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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
(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
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
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
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