Low Carbon Economy, 2013, 4, 55-67
Published Online December 2013 (http://www.scirp.org/journal/lce)
http://dx.doi.org/10.4236/lce.2013.44A006
Open Access LCE
55
Reducing Carbon Emissions through Improved Forest
Management in Cambodia
Nophea Sasaki1, Issei Abe1, Vathana Khun2, Somanta Chan1, Hiroshi Ninomiya1, Kimsun Chheng2
1Graduate School of Applied Informatics, University of Hyogo, Kobe, Japan; 2Forestry Administration, Phnom Penh, Cambodia.
Received October 18th, 2013; revised November 12th, 2013; accepted November 20th, 2013
Copyright © 2013 Nophea Sasaki et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Carbon emissions from selectively logged forests in the tropics are strongly affected by logging practices. Although
tropical forests are mainly managed under the concession system, only a handful of studies were done to assess the
impact of logging practices on emission reductions and future timber supply. In this report, carbon stocks, timber supply,
and carbon emission reductions under conventional logging (CVL), reduced-impact logging (RIL), and RIL with
special silvicultural treatments (RIL+) were assessed in 3.4 million ha of concession forests for a 55-year project time
span. Carbon emissions under a 25-year CVL practiced in Cambodia were estimated at 12.4 TgCO2 year−1 for 55 years.
We then tested four cutting cycles of selective logging and our results suggest that a 45-year selective cutting cycle was
appropriate for managing concession forests in Cambodia in terms of maintaining commercial timber supply and re-
ducing carbon emissions. By considering RIL or RIL+ as a new logging practice for improving forest management in
the tropics, carbon credits from selective logging in Cambodia were estimated at 6.2 - 7.9 TgCO2 or about $31.0 - 39.5
million annually if carbon is priced at $5. It is concluded that RIL or RIL+ should be adopted for “sustainable manage-
ment of forests” element of the REDD+ scheme.
Keywords: Carbon Credits; Forest Inventory; Liberation Treatment; Reduced Impact Logging; Timber Concession;
Wood Supply
1. Introduction
The anticipated REDD+ (reducing emissions from de-
forestation and forest degradation, forest conservation,
sustainable forest management, and enhancement of
carbon sinks) agreements have attracted increasing re-
search to estimate the carbon emission reductions and the
associated costs of implementing the specified manage-
ment activities, and how such emission reductions can be
monitored and verified. Recent data suggest that between
2000 and 2009, land use change (mostly tropical defor-
estation) was responsible for the release of 1.1 - 2.7 PgC
(about 4 billion tonnes CO2) [1,2]. Kindermann et al. [3]
suggest that 50% of carbon emissions from tropical de-
forestation could be halted at carbon prices of $5.20 -
38.15 per MgCO2 (tonne CO2) varying by continents.
Sasaki and Yoshimoto [4] focused on the opportunity
costs of managing tropical forests versus clearing these
forests to develop industrial plantations, and suggested
that managing tropical forests for timber production un-
der the REDD+ mechanism would be preferable because
of the huge potential revenues and other benefits from
the ecosystem services provided by these forests. Toni [5]
suggests the need for REDD+ decentralization in order to
effectively manage the revenues from REDD+ scheme
while protecting tropical forests. Although previous stud-
ies clarified the fundamental basis for understanding the
potential of REDD+, achieving carbon emission reduc-
tions and maintaining timber supply from the selectively
logged forests are still debatable [6,7].
Furthermore, sustained global efforts to mitigating
climate change through the REDD+ scheme were evident
at the 17th and 18th Conference of the Parties (COP17 and
COP18) of the United Nations Framework Convention
on Climate Change (UNFCCC) held in Durban, South
Africa and Doha, Qatar in 2011 and 2012 as good pro-
gress on setting up reference emission levels (REL), de-
fining the measurements of emission reductions from
forestry initiatives, and safeguarding the social and envi-
ronmental benefits was achieved. Despite such achieve-
ments, estimation of carbon emissions and reduced emis-

Reducing Carbon Emissions through Improved Forest Management in Cambodia 56
sions, especially in the “sustainable management of for-
ests or SFM” element of REDD+ scheme remained to be
addressed.
SFM is an important component because it helps stabi-
lize the timber market, maintains wood supply from
tropical forests to meet increasing demands for wood
while generating employment and revenues for owners of
the forest resource or for governments in developing
countries. SFM is strongly affected by logging practices
[8-11], and logging practices for commercial timber
production are usually carried out in production forests
under the forest concession system. As logging practices
resulted in various degrees of logging damages and wood
wastes, they strongly affect the end-use wood supply and
carbon stocks in the forests [12-14]. Therefore, it is im-
portant to determine the appropriate logging practice that
is sustainable and economical in terms of continuous
flow of wood products and other forest ecosystem ser-
vices. Such practice is obviously important for achieving
the SFM element of the REDD+ scheme.
To better inform the policy makers as well as climate
change negotiators, there is a critical need for developing
methods for estimating the carbon emissions with and
without the REDD+ activities as well as emission reduc-
tions resulted from the implementation of SFM. Until
recently, only a handful of studies were carried at re-
gional [12] and global [6,7] to estimate timber supply
and carbon retention in selectively logged forests where
logging practices affect both timber supply and carbon
stocks. In this paper, we aim to estimate the potentials of
carbon emission reductions from managing concession
forests in Cambodia using available models.
2. Study Methods and Materials
2.1. Cambodia and REDD+
Cambodia and REDD+: Cambodia ratified the UNFC-
CC in 1995 and acceded to its Kyoto Protocol in 2002. In
addition to contributing to emission reduction efforts in
energy sector, Cambodian government has put strong
commitment on managing forests under the REDD+
scheme [15]. A REDD+ pilot project in Oddar Meanchey
province was awarded Dual Gold Validation by the Cli-
mate, Community & Biodiversity Standard and the Veri-
fied Carbon Standard. Project Design Document for an-
other REDD+ project in Seima Protected Forests, Mon-
dulkiri province was submitted to a carbon standard for
validation. In 2011, the Japanese Ministry of Environ-
ment and Ministry of Economy, Trade and Industry pro-
vided subsidies, respectively to Conservation Interna-
tional and Japan Forest Technical Association for two
feasibility study projects on REDD+ in Prey Long
(Kampong Thom province) and Phnom Tbeng Protected
Forests (Preah Vihear province), Cambodia. The Forestry
and Forest Products Research Institute (Japan) in col-
laboration with Cambodia’s Forestry Administration has
conducted research on developing Monitoring, Reporting
and Verification (MRV) system for REDD+ projects in
Cambodia since 2010. All these projects showed in-
creasing interests in REDD+ projects in Cambodia. Nev-
ertheless, these projects focused only on protected and
community forests although concession forests still ac-
count for 30% of the total forest cover in Cambodia. This
study is the first attempt to introduce project ideas for
managing the production forests under the REDD+
scheme’s SFM element.
Forests and concession forests in Cambodia: FAO
[16] categorized the world’s forests according to their
functions. They are forests for production (30% of the
global forests), protection of soil and water (8%), con-
servation of biodiversity (12%), social services (4%),
multiple use (24%), other (7%), and unknown (16%)
functions. Production forests are where logging for com-
mercial timber production is allowed. Production forests
in the tropics are commonly managed under forest con-
cession system, a system that government as forest re-
source owner issues logging license to logging compa-
nies i.e. forest concessionaire to harvest the timber as per
guidelines and laws of the countries in concerns. In 2010,
Cambodia has a total forest cover of 10.4 million ha or
about 57.1% of the country’s total land area [17]. Defor-
estation rate was estimated at about 0.7% between 1973
and 2003 [13], and about 0.8% between 2002 and 2010
[17]. There are three major forest types in Cambodia
namely evergreen, semi-evergreen, and deciduous forests.
Other forest types include inundated and mangrove for-
ests, and forest plantations but they represent only a
small proportion of the total forest cover. Evergreen,
semi-evergreen, and deciduous forests annually lost
about 0.7%, 1.5%, and 0.9%, respectively between 2002
and 2010 [17]. Based on their functions, the 10.4 million
of forests are classified to concession (32.7%), protection
(43.3%), and conversion forests (24.0%), respectively
(Figure 1). The 3.4 million ha of concession forests are
under the jurisdiction of Forestry Administration of the
Ministry of Agriculture, Forestry, and Fisheries (MAFF).
Protection forests include 1.4 million ha of forests under
the jurisdiction of the FA and 3.1 million ha of protected
areas under the jurisdiction of the Ministry of Environ-
ment, and mangrove and inundated forests under the ju-
risdiction of Fisheries Administration. Conversion forests
are under jurisdiction of MAFF. Large-scale logging by
forest concessionaires was suspended in late 2001 due to
concern over indiscriminate logging and rapid forest
degradation. Despite logging ban, small-scale logging is
still going on to harvest timber to supply the domestic
demands in Cambodia. A permanent logging ban would
not solve the problems of forest protection and wood
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia
Open Access LCE
57
Figure 1. Location map of forest land uses (including forest concessions) in Cambodia in 2008. Source: Courtesy of Cambo-
dia’s Forestry Administration.
2.2. Logging Scenarios: CVL, RIL, RIL+ shortage for growing population and economic develop-
ments because if wood demand is increasing, it is likely
that timber price will also be increasing. At a point in time
when timber price is high enough comparable to car-
bon-based revenues from protecting, logging (either legal
or illegal) can no longer be controlled. Therefore, the
most appropriate alternative is to continue logging but
under a sound management system that can ensure long-
term sustainability of wood supply while reducing carbon
emissions from unsustainable management practices. As
concessions in Cambodia were granted under a long-term
contract, we assume the area of forest concessions (3.4
million ha) in Cambodia remains unchanged during the
timeframe for this study (corresponding to 55-year pro-
ject time span). Prior to logging ban, a 25-year selective
cutting cycle was used for managing concession forests
in Cambodia. We therefore use 25-year cutting cycle as
our business-as-usual or baseline cutting cycle.
Most logging practices in tropical are carried out with
little or without proper management plan and untrained
staff [7,18]. Such logging is termed here as conventional
logging (CVL). CVL scenario refers to logging practices
that require neither formal planning nor the use of trained
staff. CVL causes large amounts of damage to the resid-
ual stand and wastes large amounts of wood both in the
forest and at sawmill or pulp and paper plant [19]. In
contrast, RIL and RIL+ scenarios are referred to logging
scenario using reduced-impact logging (RIL) and RIL+
(plus), which includes RIL and a “liberation” treatment.
RIL is a logging practice that involves proper training of
the logging staff; well-defined logging plans; careful
planning of main, secondary, and feeder road locations
before harvesting and extraction; the use of directional
felling; cutting stumps low to the ground; minimizing
wood waste caused by felling, skidding, and road tran-
sportation; minimizing road and trail widths; minimizing
landing size and maximizing landing spacing; minimiz-
ing ground disturbance; paying attention to forest aes-
thetics; and minimizing damage to the residual stand.
Sasaki and Putz [10] and Holmes et al. [19] provide more
details about RIL practices. RIL is a promising logging
practice for managing tropical forests [7,11], because it
involves careful planning to minimize waste and adverse
Major commercial tree species being harvested in
Cambodia include Chorchong (in local name) (Shorea
vulgaris of Dipterocarpaceae), Lumboi (Shorea sp., Dip-
ter ocarpaceae), Phdeak (Anisoptera glabra, Dipterocar-
paceae), Chheutieal (Dipterocarpus costatus, Diptero-
carpaceae), Krakos (Sindora conchinchinnensis, Caesal-
pinaceae), and Dauchem (Tarrietia javanica, Sterculi-
aceae). DHB (diameter at breast height) for all these trees
must be greater the diameter limit for harvest.

Reducing Carbon Emissions through Improved Forest Management in Cambodia 58
impacts on the residual stand. RIL+ is exactly the same
as RIL, except that it additionally adopts a liberation sil-
vicultural treatment, in which unwanted defective trees
that are competing with future crop trees are girdled to
kill them. By so doing, forest growth can be accelerated.
Recent studies suggests that by reducing the competition
from unwanted trees, growth rates of the crop trees can
be increased by 20% to 60% compared with the growth
rate in forests where only RIL is implemented [20,21].
For this study, a 50% increase rate was assumed for
RIL+.
2.3. Logging Impact on Carbon Stocks
Using same approach of Sasaki et al. [6], aboveground
carbon stocks in concession forests in Cambodia under
the CVL, RIL, and RIL+ scenarios can be derived by:
  
i
ii
dCS tMAILM tHtBEF
dt  


(1)
 
i
MH
i
c
CS t
ff
Ht 1rTBEF



(2)
 
i
LM tH t
i
 
i
(3)
where:
CSi(t): aboveground carbon stock (MgC ha−1) under
logging system i (i is CVL, RIL, or RIL+) in year t. For-
est management was assumed to start in 2014 and simu-
lation is run for 55 years from 2014.
MAI: mean annual increment (MgC ha−1 year−1).
LMi(t): carbon in dead trees lost due to logging dam-
ages (Mg C ha−1·year−1).
αi: Rate of logging damages to residual stands in pro-
portional to Hi(t).
Hi(t): harvested carbon (Mg C ha−1·year−1).
BEF: biomass expansion factor. BEF = 1.74 [22].
fM: proportion of mature trees. Defined as trees having
DBH ≥ DBH limit for harvesting in Cambodia. Propor-
tion of standing volume of mature trees to total stand
volume was estimated at 52.7% - 56.3% with a mean of
54.1% in Kampong Thom, Cambodia [23]. For this study,
54% (fM = 0.54) was assumed.
fH: legal rate of harvesting permitted by the govern-
ment. Sub-decree 050 of the MAFF specifies that only
30% - 50% of the mature trees can be harvested depend-
ing on how dense the forest is [24]. For this study, 30%
of the mature trees (fH = 0.3) was assumed because Cam-
bodia’s forests have been logged to various degrees since
late 1980s.
r: rate of illegal logging. During 1997 and 1998, rate
of illegal logging was estimated at about 67% of the total
harvested wood [25]. This rate is comparable to rates in
other countries in the tropics such as 50% - 88% in In-
donesia [26,27], up to 70% in Ghana [28], 50% in Cam-
eroon and up to 50% - 75% in the Brazilian Amazon [29].
As Cambodia became a peaceful country and the entire
country is governed by one government, it is likely that
rate of illegal logging has decreased since 1998. For this
study, 50% rate (r = 0.5) was therefore assumed. As ille-
gal logging is very sensitive political issue in Cambodia,
this assumption should be revised when data become
available.
Tc: cutting cycle (years). Cambodia adopted a 25-year
cutting cycle, and this cycle is used here as a baseline cy-
cle. To determine an appropriate logging cycle for man-
aging concession forests in Cambodia, three more cutting
cycles, namely 35-year, 45-year, and 55-year were tested.
Initial value for CS(t) in Equation (1) is 92.7 MgC ha−1
based on the weighted average of forest area by type
(evergreen, semi-evergreen and deciduous forests) in
2010 and stand volumes published in Kim Phat et al.
[23,30,31], Kao and Iida [32], and Chheng et al. [33].
Little study on Mean Annual Increment (MAI) has been
done in Cambodia. Top et al. [34] estimated the incre-
ment of aboveground biomass of mostly small trees in 32
sample plots at 4.77 Mg ha−1·year−1 (4.77 × 0.5 carbon
content in dry wood = 2.4 MgC ha−1) between 1998 and
2000 in Kampong Them province, Cambodia. Long-term
studies from permanent sample plots suggested that
MAIs in tropical Amazon forests range from 0.64 tC
ha−1·year−1 [35] to 0.72 MgC [36]. Previous study in
Cambodia put the MAI of the natural undisturbed forests
at 0.33 m3 ha−1·year−1 or about 0.2 MgC of aboveground
carbon [37]. In Indonesia, MAI in commercially logged
forests was 1.13 m3 ha−1·year−1 or about 0.56 MgC of
aboveground carbon [38]. Due to the lack of data on
MAIs in natural forests in neighboring countries for
comparison, it is assumed that the MAI in production
forests in Cambodia is 1 m3·ha−1·year−1 or 0.5 MgC
(MAI = 0.5) under CVL and RIL, and 0.75 MgC under
RIL+ (50% increase in growth rate).
A recent study on logging damages to stand volume
under a RIL experiment in Cambodia found that 18% -
20% of the stand volume were damaged, of which about
8.3% (12.0 m3 ha−1 or 5.9 MgC ha−1) died immediately
after logging [33]. No study on logging damages under
CVL was available in Cambodia. A collection of logging
damages in Brazil, Malaysia, and Indonesia [10] sug-
gested that logging damages under RIL were about 30%
lower than that under the CVL. Therefore, the 8.3% un-
der the RIL reported by Chheng et al. [33] above is
equivalent to 27.7% [27.7 = 8.3/0.3] under the CVL or
40.0 m3 ha−1 per a 25-year cycle or about 1.6 m3 ha−1
year−1 (based on data of stand volume in [33]. Including
50% illegal logging rate gave the total harvested at 3.2
m3 ha−1 year−1 (3.2 = 1.6/0.5).
Because logging damages under both CVL and RIL
were strongly affected by harvesting density [39], dam-
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia
Open Access LCE
59
i
i
ages to stand volume here were set to equate to the har-
vesting density (α = 1) with the initial value of 1 MgC or
3.7 m3·ha−1·year−1 [3.7 = 1/(0.57 × 0.5)], which is com-
parable to that derived from Chheng et al. [33] under the
CVL and 50% reduction (α = 0.5) under RIL and RIL+.
Aboveground carbon was derived using approach devel-
oped by Brown [22], which aboveground carbon is the
product of stand volume, wood density (0.57), BEF (1.74)
and carbon content in dry wood (0.5).
tree felling, log skidding and/or transporting under log-
ging practice i (CVL, RIL, or RIL+).
No study on this proportion was conducted in Cambo-
dia. The proportion of unusable wood was estimated at
24.7%, 20.0%, 46.2%, and 24.0% under CVL but was
reduced 14.5%, 0%, to 26.2%, and 8% under RIL, re-
spectively in East Kalimantan, Indonesia [14], Sarawak,
Malaysia [41], East Kalimantan [42], and Eastern Ama-
zon [19]. For this study, it is assumed at 30% and 10%
under CVL and RIL (the latter includes RIL and RIL+),
respectively.
Parameters and initial values for Equations (1) and (2)
are provided in Table 1.
ai: wood processing inefficiency (lost wood due to
processing) under system i. Wood processing efficiency
in Cambodia under CVL was reported at 35% - 51% [40].
For this study, inefficient rate was assumed that 50%
under CVL and 40% under RIL (including RIL+).
2.4. Wood Products Model
Managing concession forests is important for commercial
timber supply and improving forest ecosystems. Under
CVL, RIL, and RIL+, we calculated the quantities of the
following wood components: wood products (WP), wood
waste (WAS), logging mortality (LM), end-use wood
products (EWP), and end-use wood waste at sawmill or
pulp and paper mill (EWAS). To do so, we used the fol-
lowing equations from Sasaki et al. [6]:
The units of WP, WAS, LM, EWP, and EWAS are
MgC ha–1·year–1, otherwise stated.
2.5. Wood Harvesting and Supply
Regardless how much timber is harvested in the forests,
final wood products (i.e. EWP) ready to be used for fur-
niture and/or other infrastructure construction are impor-
tant. Therefore such wood products need to be main-
tained through the adoption of appropriate logging prac-
tices. To compare harvesting density in each logging
practice, it was assumed that the EWP produced under
the CVL system is a timber supply baseline against
which the EWPs from RIL and RIL+ are compared.
Maintaining same final wood products under the three
logging practiced is expressed by:
 
i
i
WP t1sHt  (4)
 
ii i
WAStHtWP t (5)
 
ii
EWP t1aWP t  (6)



ii i
EWAStWP tEWPt

(7)
where:
si: proportion of unusable wood such as broken mer-
chantable stem and high stump caused by unprofessional
Table 1. Summarizes the values of these parameters, the underlying assumptions, and the sources of these data.
Scenarios
CVL RIL RIL+
Description
REL (baseline) PEL
Remarks
CS (0) 92.7 MgC (aboveground carbon) Weighted average of forest area in 2010 and stand volumes published in [23,30-33]
fM 0.54 Kim Phat et al. [23]
fH 0.30 MAFF [24]
r 0.50 Explained in the manuscript
Tc 25 (baseline cutting cycle) Practiced in Cambodia until late 2011
MAI (Mean Annual Increment) 0.50 0.50 0.75Explained in the manuscript
BEF 1.74 1.74 1.74Brown [22]
α 1.0 0.5 0.5Explained in the manuscript
s (WAS) 0.30 0.10 0.10Explained in the manuscript
Wood waste due to processing
a (EWAS) 0.50 0.40 0.4050% waste for CVL, 40% for RIL (see [40])

Reducing Carbon Emissions through Improved Forest Management in Cambodia 60
  
CVLCVL CVL
EWP t1aWP t  (8)
 
RR
EWPt1 aWPt R
L
(9)
where the subscript “R” means that the equation can be
used for both RIL and RIL+.
To maintain a long-term wood supply under the REDD+
scenario (using RIL or RIL+) that is comparable to that
under the baseline scenario (using CVL), the wood sup-
ply under the three scenarios must be maintained:
 
RCV
EWP tEWPt (10)
or


 
CVL CVL
R
RR
1a(1s )
HtH t
1a 1s


 C
VL


(11)
2.6. Emission Reductions and Carbon Credits
Accounting for carbon stocks and emission reduction is
an important component of the Monitoring, Reporting,
and Verification or MRV system of the REDD+ scheme
and for setting reference emission level. Unlike REDD
projects where carbon stocks and emissions can be sim-
ply obtained by multiplying annual deforested area and
carbon stocks per hectare, area of concession forests usu-
ally does not change. Only carbon stocks change because
of logging impact. To estimate carbon credits from man-
aging concession forests, baseline emissions and project
emissions should be accounted for. The former is the
emission in the absence of international agreements that
provide incentives for good longterm logging practices
(CVL in this study) while the latter is the emission re-
leased from project implementation (RIL and RIL+ in
this study). In addition to baseline emissions (BE) and
project emissions (PE), leakages (L) are the emissions
outside the project boundaries, which need to be taken
into account as well. Carbon credits (CC) from managing
concession forests can be derived by:
  
CCtBE tPEt1-L t34.

 
 (12)
 
CVL CVL
44
BEtCSt1CSt
12
  
 
(13)
 
RIL RIL
44
PEt CSt1CSt12   
 
(14)
 
RIL RIL
44
PELtCSt1CS t12

 



(15)
where:
BE(t): Baseline emission at year t (MgCO2 year−1).
CVL emissions are taken as baseline emissions.
PE(t): Project emission at year t (MgCO2 year−1).
L(t): Leakages (MgCO2 year−1). Murray et al. [43]
found that leakages vary greatly from one location to
another. It was at 30% for our study.
CSCVL(t), CSRIL(t), CSRIL+(t): Carbon stocks in the year
t under CVL, RIL, and RIL+ scenarios, respectively (MgC).
3.4 (3.4 million ha): total area of concession forests in
Cambodia.
44/12: the ratio of the molecular weight of CO2 (44) to
the molecular weight of carbon (12).
2.7. End-Wood Products and Overall Carbon
Stocks
Total end-use wood products and carbon stocks for each
scenario from managing 3.4 million ha of concession
forests in Cambodia are the products of respective vari-
ables with area of concession forests. Converting EWP
from carbon (TgC) to cubic meter (m3) was done fol-
lowing Brown [22].
 
m3
EWP t
EWP tWDBEF C 
(16)
where:
EWPm3 (t): total end-use wood products in million
m3·year−1).
EWP(t): total end-use wood products in TgC year−1.
WD: wood density in dry biomass (WD = 0.57).
C: carbon content in dry wood (C = 0.5).
3. Results and Discussions
Modeling timeframe for this study is 55 years com-
mencing in 2014.
3.1. End-Use Wood Products and Wood Wastes
under CVL, RIL and RIL+
By maintaining end-use wood products under both CVL
and RIL (including RIL+), annual end-use wood pro-
ducts and wood wastes were estimated under the current
cutting cycle of 25 years. Our models suggested that ma-
naging 3.4 million ha of concession forests over 55 years
in Cambodia produces, about 1.8 million m3·year−1 of the
end-use wood product at a declining rate of 1.1% an-
nually from 2.9 million m3 in 2010 (Figure 2). In terms
of logging residues (in forests) and wood wastes (at the
sawmill), CVL created 3.4 million m3·year−1 over the
same period while only 1.6 million m3·year−1 of wastes
were created under the RIL (including RIL and RIL+),
reducing 52.9% of residues and wastes due to logging.
Logging residues and wood wastes under CVL resulted
from huge damages and wood wastes caused by unpro-
fessional logging, log skidding, trimming and transpor-
ting, and wastes at sawmill. Switching from CVL to RIL
or RIL+ practice could significantly reduce wood wastes,
and therefore vulnerability of forests to fires [44].
Illegal logging strongly influences the end-use wood
products and carbon stocks in the forests. If 50% of the
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 61
0.0
0.5
1.0
1.5
2.0
2.5
3.0
2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052 2054 2056 2058 2060 2062 2064 2066 2068
End-wood Product (million m
3
/year)
Timeframe
(y
ear
)
Figure 2. Annual end-use wood products ensured under three logging practices for 55 years (2010-2065).
illegal logging rate is eliminated (r = 0.5/2), wood supply
is maintained at 1.4 million m3·year−1 but declining rate
is at about 0.6%. If illegal logging is completely elimi-
nated (r = 0), wood supply is maintained at 1.2 million
m3·year−1 at a declining rate of about 0.4%. Our esti-
mates are well within wood production estimated the
World Bank et al. [37] and DAI [25] whose annual wood
production (including illegal production) was reported at
1.5 - 4.3 million m3 from 1995 to 1997.
3.2. Carbon Stock Changes under CVL, RIL,
and RIL+
Affected by logging practices, carbon stocks in 3.4 mil-
lion ha of concession forests decrease to 125.6 Tg C at
the year 55th (the ending year of the modeling timeframe,
t = 55) from 315.26 TgC at the start of the management (t
= 0), representing an annual degradation (emissions) of
3.4 TgC or 12.7 TgCO2 (1 TgC = 44/12 TgCO2 = 3.67
million tonnes CO2) or 1.1% annually. Respectively
under the RIL and RIL+, carbon stocks also decrease to
186.2 and 216.7 TgC at t = 55 from 315.2 TgC at t = 0,
representing annual emissions from forest degradation of
7.6 TgCO2 (0.7%) and 6.6 TgCO2 (0.6%) over a 55-year
modeling timeframe (Figure 3).
Illegal logging also strongly affects carbon stocks in
the forests. If half of the rate of illegal logging used in
our study is halted, annual carbon loss (degradation) is
8.8 TgCO2, 4.9 TgCO2, and 2.7 TgCO2 under CVL, RIL,
and RIL+ scenarios, respectively. If illegal logging is
completely eliminated, managing concession forests
under the CVL, RIL, and RIL+ scenario results in annual
carbon loss (degradation) of 6.2, 2.7, and 0.3 TgCO2,
respectively over the 55-year cutting cycle (Figure 4).
0
50
100
150
200
250
300
350
2014 2018 2022 2026 2030 2034 2038 2042 2046 2050 2054 2058 2062 2066
Carbon Stocks (TgC)
Timeframe (year)
RIL+ Carbon Stocks
CVL Carbon Stocks
RIL Carbon Stocks
Figure 3. Forest carbon stocks of 25-year cutting cycle
under three logging practices (2014-2069).
As previous study on reduced emissions from forest
degradation through managing concession forests was
very limited, it is difficult to compare our carbon emis-
sion reductions with that of previous studies. However,
Asner et al. [45,46] found that at least 20% of tropical
forests were under various forms of selectively logging,
and forest degradation in Amazon doubled during the
2000s. Conventional logging also caused rapid defore-
station in Amazon, where selectively logged forests were
cleared in four years after logging [8] suggesting that
large amount of timber volume (carbon) was harvested
and degraded during and after logging.
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 62
0
50
100
150
200
250
300
350
2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042 2044 2046 2048 2050 2052 2054 2056 2058 2060 2062 2064 2066 2068
Carbon Stocks (TgC)
Timeframe (year)
CVL-25% RIL-25% REDD+%
CVL-0% RIL-0%RIL+0%
CVL-50% RIL-50% RIL+50%
Figure 4. Carbon stock changes affected by illegal logging under CVL, RIL, and RIL+. Note: CVL—50%, CVL—25%, and
CVL—0% are carbon stocks under 50%, 20%, and 0% rates of illegal logging.
3.3. Sensitivity Analysis of Illegal Logging and
Cutting Cycles
To analyze the impact of illegal logging and cutting cycle
on timber supply and carbon stocks, and thus carbon
emissions from managing 3.4 million ha of concession
forests in Cambodia, three more cutting cycles, namely
35, 45, and 55 years were tested under the CVL, RIL,
and RIL+ scenarios with three rates of illegal logging,
namely the 50% rate, 25% rate, and zero. The testing
results for a 50% rate of illegal indicate that the annual
end-use wood products from managing the 3.4 million ha
of concession forests are 1.8 (declining 1.1% annually),
1.4 (0.8%), and 1.2 million m3 (0.6%) under 35, 45, and
55 years cutting cycles, respectively for a 55-year mo-
deling timeframe. If the rate of illegal logging is reduced
by 50% (r = 0.5/2), end-wood products were estimated at
1.3 (0.6%), 1.0 (0.4%), and 0.8 (0.2%) million m3·year−1,
and if the rate of illegal logging is completely reduced (r
= 0), end-use wood products are estimated at 1.0 (0.3%),
0.8 (0.2), 0.6 (0.1%) million m3·year−1, respectively
(Table 2). If illegal logging is completely eliminated, a
55-year cutting cycle would be most appropriate and it
could ensure the sustainable supply of end-use wood pro-
duct of 0.9 million m3 under the RIL or RIL+ practice.
Given the nature of illegal logging and governance pro-
blems in developing countries, it is unlikely that illegal
logging can be completely eliminated.
Cutting cycle and illegal logging rates also affect for-
est carbon stocks (Table 3). Annual carbon emissions
over a 55-year period under the CVL, RIL and RIL+ of a
35-year cutting cycle with 50% rate of illegal logging
were estimated at 9.52 (0.82%), 5.60 (0.48%), and 3.31
(0.29%) TgCO2, respectively. With 25% rate, carbon
emissions were 5.84 (0.50%), 2.44 (0.21%), and −0.08
(−0.01%, “–” refers to carbon sinks) TgCO2, and 3.50,
0.60, and −2.06 TgCO2 without illegal logging, respec-
tively under CVL, RIL, and RIL+ (Table 3). Carbon
sequestration was achieved under the RIL and RIL+ of
45-year cutting cycle (−0.74 and −3.49 TgCO2 year−1,
respectively) without illegal logging. Under a 55-year
cutting cycle, carbon sequestration of −0.43 - 4.46
TgCO2 year−1 was achieved by switching from CVL to
RIL and by reducing the rate of illegal logging (Table 3).
From a carbon perspective, the longer the rotation is the
more carbon sinks can be achieved.
Taking into account the need for investment return, a
shorter cutting cycle is preferred by forest owners. De-
pending on incentives from the REDD+ scheme and
timber prices, forest managers or owners are likely to
choose either a 35-year or 45-year cutting cycle through
the adoption of RIL or RIL+. If carbon price is not at-
tractive enough and timber price is high, forest owners
will try to maximize their revenues under a shorter but
appropriate cycle provided that carbon emissions can be
achieved against the baseline scenario. RIL or RIL+ is
likely to become their choice if carbon incentives are
available. At a country level, countries with instable po-
litical situation are likely to adopt the short cutting cycles
for immediate financial gains in the expense of forest
resources and carbon stocks. Such practices were actual-
ly behind the rapid forest degradation and deforestation
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 63
Table 2. Average annual end-use wood product under four cutting cycles and three rates of illegal logging for 55-year time
span.
Illegal logging rate: 50% Illegal logging rate: 25% Illegal logging rate: 0%
Cutting Cycle
(million m3) Decline (%) (million m3) Decline (%) (million m3) Decline (%)
25-year cycle 2.28 −1.51 1.67 −0.97 1.32 −0.65
35-year cycle 1.77 −1.05 1.27 −0.60 0.98 −0.34
45-year cycle 1.44 −0.76 1.02 −0.37 0.78 −0.17
55-year cycle 1.22 −0.55 0.85 −0.22 0.65 −0.05
Note: Values in this table are the average for 25-year modeling timeframe.
Table 3. Annual carbon emissions or sinks under four cutting cycles and three rates of illegal logging (modeling timeframe:
55 years).
Rates of illegal logging
50% 25% 0%
CVL RIL RIL+ CVL RIL RIL+ CVL RIL RIL+
25-year cutting cycle
(TgCO2) 12.65 8.61 6.58 8.88 5.02 2.69 6.26 2.79 0.29
% 1.09% 0.74% 0.57% 0.77% 0.43% 0.23% 0.54% 0.24% 0.02%
35-year cutting cycle
(TgCO2) 9.52 5.60 3.31 5.84 2.44 −0.08 3.50 0.60 −2.06
% 0.82% 0.48% 0.29% 0.50% 0.21% −0.01% 0.30% 0.05% −0.18%
45-year cutting cycle
(TgCO2) 7.20 3.57 1.13 3.78 0.81 −1.83 1.73 −0.74 −3.49
% 0.62% 0.31% 0.10% 0.33% 0.07% −0.16% 0.15% −0.06% −0.30%
55-year cutting cycle
(TgCO2) 5.44 2.12 −0.43 2.31 −0.30 −3.03 0.49 −1.64 −4.46
% 0.47% 0.18% −0.04% 0.20% −0.03% −0.26% 0.04% −0.14% −0.39%
Note: 1 TgC = 3.67 TgCO2 = 3.67 million tonnes CO2 and “− or minus” refers to carbon sinks.
in the tropics in the last several decades [47]. It is there-
fore important that incentives under the REDD+ scheme
weight the benefits of managing the forests and the right
incentives for developing countries while make sure that
bad practice is not accepted.
Based on past experience with illegal logging and go-
vernment capability to completely reduce illegal logging,
a 45-year cutting cycle with 25% rate of illegal logging is
more realistic, and it was assumed here to be adopted for
managing forests under the REDD+ scheme. With this
assumption, we can estimate the emissions in the absence
of the REDD+ activities and emissions when REDD+
activities are implemented. The former is usually known
as reference emission level (REL) while the later is
known as project emission level (PEL).
3.4. Carbon Emission Reductions and Carbon
Credits
By taking 25-year (currently practiced cycle) cycle as
baseline cycle, against which a 45-year cutting cycle is
compared, REL, PEL and carbon credits can be estima-
ted. Based on equations (12) through (15), REL was esti-
mated at 12.4 TgCO2 year−1 over the 55-year modeling
period. Over the same period, PELs under RIL and RIL+
were estimated at 3.5 and 1.1 TgCO2 year−1, respectively
(Figure 5). Therefore, the annual emission reductions
from forest degradation were 8.9 or 11.3 TgCO2 year−1,
respectively if CVL was replaced by RIL or RIL+. After
subtracting 30% from, CC under the RIL or RIL+ was
estimated at about 6.2 TgCO2 year− or 7.9 TgCO2 year−
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 64
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
Timeframe (year)
REL PEL_RIL PEL_ RIL+
Emissions (TgCO
2
)
Figure 5. Reference emission level (red) and project emission level under RIL (blue) and under RIL+ (green). Note:
PEL_RIL and PEL_RIL+ are project emission levels under the RIL and RIL+ scenarios, respectively.
under RIL or RIL+, respectively. If carbon is priced at $5
(average carbon price at the voluntary carbon market was
$5.90 per MgCO2 in 2012 [48], total annual carbon-
based revenues from managing 3.4 million ha of conces-
sion forests were estimated at $31.0 - 39.5 million an-
nually for 55 years by adopting RIL or RIL+ practice. In
addition to these carbon revenues, revenues from timber
royalties and other benefits from long-term management
of production forests can also be obtained. The carbon
revenues alone are more than four times higher than the
timber revenues from logging in Cambodia reported in
1995 [40].
3.5. Project Activities and Costs
It is obvious that achieving high PEL requires project
activities that reduce logging damages, logging residues
(wood wastes in the forests) and wood wastes at the
wood processing factory. The RIL activities for reducing
logging damages include logging training and mapping,
well-defined logging plan, directional felling, tree felling
and skidding by trained crews, pre- and post-logging
social and environmental impact assessments, post-log-
ging assessments. Activities for reducing wood wastes
include training on directional felling, tree felling, log
trimming and exporting, and introducing wood proces-
sing technology at the processing mills. In addition,
government’s commitment to enforcing the laws and
transparency in logging practice and revenue sharing to
relevant stakeholders such as forest-dependent commu-
nity are required for the successful implementation of the
sustainable forest management projects.
Logging costs had been generally thought to be ex-
pensive under the RIL or RIL+ options but based on
various studies in the tropics, Sasaki et al. [18] argued
costs are not expensive as previously thought because
revenues under CVL continuously declines as future
commercial timber supply is decreasing. However, cost-
effective analysis is beyond the scope of this paper.
4. Conclusions
Improved forest management through adoption of RIL+
could result in significant reductions of carbon emissions
due to selective logging. Our study suggests that carbon
credits generated from switching from destructive log-
ging to sound logging practice (i.e. RIL or RIL+) are
huge and would be attractive to project developers if
there are continued financial incentives and/or carbon
markets for carbon credits from sustainable management
of forests. The inclusion of the SFM of the REDD+
scheme in the new mitigation mechanisms for post-
Kyoto project activities will ensure such incentives and
carbon markets.
Our results also suggested that a 25-year cutting cycle
currently being practiced in Cambodia is too short to
maintain the flow of wood production. A 45-year cutting
cycle under the RIL or RIL+ could maintain the long-
term supply of wood product while still contributing to
carbon emission reductions from selectively logged for-
ests. Achieving sustainable forest management under the
REDD+ mechanism will require the adoption of sound
logging practices that will reduce damage to forest re-
sidual stands and the soils that sustain these stands, and
that will therefore reduce disturbances to upstream re-
sources (e.g., forests that protect catchment ecosystem
services) while maintaining a flow of wood products.
Therefore, RIL or RIL+ should be adopted for improving
forest management in the tropics under the REDD+
scheme. Without carbon-based incentives such as carbon
incentives under the REDD+ scheme, RIL+ would not be
adopted and therefore emissions from tropical forests can
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 65
not be reduced putting global efforts to mitigating cli-
mate change and achieving sustainable development in
developing countries at risk.
For adopting RIL+, pre-cautionary measures should be
taken to prevent the killing of commercially less im-
portant but biologically important tree species. This prac-
tice of tree girdling should be carefully practiced by well-
trained professionals who have knowledge about tree
species and their interactions with other organisms in the
forests.
5. Acknowledgements
This study was partially supported by a Grant-in-Aid for
Scientific Research (No. 18402003) from the Ministry of
Education, Culture, Sports, Science and Technology of
Japan.
REFERENCES
[1] P. Friedlingstein, R. A. Houghton, G. Marland, J. Hackler,
T. A. Boden, T. J. Conway, J. G. Canadell, M. R. Raupach,
P. Ciais and C. Le Quéré, “Update on CO2 Emissions,”
Nature Geoscience, Vol. 3, No. 12, 2010, pp. 811-812.
http://dx.doi.org/10.1038/ngeo1022
[2] Y. Pan, R. A. Birdsey, J. Fang, R. Houghton, P. E. Kauppi,
W. A. Kurz, O. L. Phillips, A. Shvidenko, S. L. Lewis, J.
G. Canadell, P. Ciais, R. B. Jackson, S. Pacala, A. D.
McGuire, S. Piao, A. Rautiainen, S. Sitch and D. Hayes,
“A Large and Persistent Carbon Sink in the World’s For-
ests,” Science, Vol. 333, No. 6045, 2011, pp. 988-993.
http://dx.doi.org/10.1126/science.1201609
[3] G. Kindermann, M. Obersteiner, B. Sohngen, J. Sathaye,
K. Andrasko, E. Rametsteiner, B. Schlamadinger, S.
Wunder and R. Beach, “Global Cost Estimates of Reduc-
ing Carbon Emissions through Avoided Deforestation,”
Proceedings of the National Academy of Sciences of the
United States of America, Vol. 105, No. 30, 2008, pp.
10302-10307. http://dx.doi.org/10.1073/pnas.0710616105
[4] N. Sasaki and A. Yoshimoto, “Benefits of Tropical Forest
Management under the New Climate Change Agree-
ment—A Case Study in Cambodia,” Environmental Sci-
ence & Policy, Vol. 13, No. 5, 2010, pp. 384-392.
http://dx.doi.org/10.1016/j.envsci.2010.04.007
[5] F. Toni, “Decentralization and REDD+ in Brazil,” For-
ests, Vol. 2, No. 1, 2011, pp. 66-85.
[6] N. Sasaki, K. Chheng and S. Ty, “Managing Production
Forests for Timber Production and Carbon Emission Re-
ductions under the REDD+ Scheme,” Environmental
Science & Policy, Vol. 23, 2012, pp. 35-44.
http://dx.doi.org/10.1016/j.envsci.2012.06.009
[7] F. E. Putz, P. A. Zuidema, M. A. Pinard, R. G. A. Boot, J.
A. Sayer, D. Sheil, P. Sist and J. K. Vanclay, “Improved
Tropical Forest Management for Carbon Retention,”
PLOS Biology, Vol. 6, No. 7, 2008, Article ID: e166.
http://dx.doi.org/10.1371/journal.pbio.0060166
[8] G. P. Asner, E. N. Broadbent, P. J. Oliveira, M. Keller, D.
E. Knapp and J. N. Silva, “Condition and Fate of Logged
Forests in the Brazilian Amazon,” Proceedings of the Na-
tional Academy of Sciences of the United States of Amer-
ica, Vol. 103, No. 34, 2006, pp. 12947-12950.
http://dx.doi.org/10.1073/pnas.0604093103
[9] D. W. Pearce, E. F. Putz and J. K. Vanclay, “Sustainable
Forestry in the Tropics: Panacea or Folly?” Forest Ecol-
ogy and Management, Vol. 172 No. 2-3, 2003, pp. 229-
247. http://dx.doi.org/10.1016/S0378-1127(01)00798-8
[10] N. Sasaki and F. E. Putz, “Critical Need for New Defini-
tions of Forest and Forest Degradation in Global Climate
Change Agreements,” Conservation Letters, Vol. 2, No. 5,
2009, pp. 226-232.
http://dx.doi.org/10.1111/j.1755-263X.2009.00067.x
[11] S. D. Miller, M. L. Goulden, L. R. Hutyra, M. Keller, S.
R. Saleska, S. C. Wofsy, A. M. Figueira, H. R. Da Rocha
and P. B. De Camargo, “Reduced Impact Logging Mini-
mally Alters Tropical Rainforest Carbon and Energy Ex-
change,” Proceedings of the National Academy of Sci-
ences of the United States of America, Vol. 108, No. 48,
2011, pp. 19431-19435.
http://dx.doi.org/10.1073/pnas.1105068108
[12] N. Kim Phat, W. Knorr and S. Kim, “Appropriate Meas-
ures for Conservation of Terrestrial Carbon Stocks—
Analysis of Trends of Forest Management in Southeast
Asia,” Forest Ecology and Management, Vol. 191, No.
1-3, 2004, pp. 283-299.
http://dx.doi.org/10.1016/j.foreco.2003.12.019
[13] N. Sasaki, “Carbon Emissions Due to Land-Use Change
and Logging in Cambodia—A Modeling Approach,”
Journal of Forest Research, Vol. 11, No. 6, 2006, pp.
397-403. http://dx.doi.org/10.1007/s10310-006-0228-5
[14] P. Sist, D. Sheil, K. Kartawinata and H. Priyadi, “Re-
duced-Impact Logging in Indonesian Borneo: Some Re-
sults Confirming the Need for New Silvicultural Prescrip-
tions,” Forest Ecology and Management, Vol. 179, No.
1-3, 2003, pp. 415-427.
http://dx.doi.org/10.1016/S0378-1127(02)00533-9
[15] S. Ty, N. Sasaki, A. H. Ahmad and A. Z. Zainal, “REDD
Development in Cambodia—Potential Carbon Emission
Reductions in a REDD Project,” FORMATH, Vol. 10,
2011, pp. 1-23.
[16] FAO, “Global Forest Resources Assessment 2010,” FAO
Forestry Paper, Vol. 163, FAO, Rome, 2010.
[17] FA (Forestry Administration), “Forest Cover Statistics in
Cambodia 2002-2010,” FA, Phnom Penh, 2011.
[18] N. Sasaki, G. P. Asner, W. Knorr, P. B. Durst, H. Priyadi
and F. E. Putz, “Approaches to Classifying and Restoring
Degraded Tropical Forests for the Anticipated REDD+
Climate Change Mitigation Mechanism,” iForest—Bio-
geosciences and Forestry, Vol. 4, 2011, pp. 1-6.
[19] T. P. Holmes, G. M. Blate, J. C. Zweede, R. Pereira, P.
Barreto, F. Boltz and R. Bauch, “Financial and Ecological
Indicators of Reduced Impact Logging Performance in
the Eastern Amazon,” Forest Ecology and Management,
Vol. 163, No. 1-3, 2002, pp. 93-110.
http://dx.doi.org/10.1016/S0378-1127(01)00530-8
[20] M. Peña-Claros, T. S. Fredericksen, A. Alarcón, G. M.
Blate, U. Choque, C. Leaño, J. C. Licona, B. Mostacedo,
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia 66
W. Pariona, Z. Villegas and F. E. Putz, “Beyond Re-
duced-Impact Logging: Silvicultural Treatments to In-
crease Growth Rates of Tropical Trees,” Forest Ecology
and Management, Vol. 256, No. 7, 2008, pp. 1458-1467.
http://dx.doi.org/10.1016/j.foreco.2007.11.013
[21] Z. Villegas, M. Peña-Claros, B. Mostacedo, A. Alarcón, J.
C. Licona, C. Leaño, W. Pariona and U. Choque, “Silvi-
cultural Treatments Enhance Growth Rates of Future
Crop Trees in a Tropical Dry Forest,” Forest Ecology and
Management, Vol. 258, No. 6, 2009, pp. 971-977.
http://dx.doi.org/10.1016/j.foreco.2008.10.031
[22] S. Brown, “Estimating Biomass and Biomass Change of
Tropical Forest: A primer. FAO Forestry Paper 134,”
Food and Agriculture Organization of the United Nations
(FAO), Cambridge, Rome, 1997.
[23] N. Kim Phat, S. Ouk, Y. Uozumi and T. Ueki, “Stand
dynamics of Dipterocarp trees in Cambodia’s Evergreen
Forest and Management Implications—A Case Study in
Sandan District, Kampong Thom,” Journal of Forest
Planning, Vol. 6, No. 1, 2000, pp. 13-23.
[24] MAFF, “Sub-Decree No. 050 on Tree Species Classifica-
tion and Diameter Limit for Harvesting,” MAFF, Phnom
Penh (in Khmer), 1986.
[25] DAI (Development Alternatives, Inc.), “Findings and
Recommendations of the Log Monitoring and Logging
Control Project,” Reported Submitted to the Royal Gov-
ernment of Cambodia, Department of Forestry and Wild-
life, Phnom Penh, Cambodia, 1998.
[26] WRI (World Resource Institute), “World Resources
2002-2004: Decisions for the Earth: Balance, Voice, and
Power,” World Resources Institute, Washington DC,
2003.
[27] C. Nellemann, L. Miles, B. P. Kaltenborn, M. Viture and
H. Ahlenius, “The Last Stand of the Orangutan—State of
Emergency: Illegal Logging, Fire and Palm Oil in Indo-
nesia’s National Parks,” United Nations Environment
Program and United Nations Economic, Social and Cul-
tural Office, Arendal, 2007.
[28] C. P. Hansen and T. Treue, “Assessing Illegal Logging in
Ghana,” International Forestry Review, Vol. 10, No. 4,
2008, pp. 573-590.
http://dx.doi.org/10.1505/ifor.10.4.573
[29] S. Lawson and L. Macfaul, “Illegal Logging and Related
Trade Indicators of the Global Response,” Chatham
House, London, 2010.
[30] N. Kim Phat, S. Kim, S. Ouk, Y. Uozumi and T. Ueki,
“Management of Mixed Forest in Cambodia—A Case
Study in Sandan District, Kampong Thom,” Bulletin of
Faculty of Agriculture, Shinshu University, Vol. 38, No.
1-2, 2002, pp. 45-54.
[31] N. Kim Phat, S. Ouk, Y. Uozumi, T. Ueki and S. Kim,
“Management of Mixed Deciduous Forest in Central
Cambodia—A Case Study in Sandan District,” Bulletin of
Shinshu University Forest Research, Vol. 2, No. 38, 2002,
pp. 290-309.
[32] D. Kao and S. Iida, “Structural Characteristics of Logged
Evergreen Forests in Preah Vihear, Cambodia, 3 Years
after logging,” Forest Ecology and Management, Vol.
225, No. 1-3, 2006, pp. 62-73.
http://dx.doi.org/10.1016/j.foreco.2005.12.056
[33] K. Chheng, N. Sasaki and N. Mizoue, “Impacts of Re-
duced Impact Logging on Stand Structures in Mixed For-
ests in Three Northeastern Provinces in Cambodia,” 2nd
International Conference on FORCOM Follow-Up and
New Challenge for Coming Generations, Mie, 25-30
September 2011, 23 p.
[34] N. Top, N. Mizoue and S. Kai, “Estimating Forest Bio-
mass Increment Based on Permanent Sample Plots in Re-
lation to Woodfuel Consumption: A Case Study in Kam-
pong Thom Province, Cambodia,” Journal of Forest Re-
search, Vol. 9, No. 2, 2004, pp. 117-123.
http://dx.doi.org/10.1007/s10310-003-0064-9
[35] S. L. Lewis, G. Lopez-Gonzalez, B. Sonke, K. Affum-
Baffoe, T. R. Baker, L. O. Ojo, et al., “Increasing Carbon
Storage in intact African Tropical Forests,” Nature, Vol.
457, No. 7232, 2009, pp. 1003-1006.
http://dx.doi.org/10.1038/nature07771
[36] O. L. Phillips, Y. Malhi, N. Higuchi, W. F. Laurance, P.
V. Nunez, R. M. Vasquez, S. G. Laurance, L. V. Ferreira,
M. Stern, S. Brown and J. Grace, “Changes in the Carbon
Balance of Tropical Forests: Evidence from Long-Term
Plots,” Science, Vol. 282, No. 5388, 1998, pp. 439-442.
http://dx.doi.org/10.1126/science.282.5388.439
[37] World Bank, United Nations Development Program
(UNDP) and FAO, “Cambodian Forest Policy Assess-
ment,” World Bank, Phnom Penh, 1996.
[38] Center for Forestry Planning and Statistics and Ministry
of Forestry, “Indonesia Forestry Outlook,” Asia-Pacific
forestry sector study II, Working Paper No. APFSOS
II/WP/2009/13, FAO, Bangkok, 2009.
[39] H. Priyadi, P. Gunarso, P. Sist and H. Dwiprabowo, “Re-
duced-Impact Logging (RIL) Research and Development
in Malinau Research Forest, East Kalimantan: A Chal-
lenge of RIL Adoption,” Paper presented in the Regional
Workshop, RIL Implementation in Indonesia with Refer-
ence to Asia-Pacific Region: Review and Experiences,
Bogor, 15-16 February 2006, 18 p.
[40] S. Kim, N. Kim Phat, M. Koike and H. Hayashi, “Esti-
mating Actual and Potential Government Revenues from
timber Harvesting in Cambodia,” Forest Policy and Eco-
nomics, Vol. 8, No. 6, 2006, pp. 625-635.
http://dx.doi.org/10.1016/j.forpol.2004.12.001
[41] FAO (Food and Agriculture Organization of the United
Nations), “Financial and Economic Assessment of Tim-
ber Harvesting Operations in Sarawak, Malaysia,” Forest
Harvesting Case-Studies 17, FAO, Rome, 2001.
[42] P. Sist and A. Saridan, “Description of the Primary Low-
land Forest of Berau,” In: J. G. Bertault and K. Kadir,
Eds., Silvicultural Research in a Lowland Mixed Dip-
terocarp Forest of East Kalimantan: The Contribution of
STREK Project, CIRADFORDA-P.T. INHUTANII, In-
donesia, 1998, pp. 51-94.
[43] B. C. Murray, B. A. Mccarl and H. C. Lee, “Estimating
Leakage from Forest Carbon Sequestration Programs,”
Working Paper, 2-6 May 2002, RTI International, 2002,
pp. 1-22.
[44] D. C. Nepstad, A. Veri´Ssimo, A. Alencar, C. Nobre, E.
Open Access LCE

Reducing Carbon Emissions through Improved Forest Management in Cambodia
Open Access LCE
67
Lima, P. Lefebvre, P. Schlesinger, C. Potter, P. Moutinho,
E. Mendoza, M. Cochrane and V. Brooks, “Large-scale
Impoverishment of Amazon Forests by Logging and
Fire,” Nature, Vol. 398, No. 6727, 1999, pp. 505-508.
http://dx.doi.org/10.1038/19066
[45] P. G. Asner, K. T. Rudel, T. M. Aide, R. Defries and R.
Emerson, “A Contemporary Assessment of Change in
Humid Tropical Forests,” Conservation Biology, Vol. 23,
No, 6, 2009, pp. 1386-1395.
http://dx.doi.org/10.1111/j.1523-1739.2009.01333.x
[46] G. P. Asner, G. V. N. Powell, J. Mascaro, D. E. Knapp, J.
K. Clark, J. Jacobson, T. Kennedy-Bowdoin, A. Balaji, G.
Paez-Acosta, E. Victoria, L. Secada, M. Valqui and R. F.
Hughes, “High-Resolution Carbon Stocks and Emissions
in the Amazon,” Proceedings of the National Academy of
Sciences of the United States of America, Vol. 107, No.
38, 2010, pp. 16738-16742.
http://dx.doi.org/10.1073/pnas.1004875107
[47] A. Casson and K. Obidzinski, “From New Order to Re-
gional Autonomy: Shifting Dynamics of ‘illegal’ Logging
in Kalimantan, Indonesia,” World Development, Vol. 30,
No. 12, 2002, pp. 2133-2151.
http://dx.doi.org/10.1016/S0305-750X(02)00125-0
[48] M. Peters-Stanley and D. Yin, “Maneuvering the Mosaic
State of the Voluntary Carbon Markets 2013,” A Report
by Forest Trends’ Ecosystem Marketplace & Bloomberg
New Energy Finance, Washington, D.C., 2013, pp. 126.