IMPACT OF HARVESTING METHODS ON BIOMASS AND …jamrpublication.com/uploads/72/3861_pdf.pdf · optimum biodiversity and conservation, but also for climate change mitigation via stocking

Journal of Advance Management Research, ISSN: 2393-9664

Vol.05 Issue-04, (October 2017), Impact Factor: 4.598

Double-Blind Peer Reviewed Refereed International Journal - Included in the International Serial Directories


(JAMR)http://www.jamrpublication.com email id- [email protected] Page 272

IMPACT OF HARVESTING METHODS ON BIOMASS AND CARBON STOCK IN PRODUCTION

FOREST OF SABAH, MALAYSIA

MASHOR, M.J.1, JUPIRI, T.1, NIZAM, M.S.2& ISMAIL, P.3+

1Sabah Forestry Department, Locked Bag 68, 90009 Sandakan, Sabah, Malaysia.

2School of Environmental and Natural Resource Sciences, Faculty of Science and Technology,

Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

3+Forest Research Institute Malaysia (FRIM), Kepong 52109 Selangor, Malaysia.

Abstract

A study was conducted to determine the status of biomass and carbon stocks in two logged-over lowland dipterocarp forests of Deramakot Forest Reserve (FR) and Tangkulap FR in Sabah. It represent two harvesting methods being used for timber extraction, namely; reduced impact logging (RIL) in Deramakot FR and conventional logging (CL) in Tangkulap FR. Sixteen circular plots of 20 m radius (0.1256 ha plot-1) were established in each forest reserve. A total combined 2012 trees with ≥10 cm diameter at breast height (dbh) have been enumerated in all sampling plots. Results of this study show that, total tree biomass in Deramakot FR was estimated at 574.65 t ha-1 and in Tangkulap FR at 465.68 t ha-1 with total carbon of 287.32 and 232.84 t ha-1 respectively. The total biomass, as well as the carbon stocks was greater in Deramakot FR by almost 23% as compared to Tangkulap FR. It shows an import contribution of RIL in climate change mitigation. Extrapolating for the entire area of Deramakot FR, RIL brought a net addition of about 3.0 million tonnes of carbon with estimated values hypothetically at USD63.31 million whereas the value of carbon loss due to CL for the whole area of Tangkulap FR would be about USD22 million. As a conclusion, it is established that RIL is needed as an essential tool in forest management not only to achieve optimum biodiversity and conservation, but also for climate change mitigation via stocking of higher biomass and carbon stock in the forest. Keywords: Tropical rainforests, logged-over forest, reduced impact logging, conventional logging, climate change mitigation. Introduction Globally, tropical rainforests are well known for their high biodiversity and key roles in carbon storage and influence on climate. With tropical forests emerging as the most important natural resource on earth, the depletion and degradation of tropical forests, especially in connection with climate changes and loss of biodiversity, have become among the main issues of international discussions in recent years. In addition to containing as much as 90% of terrestrial biodiversity (Brooks et al.2006), tropical forests store more than 320 billion tonnes of carbon (Gibbs et al.2007). Clearing these forests results in large emissions of carbon dioxide (CO2) to the atmosphere; the emissions from current tropical






deforestation have been estimated at 20% of the total global CO2 emissions (IPCC 2007). It is also important to note that quite apart from the tangible benefits and the issues of carbon sinks, it is essential to conserve forest for the enormous value of the variety of its biological goods and services that emanate from the biodiversity system. In spite of its rapid rate of development, Malaysia has still been able to maintain vast areas of forested land for about 18.56 million ha (56.5% of total land area) in which 14.30 million is under permanent reserved forest (PRF) at the end of 2007 (FAO 2010). The management of this forest resource has evolved from sustained timber production to multiple-use forestry, with greater emphasis on environmental protection and conservation of biological diversity. Thus, the practice of sustainable forest management (SFM) in managing forest resources is also able to protect the environment. Malaysia also recognizes the immense value of the forest resources in providing environmental protection, particularly related to climate change (Shamsudin et al. 2009). In this regard, the issue of deforestation and forest degradation being addressed under the United Nations Framework Convention on Climate Change (UNFCCC) is relevant and important for Malaysia. Malaysia has ratified both the UNFCCC in July 1994 and the Kyoto Protocol in September 2002 (Wan Razali 2008). The ratification of these protocols signifies the commitment of Malaysia in addressing the problems of climate change and sets the stage for further work on the issue (Shamsudin et al. 2009). Sabah is the second largest state in Malaysia lying on the north-eastern tip of one of the world’s largest tropical islands–Borneo, and it is still swathed in tropical evergreen rainforests. Forestry has traditionally been the main stay of the state’s economy and has been for a long time the major backbone of the state’s socio-economic well-being. The forests are relatively well conserved, covering more than 60% of Sabah’s total land area, at more than 44 000 km2 (SFD 2005a). These forests are fairly heterogeneous but dipterocarp forests account for more than 75% of Sabah’s natural forests (SFD 2005a). Commercially they are the most important asset in terms of revenue and economic activity for the state. In addition, the natural ecosystem of Sabah hosts an astounding array of plants and other life forms, of which more than 3000 species are of trees alone, not including the thousands of other plant species (SFD 2005a). Since 1997 all state commercial productive forests are managed based on the SFM concept. The practice of SFM is crucial to ensure the forest continues to provide socio-economic development to benefit society. In order to comply with the principle of SFM and to minimize harvesting damage to forest stands and soils, various planning activities including employing eco-friendly harvesting practices such as reduced impact logging (RIL) techniques and timber stand improvement measures are among the requirements (Norizah et al. 2016). If the SFM mechanism is successful in maintaining the existing forests, it is likely to deliver a range of environmental benefits, in addition to its contribution to climate-change mitigation. These benefits chiefly take the form of maintaining the biodiversity and ecosystem services supported by these forests. However, the sustainability and renewability of the forest resources will rely on how effectively the forest is managed in accordance with






sound ecological principle based on exhaustive scientific findings. It is, therefore, important to have a firm knowledge and good understanding of the resource base (resource inventory as a basis of stand history, structure, composition, diversity and dynamics), and availability and implementation of environmentally sound forest harvesting practices.

Apart from vegetation study, studies on forest biomass-carbon are also important. The uses

of this information vary, such as quantitatively describing ecosystems and indicating the

biomass resources available (Brown 1997; Young & Tyron 1978), quantifying the amounts of

nutrients in the ecosystem (Baker et al. 1984; Lim 1988), quantifying the increments in

forest yield, growth or productivity (Burkhart & Strub 1973), assessing the changes in forest

structure (Brown 1997), and assessing the detrimental effects of harvesting (Roland & Lim

1999). Biomass estimation is also important for site evaluation and improvement which

form the bases for sound forest management (Lim 1993).

Biomass is an important indicator in carbon sequestration. For this reason, one needs to

know how much biomass is accumulated or lost over time. Consequently, the amount of

carbon sequestered can be inferred from the biomass change since 50% of the forest dry

biomass is carbon (Losi et al. 2003). Lately, the ability to accurately and precisely measure

the carbon stored and sequestered in forests is increasingly gaining global attention in

recognition of the role forests have in the global carbon cycle and its relation to the

greenhouse effect, particularly with respect to mitigating CO2 emissions (Brown et al. 1996).

The UNFCC and its Kyoto Protocol also recognizes the role of forests in carbon

sequestration. Specifically, Articles 3.3 and 3.4 of the Kyoto Protocol pointed out forest as a

potential carbon store (Brown 2002; United Nations 1998). Thus, estimating of biomass is

the most critical step in quantifying carbon stocks and fluxes from the forest. Forests can be

a carbon source and sink of carbon dioxide (Roland & Lim 1999), thus, it can contribute to

reducing the greenhouse effect and they can also offer opportunities to mitigate climate

change.

Climate change is one of the truly global issues of our time, and forests feature prominently

in it. Forests play a vital role in the mitigation of climate change as they have the ability to

absorb and sequester carbon from the atmosphere (Shamsudin et al. 2009). According to

Pinard (1995), the forestry-based offsets increase terrestrial carbon storage either by

expanding the forest cover or by maintaining or improving the existing forest for carbon

storage. Estimation of the magnitude of CO2 sources and sinks requires reliable estimates of

the biomass density of forests (Brown 1997). Thus a good understanding of the carbon

dynamics of forests is therefore important, particularly about how carbon stocks vary in

relation to forest conditions and human land-use activities (Keith et al. 2009) such as

silviculture, harvesting and degradation (Brown 1997).






This study attempts to describe the status of biomass and carbon stocks of tree

communities of the lowland dipterocarp forests in two production forests of Deramakot FR

and Tangkulap FR in Sabah. The forest reserves representing two different harvesting

methods; RIL in the Deramakot FR and conventional logging (CL) in Tangkulap FR. Findings of

this study will be used to determine impact of the harvesting technique on biomass and

carbon stock to be further related on role of forests on climate change mitigation.

Materials and Methods The study was conducted in two productive forest reserves in Sabah, viz. Deramakot FR and Tangkulap FR (Figure 1). These forest reserves form a contiguous stretch covering areas of 55 083 ha and 27 550 ha respectively (SFD 2005b). Both reserves have been established since the 1960s and were re-gazetted as production forest reserves in 1984. These areas were arbitrarily chosen to reflect two harvesting methods being used for extraction of timbers, i.e. RIL in Deramakot FR and CL in Tangkulap FR. Deramakot and Tangkulap FRs were originally licensed for CL as early as from 1955 (Kleine & Heuveldop 1993). In 1989, Deramakot FR was chosen as a model project site for the Malaysian-German Sustainable Forest Management Project (MGSFMP) which was to be managed in accordance with the SFM principles and multiple-use approach to natural forest management (NFM) and all logging activities were suspended thereafter. A new system of SFM was adopted with RIL being practised in 1995. Deramakot FR became the first well-managed tropical forest in the world certified under the Forest Stewardship Council (FSC) scheme in 1997. The certification then was extended in 2008 for the third time making Deramakot FR the longest continuously certified rainforest in the world. By contrast, CL was continued in Tangkulap FR until 2002 when all logging activities in this area were ceased. These forest reserves are located at central-east of Sabah. Deramakot FR is situated between longitudes 117o 20’ E and 117o 42’ E and between latitudes 5o 19’N and 5o 20’ N. Tangkulap FR is situated between longitudes 117o 02’ 32.43” E and 117o 22’ 00.00” E and between latitudes 5o 31’ 08.10” N and 5o 16’ 00.00”N.






Figure 1. Locations of Deramakot and Tangkulap FRs in Sabah In this study, four circular plots measuring 20 m radius each (0.1256 ha per plot) were established systematically which consist of 16 plots for every forest reserve. All trees in the study plots with diameter at breast height (dbh) of ≥10 cm were tagged with plastic labels, measured and identified. The following data were recorded from all 32 plots: (1) botanical and local names of trees (2) numbers of trees and (3) dbh or 1.8 above the ground or buttresses of trees. Leaf samples of unknown trees were collected for identificationat the Herbarium of Sabah Forest Research Centre in Sepilok, Sandakan. As for calculation of merchantable tree volume, the estimation was based on Valentine (2005) and Sabah Forestry Department (2009) as follows: V= 0.00026466DBH2.279212554 x Vi where,

V = merchantable volume (m3); dbh = diameter at breast height (cm); Vi = correction factor of 1.042

Estimations of above-ground biomass were carried out using all the data sets, by means of the regression equation of Kato et al. (1978). In this equation, for the known dbh (cm) and height (H m), the biomass values (kg) for stems (WS), branches (WB) and leaves (WL) are calculated as follows:

i) WS = 0.313 (D2H)0.9733 ii) WB = 0.136 WS

1.070

iii) 1

WL =

10.124WS

0.794 + 1

125






The above-ground biomass is the sum of (WS), (WB) and (WL). Tree height (H m) is estimated from the dbh measurement using the formula: H = 122+ D 2D + 61

The estimation of below-ground biomass or roots biomass (kg) is calculated using dbh (cm) measurement by means of the regression equation of Niiyama et al. (2009) as follows:

Below-ground biomass = 0.0254 D 2.521 The total biomass for trees is the total sum of the total above-ground biomass and below-ground biomass. Meanwhile, carbon content in biomass is derived using a conversion factor. As the conversion factor may vary according to plant part, species and site, the global default conversion factor of 50% as recommended by the IPCC is adopted for this study (Brown 1997). Hence, the estimation of the tree carbon content is derived by multiplying the conversion factor of 0.5 by the total biomass of the tree. Results of tree abundance and biomass for both forest reserves were further analysed by using Two Sample t-test to compare their differences (p < 0.05). Rstatistical software was used to compute the calculation of the t-test (R Development Core Team 2010). Results and Discussion a) Tree abundance The stem density of trees >10 cm dbh in Deramakot FR and Tangkulap FR were 544 trees ha-

1 and 457 trees ha-1, respectively (Table 1). The results indicated that Deramakot FR had a higher number of trees by 19% or 87 stems ha-1 more of individuals compared to Tangkulap. The t-test showed there was a significant difference (P = 0.03) in stocking between the two areas with more trees in Deramakot FR than in Tangkulap FR. Table 1. Tree density of trees >10 cm dbh in all plots at Deramakot FR and Tangkulap FR

Dbh Deramakot FR Tangkulap FR

Class (cm) Density Percentage Density Percentage

(stem ha-1

) of the total

(%) (stem ha

-1)

of the total (%)

10.0 – 19.9 327 60.15 284 62.2

20.0 – 29.9 94 17.18 88 19.28

30.0 – 39.9 47 8.59 32 7.08

40.0 – 49.9 32 5.85 19 5.85

50.0 – 49.9 17 3.20 12 2.61

≥ 60 27 5.03 22 4.79

Total 544 100 457 100






Total basal areas for trees of >10 cm dbh in Deramakot FR and Tangkulap FR in all 16 plots were 73.74 m2 (36.69 m2 ha-1) and 59.20 m2 (29.48 m2 ha-1) respectively (Table 2). The result shows that Deramakot FR had greater basal area by 14.54 m2 or 7.21 m2 ha-1 more than Tangkulap FR. However, the total basal areas were not significantly different (P = 0.13) between plots for all trees of >10 cm dbh at Deramakot FR and Tangkulap FR. Table 2. Basal area of trees >10 cm dbh in all plots at Deramakot FR and Tangkulap FR

Diameter Deramakot FR Tangkulap FR

Class (cm) Basal area Percentage Density Percentage

(m2 ha-1) of the total

(%) (m2 ha-1)

of the total (%)

10.0 – 19.9 5.06 13.78 4.54 15.41

20.0 – 29.9 4.58 12.48 4.05 13.74

30.0 – 39.9 4.40 12.00 3.01 10.20

40.0 – 49.9 4.90 13.35 2.85 9.66

50.0 – 49.9 4.07 11.09 2.84 9.64

≥ 60 13.68 37.30 12.19 41.36

Total 36.69 100.00 29.48 100.00

The total volume of trees with of >10 cm dbh in Deramakot FR and Tangkulap FR were 760.40 m3 (378.38 m3 ha-1) and 617.68 m3 (307.36 m3 ha-1) respectively (Table 3). The results show that Deramakot FR had a greater volume by 142.72 m3 or 71.02 m3 ha-1 more than Tangkulap FR. In general, the total volumes of trees in the medium-size classes (30.0 – 59.9 cm dbh) were higher in Deramakot FR than in Tangkulap FR. The highest volumes for both Deramakot FR and Tangkulap FR were recorded in dbh class of ≥ 60 cm at 166.03 and 150.95 m3 ha-1 respectively. However, based on the t-test analysis, the total volumes were not significantly different between the Deramakot FR and Tangkulap FR (P = 0.76). Table 3. Estimated merchantable standing volumes of trees >10 cm dbh in all plots at

Deramakot FR and Tangkulap FR

Diameter Deramakot FR Tangkulap FR

Class (cm) Volume Percentage Volume Percentage

(m3 ha-1) of the total (%) (m3 ha-1) of the total (%)

10.0 – 19.9 37.51 9.91 33.81 11.00

20.0 – 29.9 39.72 10.50 34.79 11.31

30.0 – 39.9 41.81 11.05 28.46 9.26

40.0 – 49.9 49.59 13.10 28.85 9.39

50.0 – 49.9 43.73 11.56 30.53 9.93

≥ 60 166.03 43.88 150.95 49.11

Total 378.38 100.00 307.36 100.00






b) Tree Biomass The biomass values of trees with >10 cm dbh in all plots at Deramakot FR and Tangkulap FR are shown in Table 4. It was observed that generally the biomass values also produced almost a similar trend as for basal area and volume. The total tree biomass in Deramakot FR was estimated at 574.65 t ha-1, which was contributed by the above-ground biomass and below-ground biomass of 484.01 and 90.64 t ha-1 respectively. In Tangkulap FR, the total biomass of trees were relatively lower than Deramakot FR, estimated at 465.68 t ha-1, where the above-ground biomass was of 390.92 t ha-1 whilst the below-ground biomass was 74.76 t ha-1. The results indicated that Deramakot FR had higher tree biomass by almost 23% or 108.97 t ha-1 than Tangkulap FR. However, based on the t-test analysis, the total tree biomass values were found not to be different significantly between the Deramakot and Tangkulap FRs (P = 0.18). Table 4. Tree biomass and estimated carbon content values (t ha-1) in Deramakot FR and Tangkulap FR (figures in brackets are the percentages of the total)

Diameter Deramakot Forest Reserve Tangkulap Forest Reserve

Class (cm) AGB (t ha-1)

BGB (t ha-1)

Total Biomass (t ha-1)

Carbon (t ha-1)

AGB (t ha-1)

BGB (t ha-1)

Total Biomass (t ha-1)

Carbon (t ha-1)

10.0 – 19.9 39.31 6.63 45.93 22.97 35.62 6.00 41.61 20.81

20.0 – 29.9 48.29 8.00 56.29 28.15 41.97 6.95 48.92 24.46

30.0 – 39.9 53.70 9.10 62.80 31.40 36.53 6.18 42.71 21.35

40.0 – 49.9 65.35 11.44

76.78 38.39 38.03 6.66 44.69 22.35

50.0 – 59.9 58.29 10.60

68.89 34.45 40.72 7.42 48.13 24.07

≥ 60 219.07 44.87

263.95

131.97

198.05

41.56

239.61

119.81

Total 484.01 90.64

574.65

287.32

390.92

74.76

465.68

232.84

AGB: Above-ground biomass, BGB: Below-ground biomass

In terms of distribution based on dbh classes, the dbh class of ≥60 cm registered the highest total tree biomass in both areas at 263.95 t ha-1 in Deramakot FR, and 239.61 t ha-1 in Tangkulap FR. The lowest values were given in small dbh class of 10.0 – 19.9 cm also in both forest reserves at 45.93 and 41.61 t ha-1 of biomass respectively. Approximately 45-50% of biomass was in trees ≥ 60 cm dbh size class whereas small trees of <20 cm dbh only contributed about 8-9 % of the total. The distribution among the dbh classes (the highest to lowest values) was according to dbh size class in Deramakot FR, but, it was not the case in Tangkulap FR where the second highest values of biomass was in dbh class of 20.0 – 29.9 cm. This implies the significant contribution of pole-size trees in the accumulation of biomass in Tangkulap FR. On the other hand, the main difference in biomass values between the two reserves was found in the dbh class 40.0 – 49.9 cm whereby 72% more was registered in Deramakot FR than in Tangkulap FR. The general finding can be drawn from






this results is the amount of tree biomass tends to be influenced more by the dbh size and height of the tree than the number of stems. As a comparison with the other studies in lowland forest in Malaysia, Kato et al. (1978) estimated total above-ground biomass of 475 t ha-1, while Niiyama et al. (2009) estimate of total below-ground biomass and above-ground biomass at 95.9 and 536 t ha-1 respectively of trees with >5 cm dbh in Pasoh FR, Negeri Sembilan. The above-ground biomass values in present study, particularly in Deramakot FR were slightly higher than the former but slightly lower than the latter. However, the ground biomass of 475 t ha-1, while Niiyama et al. (2009) estimate of total below values in both areas (Deramakot and Tangkulap FRs), were relatively lower than those values reported by Niiyama et al. (2009). A possible reason for the lower value reported in this study was the trees measured were >10 cm dbh, thus the values may be under estimated. The result shows that the Deramakot FR forest still retains a high amount of biomass and is capable to recover after harvesting. The value of tree biomass usually depends on the forest types where the studies are conducted. These reported studies used allometric equations derived by Kato et al. (1978) to estimate tree biomass in their respective study areas. For instance, Mohd Ridza (2004) estimated the above-ground biomass of logged-over lowland dipterocarp forest in Lepar and Tersang FRs, Pahang at about 399.01 and 383.05 t ha-1 respectively. Further, Rohani (2008) reported the above-ground biomass in a limestone hill area was 316.3 t ha-1, which was lower than in a lowland area of 368.2 t ha-1 at Kenong Forest Park, Pahang. Meanwhile, Raffae (2003) reported above-ground biomass of an island in Langkawi, Kedah, Malaysia to be about 529 t ha-1. The biomass of a montane forest in Fraser’s Hill was estimated at 218.7 t ha-1 (Petol 1994) and 306.40 t ha-1 (Shamsul 2002). The biomass amount estimated from those studies and the current study are varied, indicating that various forest ecosystems have various productivities which are reflected through their biomass. This study recorded five leading families and genera based on tree biomass in Deramakot FR and Tangkulap FR (Table 5). As for basal area and standing volume, both reserves also recorded the family of Dipterocarpaceae as having the highest biomass at 368.56 t ha-1 for Deramakot FR and 309.15 t ha-1 for Tangkulap FR, therefore contributing nearly 64.14% and 66.39% of the total biomass in each forest reserve respectively. The second highest was Euphorbiaceae at 33.59 and 35.85 t ha-1 of biomass in Deramakot FR and Tangkulap FR respectively, followed by Sterculiaceae, Anacardiaceae and Leguminosae in Deramakot FR and Tangkulap FR respectively, and finally by Myrtaceae in both areas. It was also observed that the differences in biomass between the highest and the second ranks were substantial at about 58%. At genus level, Shorea had the highest tree biomass values in both areas at 236.13 and 115.28 t ha-1 respectively. The genus thus contributed nearly 41.09% and 24.76% of the total in each forest reserve respectively. Nonetheless, it was nearly two-fold greater in Deramakot FR compared with Tangkulap FR. Both areas had a similarity of genera except for Parashorea and Scaphium. However, the tree biomass of Macaranga was 42% greater in Tangkulap FR (31.82 t ha-1) than in Deramakot FR (22.32 t ha-1). The pioneer trees may not accumulate as much biomass per unit area as similar-sized persistent forest species because of their low densities and short life spans (Jordan & Farnworth 1980 in Pinard & Putz 1996).




Journal of Advance Management Research, ISSN: 2393-9664 (JAMR)http://www.jamrpublication.com email id- [email protected] Page 281

Table 5. The top five families and genera based on tree biomass and carbon content values in Deramakot FR and Tangkulap FR (figures in

brackets are the percentages of the total)

Rank Deramakot Forest Reserve Tangkulap Forest Reserve

Family N Biomass (t ha

-1)

Carbon (t ha

-1)

Family N Biomass (t ha

-1)

Carbon (t ha

-1)

1 Dipterocarpaceae

375 368.56 184.28 (64.14) Dipterocarpaceae

298 309.15 154.57 (66.39)

2 Euphorbiaceae 113 33.59 16.79 (5.85) Euphorbiaceae 194 35.85 17.93 (7.70)

3 Sterculiaceae 18 26.98 13.49 (4.70) Sterculiaceae 18 18.26 9.13 (3.92)

4 Anarcadiaceae 67 17.95 8.97 (3.12) Leguminosae 22 9.66 4.83 (2.07)

5 Myrtaceae 33 14.76 7.38 (2.57) Myrtaceae 41 9.38 4.69 (2.01)

Genus

1 Shorea 260 236.13 118.07 (41.09) Shorea 158 115.28 57.64 (24.76)

2 Dryobalanops 26 59.30 29.65 (10.32) Dipterocarpus 52 91.70 45.85 (19.69)

3 Parashorea 40 39.18 19.59 (6.82) Dryobalanops 53 65.13 32.57 (13.99)

4 Macaranga 37 23.32 11.66 (4.06) Macaranga 150 31.82 15.91 (6.83)

5 Dipterocarpus 26 22.91 11.45 (3.99) Sacphium 11 17.44 8.72 (3.75)

N: Number of individuals






c) Carbon stock As for the carbon (C), the estimated carbon contents in the study areas ranged from 20.81 to 287.32 t ha-1, followed the same proportional pattern as total tree biomass. Total carbon stock for the entire area of Deramakot FR (55 083 ha) and Tangkulap FR (27 550 ha) were 15.83 and 6.41 million tonnes or 287.32 and 232.84 t C ha-1 respectively with approximately 19% occurring belowground. Other findings of carbon stocks related studies on various forest types in Malaysia also showed variable results which is summarized in Table 6. Generally, the total carbon stock in this study area (i.e. Deramakot FR) of logged-over forest was comparable with or even higher than those of several sites of various forest types except for Semangkok and Bukit Lagong FRs (Abd Rahman & Philip 2009). In a Global Forest Resources Assessment 2010, the estimated total carbon stock in a living forest of Malaysia in 2010 was reported as 3212 million tonnes or 157 t ha-1 (FAO 2010). Therefore, it indicates that the residual stands in the RIL area of Deramakot FR are capable to retain a substantial amount of carbon stock after harvesting relative to mature secondary and undisturbed primary forests.

Table 6. Above-ground and below-ground carbon stock values in different forest types of

Malaysia Carbon stock (t ha-1)

Forest type Above-ground Below-ground Total

HF-Semangkok FR 282.0 67.90 349.92 HF- Bukit Lagong FR 281.1 68.30 349.42 LF-Sungei Menyala FR 177.2 35.70 212.86 LF- Pasoh FR 157.1 31.1 188.22 PSF-Pekan FR 171.3 34.40 205.74 MSF-Matang FR 203.70 76.06 279.76 LF- Deramakot FR* 242.01 45.32 287.32 LF- Tangkulap FR* 195.46 37.38 232.84

HF: Hill forest, LF: Lowland forest; PSF: Peat-swamp forest; MSF: Mangrove-swamp forest. (*): Denotes the results from present study Source: Adapted from Abd Rahman & Philip (2009)

Overall, carbon stocks in the plots of Deramakot FR were greater in absolute values compared with the plots in Tangkulap FR. The study shows that the regenerated forest areas under RIL had greater carbon stock by 54.48 t ha-1 or 23.40% more carbon than area of CL. Extrapolating for the entire area, RIL brought a net addition of about 3.0 million tonnes of carbon for 55 083 ha. The results of the study are consistent with the findings obtained from other previous studies. In a study to assess the forest biomass retained by reduced-impact logging at lowland productive forest of Ulu Segama in Sabah, Pinard and Putz (1996) estimated that the total tree biomass in a RIL method area was 268 t ha-1 compared with 176 t ha-1 in a conventionally logged area, one year after logging. It showed that the RIL area had thus retained more biomass at about 23% to the total amount of original pre-logging biomass than the CL. In a similar study in Amazonian Brazil, where forests were logged much less intensively, the benefit of improved timber






harvesting practices was estimated to be 7 t C ha-1 (Keller et al. 2004 in Putz et al. 2008). In another study, using remote sensing analyses, Sam et al. (2008) in their study in Sabah, found that the RIL area contained about 33 tC ha-1 or 26% more carbon as compared to the CL. Comparatively, it can be concluded that Deramakot FR had a relatively higher amount of total tree biomass corresponding to its higher carbon stock than Tangkulap FR, due to its greater number of stems and larger dbh trees. This probably demonstrates that by improving harvesting practices, such as via RIL, fewer trees are killed or damaged during logging thereby creating healthier residual stands and, consequently, more carbon remains in the forest in living trees. In contrast, the degraded forests tend to have fewer large trees and, consequently, have much lower stores of biomass (Brown et al. 1991), as in Tangkulap FR. Pinard (1995) in describing the distribution patterns of biomass, species richness and sapling density across habitats in a logged forest suggest that even at 18 years after conventional logging, areas with soil disturbance are less productive than areas without logging. Moreover, from a climate change point of view, excessive of soil disturbance, logging residues and damage to residual trees could cause increased emissions of CO2 and other greenhouse gases and decreases the capacity of the residual forest to sequester carbon. Adoption of the RIL system may provide a low-cost method of maintaining the carbon sequestration functions (Boscolo et al. 1997; Putz & Pinard 1993), and therefore should be encouraged to be used widely in timber harvesting operations. At the same time, expanding the forest cover (e.g. afforestation, reforestation and adds protected areas) and/or maintaining or improving the existing forest (e.g. improved silvicultural practices, forest protection from fire and disease; and sustainable forest management) also increase terrestrial carbon storage. The results of this study are consistent with the findings of Forshed et al. (2006, 2008), who reported that supervised logging (SL) which is equivalent to RIL, gave rise to denser residual stand and basal area than conventional logging in absolute numbers by 54.50 trees ha-1 and 1.6 m2 ha-1 respectively. Moreover, Forshed et al. (2006, 2008) also further revealed that more stems survived on SL area of about 20% (all species) and 21% (dipterocarps) as compared to CL. Further, RIL areas contain more undamaged trees and more trees in the larger diameter classes than CL areas and so the residual trees in RIL sites will probably have larger volume increments than residual trees in conventional sites (Pinard & Putz 1996; Sist et al. 2003). If residual stands contain more trees of larger dbh than those conventionally logged, future yields of timber are also likely be higher. Several studies throughout the tropic have also demonstrated RIL to be more ecologically benign than conventional logging (Boltz et al. 2003). Therefore, it is clear that implementation of RIL techniques in tree harvesting operations help to minimize damage to residual stands, indicated by the higher tree density, greater basal area and volume relative to conventional logging. At the same time, it creates the environment for healthier residual trees which is better suited to dipterocarps regeneration, as reflected by the denser trees in the medium diameter classes and superiority of dipterocarps populations.






Kyoto Protocol also recognized the role of forests and forest management in reducing CO2 emissions. Although improved forest management in developing countries is yet to be eligible for carbon credits at least for the first commitment period of 2008-2010 under this protocol, it will however be considered for future commitment periods (Smith & Applegate 2009). At present, the economic value of above-ground and below-ground forest carbon in carbon markets is relatively low, and as a result, the current impact of carbon sequestration of forest management planning is relatively low (Bettinger et al. 2009). Carbon prices vary among regions and projects, as well as over time, so any single value for carbon stored in forests should be considered as notional, particularly given that the scale of the market will be strongly influenced by Reduced Emissions from Deforestation and Forest Degradation (REDD) implementation. Based on reviews of forest carbon market prices and voluntary carbon market, Camphell et al. (2008) had suggested that the value of forest carbon is likely to range from USD1−15. However, the mid-range estimates of carbon price traded at the Chicago Climate Exchange (CCX) in mid-2009 adopted by Lian and Rhett (2010) is appropriate as a conservative value to convert carbon stocks in the study area to financial values. At USD4 t-1, the total carbon stocks in Deramakot and Tangkulap FRs would be around USD63.31 and 25.66 million respectively. On the other hand, to convert carbon loss (due to the conventional logging practice against RIL) to financial values, the difference of carbon value (54.48 t ha-1) are multiplied by the default conversion factor of 3.66 to obtain tCO2e (IPCC 2007). The CO2 equivalent tonnes are then multiplied by carbon price (USD4 tCO2e-1) to provide an estimate of the total financial value of carbon emissions, thus, hypothetically, the value of carbon loss due to conventional logging would be about USD22 million for the whole area of Tangkulap FR.

Conclusion The study has succeeded to determine the status of biomass and carbon stocks of tree communities of two regenerated lowland dipterocarp forests of Deramakot and Tangkulap FRs. The overall results with respect to the parameters being studied have demonstrated that there was variation between the two areas. The Deramakot FR, which was associated with RIL, produced higher biomass and carbon stock over the Tangkulap FR which had been conventionally logged. The RIL techniques constitute a substantial step toward sustainable management. A further improvement in RIL is the integration of silviculture principles, guidelines, and practices. These techniques should in particular aim to keep extraction rates below an acceptable threshold compatible with timber yield capability, limit the impact of harvesting on tree species’ diversity and composition, and maintaining timber species’ populations by reducing the impact on logging. Perhaps the main significance of this study is that it shows, a well-managed harvesting practice could reduce damage to the residual stands and capable in maintaining a level of richness and composition of forest tree communities comparable to mature secondary or undisturbed forests. Secondly, it could substantially reduce carbon loss from forest degradation due to logging. A good and healthier forest would certainly provide a range of environmental benefits and






ecosystem services. Besides that, the information from this study can serve as reference to the potential productivity of a different forest type in Malaysia. It is also useful in the initial estimation of carbon benefits whenever forestry projects are included under the Clean Development Mechanism (CDM) of the Kyoto Protocol. For example, the data obtained could be used to establish the baseline or reference case for avoided logging and RIL projects. This study is still far from perfect because there are other ecological aspects that need to be accounted for. Therefore, it should be continued and expanded. Based on these studies, the following recommendations are suggested: i. The role of tropical rainforests is becoming more important to mitigate the effects of

climate change, therefore, it is suggested that consideration should be given to incorporate biomass-carbon related aspects in any forest management and planning.

ii. Forests, like other ecosystems, are affected by climate change. In some places, impacts may be negative, while in others they may be positive. How forest trees respond to the climate change is a critical research question and area of study to be explored.

iii. Further studies are required along the lines suggested and the establishment of yield plots as a matter of routine district work, to provide a broader base on which forest management decisions can be made and this should be seriously considered.

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