shifting cultivation in the upland secondary forests …384780/s4282325...shifting cultivation are...

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

ii

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

iii

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.

iv

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.

v

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.

vi

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.

vii

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

viii

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.

ix

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


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


Mukul, S.A., Herbohn, J., Firn, J. (in review) High resilience of tropical forest diversity and




Author SA Mukul (Candidate) Conceptualised the study (90%), designed and

conducted the fieldwork (100%), wrote and

edited the paper (80%)



Author J Firn Conceptualised the framework (5%), and wrote


x

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.



Author SA Mukul (Candidate) Conceptualised the study (90%), designed and

conducted the fieldwork (100%), wrote and

edited the paper (80%)





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.



Author SA Mukul (Candidate) Conceptualised the framework (90%), study

design and analyse (100%), wrote and edited the

paper (80%)





Author A Almendras-Ferraren Wrote and edited the paper (5%)

Author R Congdon Wrote and edited the paper (5%)

xi

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




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%)



xii

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.

xiii

Statement of parts of the thesis submitted to qualify for the award of another degree

None.

xiv

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).

xv

Dedication

This thesis is dedicated to the memory of my father Mostaque Ahmed (1955-2016) who left

us on January 17, 2016.

xvi

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%

xvii

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

xviii

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


3.8 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

xix

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


4.8 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

xx

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


5.8 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

xxi

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


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 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 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?


What are the aboveground carbon stocks in secondary forests after shifting cultivation, and

how is biomass carbon is allocated in different forest biomass components?


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.


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?

http://scholar.google.com.au/citations?user=BF1ECe0AAAAJ&hl=en&oi=sra

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


Litter and woody debris

sample

100 Dry biomass


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.

Herbohn, J.L., Vanclay, J.K., Ngyuen, H., Le, H.D., Harrison, S.R., Cedamon, E., Smith, C., Firn,

J., Gregorio, N.O., Mangaoang, E., Lamarre, E., 2014. Inventory procedures for smallholder

and community woodlots in the Philippines: methods initial findings and insights. Small-scale

Forestry, 13, 79-100.

Hughes, R.F., Kaufman, J.B., Jaramillo, V.J. 1999. Biomass, carbon, and nutrient dynamics of

secondary forests in a humid tropical region of Mexico. Ecology, 80, 1892-1907.

Kellman, M.C., 1970. Secondary plant succession in tropical montane Mindano. Department of

Biogeography and Geomorphology, Australian National University, Canberra.

Kummer, D.M., 1992. Upland agriculture, the land frontier and forest decline in the Philippines.

Agroforestry Systems, 18, 31-46.

Lasco, R.D., Pulhin, F.B., 2000. Forest land-use change in the Philippines and climate change

mitigation. Mitigation and Adaptation Strategies for Global Change, 5, 81-97.

Lasco, R.D., Pulhin, F.B., 2003. Philippine forest ecosystems and climate change: Carbon stocks,

rate of sequestration and the Kyoto protocol. Annals of Tropical Research, 25, 37-51.

Lasco, R.D., Pulhin, F.B., 2009. Carbon budgets of forest ecosystems in the Philippines. Journal of

Environmental Science and Management, 12, 1-13.

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, A., 1997. Kaingin in the Philippines: is it the end of the forest? Rural Development

Forestry Network Paper 21, London, UK.

Lawrence, D., Radel, C., Tully, K., Schmook, B., Schneider, L., 2010. Untangling a decline in

tropical forest resilience: constraints on the sustainability of shifting cultivation across the

globe. Biotropica, 42, 21-30.

Le, H.D., Smith, C., Herbohn, J., 2014. What drives the success of reforestation projects in tropical

developing countries? The case of the Philippines. Global Environmental Change, 24, 334–

348.

Lewis, S.L., Edwards, D.P., Galbraith, D., 2015. Increasing human dominance of tropical forests.

Science, 349: 827-832.

Malhi, Y., Gardner, T.A., Goldsmith, G.R., Silman, M.R., Zelazowski, P., 2014. Tropical forests in

the Anthropocene. Annual Review of Environment and Resources, 39, 125-159.

Martin, P.A., Newton, A.C., Bullock, J.M., 2013. Carbon pools recover more quickly than plant

biodiversity in tropical secondary forests. Proceedings of the Royal Society B, 280, 20132236.

14

Mertz, O., Müller, D., Sikor, T., Hett, C., Heinimann, A., Castella, J.C., Lestrelin, G., Ryan, C.M.,

Reay, D.S., Schmidt-Vogt, D., Danielsen, F., Theilade, I., van Noordwijk, M., Verchot, L.V.,

Burgess, N.D., Berry, N.J., Pham, T.T., Messerli, P., Xu, J., Fensholt, R., Hostert, P.,

Pflugmacher, D., Bruun, T.B., de Neergaard, A., Dons, K., Dewi, S., Rutishauser, E., Sun, Z.,

2012. The forgotten D: challenges of addressing forest degradation in complex mosaic

landscapes under REDD+. Danish Journal of Geography, 112, 63-76.

Mertz, O., Padoch, C., Fox, J., Cramb, R.A., Leisz, S.J., Nguyen, T.L., Tran, D.V., 2009. Swidden

change in Southeast Asia: Understanding causes and consequences. Human Ecology, 37, 259-

264.

Metzger, M.J., Rounsvell, M.D.A., Acosta-Michlik, L., Leemans, R., Schroter, D., 2006. The

vulnerability of ecosystem services to land-use change. Agriculture, Ecosystems &

Environment, 114, 69-85.

Mukul, S.A., Herbohn, J., 2013. The future of reforestation programs in the tropical developing

countries: insights from the Philippines. 2013 American Geophysical Union (AGU)’s Fall

Meeting Book of Abstract (Abstract 1050).

Mukul, S.A., Herbohn, J., 2016. The impacts of shifting cultivation on secondary forests dynamics


Environmental Science & Policy, 55, 167-177.

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.

Niles, J.O., Brown, S., Pretty, J., Ball, A.S., Fay, J., 2002. Potential carbon mitigation and income in

developing countries from changes in use and management of agricultural and forest lands.

Philosophical Transactions of the Royal Society of London A 360: 1621-1639.

Padoch, C., Coffey, K., Mertz, O., Lesiz, S.J., Fox, J., Wadley, R.L., 2007. The demise of swidden

in Southeast Asia? Local realities and regional ambiguities. Danish Journal of Geography,

107, 29-41.

Parrotta, J.A., Wildburger, C., Mansourian, S. (eds.), 2012. Understanding relationships between

biodiversity, carbon, forests and people: The key to achieving REDD+ objectives, A global

assessment report. Global Expert Panel on Biodiversity, Forest Management, and REDD+,

World Series Volume 31. International Union of Forest Research Organizations (IUFRO),

Vienna, Austria.

Piotto, D., Montagnini, F., Thomas, W., Ashton, M., Oliver, C., 2009. Forest recovery after swidden

cultivation across a 40-year chronosequence in the Atlantic forest of southern Bahia, Brazil.

Plant Ecology, 205, 261-272.

http://scholar.google.com.au/citations?user=BF1ECe0AAAAJ&hl=en&oi=sra

http://scholar.google.com.au/citations?user=eu67V8YAAAAJ&hl=en&oi=sra

http://www.springerlink.com/index/RW776K270H6101M4.pdf

http://www.springerlink.com/index/RW776K270H6101M4.pdf

15

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.

Sodhi, N.S., Koh, L.P., Clements, R., Wanger, T.C., Hill, J.K., Hamer, K.C., Clough, Y.,

Tscharntke, T., Posa, M.R.C., Lee, T.M., 2010. Conserving Southeast Asian forest

biodiversity in human-modified landscapes. Biological Conservation, 143, 2375–2384.

Suarez, R.K., Sajise, P.E., 2010. Deforestation, swidden agriculture and Philippine biodiversity.

Philippine Science Letters, 3, 91-99.

Trumbore, S., Brando, P., Hartmann, H., 2015. Forest health and global change. Science, 349, 814-

818.

van Vliet, N., Mertz, O., Heinimann, A., Langanke, T., Pascual, U., Schmook, B., Adams, C.,

Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.-C., Jørgensen, L., BirchThomsen, T.,

Hett, C., Bech-Bruun, T., Ickowitz, A., Vu, K.C., Yasuyuki, K., Fox, J., Padoch, C., Dressler,

W., Ziegler, A.D., 2012. Trends, drivers and impacts of changes in swidden cultivation in

tropical forest-agriculture frontiers: a global assessment. Global Environmental Change, 22,

418–429.

Ziegler, A.D., Fox, J. M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Bruun, T.B.,

Vien, T.D., 2011. Recognizing contemporary roles of swidden agriculture in transforming

landscapes of Southeast Asia. Conservation Biology, 25, 846-848.

Ziegler, A.D., Phelps, J., Yuen, J.Q., Webb, E.L., Lawrence, D., Fox, J.M., Bruun, T.B., Leisz, S.J.,

Ryan, C.M., Padoch, C., Koh, L.P., 2012. Carbon outcomes of major land-cover transitions in

SE Asia: great uncertainties and REDD+ policy implications. Global Change Biology, 18,

3087-3099.

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.


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.

2.7 References

Adedeji, F.O., 1984. Nutrient cycles and successional changes following shifting cultivation

practice in moist semi-deciduous forests in Nigeria. Forest Ecology and Management, 9, 87–

99.

Anderson, D.L., 2001. Landscape heterogeneity and diurnal raptor diversity in Honduras: The role

of indigenous shifting cultivation. Biotropica, 33, 511-519.

31

Ahrends, A., Hollingsworth, P.M., Ziegler, A.D., Fox, J.M., Chen, H., Su, Y., Xu, J., 2015. Current

trends of rubber plantation expansion may threaten biodiversity and livelihoods. Global

Environmental Change, 34, 48-58.

Baccini, A., Goetz, S.J., Walker, W.S., Laporte, N.T., Sun, M., Sulla-Menashe, D., Hackler, J.,

Beck, P.S.A., Dubayah, R., Friedl, M.A., Samanta, S., Houghton, R.A., 2012. Estimated

carbon dioxide emissions from tropical deforestation improved by carbon-density maps.

Nature Climate Change, 2, 182-185.

Bonilla-Moheno, M., Hol, K.D., 2010. Direct seeding to restore tropical mature-forest species in

areas of slash-and-burn agriculture. Restoration Ecology, 18, 438–445.

Borges, S.H., 2007. Bird assemblages in secondary forests developing after slash-and-burn

agriculture in the Brazilian Amazon. Journal of Tropical Ecology, 23, 469–477.

Borggaard, O.K.,Gafur, A., Petersen, L., 2003. Sustainability appraisal of shifting cultivation in the

Chittagong Hill Tracts of Bangladesh. Ambio, 32,118-123.

Bowman, D. M.J.S., Woinarski, J.C.Z., Sands, D.P.A., Wells, A., McShane, V.J., 1990. Slash-and-

burn agriculture in the wet coastal lowlands of Papua New Guinea: Response of birds,

butterflies and reptiles. Journal of Biogeography, 17, 227-239.

Brand, J., Pfund, J.L., 1998. Site and watershed level assessment of nutrient dynamics under

shifting cultivation in eastern Madagascar. Agriculture, Ecosystems & Environment, 71: 169–

183.

Bruun, T.B., de Neergaard, A., Lawrence, D., Ziegler, A.D., 2009. Environmental consequences of

the demise in swidden agriculture in Southeast Asia: soil nutrients and carbon stocks. Human

Ecology, 37, 375–388.

Bruun, T.B., Egay, K., Mertz, O., Magid, J., 2013. Improved sampling methods document decline

in soil organic carbon stocks and concentrations of permanganate oxidizable carbon after

transition from swidden to oil palm cultivation. Agriculture, Ecosystems & Environment, 178,

127–134.

Castro-Luna, A. A., Castillo-Campos, G., Sosa, V. J., 2011. Effects of selective logging and

shifting cultivation on the structure and diversity of a tropical evergreen forest in South-

Eastern Mexico. Journal of Tropical Forest Science, 23, 17-34.

d’Oliveira, M.V.N., Alvarado, E.C., Santos, J.C., Carvalho Jr, J.A., 2011. Forest natural

regeneration and biomass production after slash and burn in a seasonally dry forest in the

Southern Brazilian Amazon. Forest Ecology and Management, 261, 1490–1498.

Dalle S.P., Pulido, M.T., de Blois, S., 2011. Balancing shifting cultivation and forest conservation:

lessons from a "sustainable landscape" in southeastern Mexico. Ecological Applications, 21,

1557-72.

32

Davidson, E.A., de Abreusa , T.D., Carvalho, C.J.R., Figueiredo, R.D.O., Kato, M.D.A., Kato,

O.R., Ishida, F.Y., 2008. An integrated greenhouse gas assessment of an alternative to slash-

and-burn agriculture in eastern Amazonia. Global Change Biology, 14, 998–1007.

DeFries, R., Rosenzweig, C., 2010.Toward a whole-landscape approach for sustainable land use in

the tropics. Proceedings of the National Academy of Sciences, USA, 107, 19627-19632.

Ding, Y., Zang, R., Liu, S., He, F., Letcher, S.G., 2012. Recovery of woody plant diversity in

tropical rain forests in southern China after logging and shifting cultivation. Biological

Conservation, 145 225–233.

Do, T.V., Osawa, A., Thang, N.T. 2010. Recovery process of a mountain forest after shifting

cultivation in Northwestern Vietnam. Forest Ecology and Management, 259, 1650–1659.

Do, T.V., Osawa, A., Thang, N.T., Van, N.B., Hang, B.T., Khanh, C.Q., Thao, L.T., Tuan, D.X.,

2011. Population changes of early successional forest species after shifting cultivation in

Northwestern Vietnam. New Forests, 41, 247–262.

Dressler, W., Wilson, D., Clendenning, J., Cramb, R., Mahanty, S., Lasco, R., Keenan, R., To, P.,

Gevana, D., 2015. Examining how long fallow swidden systems impact upon livelihood and

ecosystem services outcomes compared with alternative land-uses in the uplands of Southeast

Asia. Journal of Development Effectiveness, 7, 210-229.

Dung, N.V., Vien, T.D., Lam, N.T., Tuong, T.M., Cadisch, G., 2008. Analysis of the sustainability

within the composite swidden agroecosystem in northern Vietnam: 1. Partial nutrient balances

and recovery times of upland fields. Agriculture, Ecosystems & Environment, 128, 37–51.

Eaton, J.M., Lawrence, D., 2009. Loss of carbon sequestration potential after several decades of

shifting cultivation in the Southern Yucatan. Forest Ecology and Management, 258, 949–958.


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


Funakawa, S., Makhrawie, M., Pulunggono, H.B., 2009. Soil fertility status under shifting

cultivation in East Kalimantan with special reference to mineralization patterns of labile

organic matter. Plant and Soil, 319, 57-66.

Gafur, A., Jensen, J.R., Borggaard, O.K., Petersen, L., 2003. Runoff and losses of soil and nutrients

from small watersheds under shifting cultivation (Jhum) in the Chittagong Hill Tracts of

Bangladesh. Journal of Hydrology, 274, 30–46.

33

Gafur, A., Koch, C.B., Borggaard, O.K., 2004. Weathering intensity controlling sustainability of

Ultisols under shifting cultivation in the Chittagong Hill Tracts of Bangladesh. Soil Science,

169, 663-674.

Garcı́a-Oliva, F., Sanford Jr., R.L., Kelly, E., 1999. Effects of slash-and-burn management on soil

aggregate organic C and N in a tropical deciduous forest. Geoderma, 88, 1–12.

Gathorne-Hardy, F.J., Syaukani,. Inward, D. J.G., 2006. Recovery of termite (Isoptera) assemblage

structure from shifting cultivation in Barito Ulu, Kalimantan, Indonesia. Journal of Tropical

Ecology, 22, 605–608.

Gehring, C., Denich, M., Vlek, P.L.G., 2005. Resilience of secondary forest regrowth after slash-

and-burn agriculture in central Amazonia. Journal of Tropical Ecology, 21, 519 – 527.

Gehring, C., Muniz, F.H., de Souza, L.A.G., 2008. Leguminosae along 2–25 years of secondary

forest succession after slash-and-burn agriculture and in mature rain forest of Central

Amazonia. The Journal of the Torrey Botanical Society, 135, 388-400.

Geist, H.J., Lambin, E.F., 2002. Proximate causes and underlying driving forces of tropical

deforestation. BioScience, 52, 143-150.

Gemerden, B.S.V., Shu, G.N., Olff, H., 2003. Recovery of conservation values in Central African

rain forest after logging and shifting cultivation. Biodiversity and Conservation, 12, 1553–

1570.

Giardina, C.P., Sanford, R.L., Dockersmith, I.C., 2000.Changes in soil phosphorus and nitrogen

during slash-and-burn clearing of a dry tropical forest. Soil Science Society of America

Journal, 64, 399–405.

Grange, I., Kansuntisukmongkol, K., 2000. Effect of fallow length on soil structure, hydraulic

properties, and soil organic C in a swidden cultivation system of western Thailand. Tropical

Agriculture, 80, 246-251.

Hattori, D., Sabang, J., Tanaka, S., Kendawang, J.J., Ninomiya, I., Sakurai, K., 2005. Soil

Characteristics under three vegetation types associated with shifting cultivation in a mixed

Dipterocarp forest in Sarawak, Malaysia. Soil Science & Plant Nutrition, 51, 231–241.

Hett, C., Castella, J.C., Heinimann, A., Messerli, P., Pfund, J., 2012. A landscape mosaics approach

for characterizing swidden systems from a REDD+ perspective. Applied Geography, 32, 608-

618.

Jasco, P., 2005. As we may search – comparison of major features of the Web of Science, Scopus,

and Google Scholar citation-based and citation enhanced databases. Current Science, 89,

1537-1547.

Kenzo, T., Ichie, T., Hattori, D., Kendawang, J.J., Sakurai, K., Ninomiya, I., 2010. Changes in

above- and belowground biomass in early successional tropical secondary forests

34

after shifting cultivation in Sarawak, Malaysia. Forest Ecology and Management, 260, 875–

882.

Klanderud, K., Mbolatiana, H.Z.H., Vololomboahangy, M.N., Radimbison, M.A., Roger, E.,

Totland, Ø., Rajeriarison, C., 2010. Recovery of plant species richness and composition after

slash-and-burn agriculture in a tropical rainforest in Madagascar. Biodiversity Conservation,

19, 187–204.

Kotto-Same, J., Woomer, P.L., Appolinaire, M., Louis, Z., 1998. Carbon dynamics in slash-and-

bum agriculture and land use alternatives of the humid forest zone in Cameroon. Agriculture,

Ecosystems & Environment, 65, 245-256.

Kupfer, J.A., Webbeking, A.L., Franklin, S.B., 2004. Forest fragmentation affects early

successional patterns on shifting cultivation fields near Indian Church, Belize. Agriculture,

Ecosystems & Environment, 103, 509–518.

Lawrence, D., 2004. Erosion of tree diversity during 200 years of shifting cultivation in Bornean

rain forest. Ecological Applications, 14, 1855–1869.

Lawrence, D., 2005. Biomass accumulation after 10-200 years of shifting cultivation in Bornean

rain forest. Ecology, 86, 26-33.

Lawrence, D., Foster, D., 2002. Changes in forest biomass, litter dynamics and soils following

shifting cultivation in southern Mexico: an overview. Interciencia, 27, 400-408.

Lawrence, D., Radel, C., Tully, K., Schmook, B., Schneide, L., 2010.Untangling a decline in

tropical forest resilience: Constraints on the sustainability of shifting cultivation across the

globe. Biotropica, 42, 21–30.

Lawrence, D., Schlesinger, W.H., 2001. Changes in soil phosphorus during 200 years of shifting

cultivation in Indonesia. Ecology, 82, 2769–2780.

Lawrence, D., Suma, V., Mogea, J.P., 2005. Change in species composition with repeated shifting

cultivation: limited role of soil nutrients. Ecological Applications, 15, 1952–1967.

Lele, S., Kurien, A., 2011. Interdisciplinary analysis of the environment: insights from tropical

forest research. Environmental Conservation, 38, 211–233.

Lestrelin, G., Vigiak, O., Pelletreau, A., Keohavong, B., Valentin, C., 2012. Challenging established

narratives on soil erosion and shifting cultivation in Laos. Natural Resources Forum, 36, 63–

75.

Lima, S.S., Leite, L.F.C., Oliveira, F.C., Costa, D.B., 2011. Chemical properties and carbon and

nitrogen stocks in an acrisol under agroforestry system and slash and burn practices in

northern Piauí state. Revista Árvore, 35, 51-60.

35

Matsumoto, T., Itioka, T., Yamane, S., Momose, K., 2009. Traditional land use associated with

swidden agriculture changes encounter rates of the top predator, the army ant, in Southeast

Asian tropical rain forests. Biodiversity Conservation, 18, 3139–3151.

Mertz, O., Padoch, C., Fox, J., Cramb, R.A., Leisz, S.J., Nguyen, T.L. and Tran, D.V., 2009a.

Swidden change in Southeast Asia: Understanding causes and consequences. Human Ecology,

37, 259-264.

Mertz, O., Leisz, O., Heinimann, A., Rerkasem, K., Thiha, Dressler, W., Pham, V.C., Vu, K.C.,

Schimdt-Vogt, D., Colfer, C.J.P., Epprecht, M., Padoch, C., Potter, L. 2009b. Who counts?

Demography of swidden cultivators in Southeast Asia. Human Ecology, 37, 281–289.

Metzger, J.P., 2003. Effects of slash-and-burn fallow periods on landscape structure. Environmental

Conservation, 30, 325–333.

Miller, P.M., Kauffman, J.B, 1998a. Effects of slash and burn agriculture on species abundance and

composition of a tropical deciduous forest. Forest Ecology and Management, 103, 191-201.

Miller, P.M., Kauffman, J.B., 1998b. Seedling and Sprout Response to Slash-and-Burn Agriculture

in a Tropical Deciduous Forest. Biotropica, 30, 538-546.

Mishra, K.C., Ramakrishnan, P.S., 1988. Earthworm population dynamics in different jhum fallows

developed after slash and burn agriculture in north-eastern India. Proceedings of the Indian

Academy of Sciences, 97, 309-318.

Naughton-Treves, L., Mena, J.L., Treves, A., Alvarez, N., Radeloff, V.C., 2003. Wildlife survival

beyond park boundaries: the impact of slash-and-burn agriculture and hunting on mammals in

Tambopata, Peru. Conservation Biology, 17, 1106-1117.

N'Dja, J.K.K., Decocq, G., 2008. Successional patterns of plant species and community diversity in

a semi-deciduous tropical forest under shifting cultivation. Journal of Vegetation Science, 19,

809-820.

Neergaard, A., Magid, J., Mertz, O., 2008. Soil erosion from shifting cultivation and other

smallholder land use in Sarawak, Malaysia. Agriculture, Ecosystems & Environment, 125,

182–190.

Ochoa-Gaona, S., Hernandez-Vazquez, F., Jong, B.H.J.D., Gurri-Garcia, F.D., 2007. Loss of

floristic diversity over an intensification gradient of the slash-and-burn agricultural system: a

case study in the Selva Lacandona region, Chiapas, Mexico. Boletin de la Sociedad Botanica

de Mexico, 81, 65-80.

Osman, K.S., Jashimuddin, M., Haque, S.M.S., Miah, S., 2013. Effect of shifting cultivation on

soil physical and chemical properties in Bandarban hill district, Bangladesh. Journal of

Forestry Research, 24, 791-795.

36

Phongoudome, C., Park, P.S., Kim, H., Sawathvong, S., Park, Y.D., Combalicer, M.S., Ho, H.M.,

2013. Changes in stand structure and environmental conditions of a mixed deciduous forest

after logging and shifting cultivation in Lao PDR. Asia Life Sciences, 22, 75-94.



Plant Ecology, 205, 261–272.

R Development Core Team, 2012. R: A Language and Environment for Statistical Computing. R

Foundation for Statistical Computing, Vienna.

Raharimalala, O., Buttler, A., Ramohavelo, C.D., Razanaka, S., Sorge, J.P., Gobat, J.M., 2010.

Soil–vegetation patterns in secondary slash and burn successions in Central Menabe,

Madagascar. Agriculture, Ecosystems & Environment, 139, 150–158.

Raharimalala, O., Buttler, A., Schlaepfer, R., Gobat, J.M., 2012. Quantifying biomass of secondary

forest after slash-and-burn cultivation in central Menabe, Madagascar. Journal of Tropical

Forest Science, 24, 474-489.

Raman, T.R.S., 1996. Impact of shifting cultivation on diurnal squirrels and primates in

Mizoram,northeast India: a preliminary study. Current Science, 70, 747-750.

Raman, T.R.S., 2001. Effect of Slash-and-Burn Shifting Cultivation on Rainforest Birds in

Mizoram, Northeast India. Conservation Biology, 15, 685-698.

Raman, T.R.S., Rawat, G.S., Johnsingh, A.J.T., 1998. Recovery of tropical rainforest avifauna in

relation to vegetation succession following shifting cultivation in Mizoram, north-east India.

Journal of Applied Ecology, 35, 214–231.

Read, L., Lawrence, D., 2003. Recovery of biomass following shifting cultivation in dry tropical

forests of the Yucatan. Ecological Applications, 13, 85–97.

Rodenburg, J., Stein, A., Noordwijk, M., Ketterings, Q.M., 2003. Spatial variability of soil pH and

phosphorus in relation to soil run-off following slash-and-burn land clearing in Sumatra,

Indonesia. Soil and Tillage Research, 71, 1–14.

Salcedo, I.H., Tiesse, H., Sampaio, E.V.S.B., 1997. Nutrient availability in soil samples from

shifting cultivation sites in the semi-arid Caatinga of NE Brazil. Agriculture, Ecosystems &

Environment, 65, 177–186.

Schmook, B., 2010. Shifting maize cultivation and secondary vegetation in the Southern Yucatan:

successional forest impacts of temporal intensification. Regional Environmental Change, 10,

233–246.

Schroth, G., da Fonseca, G.A.B., Harvey, C.A., Gascon, C., Vasconcelos, H.L., Izac, A.N., 2004.

Agroforestry and biodiversity conservation in tropical landscapes. Island Press, Washington,

DC.

37

Schulze, M.D., Seavy,

N.E., Whitacre, D.F., 2000. A Comparison of the Phyllostomid Bat

Assemblages in Undisturbed Neotropical Forest and in Forest Fragments of a Slash-and-Burn

Farming Mosaic in Petén, Guatemala. Biotropica, 32, 174-184.

South, A., 2011. rworldmap: A New R package for Mapping Global Data. The R Journal, 3, 35-43.

Sovu, Tigabu, M., Savadogo, P., Oden, P.C., Xayvongsa, L., 2009. Recovery of secondary forests

on swidden cultivation fallows in Laos. Forest Ecology and Management, 258, 2666–2675.

Tanaka, S., Andoa, T., Funakawa, S., Sukhrun, C., Kaewkhongkha, T.,Sakurai, K., 2001. Effect of

burning on soil organic matter content and N mineralization under shifting cultivation system

of Karen people in Northern Thailand. Soil Science and Plant Nutrition, 47, 547-558.

Thomaz, E. L., 2013. Slash-and-burn agriculture: Establishing scenarios of runoff and soil loss for a

five-year cycle. Agriculture Ecosystems & Environment, 168, 1–6.

Tschakert, P., Coomes, O.T., Potvin, C., 2007. Indigenous livelihoods, slash-and-burn agriculture,

and carbon stocks in Eastern Panama. Ecological Economics, 60, 807 – 820.

van Vliet, N., Mertz, O., Birch-Thomsen, T., Schmook, B., 2013. Is there a continuing rationale for

swidden cultivation in the 21st century? Human Ecology, 41, 1–5.


Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.-C., Jørgensen, L., BirchThomsen, T.,




418–429.

Vieira, I.C.G., Proctor, J., 2007.Mechanisms of Plant Regeneration during Succession after Shifting

Cultivation in Eastern Amazonia. Plant Ecology, 192, 303-315.

Vongvisouk,T., Mertz, O., Thongmanivong, S., Heinimann, A., Phanvilay, K., 2014. Shifting

cultivation stability and change: Contrasting pathways of land use and livelihood change in

Laos. Applied Geography, 46, 1-10.

Wangpakapattanawonga, P., Kavinchan, N., Vaidhayakarn, C., Schmidt-Vogt, D., Elliott, S., 2010.

Fallow to forest: Applying indigenous and scientific knowledge of swidden cultivation to

tropical forest restoration. Forest Ecology and Management, 260, 1399–1406.

Web of Science., 2014. ISI Web of Science, Thomson Scientific Products,

http://apps.webofknowledge.com.ezproxy.library.uq.edu.au/.

Wilde, M.D., Buisson, E., Ratovoson, F., Randrianaivo, R., Carrière, S.M., Ii, P.P.L., 2012.

Vegetation dynamics in a corridor between protected areas after slash-and-burn cultivation in

south-eastern Madagascar. Agriculture, Ecosystems & Environment, 159, 1–8.

38

Wilkie, D.S., Finn, J.T., 1990. Slash-Burn Cultivation and Mammal Abundance in the Ituri Forest,

Zaire. Biotropica, 22, 90-99.

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.,


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


Schulze et al., 2000 Guatemala Humid forest Comparison Bat diversity Negative Undisturbed forest

Raman et al., 1998 India Dry forest Chronosequnce, 1-

100 yr


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


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


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


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


structure


Sovu et al., 2009 Lao PDR Humid forest Chronosequence, 1-

20 yr

Species diversity,

Forest structure


Eaton and Lawrence,

2009

Mexico Dry forest Chronosequence, 2-

25 yr


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


biomass


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


Metzger, 2003 Brazil Humid forest Chronosequence, 4-

10 yr

Plant diversity/

Succession


Gemerden et al., 2003 Cameroon Humid forest Chronosequence, Plant diversity Negative Undisturbed forest,

41

10-60 yr Logged forest

Read and Lawrence,

2003


25


Lawrence and Foster,

2002


25


Miller and Kauffman,

1998a

Mexico Dry forest Chronosequence; 2-

19 yr

Plant diversity/

Succession


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


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


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


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


*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



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


Horsfieldia costulata** 4.63 2.08 1.80 8.51

Bischofia javanica** 3.37 2.08 2.93 8.38

Middle-aged

fallow



Shorea contorta 2.27 2.04 9.47 13.78

Leucosyke capitellata 8.52 2.55 1.78 12.85




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


Shorea polysperma 1.95 1.31 10.03 13.29

Calophyllum blancoi 3.07 2.18 7.97 13.22



Ficus gul 4.46 1.75 1.43 7.63


Caryota cumingii *** 3.62 1.75 1.42 6.78

Ormosia calavensis 2.65 1.75 1.67 6.07

Old-growth

forest



Caryota cumingii*** 11.39 2.21 1.50 15.10

Shorea guiso 4.25 2.21 2.85 9.32


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.


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.

3.8 References

Achard, F., Eva, H.D., Stibig, H.J., Mayaux, P., Gallego, J., Richards, T., Malingreau, J.P., 2002.

Determination of deforestation rates of the world’s humid tropical forests. Science, 297, 999-

1002.

Angelsen, A., 1995. Shifting cultivation and “deforestation”: A study from Indonesia. World


Arroyo-Rodriguez, V., Pineda, E., Escobar, F., Benitez-Malvido, J., 2008. Value of small patches in

the conservation of plant-species diversity in highly fragmented rainforest. Conservation

Biology, 23, 729–739.

Asio, V.B., Jahn, R., Stahr, K., Margraf, J., 1998. Soils of the tropical forests of Leyte, Philippines

II: Impact of different land uses on status of organic matter and nutrient availability. In:

Schulte, A., Ruhiyat, D. (eds), Soils of Tropical Forest Ecosystems: characteristics, ecology

and management, pp 37-44. Springer, New York.

Aurelio, M.A., 2000. Shear partitioning in the Philippines: constraints from Philippine fault and

global positioning. Island Arc 9, 584–597.

Baraloto, C., Molto, Q., Rabaud, S., Herault, B., Valencia, R., Blanc, L., Fine, P.V.A., Thompson,

J., 2013. Rapid simultaneous estimation of aboveground biomass and tree diversity across

Neotropical forests: a comparison of field inventory methods. Biotropica 45, 288–298.

Bartoń, K., 2011. Package ‘MuMIn’. Available at: http://cran.r-

project.org/web/packages/MuMIn/MuMIn.pdf.




http://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf


63

Brook, B.W., Bradshaw, C.J.A., Koh, L.P., Sodhi, N.S., 2006. Momentum drives the crash: mass

extinction in the tropics. Biotropica, 38, 302-305.


the demise in swidden agriculture in Southeast Asia: soil nutrients and carbon stocks. Human

Ecology, 37, 375–388.

Cannon, C.H., Peart, D.R., Leighton, M., 1998. Tree species diversity in commercially logged

Bornean rainforest. Science, 281, 1366-1368

Castro-Luna, A.A., Castillo-Campos, G., Sosa, V.J., 2011. Effects of selective logging and shifting

cultivation on the structure and diversity of a tropical evergreen forest in south-eastern

Mexico. Journal of Tropical Forest Science, 23, 17-34.




Perspectives in Plant Ecology, Evolution and Systematics, 6, 51-71.

Chazdon, R.L., 2008. Beyond deforestation: Restoring forests and ecosystem services on degraded

lands. Science, 320, 1458-1460.

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.

Chokkalingam, U., Carandang, A.P., Pulhin, J.M., Lasco, R.D., Peras, R.J.J., Toma, T., 2006. One

Century of Forest Rehabilitation in the Philippines: Approaches, Outcomes and

LessonsCenter for International Forestry Research (CIFOR), Bogor, Indonesia.



Curtis, J.T., Cottam, G., 1962. Plant ecology work book. Burgess, Minneapolis.

Dalle, S.P., Pulido, M.T., de Blois, S., 2011. Balancing shifting cultivation and forest conservation:

lessons from a "sustainable landscape" in southeastern Mexico. Ecological Applications, 21,

1557-72.

Dawson, I.K., Guariguata, M.R., Loo, J., Weber, J.C., Lengkeek, A., Bush, D., Cornelius, J.,

Guarino, L., Kindt, R., Orwa, C. et al., 2013. What is the relevance of smallholders’

agroforestry systems for conserving tropical tree species and genetic diversity in circa situm,

in situ and ex situ settings? A review. Biodiversity and Conservation, 22, 301-324.

DENR (Department of Environment and Natural Resources), 2007. The national list of threatened

Philippine plants and their categories, and the list of other wildlife species. Adminsinistrative

Order 2007.01, DENR, Republic of the Philippines.

64

Ding, Y., Zang, R., Liu, S., He, F., Letcher, S.G., 2012. Recovery of woody plant diversity in

tropical rain forests in southern China after logging and shifting cultivation. Biological


Ding, Y., Zang, R.G., Jiang, Y.X., 2006. Effect of hillslope gradient on vegetation recovery on

abandoned land of shifting cultivation in Hainan Island, South China. Journal of Integrative

Plant Biology, 4, 642-653.

Do, T.V., Osawa, A., Thang, N.T., Van, N.B., Hang, B.T., Khanh, C.Q., Thao, L.T., Tuan, D.X.,

2011. Population changes of early successional forest species after shifting cultivation in

Northwestern Vietnam. New Forests, 41, 247–262.

Echeverria, C., Newton, A.C., Lara, A., Benayas, J.M.R., Comes, D.A., 2007. Impact of forest

fragmentation on species composition and forest structure in the temperate landscape of

Southern Chile. Global Ecology and Biogeography, 16, 426-439.

Ehrlen, J., Morris, W.F., 2015. Predicting changes in the distribution and abundance of species

under environmental change. Ecology Letters, 18, 303–314.

Erskine, P.D., Lamb, D., Bristow, M., 2006. Tree species diversity and ecosystem function: Can

tropical multi-species plantations generate greater productivity? Forest Ecology and

Management, 233, 205–210.

FAO (Food and Agriculture Organization of the United Nations), 2005. State of the Worlds Forests

2005. FAO, Rome, Italy.

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.

Fredericksen, T.S., Mostacedo, B., 2000. Regeneration of timber species following selection

logging in a Bolivian tropical dry forest. Forest Ecology and Management, 131, 47–55.

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.

Geist, H.J., Lambin, E.F., 2002. Proximate causes and underlying driving forces of tropical

deforestation. BioScience, 52, 143-150.

Gemerden, B.S.V., Shu, G.N., Olff, H., 2003. Recovery of conservation values in Central African

rain forest after logging and shifting cultivation. Biodiversity and Conservation, 12,1553–

1570.

Gentry, A.H., 1982. Patterns of neotropical plant species diversity. Evolutionary Biology, 15, 1–84.

Ghazoul, J., Burivalova, Z., Garcia-Ulloa, J., King, L.A., 2015. Conceptualizing forest degradation.

Trends in Ecology & Evolution, 30, 622-632.

65

Grueber, C.E., Nakagawa, S., Laws, R.J., Jamieson, I.G., 2011. Multimodel inference in ecology

and evolution: challenges and solution. Journal of Evolutionary Biology, 24, 699-711.

Häger, A., Otárola, M.F., Stuhlmacher, M.F., Castillo, R.A., Arias, A.C., 2014. Effects of

management and landscape composition on the diversity and structure of tree species

assemblages in coffee agroforests. Agriculture, Ecosystems & Environment, 199, 43–51.

Herbohn, J.L., Vanclay, J.K., Ngyuen, H., Le, H.D., Harrison, S.R., Cedamon, E., Smith, C., Firn,

J., Gregorio, N.O., Mangaoang, E., Lamarre, E., 2014. Inventory procedures for smallholder

and community woodlots in the Philippines: methods initial findings and insights. Small-scale

Forestry, 13, 79-100.

Hobbs, R., Arico, S., Aronson, J. et al., 2006. Novel ecosystems: theoretical and management

aspects of the new ecological world order. Global Ecology and Biogeography, 15, 1-7.

Hobbs, R.J., Higgs, E., Harris, J.A., 2009. Novel ecosystems: implications for conservation and

restoration. Trends in Ecology and Evolution, 24, 599-605.

IUCN (International Union of Conservation of Nature), 2014. The IUCN Red List of Threatened

Species. Version 2013.2. (available online at: http://www.iucnredlist.org). IUCN, Gland,

Switzerland.

Jahn, R., Asio, V.B., 2001. Climate, geology, geomorphology and soils of the tropics with special

reference to Leyte islands (Philippines). In: Proceedings of the 8th International Seminar and

Workshop on Tropical Ecology. Visayas State College of Agriculture, Baybay, Leyte, pp. 25–

43.

Johnson, J.B., Omland, K.S., 2004. Model selection in ecology and evolution. Trends in Ecology

and Evolution, 19, 101-108.

Kier, G., Kreft, H., Lee, T.M., Jetz, W., Ibisch, P.I., Nowicki, C., Mutke, J., Barthlott, W., 2009. A

global assessment of endemism and species richness across island and mainland regions.

Proceedings of the National Academy of Sciences, USA, 106, 9322-9327.

Kindt, R., Coe, R., 2005. Tree diversity analysis. A manual and software for common statistical

methods for ecological and biodiversity studies. World Agroforestry Centre (ICRAF),

Nairobi, Kenya.

Klanderud, K., Mbolatiana, H.Z.H., Vololomboahangy, M.N., Radimbison, M.A., Roger, E.,

Totland, Ø., Rajeriarison, C., 2010. Recovery of plant species richness and composition after

slash-and-burn agriculture in a tropical rainforest in Madagascar. Biodiversity and


Koh, L.P., Ghazoul, J., 2010. A matrix-calibrated species-area model for predicting biodiversity

losses due to land-use change. Conservation Biology, 24, 994–1001.

http://www.iucnredlist.org/

66

Kolb, M., 2003. Silvicultural analysis of “Rainforestation Farming” area on Leyte Island,

Philippines. PhD thesis, University of Göttingen, Germany, 116 p.

Kumaraswamy, S., Kunte, K., 2013. Integrating biodiversity and conservation with modern

agricultural landscapes. Biodiversity Conservation, 22, 2735-2750.

Kummer, D.M., 1992. Upland agriculture, the land frontier and forest decline in the

Philippines. Agroforestry Systems, 18, 31-46.

Kummer, D.M., Turner, B.L., 1994. The Human causes of deforestation in Southeast Asia.

BioScience, 44, 323-328.



Lasco, R.D., Veridiano, R.K.A., Habito, M., Pulhin, F.B., 2013. Reducing emissions from

deforestation and forest degradation plus (REDD+) in the Philippines: will it make a

difference in financing forest development? Mitigation and Adaptation Strategies for Global

Change, 18, 1109-1124.



Laurance, W.F., 2007. Have we overstated the tropical biodiversity crisis? Trends in Ecology and

Evolution, 22, 65-70.



Lawrence, D., Radel, C., Tully, K., Scmook, B., Schneider, L., 2010. Untangling a decline in



Lawrence, D., Suma, V., Mogea, J.P., 2005. Change in species composition with repeated shifting

cultivation: limited role of soil nutrients. Ecological Applications, 15, 1952–1967.

Letcher, S.G., Chazdon, R.L., 2009. Rapid recovery of biomass, species richness, and species

composition in a secondary forest chronosequence in northeastern Costa Rica. Biotropica, 41,

608–617.

Magurran, A.E., 2004. Measuring Biological Diversity. Blackwell, Oxford, UK.



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.

67


Change in Southeast Asia: Understanding Causes and Consequences. Human Ecology, 37,

259-264.

Miller, P.M., Kauffman, J.B., 1998. Seedling and Sprout Response to Slash-and-Burn Agriculture

in a Tropical Deciduous Forest. Biotropica, 30, 538-546.

Mo, X., Zhu, H., Zhang, Y.J., Slik, J.W.F., Liu, J.X., 2011. Traditional forest management has

limited impact on plant diversity and composition in a tropical seasonal rainforest in SW

China. Biological Conservation, 144, 1832–1840.






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.

Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B., Kent, J., 2000. Biodiversity

hotspots for conservation priorities. Nature, 403, 853-858.

Nguyen, H., Lamb, D., Herbohn, J., Firn, J., 2014. Designing Mixed Species Tree Plantations for

the Tropics: Balancing Ecological Attributes of Species with Landholder Preferences in the

Philippines. PLoS ONE, 9, e95267.

Navarrete, I.A., Tsutsuki, K., Asio, V.B., 2013. Characteristics and fertility constraints of degraded

soils in Leyte, Philippines. Archives of Agronomy and Soil Science, 59, 625–639.

N'Dja, J.K.K., Decocq, G., 2008. Successional patterns of plant species and community diversity in

a semi-deciduous tropical forest under shifting cultivation. Journal of Vegetation Science, 19,

809-820.

Newton, A.C., 2007. Forest ecology and conservation: a handbook of techniques. Oxford University

Press, New York.

Norden, N., Angarita, H.A., Bongers, F., Martínez-Ramos, M., Granzow de, la Cerda., van Breugel,

M., Lebrija-Trejos, E., Meave, J.A., Vandermeer, J., Williamson, B., Chazdon, R.L., 2015.

Successional dynamics in Neotropical forests are as uncertain as they are predictable.

Proceedings of the National Academy of Sciences, USA, 112, 8013-8018.

Norden, N., Chazdon, R.L., Chao, A., Jiang, Y.H., Vilchez-Alvarado, B., 2009. Resilience of

tropical rain forests: tree community reassembly in secondary forests. Ecology Letters, 12,

385-394.

68

Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., O’Hara, B., Simpson, G.L., Solymos, P.,

Stevens, M.H.H., Wagner, H., 2010. vegan: Community Ecology Package. R package version

2.0-10.

Olofson, H., 1980. Swidden and kaingin among the southern Tagalog: a problem in Philippine

upland ethno-agriculture. Philippine Quarterly of Culture and Society, 8, 168-180.

Paoli, G.D., Curran, L.M., Slik, J.W.F., 2008. Soil nutrients aVect spatial patterns of aboveground

biomass and emergent tree density in southwestern Borneo. Oecologia, 155, 287–299.

Peque, D., Holscher, D., 2014. The abundance of rare tree species in remnant forests across the

Visayas, Philippines. Biodiversity and Conservation, 23, 2183–2200.

Pichancourt, J.B., Firn, J., Chades, I., Martin, T.G., 2014. Growing biodiverse carbon-rich forests.

Global Change Biology, 20, 382–393.

Pickett, S.T.A., 1989. Space for time substitution as an alternative to long term studies. In: Long-

term studies in ecology (ed Liken GE). PP 71-88.Wiley, Chichester.

Pinheiro, J., Bates, D., Roy, S.D., Sarkar, D., 2011. Package ‘nlme’. Available at: http://cran.r-

project.org/web/packages/nlme/nlme.pdf.






Putz, F.E., Romero, C., 2014. Futures of Tropical Forests (sensu lato). Biotropica, 46, 495-505.

R Development Core Team, 2012. R: A Language and Environment for Statistical Computing. R


Raharimalala, O., Buttler, A., Ramohavelo, C.D., Razanaka, S., Sorge, J.P., Gobat, J.M., 2010. Soil-

vegetation patterns in secondary slash and burn successions in Central Menabe, Madagascar.

Agriculture, Ecosystems & Environment, 139, 150–158.


forests of the Yucatan. Ecological Applications, 13, 85-97.

Roskov, Y., Kunze, T., Paglinawan, L., Orrell, T., Nicolson, D., Culham, A., Bailly, N., Kirk, P.,

Bourgoin, T., Baillargeon, G., Hernandez, F., De Wever, A. (eds), 2014. Species 2000 & ITIS

Catalogue of Life, 2013 Annual Checklist. (available online at:

www.catalogueoflife.org/annual-checklist/2014/). Species 2000: Reading, UK.

Sang, P.M., Lamb, D., Bonner, M., Schmidt, S., 2013. Carbon sequestration and soil fertility of

tropical tree plantations and secondary forest established on degraded land. Plant and Soil

362, 187-200.

http://cran.r-project.org/web/packages/nlme/nlme.pdf


69



Schmook, B., 2010. Shifting maize cultivation and secondary vegetation in the Southern Yucatan:

successional forest impacts of temporal intensification. Regional Environmental Change, 10,

233–246.

Schroth, G., da Fonseca, G.A.B., Harvey, C.A., Gascon, C., Vasconcelos, H.L., Izac, A.N. (eds),

2004. Agroforestry and biodiversity conservation in Tropical Landscapes. Island Press,

Washington, DC, USA.

Slik, J.W.F., Bernard, C.S., Beek, M.V., Breman, F.C., Eichhorn, K.A.O., 2008. Tree diversity,

composition, forest structure and aboveground biomass dynamics after single and repeated

fire in a Bornean rain forest. Oecologia, 158, 579-588.

Sodhi, N.S., Koh, L.P., Brook, B.W., Ng, P.K.L., 2004. Southeast Asian biodiversity: an impending

disaster. Trends in Ecology and Evolution, 19, 654–660.




Sovu, Tigabu, M., Savadogo, P., Oden, P.C., Xayvongsa, L., 2009. Recovery of secondary forests

on swidden cultivation fallows in Laos. Forest Ecology and Management, 258, 2666-2675.

Thompson, J., Brokaw, N., Zimmerman, J.K., Waide, R.B., Everham III, E.M., Lodge, D.J., Taylor,

C.M., García-Montiel, D., Fluet, M., 2002. Land-use history, environment, and tree

composition in a tropical forest. Ecological Applications, 12, 1344-1363.

Trimble, M.J., van Aaarde, R.J., 2012. Geographical and taxonomic biases in research on

biodiversity in human-modified landscapes. Ecosphere, 3, 1-16.

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.

Valencia, V., Garcia-Barrios, L., West, P., Sterling, E.J., Naeem, S., 2014. The role coffee

agroforestry in the conservation o tree diversity community composition of native forests in a

Biosphere Reserve. Agriculture, Ecosystems & Environment, 189, 154-163.


Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.C., Jørgensen, L., Thomsen, T.B., Hett,

C., Bech-Bruun, T., Ickowitz, A., Vu, K.C., Yasuyuki, K., Fox, J., Padoch, C., Dressler, W.,

Ziegler, A.D., 2012. Trends, drivers and impacts of changes in swidden cultivation in tropical

forest-agriculture frontiers: a global assessment. Global Environmental Change, 22, 418–429.

70

Watson, D.J., 1947. Comparative physiological studies in the growth of field crops. I: Variation in

net assimilation rate and leaf area between species and varieties, and within and between

years. Annals of Botany, 11, 41-76.

Wilson, A.M., Latimer, A.M., Silander Jr, J.A., 2015. Climate controls on ecosystem resilience:

Postfire regeneration in the Cape Floristic Region of South Africa. Proceedings of the

National Academy of Sciences, USA, 112: 9058-9063.

Wright, S.J., Muller-Landau, H.C., 2006. The Future of Tropical Forest Species. Biotropica, 38,

287–301.

Ziegler, A.D., Fox, J.M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Bruun, T.B.,



71

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:

http://www.catalogueoflife.org/annual-checklist/2014/

http://www.iucnredlist.org/

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.


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).


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.

4.8 References

Armecin, R.B., Coseco, W.C., 2012. Abaca (Musa textilis Nee) allometry for above-ground

biomass and fiber production. Biomass and Bioenergy, 46, 181-189.



Schulte, A., Ruhiyat, D. (eds), Soils of Tropical Forest Ecosystems: characteristics, ecology


Aurelio, M.A., 2000. Shear partitioning in the Philippines: constraints from Philippine fault and

global positioning. Island Arc, 9, 584–597.

Baraloto, C., Molto, Q., Rabaud, S., He´rault, B., Valencia, R., Blanc, L., Fine, P.V.A., Thompson,

J., 2013. Rapid simultaneous estimation of aboveground biomass and tree diversity across

Neotropical forests: a comparison of field inventory methods. Biotropica, 45, 288–298.



Beets, P.N., Kimberley, M.O., Oliver, G.R., Pearce, S.H., Graham, J.D., Brandon, A., 2012.

Allometric Equations for Estimating Carbon Stocks in Natural Forest in New Zealand.

Forests, 3, 818-839.



96

Blanc, L., Echard, M., Herault, B., Bonal, D., Marcon, E., Chave, J., Baraloto, C., 2009. Dynamics

of aboveground carbon stocks in a selectively logged tropical forest. Ecological Applications,

19, 1397-1404.




Brown, S., 1997. Estimating biomass and biomass change of tropical forests: A primer. Forestry

Paper No. 134. FAO, Rome, Italy.



Letters, 9, 114020.

Castro-Luna, A.A., Castillo-Campos, G., Sosa, V.J., 2011. Effects of selective logging and shifting

cultivation on the structure and diversity of a tropical evergreen forest in South-Eastern

Mexico. Journal of Tropical Forest Science, 23, 17-34.

Chave, J., Andalo, C., Brown, S., Cairns, M.A., Chambers, J.Q., Eamus, D., Folster, H., Fromard,

F., Higuchi, N., Kira, T., Lescure, J.P., Nelson, B.W., Ogawa, H., Puig, H., Riera, B.,

Yamakura, T., 2005. Tree allometry and improved estimation of carbon stocks and balance in

tropical forests. Oecologia, 145, 87-99.

Chave, J., Rejou-Mechain, M., Burquez, A., Chidumayo, E., Colgan, M.S. et al., 2014. Improved

allometric models to estimate the aboveground biomass of tropical trees. Global Change

Biology, 20, 3177-3190.


Perspectives in Plant Ecology, Evolution and Systematics 6, 51-71.


century of forest rehabilitation in the Philippines: Approaches, outcomes and lessons. Center

for International Forestry Research (CIFOR), Bogor, Indonesia.

Clark, D.A., Brown, S., Kicklighter, D.W., Chambers, J.Q., Thomlinson, J.R., Ni, J., Holland, E.A.,

2001. Net primary production in tropical forests: an evaluation and synthesis of existing field

data. Ecological Applications, 11, 371-384.

DeFries, R.S., Houghton, R.A., Hansen, M.C., Field, C.B., Skole, D., Townshend, J., 2002. Carbon

emissions from tropical deforestation and regrowth based on satellite observations for the

1980s and 1990s. Proceedings of the National Academy of Sciences, USA, 99, 14256-14261.

Delaney, M., Brown, S., Lugo, A.E., Torres-Lezama, A., Quintero, N.B., 1998. The quantity and

turnover of dead wood in permanent forest plots in six life zones of Venezuela. Biotropica,

30, 2-11.

97

d'Oliveira, M.V.N., Alvarado, E.C., Santos, J.C., Jr, J.A.C., 2011. Forest natural regeneration and

biomass production after slash and burn in a seasonally dry forest in the Southern Brazilian

Amazon. Forest Ecology and Management, 261, 1490-1498.

Eaton, J.M., Lawrence, D., 2009. Loss of carbon sequestration potential after several decades of

shifting cultivation in the Southern Yucatan. Forest Ecology and Management, 258 949–958.

FAO (Food and Agriculture Organization of the United Nations)., 2010. Global Forest Resources

Assessment 2010. FAO Forestry Paper 163. FAO, Rome, Italy.


D., 2009. Policies, political economy, and swidden, in Southeast Asia. Human Ecology, 37,

305–322.

Gentry, A.H., 1982. Patterns of neotropical plant species diversity. Evolutionary Biology, 15, 1–84.


and evolution: challenges and soulution. Journal of Evolutionary Biology, 24, 699-711.

Houghton, R., 2012. Carbon emissions and the drivers of deforestation and forest degradation in the

tropics. Current Opinion in Environmental Sustainability, 4, 597-603.

Hulvey, K.B., Hobbs, R.J., Standish, R.J., Lindenmayer, D.B., Lach, L., Perring, M.P. 2013.

Benefits of tree mixes in carbon plantings. Nature Climate Change, 3, 869-874.

Hunter, M.O., Keller, M., Victoria, D., Morton, D.C., 2013. Tree height and tropical forest biomass

estimation. Biogeosciences, 10, 8385-8399.




43.

Kenzo, T., Ichie, T., Hattori, D., Kendawang, J.J., Sakurai, K., Ninomiya, I., 2010. Changes in

above- and belowground biomass in early successional tropical secondary forests after

shifting cultivation in Sarawak, Malaysia. Forest Ecology and Management, 260, 875–882.

Ketterings, Q.M., Coe, R., van Noordwijk, M., Ambagau, Y., Palm, C.A., 2001. Reducing

uncertainty in the use of allometric biomass equations for predicting above-ground tree

biomass in mixed secondary forests. Forest Ecology and Management, 146, 199-209.

Koh, L.P., 2007. Impending disaster or sliver of hope for Southeast Asian forests? The devil may lie

in the details. Biodiversity and Conservaton, 16, 3935–3938.


Philippines. PhD thesis, University of Göttingen, Germany.

98



Ecosystems & Environment, 65, 245-256



Lasco, R.D., Guillermo, I.Q., Cruz, R.V.O., Bantayan, N.C., Pulhin, F.B., 2004. Carbon stocks

assessment of a secondary forest in Mount Makiling Forest Reserve, Philippines. Journal of

Tropical Forest Science, 16, 35-45.

Lasco, R.D., MacDicken, K.G., Pulhin, F.B., Guillermo, I.Q., Sales, R.F., Cruz, R.V.O., 2006.

Carbon stocks assessment of a selectively logged dipterocarp forest and wood processing mill

in the Philippines. Journal of Tropical Forest Science, 18, 166–172.



Lasky, J.R., Uriarte, M., Boukili, V.K., Erickson, D.L., Kress, W.J., Chazdon, R.L., 2014. The

relationship between tree biodiversity and biomass dynamics changes with tropical forest

succession. Ecology Letters, 17, 1158-1167.

Lawrence, D., 2005. Biomass accumulation after 10-200 years of shifting cultivation in Bornean

rain forest. Ecology, 86, 26-33.




Letcher, S.G., Chazdon, R.L., 2009. Rapid recovery of biomass, species richness, and species

composition in a forest chronosequence in northeastern Costa Rica. Biotropica 41, 608-617.

Malhi, Y., 2010. The carbon balance of tropical forest regions, 1990–2005. Current Opinion in

Environmental Sustainability, 2, 237–244.

Malhi, Y., Wood, D., Baker, T.S., Wright, J., Phillips, O.L. et al., 2006. The regional variation of

aboveground live biomass in old-growth Amazonian forests. Global Change Biology, 12,

1107-1138.

Marin-Spiotta, E., Ostertag, R., Silver, W.L., 2007. Long-term patterns in tropical reforestation:

plant community composition and aboveground biomass accumulation. Ecological

Applications, 17, 828-839.




diversity in secondary fallow forests of Laos. Forest Ecology and Management, 281, 93– 99.

99


change in Southeast Asia: understanding causes and consequences. Human Ecology, 37, 259-

264.




Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B. and Kent, J., 2000.

Biodiversity hotspots for conservation priorities. Nature, 403, 853-858.



Ngo, K.M., Turner, B.L., Muller-Landau, H.C., Davies, S.J., Larjavaara, M., Nik Hassan, N.F.,

Lum, S., 2013. Carbon stocks in primary and secondary tropical forests in Singapore. Forest

Ecology and Management, 296, 81–89.



Orihuela-Belmonte, D.E., Jong, B.H.J., Mendoza-Vega, J., Wal, J.V., Paz-Pellat, F., Soto-Pinto, L.,

Flamenco-Sandoval, A., 2013. Carbon stocks and accumulation rates in tropical secondary

forest at the scale of community, landscape and forest type. Agriculture, Ecosystems &

Environment, 171, 72–84.

Pan, Y.D., Birdsey, R.A., Fang, J., Houghton, R., Kauppi, P.K. et al., 2011. A large and persistent

carbon sink in the world’s forests. Science, 333, 988-993.

Pelletier, J., Codjia, C., Potvin, C., 2012. Trditional shifting agriculture: tracking forest carbon stock

and biodiversity through time in western Panama. Global Change Biology, 18, 3581-3595.

Pichancourt, J.B., Firn, J., Chades, I., Martin, T.G., 2014. Growing biodiverse carbon-rich forests.

Global Change Biology, 20, 382–393.






Raharimalala, O., Buttler, A., Schlaepfer, R., Gobat, J.M., 2012. Quantifying biomass of secondary

forest after slash-and-burn cultivation in central Menabe, Madagascar. Journal of Tropical

Forest Science, 24, 474-489.


forests of the Yucatan. Ecological Applications, 13, 85-97.

100

Rozendaal, D.M.A., Chazdon, R.L., 2015. Demographic drivers of tree biomass change during

secondary succession in northeastern Costa Rica. Ecological Applications, 25, 506-516.

Saner, P., Loh, Y.Y., Ong, R.C., Hector, A., 2012. Carbon Stocks and Fluxes in Tropical Lowland

Dipterocarp Rainforests in Sabah, Malaysian Borneo. PLoS ONE, 7, e29642.



Stanley, W., Brown, S., Kant, Z., Calmon, M., Tiepolo, G., Boucher, T., 2010. The climate action

project research initiative. The Nature Conservancy, Arlington, V.A.

Taylor, P., Asner, G., Dahlin, K., Anderson, C., Knapp, D., Martin, R., Mascaro, J., Chazdon, R.,

Cole, R., Wanek, W., Hofhansl, F., Malavassi, E., Vilchez-Alvarado, B., Townsend, A., 2015.

Landscape-scale controls on aboveground forest carbon stocks on the Osa Peninsula, Costa

Rica. PLoS ONE, 10, e0126748.

Valencia, R., Condit, R., Muller-Landau, H.C., Hernandez, C., Navarrete, H., 2009. Dissecting

biomass dynamics in a large Amazonian forest plot. Journal of Tropical Ecology, 25, 473-

482.


Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.-C., Jørgensen, L., Birch Thomsen, T.,




418–429.

World Agroforestry Centre., 2014. Wood density database. Available at:

http://www.worldagroforestry.org/regions/southeast_asia/resources/db/wd. Accessed in 2014.

Tang, X., Wang, Z., Xie, J., Liu, D., Desai, A.R., Jia, M. et al., 2013. Monitoring the seasonal and

interannual variation of the carbon sequestration in a temperate deciduous forest with MODIS

time series data. Forest Ecology and Management, 306, 150–160.

Tang, X., Wang, Z., Liu, D., Song, K., Jia, M., Dong, Z. et al., 2012. Estimating the net ecosystem

exchange for the major forests in the northern United States by integrating MODIS and

AmeriFlux data. Agricultural and Forest Meteorology, 156, 75– 84.

Ziegler, A.D., Phelps, J., Yuen, J.Q., Webb, E.L., Lawrence, D., Fox, J.M. et al., 2012. Carbon

estimates of major land-cover transitions in SE Asia: great uncertainities and REDD+ policy

implications. Global Change Biology, 18, 3087-3099.

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


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.


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.


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.

5.8 References

Ahrends, A., Hollingsworth, P.M., Ziegler, A.D., Fox, J.M., Chen, H., Su, Y., Xu, J., 2015. Current

trends of rubber plantation expansion may threaten biodiversity and livelihoods. Global

Environmental Change, 34, 48-58.

Anderson, S.E., Ingram, J.S.I., 1989. Tropical soil biology and fertility: A handbook of methods.

C.A.B. International, Aberystwyth.



Schulte, A., Ruhiyat, D. (eds.), Soils of Tropical Forest Ecosystems: characteristics, ecology




Batjes, N.H., 1996. Total Carbon and Nitrogen in the soils of the world. European Journal of Soil

Science, 47, 151–163.

Bonner, M.T.L., Schmidt, S., Shoo, L., 2013. A meta-analytical global comparison of aboveground

biomass accumulation between tropical secondary forests and monoculture plantations. Forest

Ecology and Management, 291, 73-86.

Brand, J., Pfund, J.L., 1998. Site and watershed level assessment of nutrient dynamics under

shifting cultivation in eastern Madagascar. Agriculture, Ecosystems & Environment, 71, 169–

183.


the demise in swidden cultivation in Southeast Asia: Carbon storage and soil quality. Human

Ecology, 37, 375–388.



117

Bruun, T.B., Egay, K., Mertz, O., Magid, J., 2013. Improved sampling methods document decline

in soil organic carbon stocks and concentrations of permanganate oxidizable carbon after

transition from swidden to oil palm cultivation. Agriculture, Ecosystems & Environment, 178,

127–134.

Bruun, T.B., Mertz, O., Elberling, B., 2006. Linking yields of upland rice in shifting cultivation to

fallow length and soil properties. Agriculture, Ecosystems & Environment, 113, 139– 149.

Carating, R.B., Galanta, R.G., Bacatio, C.D., 2014. The soils of the Philippines. Springer, New

York.


century of forest rehabilitation in the Philippines: Approaches, outcomes and lessons. Center

for International Forestry Research (CIFOR), Bogor, Indonesia.



Congdon, R.A., 2012. Basic methods for the collection, preparation and analysis of plant tissue,

water and soil samples. James Cook University, Townsville.

de Neergaard, A., Magid, J., Mertz, O. 2008. Soil erosion from shifting cultivation and other

smallholder land use in Sarawak, Malaysia. Agriculture, Ecosystems & Environment, 125,

182–190.




Asia. Journal of Development Effectiveness, 7, 210-229.

Estes, J.A., Terborgh, J., Brashares, J.S., Power, M.E., Berger, J., Bond, W.J., Carpenter, S.R.,

Essington, T.E., Holt, R.D., Jackson, J.B.C., Marquis, R.J., Oksanen, L., Oksanen, T., Paine,

R.T., Pikitch, E.K., Ripple, W.J., Sandin, S.A., Scheffer, M., Schoener, T.W., Shurin, J.B.,

Sinclair, A.R.E., Soulé, M.E., Virtanen, R., Wardle, D.A., 2011. Trophic downgrading of

planet earth. Science, 333, 301–306.

FAO (Food and Agriculture Organization of the United Nations), 2006. Guidelines for soil

description. FAO, Rome, Italy.

Fernández-Romero, M.L., Lozano-García, B., Parras-Alcántara, L., 2014. Topography and land use

change effects on the soil organic carbon stock of forest soils in Mediterranean natural areas.

Agriculture, Ecosystems & Environment 195, 1-9.

Firn, J., Erskine, P.D., Lamb, D., 2007. Woody species diversity influences productivity and soil

nutrient availability in tropical plantations. Oecologia, 154, 521–533.

118

Fox, J., Fujita, Y., Ngidang, D., Peluso, N., Potter, N., 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, T.A., Tuyen, N.P., Cuc, L.T., Leisz, S., 2000. Shifting cultivation: A


Funakawa, S., Makhrawie, M., Pulunggono, H.B., 2009. Soil fertility status under shifting

cultivation in East Kalimantan with special reference to mineralization patterns of labile

organic matter. Plant and Soil, 319, 57-66.

Garcı́a-Oliva, F., Sanford Jr., R.L., Kelly, E., 1999. Effects of slash-and-burn management on soil

aggregate organic C and N in a tropical deciduous forest. Geoderma, 88, 1–12.

Giardina, C.P., Sanford, R.L. Jr., Døckersmith, I.C., Jaramillo, V. J., 2000. The effects of slash

burning on ecosystem nutrients during the land preparation phase of shifting cultivation. Plant

and Soil, 220, 247–260.


and evolution: challenges and solution. Journal of Evolutionary Biology, 24, 699-711.

Guo, L.B., Gifford, R.M., 2002. Soil carbon stocks and land-use change: a meta analysis. Global

Change Biology, 8, 345-360.

Hattar, B.I., Taimeh, A.Y., Ziadat, F.M., 2010. Variation in soil chemical properties along

toposequences in an arid region of the Levant. Catena, 83, 34–45.

Hett, C., Castella, J., Heinimann, A., Messerli, P., Pfund, J., 2012. A landscape mosaic approach for

characterizing swidden systems from REDD+ perspective. Applied Geograpgy, 32, 608-618.

Hughes, R.F., Kauffman, J.B., Jaramillo, V. J., 1999. Biomass, carbon, and nutrient dynamics of

secondary forests in a humid tropical region of Mexico. Ecology, 80, 1892-1907.




43.


Philippines. PhD thesis, University of Göttingen, Germany.



Ecosystems & Environment, 65, 245-256.

Krishan, G., Srivastav, S.K., Kumar, S., Saha, S.K., Dadhwal, V.K., 2009. Quantifying the

underestimation of soil organic carbon by the Walkley and Black technique - examples from

Himalayan and Central Indian soils. Current Science, 96, 1133-1136.

119

Lal, R., 1997. Degradation and resilience of soils. Philosophical Transactions of the Royal Society

B, 352, 869-889.

Lange, M., Eisenhauer, N., Sierra, C.A., Bessler, H., Engels, C., Griffiths, R.I., Mellado-Va´zquez,

P.G., Malik, A.A., Roy, J., Scheu, S., Steinbeiss, S., Thomson, B.C., Trumbore, S.E.,

Gleixner, G., 2015. Plant diversity increases soil microbial activity and soil carbon storage.

Nature Communications, 6, 6707.






Lawrence, D., Schlesinger, W.H., 2001. Changes in soil phosphorus during 200 years of shifting

cultivation in Indonesia. Ecology, 82, 2769-2780.

Lawrence, D., Suma, V., Mogea, J.P., 2005. Change is species composition with repeated shifting

cultivation: limited role of soil nutrients. Ecological Applications, 15, 1952-1967.

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.

Lugo, A.E., Brown, S., 1993. Management of tropical soils as sinks or sources of atmospheric

carbon. Plant and Soil, 149, 27-41.

Mertz, O., Padoch, C., Fox, J., Cramb, R.A., Leisz, S.J., Nguyen, T.L., Tran, D.V., 2009a. Swidden

change in Southeast Asia: Understanding causes and consequences. Human Ecology, 37, 259-

264.

Mertz, O., Leisz, S.J., Heinimann, A., Rerkasem, K., Thiha., Dressler, W., Pham, V.C., Vu, K.C.,

Schmidt-Vogt, D., Colfer, C.J.P., Epprecht, M., Padoch, C. and Potter, L., 2009b. Who

Counts? Demography of swidden cultivators in Southeast Asia. Human Ecology, 37, 281-

289.

Mertz, O., Wadley, R.L., Nielsen, U., Bruun, T.B., Colfer, C.J.P., de Neergaard, A., Jepsen, M.R.,

Martinussen, T., Zhao, Q., Noweg, G.T., Magid, J., 2008. A fresh look at shifting cultivation:

Fallow length an uncertain indicator of productivity. Agricultural Systems, 96, 75–84.






120

Mukul, S.A., Herbohn, J., Firn, J., In review. High resilience of tropical forest diversity and


Murty, D., Kirschbaum, M.U.F., Mcmurtrie, R.E., Mcgilvray, H., 2002. Does conversion of forest

to agricultural land change soil carbon and nitrogen? A review of the literature. Global

Change Biology, 8, 105–123.



Neill, C., Melillo, J.M., Steudler, P.A., Cerri, C.C., Moraes, J.F.L.D., Piccolo, M.C., Brito, M.,

1997. Soil carbon and nitrogen stocks following forest clearing for pasture in the

southwestern Brazilian Amazon. Ecological Applications, 7, 1216-1225.

Nottingham, A.T., Whitaker, J., Turner, B.L., Salinas, N., Zimmermann, M., Malhi, Y., Meir, P.,

2015. Climate warming and soil carbon in tropical forests: Insights from an elevation gradient

in the Peruvian Andes. BioScience, 65, 906-921.



Paoli, G.D., Curran, L.M., Slik, J.W.F., 2008. Soil nutrients affect spatial patterns of aboveground

biomass and emergent tree density in southwestern Borneo. Oecologia, 155, 287–299.

Parras-Alcántara, L., Martín-Carrillo, M., Lozano-García, B., 2013. Impacts of land use change in

soil carbon and nitrogen in a Mediterranean agricultural area (Southern Spain). Solid Earth, 4,

167–177.

Paudel, E., Dossa, G.G.O., Xu, J., Harrison, R.D., 2015. Litterfall and nutrient return along a

disturbance gradient in a tropical montane forest. Forest Ecology and Management, 353, 97–

106.

Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., 2011. Package ‘nlme’. Available at: http://cran.r-

project.org/web/packages/nlme/nlme.pdf.




R Development Core Team. 2012. R: A Language and Environment for Statistical Computing. R


Raharimalala, O., Buttler, A., Ramohavelo, C.D., Razanaka, S., Sorge, J.P., Gobat, J.M., 2010. Soil-

vegetation patterns in secondary slash and burn successions in Central Menabe, Madagascar.




121

Raich, J.W., Clark, D.A., Schwendenmann, L., Wood, T.E., 2014. Aboveground tree growth varies

with belowground carbon allocation in a tropical rainforest environment. PLoS ONE, 9,

e100275.

Rayment, G.E., Higginson, F.R., 1992. Australian laboratory handbook of soil and water chemical

methods. Inkata Press, Melbourne.

Richards, A.E., Dalal, R.C., Schmidt, S., 2007. Soil carbon turnover and sequestration in native

subtropical tree plantations. Soil Biology and Biochemistry, 39, 2078–2090.

Rodenburg, J., Stein, A., Noordwijk, M., Ketterings, Q.M., 2003. Spatial variability of soil pH and

phosphorus in relation to soil run-off following slash-and-burn land clearing in Sumatra,

Indonesia. Soil and Tillage Research, 71, 1–14.

Romanyá, J., Casals, P., Vallejo, V.R., 2001. Short term effects of fire on soil nitrogen availability

in Mediterranean grasslands and shrublands growing in old fields. Forest Ecology and


Sang, P.M., Lamb, D., Bonner, M., Schmidt, S., 2013. Carbon sequestration and soil fertility of

tropical tree plantations and secondary forest established on degraded land. Plant and Soil,

362, 187-200.

Sayer, E.J., Heard, M.S., Grant, H.K., Marthews, T.R., Tanner, E.V. J., 2011. Soil carbon release

enhanced by increased tropical forest litterfall. Nature Climate Change, 1, 304-307.

Sharma, K.L., Mandal, U.K., Srinivas, K., VIttal, K.P.R., Mandal, B., Grace, J.K., Ramesh, V.,

2005. Long-term soil management effects on crop yields and soil quality in a dryland Alfisol.

Soil Tillage Research, 83, 246-259.

Smith, P., House, J.I., Bustamante, M., Sobocká, J., Harper, R., Pan, G., West, P., Clark, J., Adhya,

T., Rumpel, C., Paustian, K., Kuikman, P., M. Cotrufo, M.F., Elliott, J.A., McDowell, R.,

Griffiths, R.I., Asakawa, S., Bondeau, A., Jain, A.K., Meersmans, J., Pugh, T.A.M., 2015.

Global change pressures on soils from land use and management. Global Change Biology, 22,

1008-1028.



Tanaka, S., Andoa, T., Funakawa, S., Sukhrun, C., Kaewkhongkha, T.,Sakurai, K., 2001. Effect of

burning on soil organic matter content and N mineralization under shifting cultivation system

of Karen people in Northern Thailand. Soil Science and Plant Nutrition, 47, 547-558.

Tanaka, S., Tachibe, S., Wasli, M.E.B., Lat, J., Seman, L., Kendawang, J.J., Iwasaki, K., Sakurai,

K., 2009. Soil characteristics under cash crop farming in upland areas of Sarawak, Malaysia.


122

van Noordwijk, M., Cerri, C., Woomer, P.L., Nugroho, K., Bernoux, M., 1997. Soil carbon

dynamics in the humid tropical forest zone. Geoderma, 79, 187–225.

van Straaten, O., Corre, M.D., Wolf, K., Tchienkoua, M., Cuellar, E., Matthews, R.B., Veldkamp,

E., 2015. Conversion of lowland tropical forests to tree cash crop plantations loses up to one-

half of stored soil organic carbon. Proceedings of the National Academy of Sciences, USA,

112: 9956-9960.


Schmidt-Vogt, D., Messerli, P., Leisz, S., Castella, J.-C., Jørgensen, L., Birch Thomsen, T.,




418–429.

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.

Ziegler, A.D., Fox, J. M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Bruun, T.B.,



123

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


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


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).


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).

6.6 References

133

Achard, F., Eva, H.D., Stibig, H.J., Mayaux, P., Gallego, J., Richards, T., Malingreau, J.P., 2002.

Determination of deforestation rates of the world’s humid tropical forests. Science, 297, 999-

1002.

Angelsen, A., 1995. Shifting cultivation and “deforestation”: A study from Indonesia. World


Balooni, K., Inoue, M., 2007. Decentralized forest management in South and Southeast Asia.

Journal of Forestry, 105, 414-420.

Bowler, D.E., Buyung-Ali, L.M., Healey, J.R., Jones, J.P.G., Knight, T.M., Pullin, A.S., 2012. Does

community forest management provide global environmental benefits and improve local

welfare? Frontiers in Ecology and the Environment, 10, 29–36.

Brown, S., 1997. Estimating biomass and biomass change of tropical forests: A primer. FAO

Forestry Paper 134. Food and Agriculture Organization of the United Nations (FAO), Rome,

Italy.



Letters, 9, 114020.

Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M.S., et al., 2014. Improved

allometric models to estimate the aboveground biomass of tropical trees. Global Change

Biology, 20, 3177-3190.

Chazdon, R.L., 2013. Making tropical succession and landscape reforestation successful. Journal of

Sustainable Forestry, 32, 649-658.



Chokkalingam, U., Bhat, D.M., von Gemmingen, G., 2001. Secondary forests associated with the

rehabilitation of degraded lands in tropical Asia: a synthesis. Journal of Tropical Forest

Science, 13, 816-831.

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.

Conservation International, 2013. Biological diversity in the Philippines. Retrieved from

http://www.eoearth.org/view/article/150648.

Cramb, R., 1998. Environment and development in the Philippine uplands: the problem of

agricultural land degradation. Asian Studies Review, 22, 289-308.

de Jong, W., Chokkalingam, U., Perera, G.A.D., 2001. The evolution of swidden fallow secondary

forests in Asia. Journal of Tropical Forest Science, 13, 800-815.

134




Asia. Journal of Development Effectiveness, 7, 210–229.

Erskine, P.D., Lamb, D., Bristow, M., 2006. Tree species diversity and ecosystem function: Can

tropical multi-species plantations generate greater productivity? Forest Ecology and


Evans, M.C., Carwardine, J., Fensham, R.J., Butler, D.W., Wilson, K.A., Possingham, H.P., Martin,

T.G., 2015. Carbon farming via assisted natural regeneration as a cost-effective mechanism

for restoring biodiversity in agricultural landscapes. Environmental Science & Policy, 50,

114–129.

Gibbs, H.K., Brown, S., Niles, J.O., Foley, J.A., 2007. Monitoring and estimating tropical forest

carbon stocks: making REDD a reality. Environmental Research Letters, 2, 045023.

Gilroy, J.J., Woodcock, P., Edwards, F.A., Wheeler, C., Baptiste, B.L.G., Uribe, C.A.M.,

Haugaasen, T., Edwards, D.P., 2014. Cheap carbon and biodiversity co-benefits from forest

regeneration in a hotspot of endemism. Nature Climate Change, 4, 503–507.

Grabowski, Z.J., Chazdon, R.L., 2012. Beyond carbon: Redefining forests and people in the global

ecosystem services market. SAPIENS- Surveys and Perspectives Integrating Environment and

Society, 5, 1-14.

Gregorio, N., Herbohn, J., Harrison, S., Smith, C., 2015. A systems approach to improving the

quality of tree seedlings for agroforestry, tree farming and reforestation in the Philippines.

Land Use Policy, 47, 29–41.

Hamrick, K., 2015. Ahead of the Curve: State of the Voluntary Carbon Markets 2015. Forest

Trends, Washington, DC and Ecosystem Market Place Initiative, New York.

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.

Herbohn, J.L, Vanclay, J.K., Ngyuen, H., Le, H.D., Harrison, S.R., Cedamon, E., Smith, C., Firn, J.,

Gregorio, N.O., Mangaoang, E., Lamarre, E., 2014. Inventory procedures for smallholder and

community woodlots in the Philippines: methods initial findings and insights. Small-scale

Forestry, 13, 79-100.

Houghton, R.A., 2012. Carbon emissions and the drivers of deforestation and forest degradation in

the tropics. Current Opinion in Environmental Sustainability, 4, 597–603.



135


43.

Kettle, C.J., 2010. Ecological considerations for using dipterocarps for restoration of lowland

rainforest in Southeast Asia. Biodiversity and Conservation, 19, 1137-1151.

Koh, L.P., 2007. Impending disaster or sliver of hope for Southeast Asian forests? The devil may lie

in the details. Biodiversity and Conservation, 16, 3935–3938.



Lasco, R., Pulhin, F., Bugayong, L., Mendoza, M., 2011. An assessment of potential benefits to

smallholders of REDD+ components in the Philippines. Annals of Tropical Research, 33, 31–

48.



Lasco, R.D., Veridiano, R.K. A., Habito, M., Pulhin, F.B. 2013. Reducing emissions from

deforestation and forest degradation plus (REDD+) in the Philippines: will it make a

difference in financing forest development? Mitigation and Adaptation Strategies for Global

Change, 18, 1109-1124.



Law, E.A., Bryan, B.A., Torabi, N., Bekessy, S.A., McAlpine, C.A., Wilson, K.A., 2015.

Measurement matters in managing landscape carbon. Ecosystem Services, 13, 6-15.

Lawrence, A., 1997. Kaingin in the Philippines: is it the end of the forest? Rural Development

Forestry Network Paper 21, London, UK.

Le, H.D., Smith, C., Herbohn, J., 2015. Identifying interactions among reforestation success drivers:

A case study from the Philippines. Ecological Modelling, 316, 62-77.

Le, H.D., Smith, C., Herbohn, J.L., 2014. What drives the success of reforestation projects in

tropical developing countries? The case of the Philippines. Global Environmental Change, 24,

334-348.




Manuel, W.V., 2014. Land cover data in the Philippines. Presentation at the 5th UN-REDD

Regional Lessons Learned Workshop on Monitoring Systems and Reference Levels for

REDD+, October 20 – 22, 2014, Hanoi, Viet Nam.

136

Maron, M., Rhodes, J.R., Gibbons, P., 2013. Calculating the benefit of conservation actions.

Conservation Letter, 6, 359-367.

McNicol, I.M., Berrya, N.J., Bruun, T.B., Hergoualch, K., Mertz, O., de Neergaard, A., Ryan, C.M.,

2015. Development of allometric models for above and belowground biomass in swidden

cultivation fallows of Northern Laos. Forest Ecology and Management, 357, 104-116.

Mertz, O., 2009. Trends of shifting cultivation and the REDD mechanism. Current Opinion in

Environmental Sustainability, 1, 156–160.

Mertz, O., Leisz, O., Heinimann, A., Rerkasem, K., Thiha, Dressler, W., Pham, V.C., Vu, K.C.,

Schimdt-Vogt, D., Colfer, C.J.P., Epprecht, M., Padoch, C., Potter, L., 2009. Who counts?

Demography of Swidden cultivators in Southeast Asia. Human Ecology, 37, 281–289.






Mukul, S.A., Herbohn, J., Firn, J., in review. High resilience of tropical forest diversity and


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.

Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonseca, G.A.B., Kent, J., 2000. Biodiversity

hotspots for conservation priorities. Nature, 403, 853-858.



Nguyen, H., Lamb, D., Herbohn, J., Firn, J., 2014. Designing Mixed Species Tree Plantations for

the Tropics: Balancing Ecological Attributes of Species with Landholder Preferences in the

Philippines. PLoS ONE, 9, e95267.

Peters-Stanley, M., Yin, D. 2013. Maneuvering the Mosaic: State of the voluntary carbon markets

2013. Forest Trends, Washington, DC and Bloomberge New Energy Finance,New York.

Petrokofsky, G.,Holmgren, P., Brown, N.D., 2011. Reliable forest carbon monitoring – systematic

reviews as a tool for validating the knowledge base. International Forestry Review, 13, 56-66.



Pulhin, F.B., Lasco, R.D., Urquiola, J.P. 2014. Carbon sequestration potential of Oil palm in Bohol,

Philippines. Ecosystems & Development Journal, 4, 14-19.

137

Pulhin, J.M., Inoue, M., Enters, T., 2007. Three decades of community-based forest management in

the Philippines: Emerging lessons for sustainable and equitable forest management.

International Forestry Review, 9, 865-883.

Racelis, E.L., Carandang, W.M., Lasco, R.D., Racelis, D.A., Castillo, A.S.A., Pulhin, J.M., 2008.

Assessing the carbon budgets of large leaf mahogany (Swietenia macrophylla King) and

Dipterocarp plantations in the Mt. Makiling Forest Reserve, Philippines. Journal of


Robinson, B.E., Holland, M.B., Naughton-Treves, L., 2014. Does secure land tenure save forests?

A meta-analysis of the relationship between land tenure and tropical deforestation. Global

Environmental Change, 29, 281–293.

Sheeran, K.A., 2006. Forest conservation in the Philippines: A cost effective approach to mitigating

climate change? Ecological Economics, 58, 338-349.






Thomas, S., Dargusch, P., Harrison, S., Herbohn, J., 2010. Why are there so few afforestation and

reforestation Clean Development Mechanism projects? Land Use Policy, 27, 880-887.

World Agroforestry Centre, 2014. Wood density database. Available at:

http://www.worldagroforestry.org/regions/Southeast_asia/resources/db/wd (Date of access:

14/11/2014).

Yasmi, Y., Kelley, L., Murdiyarso, D., Patel, T., 2012. The struggle over Asia’s forests: an

overview of forest conflict and potential implications for REDD+. International Forestry

Review, 14, 99-109.

Ziegler, A.D., Phelps, J., Yuen, J.Q., Webb, E.L., Lawrence, D., Fox, J.M., Bruun, T.B., Leisz, S.J.,

Ryan, C.M., Padoch, C., Koh, L.P., 2012. Carbon outcomes of major land-cover transitions in

SE Asia: great uncertainties and REDD+ policy implications. Global Change Biology, 18,

3087-3099.

Ziegler, A.D., Fox, J.M., Webb, E.L., Padoch, C., Leisz, S.J., Cramb, R.A., Mertz, O., Brunn, T.B.,



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.



Letters, 9, 114020.



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.





Lawrence, D., Vandecar, K., 2015. Effects of tropical deforestation on climate and agriculture.

Nature Climate Change, 5, 27-36.





diversity in secondary fallow forests of Laos. Forest Ecology and Management, 281, 93–99.






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.



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.



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


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


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)

161

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.