. 0.03 (0.01%) 0 (0) 0.03 (0.08%) 0 (0) 0 (0) 0 (0)
Mallotus ricinoides (Pers.) Müll.Arg. 0.31 (0.10%) 0 (0.01%) 0.06 (0.16%) 0.15 (0.27%) 0.10 (0.17%) 0 (0)
Melicope triphylla (Lam.) Merr. 0.09 (0.03%) 0 (0) 0.02 (0.04%) 0.03 (0.06%) 0.04 (0.06%) 0 (0)
Mussaenda philippica A.Rich. 0.01 (0) 0 (0.02%) 0.01 (0.02%) 0 (0) 0 (0) 0 (0)
Myrica javanica Reinw. ex Bl. 0.35 (0.11%) 0.30 (1.79%) 0 (0) 0 (0) 0 (0) 0.05 (0.03%)
Neolitsea vidalii Merr. 6.08 (1.90%) 0 (0) 0 (0) 2.61 (4.67%) 0.73 (1.22%) 2.73 (1.72%)
Neonauclea bartlingii (DC.) Merr. 0.38 (0.12%) 0 (0) 0 (0.01%) 0.05 (0.09%) 0.17 (0.28%) 0.17 (0.11%)
Neonauclea formicaria (Elmer) Merr. 1.34 (0.42%) 0 (0) 0.17 (0.46%) 0.81 (1.45%) 0.20 (0.34%) 0.16 (0.10%)
Neotrewia cumingii (Müll.Arg.) Pax & K.Hoffm. 0.49 (0.15%) 0 (0) 0.02 (0.06%) 0.01 (0.02%) 0.18 (0.30%) 0.27 (0.17%)
Nephelium lappaceum 0.01 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0) 0 (0)
Octomeles sumatrana Miq. 0.25 (0.08%) 0 (0) 0 (0) 0 (0) 0.25 (0.42%) 0 (0)
Ormosia calavensis Blanco 1.53 (0.48%) 0 (0) 0.81 (2.19%) 0.03 (0.05%) 0.66 (1.10%) 0.04 (0.02%)
Palaquium luzoniense (Fern.-Vill.) Vidal 9.60 (3.01%) 0 (0) 0.63 (1.69%) 1.27 (2.27%) 3.32 (5.52%) 4.39 (2.77%)
Pandanus radicans Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0.01 (0.02%) 0 (0)
Parartocarpus venenosus (Zoll. & Morr.) Becc. ssp.
papuanus (Becc.) Jarr.
0.17 (0.05%) 0.02 (0.15%) 0.02 (0.05%) 0.03 (0.05%) 0.02 (0.04%) 0.08 (0.05%)
Parashorea malaanonan (Blanco) Merr. 106.08 (33.23%) 3.63 (21.73%) 2.54 (6.84%) 13.57 (24.28%) 12.95 (21.59%) 73.38
(46.30%)
Petersianthus quadrialatus (Merr.) Merr. 8.72 (2.73%) 0 (0) 0 (0) 0 (0) 0.39 (0.65%) 8.33 (5.26%)
Piper anduncum L. 0.02 (0.01%) 0.00 (0.03%) 0 (0) 0.00 (0.01%) 0.00 (0.01%) 0.01 (0.01%)
Pipturus arborescens (Link) C. B. Rob. 0.27 (0.08%) 0 (0) 0 (0) 0.08 (0.14%) 0.19 (0.32%) 0 (0)
Planchonella nitida (Blume) Dubard. 1.09 (0.34%) 0 (0) 0 (0) 0.03 (0.06%) 1.06 (1.77%) 0 (0)
160
Polyalthia flava 2.59 (0.81%) 0 (0) 0.07 (0.19%) 0.01 (0.03%) 0.01 (0.02%) 2.49 (1.57%)
Polyalthia oblongifolia Burck 0.37 (0.12%) 0 (0) 0.17 (0.47%) 0.01 (0.01%) 0.18 (0.31%) 0 (0)
Polyscias nodosa (Blume) Seem. 3.23 (1.01%) 0.04 (0.22%) 0.65(1.75%) 0.82 (1.47%) 1.22 (2.04%) 0.51 (0.32%)
Premna cumingiana Schauer 0.07 (0.02%) 0.00 (0.03%) 0 (0) 0 (0) 0 (0) 0.06 (0.04%)
Premna odorata Blanco 0.14 (0.04%) 0.13 (0.75%) 0 (0) 0.01 (0.03%) 0 (0) 0 (0)
Premna stellate Merr. 0.04 (0.01%) 0 (0) 0 (0) 0.04 (0.07%) 0 (0) 0 (0)
Pterocarpus indicus Willd. 1.51 (0.47%) 1.51 (9.01%) 0 (0) 0 (0) 0 (0) 0 (0)
Pterospermum diversifolium Bl. 0.02 (0.01%) 0 (0) 0 (0) 0.01 (0.02%) 0 (0) 0 (0)
Pterospermum obliquum Blanco 0.01 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Radermachera pinnate (Blanco) Seem. 2.83 (0.89%) 0.01 (0.03%) 1.21 (3.25%) 0.87 (1.56%) 0.58 (0.97%) 0.17 (0.11%)
Securinega fIexuosa (Muell. -Arg.) 0.45 (0.14%) 0 (0) 0.16 (0.42%) 0.15 (0.27%) 0.14 (0.23%) 0 (0)
Senna siamea (Lam.) Irwin et Barneby 0.02 (0) 0 (0) 0 (0) 0.01 (0.02%) 0.01 (0.01%) 0 (0)
Shorea almon Foxw. 0.40 (0.13%) 0 (0) 0.01 (0.02%) 0 (0) 0.40 (0.66%) 0 (0)
Shorea contorta Vidal 12.41 (3.89%) 0.26 (1.57%) 2.35 (6.32%) 6.59 (11.80%) 2.67 (4.45%) 0.53 (0.34%)
Shorea guiso (Blanco) Blume 8.24 (2.58%) 0 (0) 2.57 (6.92%) 0.71 (1.27%) 0.20 (0.34%) 4.76 (3.01%)
Shorea palosapis (Blanco) Merr. 2.47 (0.77%) 0 (0) 0.55 (1.49%) 0.35 (0.63%) 0.03 (0.05%) 1.54 (0.97%)
Shorea polysperma (Blanco) Merr. 10.36 (3.25%) 7.39 (44.23%) 0.61 (1.65%) 2.19 (3.91%) 8.17 (13.62%) 1.02 (0.64%)
Strombosia philippinensis (Baill.) Rolfe 1.61 (0.50%) 0 (0) 0.25 (0.67%) 0.54 (0.97%) 0.20 (0.34%) 0.62 (0.39%)
Syzygium crassilimbum (Merr.) Merr. 0.09 (0.03%) 0 (0) 0.03 (0.07%) 0.02 (0.04%) 0.04 (0.06%) 0 (0)
Syzygium gigantifolium (Merr.) Merr. 0.62 (0.19%) 0 (0) 0.22 (0.59%) 0 (0) 0.29 (0.48%) 0.11 (0.07%)
Syzygium hutchinsonii (C.B.Robinson) Merr. 1.13 (0.36%) 0.06 (0.34%) 0.16 (0.44%) 0.23 (0.42%) 0.47 (0.79%) 0.21 (0.13%)
Syzygium surigaense (Merr.) Merr. 2.51 (0.79%) 0 (0) 0 (0) 0 (0) 0.05 (0.09%) 2.45 (1.55%)
Tectona grandis L. f. 0.14 (0.04%) 0 (0) 0 (0) 0 (0) 0.14 (0.24%) 0 (0)
Terminalia microcarpa Decne. 0.03 (0.01%) 0 (0) 0 (0) 0.03 (0.05%) 0 (0) 0 (0)
Toona philippinensis Elmer. 0.84 (0.26%) 0 (0) 0.01 (0.01%) 0.13 (0.23%) 0.13 (0.21%) 0.58 (0.36%)
Trema orientalis (L.) Bl. 0.08 (0.03%) 0.00 (0.01%) 0 (0) 0 (0) 0 (0) 0.08 (0.05%)
Trichospermum involucratum (Merr.) Elmer 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Vitex quinata (Lour.) F. N. Williams 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Vitex turczaninowii (Turcz.) Merr. 0 (0) 0 (0) 0 (0) 0 (0) 0 (0) 0 (0)
Wrightia pubescens R.Br. 0.80 (0.25%) 0 (0) 0.56 (1.50%) 0.12 (0.21%) 0.13 (0.22%) 0 (0)
Xanthostemon verdugonianus Naves 1.19 (0.37%) 1.19 (7.10%) 0 (0) 0 (0) 0 (0) 0 (0)
Anungo 0.98 (0.31%) 0 (0) 0.17 (0.46%) 0.04 (0.07%) 0.03 (0.04%) 0.75 (0.47%)
Nandamai 0.001 (0.001%) 0 (0) 0 (0) 0 (0) 0.01 (0.01%) 0 (0)
Pandukaki 0.003 (0.001%) 0 (0) 0 (0) 0 (0) 0.003 (0.01%) 0 (0)
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Pegonngon 0 (0) 0 (0) 0 (0) 0 (0) 0.003 (0.01%) 0 (0)
Poelig 0.80 (0.25%) 0 (0) 0.56 (1.5%) 0.12 (0.21%) 0.13 (0.22%) 0 (0)
Siyao 1.19 (0.37%) 1.19 (7.10%) 0 (0) 0 (0) 0 (0) 0 (0)
* Values in the parenthesis indicatse the percentage share of respective species in sites total living woody biomass carbon.
162
Supplementary Figure 4.1. Relative contribution of living stems of different diameter class in
living woody biomass carbon (LWBC). Values in the bars indicate absolute contribution (Mg C ha -
1) to LWBC of respective diameter class.
163
Supplementary Figure 4.2. Relative contribution of living stems of different height class in living
woody biomass carbon (LWBC). Values in the bars indicate absolute contribution (Mg C ha -1
) to
LWBC of individual height class.
164
Supplementary Table 5.1. Pearson’s correlation (2 tailed) between site environmental attributes.
Where, FA = fallow age, EL = elevation, SL = slope, PS = patch size, DIS = distance, N = tree
species richness, A = tree species abundance, BA = tree basal area, LAI = leaf area index.
FA EL SL PS DIS N A BA LAI
FA 1 -0.09 0.25 0.07 -0.35 0.73** 0.65** 0.61** 0.57**
EL -0.09 1 0.52* -0.01 -0.12 -0.31 -0.16 -0.56* -0.41
SL 0.25 0.52* 1 -0.16 0.07 0.08 0.2 -0.18 0.02
PS 0.07 -0.01 -0.16 1 -0.09 -0.06 0.06 -0.03 -0.04
DIS -0.3 -0.12 0.07 -0.09 1 -0.14 0.13 -0.25 0.22
N 0.73** -0.31 0.08 -0.06 -0.14 1 0.87** 0.68** 0.84**
A 0.65** -0.16 0.2 0.06 0.13 0.87** 1 0.58** 0.9**
BA 0.61** -0.55* -0.18 -0.03 -0.25 0.68** 0.58** 1 0.69**
LAI 0.57** -0.41 0.02 -0.04 0.22 0.84** 0.9** 0.69** 1
**correlation is significant at the p < 0.01 level;
*correlation is significant at the p < 0.05 level.
165
Supplementary Figure 5.1. Percentage concentrations of soil organic carbon and soil nutrients on
Leyte Island, the Philippines. Note the different scales are used on the Y axes.