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· ABOVEGROUND TREE BIOMASS AND CARBON STOCK OF LOGGED-OVER FOREST IN SUNGAI ASAP, BELAGA , Melissa Melody Leduning Master of Environmental Science (Land Use and Water Resource Management) 2014

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Page 1: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

middot ABOVEGROUND TREE BIOMASS AND CARBON STOCK OF LOGGED-OVER FOREST IN SUNGAI ASAP BELAGA

Melissa Melody Leduning

Master of Environmental Science (Land Use and Water Resource Management)

2014

DECLARATION

I certify that this thesis does not incorporate without acknowledgement any material

previously submitted for degree in any university and that to the best of my knowledge

and it does not contain any material previously published or written by another person

where due reference has not made in the text

ACKNOWLEDGEMENT

To the glory of God who gave us the sun (Morris 1978)

In the completion of this Masters dissertation sincere gratitude goes foremost to

my research supervisor Prof Dr Ismail Jusoh who guided me well and patiently in

completing this dissertation I would also like to express appreciation to Dr Haji Idris Abu

Seman from MPOB for the opportunity and for allowing me in conducting my research at

the MPOB biodiversity area in Sungai Asap Belaga

Additionally special thanks to the SLUSE Program Coordinator Dr Tay Meng

Guan for all his hard work and supervision in the program and my examiner Dr Siti

Rubiah Zainudin for her kind advice I would also like to thank Mr Mohd Rizan Abdullah

for his help during field samplings

I am exceptionally grateful to my coursemates specifically to Doulos Nalau for his

help and support during the challenging period of completing this dissertation Thank you

as always

Subsequently an expression of gratitude to my family who have been so kind in

tolerating with my antics in the duration ofthe completion of this thesis Thank you

ii

Pusat Khidmat MakJumatAkademik UNIVERSm MALAYSIA SARAWAK

LIST OF CONTENTS

Page

DEC LARA TION

ACKNOWLEDGEMENT 11

LIST OF CONTENTS III

LIST OF TABLES v

LIST OF FIGURES VI

LIST OF PLATES VIII

LIST OF APPENDICES IX

LIST OF UNITS SYMBOLS AND ABBREVIATIONS X

ABSTRACT XII

CHAPTER 1 INTRODUCTION 1

11 Rationale of the study 3

12 Research objectives 3

CHAPTER 2 LITERATURE REVIEW 4

21 Physiography of Malaysia 4

21 1 Geography 5

212 GlillJate and rainfall 5

213 Forest types 6

214 Aboveground biomass and carbon stock 6

22 Approaches 7

23 Findings 16

24 Interpretation 18

iii

CHAPTER 3 METHODOLOGY 22

31 Study area 22rlt

32 Materials and methods 24

321 Data collection 24

322 Data analysis 27

A Aboveground biomass 27

B Carbon stocks 29

CHAPTER 4 RESULTS AND DISCUSSION 30

41 Aboveground biomass 30

411 Aboveground biomass by family 30

412 Aboveground biomass by species 33

413 Comparison of aboveground biomass between dipterocarp

and non-dipterocarp 35

414 Aboveground biomass in different diameter classes 39

415 Comparison with previous studies 41

42 Carbon stocks 43

421 Carbon stock by family 43

422 Carbon stock by species 45

423 CaIbon stock in different diameter classes 46 424 Comparison with previous studies 46

CHAPTER 5 CONCLUSION 48

REFERENCES 50

APPENDICES 56

iv

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 2: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

DECLARATION

I certify that this thesis does not incorporate without acknowledgement any material

previously submitted for degree in any university and that to the best of my knowledge

and it does not contain any material previously published or written by another person

where due reference has not made in the text

ACKNOWLEDGEMENT

To the glory of God who gave us the sun (Morris 1978)

In the completion of this Masters dissertation sincere gratitude goes foremost to

my research supervisor Prof Dr Ismail Jusoh who guided me well and patiently in

completing this dissertation I would also like to express appreciation to Dr Haji Idris Abu

Seman from MPOB for the opportunity and for allowing me in conducting my research at

the MPOB biodiversity area in Sungai Asap Belaga

Additionally special thanks to the SLUSE Program Coordinator Dr Tay Meng

Guan for all his hard work and supervision in the program and my examiner Dr Siti

Rubiah Zainudin for her kind advice I would also like to thank Mr Mohd Rizan Abdullah

for his help during field samplings

I am exceptionally grateful to my coursemates specifically to Doulos Nalau for his

help and support during the challenging period of completing this dissertation Thank you

as always

Subsequently an expression of gratitude to my family who have been so kind in

tolerating with my antics in the duration ofthe completion of this thesis Thank you

ii

Pusat Khidmat MakJumatAkademik UNIVERSm MALAYSIA SARAWAK

LIST OF CONTENTS

Page

DEC LARA TION

ACKNOWLEDGEMENT 11

LIST OF CONTENTS III

LIST OF TABLES v

LIST OF FIGURES VI

LIST OF PLATES VIII

LIST OF APPENDICES IX

LIST OF UNITS SYMBOLS AND ABBREVIATIONS X

ABSTRACT XII

CHAPTER 1 INTRODUCTION 1

11 Rationale of the study 3

12 Research objectives 3

CHAPTER 2 LITERATURE REVIEW 4

21 Physiography of Malaysia 4

21 1 Geography 5

212 GlillJate and rainfall 5

213 Forest types 6

214 Aboveground biomass and carbon stock 6

22 Approaches 7

23 Findings 16

24 Interpretation 18

iii

CHAPTER 3 METHODOLOGY 22

31 Study area 22rlt

32 Materials and methods 24

321 Data collection 24

322 Data analysis 27

A Aboveground biomass 27

B Carbon stocks 29

CHAPTER 4 RESULTS AND DISCUSSION 30

41 Aboveground biomass 30

411 Aboveground biomass by family 30

412 Aboveground biomass by species 33

413 Comparison of aboveground biomass between dipterocarp

and non-dipterocarp 35

414 Aboveground biomass in different diameter classes 39

415 Comparison with previous studies 41

42 Carbon stocks 43

421 Carbon stock by family 43

422 Carbon stock by species 45

423 CaIbon stock in different diameter classes 46 424 Comparison with previous studies 46

CHAPTER 5 CONCLUSION 48

REFERENCES 50

APPENDICES 56

iv

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 3: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

ACKNOWLEDGEMENT

To the glory of God who gave us the sun (Morris 1978)

In the completion of this Masters dissertation sincere gratitude goes foremost to

my research supervisor Prof Dr Ismail Jusoh who guided me well and patiently in

completing this dissertation I would also like to express appreciation to Dr Haji Idris Abu

Seman from MPOB for the opportunity and for allowing me in conducting my research at

the MPOB biodiversity area in Sungai Asap Belaga

Additionally special thanks to the SLUSE Program Coordinator Dr Tay Meng

Guan for all his hard work and supervision in the program and my examiner Dr Siti

Rubiah Zainudin for her kind advice I would also like to thank Mr Mohd Rizan Abdullah

for his help during field samplings

I am exceptionally grateful to my coursemates specifically to Doulos Nalau for his

help and support during the challenging period of completing this dissertation Thank you

as always

Subsequently an expression of gratitude to my family who have been so kind in

tolerating with my antics in the duration ofthe completion of this thesis Thank you

ii

Pusat Khidmat MakJumatAkademik UNIVERSm MALAYSIA SARAWAK

LIST OF CONTENTS

Page

DEC LARA TION

ACKNOWLEDGEMENT 11

LIST OF CONTENTS III

LIST OF TABLES v

LIST OF FIGURES VI

LIST OF PLATES VIII

LIST OF APPENDICES IX

LIST OF UNITS SYMBOLS AND ABBREVIATIONS X

ABSTRACT XII

CHAPTER 1 INTRODUCTION 1

11 Rationale of the study 3

12 Research objectives 3

CHAPTER 2 LITERATURE REVIEW 4

21 Physiography of Malaysia 4

21 1 Geography 5

212 GlillJate and rainfall 5

213 Forest types 6

214 Aboveground biomass and carbon stock 6

22 Approaches 7

23 Findings 16

24 Interpretation 18

iii

CHAPTER 3 METHODOLOGY 22

31 Study area 22rlt

32 Materials and methods 24

321 Data collection 24

322 Data analysis 27

A Aboveground biomass 27

B Carbon stocks 29

CHAPTER 4 RESULTS AND DISCUSSION 30

41 Aboveground biomass 30

411 Aboveground biomass by family 30

412 Aboveground biomass by species 33

413 Comparison of aboveground biomass between dipterocarp

and non-dipterocarp 35

414 Aboveground biomass in different diameter classes 39

415 Comparison with previous studies 41

42 Carbon stocks 43

421 Carbon stock by family 43

422 Carbon stock by species 45

423 CaIbon stock in different diameter classes 46 424 Comparison with previous studies 46

CHAPTER 5 CONCLUSION 48

REFERENCES 50

APPENDICES 56

iv

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 4: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

Pusat Khidmat MakJumatAkademik UNIVERSm MALAYSIA SARAWAK

LIST OF CONTENTS

Page

DEC LARA TION

ACKNOWLEDGEMENT 11

LIST OF CONTENTS III

LIST OF TABLES v

LIST OF FIGURES VI

LIST OF PLATES VIII

LIST OF APPENDICES IX

LIST OF UNITS SYMBOLS AND ABBREVIATIONS X

ABSTRACT XII

CHAPTER 1 INTRODUCTION 1

11 Rationale of the study 3

12 Research objectives 3

CHAPTER 2 LITERATURE REVIEW 4

21 Physiography of Malaysia 4

21 1 Geography 5

212 GlillJate and rainfall 5

213 Forest types 6

214 Aboveground biomass and carbon stock 6

22 Approaches 7

23 Findings 16

24 Interpretation 18

iii

CHAPTER 3 METHODOLOGY 22

31 Study area 22rlt

32 Materials and methods 24

321 Data collection 24

322 Data analysis 27

A Aboveground biomass 27

B Carbon stocks 29

CHAPTER 4 RESULTS AND DISCUSSION 30

41 Aboveground biomass 30

411 Aboveground biomass by family 30

412 Aboveground biomass by species 33

413 Comparison of aboveground biomass between dipterocarp

and non-dipterocarp 35

414 Aboveground biomass in different diameter classes 39

415 Comparison with previous studies 41

42 Carbon stocks 43

421 Carbon stock by family 43

422 Carbon stock by species 45

423 CaIbon stock in different diameter classes 46 424 Comparison with previous studies 46

CHAPTER 5 CONCLUSION 48

REFERENCES 50

APPENDICES 56

iv

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 5: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

CHAPTER 3 METHODOLOGY 22

31 Study area 22rlt

32 Materials and methods 24

321 Data collection 24

322 Data analysis 27

A Aboveground biomass 27

B Carbon stocks 29

CHAPTER 4 RESULTS AND DISCUSSION 30

41 Aboveground biomass 30

411 Aboveground biomass by family 30

412 Aboveground biomass by species 33

413 Comparison of aboveground biomass between dipterocarp

and non-dipterocarp 35

414 Aboveground biomass in different diameter classes 39

415 Comparison with previous studies 41

42 Carbon stocks 43

421 Carbon stock by family 43

422 Carbon stock by species 45

423 CaIbon stock in different diameter classes 46 424 Comparison with previous studies 46

CHAPTER 5 CONCLUSION 48

REFERENCES 50

APPENDICES 56

iv

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 6: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

I

LIST OF TABLES

Table Description Page

21 Total aboveground biomass and carbon stock values reported for a number 16

of forested land cover types

31 Location oftransects and coordinate of plots 25

32 The coefficients a and b respectively for different types of dependent 28

variable (Source Kenzo et aI 2009)

I

v

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 7: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

LIST OF FIGURES

Figure Description Page

31 Sungai Asap Sarawak (Source Google Earth 2013) 23

32 The area ofMPOB Belaga Research Station (Source MPOB 2009) 23

33 Flowchart of the methodology 24

34 Flowchart of sampling method 24

35 The first and the second transect at MPOB Belaga Research Station 26

(Source MPOB 2009)

36 Enlargement of inset in Figure 35 Location of plots within transects 27

(Source Google Earth 2013)

41 Above-ground biomass by family 32

42 Total aboveground stem and branch biomass of the top ten species 34

43 Biomass ofleaves of the ten top-most species 35

44 Percentage and value of the total aboveground biomass 36

45 Comparison of the aboveground biomass components between dipterocarp 37

and non-dipterocarp plants

46 Aboveground biomass of non-dipterocarp species 38

47 Aboveground biomass of dipterocarp species 38

48 Distribution of total aboveground biomass total basal area and tree 40

density in different diameter classe

49 Comparison of trend among aboveground biomass total basal area and 40

tree density in different diameter classes

410 Comparison of aboveground biomass from different studies 42

411 Carbon stock by family 44

vi

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 8: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

I

I 412 Carbon stocks of the ten top-most species 45

413 Distribution of carbon stock in different diameter classes 46

414 Carbon stock of different forest type 47

vii

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 9: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

LIST OF PLATE

Plate Description Page

31 MPOB Belaga Research Station office 22

I

viii

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 10: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

I

LIST OF APPENDICES

Appendix Description Page

A Aboveground biomass and carbon stock by family 56

B Aboveground biomass and carbon stock by species 58

ix

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 11: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

LIST OF UNITS SYMBOLS AND ABBREVIATIONS

percent

0 degree

degC degree Celsius

cm centimetre

g cmshy3 gram per cubic centimetre

ha hectare

kg kilogram

km2 kilometre square

m meter

M g ha- I Megagram per hectare

Mglha Megagram per hectare

m 2 meter square

mm millimetre

a coefficients

b coefficients

CF carbon fraction

CO2 carbon dioxide

Csock carbon stock

HI equations derived for height estimates

H2 equations derived for height estimates

Wb Branch biomass (kg)

WD wood density in g cm-3

WI Leaves biomass (kg)

x

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 12: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

I

Ws

x

y

y

y

Ybranch

Yleaf

Ystem

Ytotal

(l

p

p

PO5

AGB

DBH

GAP

GHG

H

IVI

MPOB

NIR

SG

TAGB

UNFCCC

Stem biomass (kg)

diameter breast height (cm)

total tree biomass (kg)

aboveground biomass (kg)

biomass (kg)

aboveground biomass of branch

aboveground biomass of leaf

aboveground biomass of stem

total aboveground biomass of tree

slope coefficient of the regression for mixed species forest

slope coefficient of the regression for mixed species forest

refers to wood density (g cm-2)

wood density is 05 g cm-2

aboveground biomass

diameter breast height

good agricultural practice

green house gas

height

Important Value Index

Malaysian Palm Oil Board

National Inventory Reports

specific gravity

total aboveground biomass

United Nations Framework Convention on Climate Change

xi

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 13: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

Aboveground tree biomass and carbon stock of logged-over forest in Sungai Asap

Belaga

Melissa Melody Leduning

Master of Environmental Science

Faculty of Science and Technology

Universiti Malaysia Sarawak

ABSTRACT

(Global warming and climate change are intermittent issues referring to increment in average global

temperatures These are chiefly caused by increases in greenhouse gas (GHG) viz carbon dioxide Malaysian

Palm Oil Board (MPOB) had set up a research station to be developed as a model plantation located in

Belaga to address the issue on sustainability biodiversity and enhanced green house gas emissions (GHG)

Bence a scientific study to determine the aboveground biomass and carbon stock of the logged-over forest in

Sungai Asap Belaga was conductej The methods involved in determining the aboveground biomass and

carbon stock was firstly (i) collection of data at Sungai Asap Belaga followed by (ii) analysis of data which

involves the estimation of aboveground biomass through allometry equation Finally the carbon stock was

estimated through conversion of the aboveground biomass value A total of 187 tree species (46 families)

were identified within the 22 quadrates of20 m x 20 m The estimated above ground biomass of the area was

17530 M g hamiddot 1 where the species with the highest amount of aboveground biomass was Shorea parvifolia

(Dipterocarpaceae) with 1588 M g ha- I followed by Macaranga triloba (Euphorbiaceae) with 1432 M g ha-

I and Dipterocarplls aClltangllllls at 1220 M g ha- I The estimation of carbon stock contained in the MPOB

Research Station was 8239 M g ha- I of carbon stocks In tropical forests biomass and carbon content are

generally high which reflects their influence on the global carbon cycle Therefore the aboveground biomass

and carbon stock value of the logged-over forest in Sungai Asap Belaga have large potential for the

reduction ofGHG through proper conservation and sustainable management

Keywords Aboveground biomass carbon stock logged-over forest

xii

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 14: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

ABSTRAK

Pemanasan global dan perubahan iklim merupakan isu yang saling berkait merujuk kepada peningkatan suhu

purala global Punca utama fenomena ini ialah peningkatan kandungan gas rumah hijau seperti karbon

dioksida Lembaga Minyak Sawit Malaysia (MPOB) telah menubuhkan sebuah stesen penyelidikan untuk

dibangunkan sebagai perladangan contoh yang terletak di Belaga bagi menangani isu tentang kemapanan

pembebasan gas rumah hijau dan biodiversiti Oleh itu kajian saintifik bagi menentukan bioj isim atas tanah

dan stok karbon hutan yang telah dibalak telah dijalankan Kaedah menentukan biojisim atas tanah dan stok

karbon dimulakan dengan (i) kutipan data pokok-pokok di Sungai Asap Belaga diikuti oleh (ii) analisis data

yang melibatkan anggaran biojisim atas tanah melalui rumus alometri Akhir sekali stok karbon akan

dianggar melalui penukaran data biojisim atas tanah Sejumlah 187 spesies pokok (46 famili) telah dikenal

pasti dalam 22 kuadrat berukuran 20 m x 20 m Biojisim atas tanah dianggarkan sebanyak 17530 M g hamiddot di

mana spesis yang menunjukkan jumlah biojisim atas tanah yang tertinggi ialah Shorea panifoiia

(Oiplerocarpaceae) dengan 1588 M g hamiddot diikuti oleh Macaranga triloba (Euphorbiaceae) dengan 1432 M

g hamiddot dan Dipterocarplls aClitangllius pada 1220 M g hamiddot Stok karbon yang terkandung di Stesen

Penyelidikan MPOB berjumlah sebanyak 8239 M g hamiddot Di hutan tropika biojisim dan kandungan karbon

I~mnya tinggi menunjukkan pengaruhnya terhadapkitaran karbon global Oleh itu nilai biojisim atas tanah

dan stok karbon dalam hutan di Sungai Asap Belaga mempunyai potensi yang besar dalam pengurangan gas

rumah hijau melalui pemuliharaan dan pengurusan mapan

Kala kunci Biojisim tanah stok karbon hutan yang telah dibalak

xiii

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 15: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

CHAPTER 1

INTRODUCTION

Belaga District is located in Kapit and Sungai Asap is a small town situated in Belaga In

view of the importance of Sarawak MPOB set up the research station located in Belaga to

address the issue on sustainability biodiversity and green house gas emissions (GHG) The

research station is being developed as a model plantation poised to be the first of its kind

in the country which focuses on good agricultural practice (GAP) (Wahid 2008) An area

of about 120 ha was allocated to Malaysian Palm Oil Berhad (MPOB) for establishment of

oil palm estate in Sungai Asap Belaga MPOB is steadfast in setting up an oil palm

plantation that merges oil palm plantation with conservation areas Its oil palm plantation

and conservation area are largely secondary forest and logged-over mixed dipterocarp

forests (Jusoh 2012) The conversion of forest to oil palm plantations affects the

environment directly or indirectly (Ahmad Ali et at 2012)

The tropical forests in Borneo on average have an aboveground biomass (AGB) about

60 higher compared to similar eco-systems in other regions (Slik et at 20 I 0) Forest

biomass is an important active participant in the global carbon cycle (Kueh et at 2013)

Biomass estimation for forest is an essential part of tlie process in assessing carbon stocks

in tropical forests (Yoneda et at 1994) which detennines probable carbon emission The

potential carbon emission could be linked to the change of the biomass regionally which is

a crucial component of climate change (Lu et at 2002)

1

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 16: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

One of the most imperative environmental issues in this millennium is climate change

(Lasco et ai 2006) Therefore there is a surge in the researches on climate change and

global warming within the past decade (Jepsen 2006) due to the awareness on these issues

which emphasised on the environmental aspects such as deforestation (Geist and Lambin

2002) land cover and land use change (Veldkamp and Verburg 2004) Through

management of the current carbon storage increment of carbon sinks and the utilization of

alternative fuels such as wood products instead of fossil fuels these shows how tropical

forests have the prevalent potential to mitigate climate change (Khun et aI 2012)

There are not many studies that have been conducted on biomass estimation and

carbon allocation to parts of individual tree species in Sarawak The carbon stock

as essment is still poor and little is known about the carbon sequestration potential of the

logged-over forest

Currently allometric equations derived from tropical pnmary forest trees are

largely used to estimate the forest biomass of tropical regions (Chave et ai 2005) Kenzo

et al (2009) have developed an allometric relationship between tree size variables and leaf

branch stem and total aboveground biomass in logged- over tropical rainforests with

different soil conditions in Sarawak Malaysia This allometric equation is suitable to

determine the aboveground biomass of the logged-over forest in Sungai Asap Sarawak

which consequently estimates the carbon stock of the logged-over forest in Sungai Asap

2

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 17: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

11 Rationale of the study

The importance of this research is obtaining field data on carbon stock in Sungai Asap

logged-over forests which are not available but as stated by Nsabimana (2009) such data

as carbon storage annual carbon increment in biomass and litter production are necessary

for calculating the forest carbon balance predicting carbon emissions from the forest

conversion to cleared land and predicting carbon sequestration potentials for future

researches These data are also needed to support policy negotiations in relation to carbon

offset and carbon sequestration market through reforestation projects and to estimate

sources and sinks of greenhouse gases (Nsabimana 2009) Measurement of aboveground

biomass is also the only way to estimate the value of forests as carbon sinks Therefore it

is essential to estimate the aboveground biomass of the logged-over forest ofSungai Asap

12 Research objectives

The two main objectives executed to accomplish this research are

(i) To determine the aboveground biomass of logged-over forest III Sungai Asap

Belaga

(ii) To estimate the carbon stock of the logged-over forest in Sungai Asap Belaga

3

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 18: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

CHAPTER 2

LITERATURE REVIEW

This chapter reassess the research and techniques of aboveground biomass and carbon

stock estimation in Malaysia the country where the current study is conducted The review

compared and discussed the similarities and differences between the previous studies

conducted It is divided into three main sections namely the approaches and secondly the

findings Finally it gives an overview of the interpretations derived from the past

researches

21 Pbysiography of Malaysia

The location of Malaysia being entirely in the equatorial zone bestowed it with a suitable

climate and quantity of rainfall to sustain tropical forests The existence of rainforests

supplies Malaysia with considerable amount of biomass and carbon stocks Therefore

studies estimating and determining the aboveground biomass and carbon stocks in

Malaysia is important is important in several different ways firstly to more fully explain

the degree to which human activity may contribute to global climate change it is necessary

to clarify elements of the global carbon cycle (Drake 2001) Secondly biomass represents

the sum of all biological material in a given area and is needed for many forestry and

ecological purposes (Drake 200 I)

4

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 19: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

PU~Bt Khidnrd Makl~Akademik UNIVERSm MALAYSIA SAItAWAK

211 Geography

Malaysia covers an area of about 329847 km2 occupying Peninsular Malaysia (Abdul

Malik et al 2013) which lies on the southern shores of the Asian land mass and Sabah

and Sarawak in the northwestern coastal of Borneo Island Separating the two regions are

about 720 km of the South China Sea (WWF Malaysia 1994) Peninsular Malaysia

covering 132090 km2 (Abdul Malik et al 2013) has its land frontier with Thailand to the

north and is connected to Singapore by a causeway in the south (Framji et al 1982) East

Malaysia composed of Sabah and Sarawak covering 198847 km2 (Abdul Malik et al

2013) border the territory of Indonesias Kalimantan and has land frontiers with the two

enclaves which make up Brunei (Framji et al 1982)

212 Climate and rainfall

Malaysia lies near the Equator between latitude 1 deg and 7deg North and between longitude

100deg and 119deg East (Framji et al 1982) The climate is governed by the northeast and

southwest monsoons (FAO 2011) The Northeast monsoon is dominant from November to

March bringing moisture and heavy rain (Ismail 2010) It also causes the wettest season

in Sabah and Sarawak Between June and September the Southwest monsoon winds blow

(Ismail 2010) and is a drier period for the whole country The period between these two

monsoons April is marked by heavy rainfall (F AO 2011)

The characteristic features of the climate of Malaysia are of uniform temperature

ranging from 23degC to 33degC high humidity and the mean monthly relative humidity is

5

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 20: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

between 70 to 90 and copious rainfall The average rainfall is 2400 mm for Peninsular

Malaysia 3800 mm for Sarawak and 2600 mm for Sabah (Arnirzudi 2010)

213 Forest types

Different types of forests can be found in the three regions in Malaysia Peninsular Sabah

and Sarawak In general the vegetation changes with altitude from coastal beach forest and

mangrove to lowland dipterocarp forest hill dipterocarp forest and eventually montane

forest (Abdul Malik et al 2013) Malaysia reports its forests according to three forest

types dry inland forest peat swamp forest and mangrove forest (Blaser et aI 2011)

Malaysias forests are generally moist tropical forests those in the lowlands and lower

parts of the hills being dominated by Dipterocarpaceae (lTTO 2006) Of the estimated

171 million hectares of dipterocarp forests 540 million hectares are in Peninsular

Malaysia 792 million hectares in Sarawak and 383 million hectares in Sabah (lTTO

2006) There are also 154 million hectares of peat swamp forest 112 million hectares of

which are in Sarawak Mangrove forests cover about 567000 hectares more than half are

in Sabah (lTTO 2006)

21 4 Aboveground biomass and carbon stock

The studies on carbon sequestration have been focusing on and expressmg the

sequestration in terms of biomass and carbon stock (Baishya et al 2009) In terms of

biomass in the natural forests at the end of 2005 Malaysia had a total of 478091 million

tonnes of above-ground biomass while below-ground biomass and dead wood biomass

were estimated to be 114742 million tonnes and 88925 million tonnes respectively

6

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 21: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

(Chiew 2009) The total carbon stock in the natural forests in Malaysia at the end of 2005

was estimated to be 344233 million tonnes with the Peninsula Sabah and Sarawak

having 113871 million tonnes 75163 million tonnes and 155199 million tonnes

respectively (Chiew 2009)

The potential of tropical forests for increased carbon sequestration capability can be

assessed either through the amount of carbon stored or estimating the annual carbon

sequestration rate (Iverson et al 1993) Various methods attempt to use biomass estimates

to quantify terrestrial pools of carbon Since biomass is largely carbon it serves as a useful

predictor of the amount of carbon in terrestrial pools (Brown 1997)

22 Approaches

Most of the studies on above-ground biomass and carbon stocks conducted in Malaysia

were assessed through in situ measurements such as the studies by Jepsen (2006) Chandra

et al (20 II) and Saner et al (2012) Several studies combined field survey with remote

sensing data for instance the researches by Tangki and Chappell (2008) Morel et al

(2011 ) and Singh (2011) Okuda et al (2004) estimated the above-ground biomass in

logged and primary lowland forest through field sampling aerial photographs remote

sensing data and modelling

Field sampling conducted usually begins with the establishment of plots (Okuda et

aI 2004 Jepsen 2006 Tangki and Chappell 2008 Chandra et al 2011 Singh 2012

Kueh et al 2013) or line transects (Morel et al 2011 Saner et al 2012) Followed by the

7

=

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 22: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

measurements of diameter breast height (DBH) identifications of species and estimation

of height of the trees studied

Traditional methods which depend on field surveys within the study plots such as

measurement of DBH or tree height are important in estimating biomass in a forest Field

surveys undoubtedly produce the most accurate biomass information but are also the most

labour intensive and time consuming The limitation of these traditional methods of

estimating biomass lies within the statistical extrapolations made from the samples to the

plot and the bias in the selection of representative samples (Yava~li 2012) However these

statistiaal errors are acknowledged and are considered as tolerable (Yava~li 2012)

Yava~li (2012) claims that the use of remote sensing method is the most practical

and cost effective alternative to acquire data over larger areas The advantages of remotely

sensed data over traditional field inventory methods for biomass estimation were indicated

by a number of publications (Lu et al 2002) In a study by Morel et al (2011) utilizing

radar system it was noteworthy that plot average height and dominant height were not well

correlated with biomass nor was dominant height correlated with the synthetic aperture

radar (SAR) backscatter for that reason this study would conclude that efforts to model

height from SAR data as a proxy for aboveground biomass may be difficult Therefore

surveys of ground elevation are a prerequisite for the calculation of both canopy height and

individual tree heights because the latter measurements are based on aerial triangulation

(Okuda et al 2004)

Researchers have developed indirect methods to estimate the above ground biomass

(Yav~li 2012) The most common approach uses allometric equations which can be used

8

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 23: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

to link difficult to measure variables such as volume or biomass to easy-to-measure tree

characteristics diameter or height for example with statistically determined parameters

(Phuong et al 2012) The broadest definition of allometry is the linear or non-linear

correlation between increases in tree dimensions (Picard et al 2012) Indisputably the

frequently used mathematical model

following allometric equation (Brown

for

1997)

estimating tree biomass in Malaysia is the

Y = expmiddot2134 +2530 In(DBH) (21)

where

Y

DBH

total tree biomass (kg)

diameter breast height (m)

Equation 21 was utilized in the study of Jepsen (2006) Tangki and Chappell

(2008) and Moral et al (2011) Suitable to the study region ofTangki and Chappell (2008)

which is located 225 km2 within the Ulu Segama Forest Reserve Sabah in Northern

Borneo the biomass was calculated using Equation 21 which was derived from inventory

data collected in the moist tropics including dipterocarps in Borneo While this is the only

allometric equation used by Tangki and Chappell (2008) besides using remotely sensed

data to derive mean radiances for each of the 10 regions for correlation with the areal

averages of biomass density derived from the enumeration plots Jepsen (2006) and Morel

et al (2011) used it alongside several other equations to enumerate the aboveground

biomass of their study site

9

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10

Page 24: AND CARBON LOGGED-OVER FOREST IN SUNGAI ASAP, … Tree Biomass and Carbon Stock... · and carbon stock value of the logged-over forest in Sungai Asap, Belaga have large potential

Jepsen (2006) research combines in situ sampled biometric data and quantitative

data from structured interviews to assess biomass stocks and biomass accumulation rates

for secondary regrowth following hill rice cultivation The results from Jepsen (2006)

study were based on an average of the equation outputs from Brown (1997) (Equation 21)

Yamakura et al (1986) (Equation 22 Equation 23 and Equation 24) and Uhl et al

(1988) (Equation 25 and Equation 26)

(2 2)

Wb =01192(W )lo59 (23) s

(24)

where

Ws Stem biomass (kg)

Wb Branch biomass (kg)

WI Leaves biomass (kg)

For height ~ 2 m on abandoned pastures

In Y = -217 + 102 In(DBH)2 + 039 In(H) (25)

For DBH gt 10 cm in forest and precipitation of 1750 mm yea(l

In Y = 0991 InlaquoDBH)2 x H x SG) - 2968 (2 6)

10