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The biodiversity and complexities of natural tropical forests are known as the lives that depend on each other within ecosystems, species and genetics. Thus, the tropical forests provide variety of …

The biodiversity and complexities of natural tropical forests are known as the lives that depend on each other within ecosystems, species and genetics. Thus, the tropical forests provide variety of products and services for human over century and play disproportionally important role in the global carbon cycle and biodiversity conservation. However, forest fragmentation results because the spatial scales of resource extraction do not match the scales of natural disturbance that shaped the evolution of the landscape. This is because until the 1990s many tropical countries had no recent published, or stated, sustainable forest management; and also a stated yield or stock may not correspond to a government’s actual forest management plan, i.e. its true attitude and intentions. Assessment of sustainability however, is often lacking or incomplete at the time a system is adopted.
To manage forests to achieve sustainable productive capacity for future generation have not also enough but Southeast Asian countries cut forests illegally. Therefore, strategic implementation on the uses of forest products should then be carefully considered. Strategic management planning according to available natural potential capacities should also evaluate with caution because natural stand structure will change after disturbances resulting in extend the rotation lengths. Maintenance of productive capacity is one of the most important criteria for sustainable forest management, but very little is known about productive capacity of tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia, but there have been lack of scientific evaluations of them.
This dissertation would be an important report for production forest management of ECE/FAO, which it is not available yet in this country and especially in the tropics of Main Land of Southeast Asia. The results of this study would be successful experimental indicators before they will be approved to go in to effect for harvesting.

In order to ensure sustainable uses of forests for long-term uses as mentioned in the ECE/FAO, there are urgent needs to know the potential capacity and its dynamics of natural tropical forests, which are very important information for managers to make plan and to decide rotation lengths for next harvestings. The below objectives would serve a framework within criteria 2 and indicators of Montréal Process in 2007 presented in Fig. 1 and Fig. 2. This dissertation aims at (1) assessing stand dynamics and structure of natural seasonal tropical forests (2) planning procedures and (3) selecting appropriate methods for estimating annual allowable cut at a suitable rotation length.

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  • 1. Evaluating productive capacity of tropical seasonal forests in Cambodia Kao Dana 2010
  • 2. Evaluating productive capacity of tropical seasonal forests in Cambodia Dissertation in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Ph.D.) Kao Dana 2010 Kyushu University, Japan
  • 3. Table of Contents Chapters 1. General Introduction…………………………………………………………………………………………………………………………………………………………. 1.1. Background……………………………………………………………………………………………………………………………………………………………………. 1.2. Objectives…………………………………………………………………………………………………………………………………..……………………………………. 1.3. Past studies……………………………………………………………………………………………………………………………………………..………………………. 1.4. Study site………………………………………………………………………………………………………………………………………………………………….………. 1.5. Methods of this thesis…………………………………………………………………………………………………...………………………………………. 2. Assessment of Cambodian forest concession management planning based on criteria and indicators of Montréal Process: a case study of CFC Company ………………. 2.1. Introduction……………………………………………………………………………………………………………………………………………………………………. 2.2. Material and Methods……………………………………………………………………………………………………………..……………………………. 2.2.1. Data sources…………………………………………………………………………………………………………...……………………………………………. 2.2.2. Data analysis……………………………………………………………………...………………………………………………………………..………………. 2.3. Results and Discussion……………………………………………………………...……………………………………………………………...…………. 2. 4. Conclusion……………………………………………………………………………………………….……………………………………………………………………. 3. Stand structure of an ecosystem in Northern Cambodia: a case at concession management level in Preah Vihear Forests…………………………………………………………………………………………….……. 3.1. Introduction……………………………………………………………………………………………………………………………………………………………………. 3.2. Methods…………………………………………………………………………………………………………………………………………………………………………..…. 3.2.1. Forest Inventory………………………………………………………………………………………….……………………………………………………. 3.2.2. Data Processing……………………………………………………………………………………………………………………...…………………………. 3.2.3. Overview of study area………………………………………………………….……………………………………………………………..……. 3.3. Results and discussion…………………………………………………………………………………………………………………………………………. 3.3.1 Density and dispersion of trees……………………………………………………………………………………………………………. 3.3.2. Stratification………………………………………………………………………………………..………………………………………………………….……. 3.3.3. Species density……………………………………………………………………………………………….…………………………………………………. 3.4. Conclusion………………………………………………………………………………………………………………………………...……………………………………. 4. Structural characteristics of logged evergreen forests in Preah Vihear, Cambodia, three years after logging at coupe level ………..……………………………………………………………………………………………..…. 4.1. Introduction ……………………………………………………………………………………………….…………………………………………………………………. 4.2. Methods……………………………………………………………………………………………………………………………..………………………………………………. 4.2.1. Overview of study site……………………………………………………………………………………………………………………………..…. 4.2.2. Forest Inventory……………………………………………………………………………………………………………….………………………………. 4.2.3. Data processing……………………………………………………………………………………………………………………………………...…………. 4.3. Results………………………………………………………………………………………………………………………………………………………………………...………. 4.3.1. Tree family stand structure …………………………………………………………………………………………………...………………. 4.3.2. LGFE tree species structure……………………………………………………………………………………………………..……………. 4.3.3. UNFE tree species structure…………………………………………………………………………………………………………….……. 4.3.4. Tree harvested……………………………………………………………………………………………………………………………………………………. 4.3.5. Tree damaged…………………………………………………………………………………………………………………………………………..…………. 4.4. Discussion………………………………………………………………………………………………………………………………………………………………….……. 4.5. Conclusion…………………………………………………………………………………………………………………………………………………………...…………. 5. Stand dynamics of tropical seasonal evergreen forest in, Central Cambodia…………….. 5.1. Introduction……………………………………………………………………………………………………………………………………………………………………. 5.2. Methods……………………………………………………………………………………………………………...……………………………………………………………. 5.2.1. Study site and Data collection…………………………………………………………………………..…………………………………. 5.2.2. Data analysis………………………………………………………………………………….……………………………………………………………………. Page 1 1 2 3 6 9 13 13 16 17 17 19 23 26 26 28 28 30 30 34 34 36 36 39 42 42 44 44 47 49 50 50 52 53 54 55 56 58 59 59 60 60 60
  • 4. 5.3. Results and discussion…………………………………………………………………………………………………………………………………………. 5.3.1. Stand structure……………………………………………………………………………………………………………………………………...……………. 5.3.2. Diameter increment………………………………………………………………………………………………………………………………………. 5.3.3. Recruitment, Mortality and Illegal Cut…….…………………………………………………………………………………. 5.3.4. Volume increment………………………………………………………………………………………….………………………………………………. 5.4. Conclusion…………………………………………………………………………………………………………………...…………………………………………………. 6. Potential woodfuel supply and demand of two community forestry in Kampong Chhnang, central Cambodia………………………………………………………………………………………………………………………………………. 6.1. Introduction……………………………………………………………………………………………………………………………………………………………………. 6.2. Methodologies……………………………………………………………………………………………………………………………………………………..………. 6.2.1. Study site and history…………………………………………………….……………………………………………………………………………. 6.2.2. Data collection……………………………………………………………………………………..……………………………………………………………. 6.2.3. Data processing and analysis…………………………………………………………………………………..……………………………. 6.3. Result………………………………………………………………………………………………………………………………………………………………………………...…. 6.3.1. Species and stand structure……………………………………………..………………………...…………...………………………………. 6.3.2. Supply and demand increments…………………………………..………………………………………...…………...………………. 6.3.3. The comparison between supply and demand………………………………………………...……………………. 6.4. Discussion………………………………………………………………………………………………………………………………………………………………….……. 6.4.1. Species and stand structure……………………………………………………………………………………………………………………. 6.4.2. Biomass supply increment………………………………………………………………………………...……………………………………. 6.4.3 Biomass demand increment……………………………………………………………………………………………………………………. 6.4.4. Woodfuel supply and demand………………………………………………………………………………….…………………………. 6.5. Conclusion………………………………………………………………………………………………………………………………………………………...……………. 7. Chapter 7: Evaluating of the Cambodian yield regulation for tropical natural forest management…..…………………………………………………………………………………………………………………………………………………….……. 7.1. Introduction……………………………………………………………………………………………………………………………………………………………………. 7.2. Methods…………………………………………………………………………………………………………...……………...…………………………………………………. 7.2.1 Study site………………………………………………………………………………………………………………………………………………………………..… 7.2.2 Data processing………………………………………………………………………………………………………………..…………………………………. 7.3. Results and Discussion…………………...……………………………………………………………………………………………...……………………. 8. General discussion and conclusion………………………………………………………...……………………………………………………………. 8.1. Usefulness and limitation…………………………………………………………………………………...………………..……………………………. 8.2. Recommendation and conclusion…………………………………………………………………………………………………………...…. Summary………………………………………………………………………………………………………………………………………………………………………………………………... Acknowledgements…………………………………………………………………………………………………………………………………………………………………...…. List of references………………………………………………………………………………………………………………………………………………………………………….…. List of tables…………………………………………………………………………………………………………………………………………………………………………………..……. List of figures……………………………………………………………………………………………………………………………………………………………………….……………. List of acronyms…………………………………………………………………………………………..…………………………………………………………………….……………. 61 61 63 64 65 66 67 67 68 68 70 72 74 74 75 77 77 77 78 78 79 81 83 83 84 84 87 90 92 92 93 96 99 100 113 114 115
  • 5. This thesis was compiled as partial accomplishment for Doctor of Philosophy (Ph.D.) under the coordination and supervision committee composed of Professor, Associate Professor of the Laboratory of Forest Management Professor Dr. Shigejiro YOSHIDA Laboratory of Forest Management Faculty of Agriculture …………………………………….……….……… (Professor/Coordinator) Kyushu University Professor Dr. Nobuya MIZOUE Laboratory of Forest Management Faculty of Agriculture Kyushu University …………………………………….……….……… (Academic Supervisor)
  • 6. Declaration I would like to sincerely declare that this thesis topic: “Evaluating productive capacity of tropical seasonal forests in Cambodia” is my original work. It is the results of my own research and efforts except for the reference cited with the exception of my all academic professors, tutors and special acknowledgements. This is the first one of its type and has not been submitted in any other Institution or Publisher. Fukuoka, 29 July 2010 ………………………………………………….. Dana KAO
  • 7. Abstract Evaluating productive capacity of tropical seasonal forests in Cambodia Dana KAO Laboratory of Forest Management, Faculty of Agriculture, Kyushu University, Japan There have been increasing concerns on sustainable forest management (SFM) in tropical natural forests, being disproportionately important in the global carbon budget and biodiversity conservation. Maintenance of productive capacity (Fig. 1) is one of the most important criteria for SFM, but very little is known about productive capacity of tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia. About of 34% of Cambodia is classified into production forests, and a broad set of regulations and guidelines of forest management practices has been developed, but there have been lack of scientific evaluations of them. This study aims at Fig. 1 Research Framework evaluating indicators of productive capacity of tropical seasonal forests in Cambodia, mainly focusing on stand structure, dynamics and sustained yield of unlogged and logged evergreen forests (Fig. 1). First, the 25-year strategic forest concession management plan for a company was evaluated based on criteria and indicators of Montréal Process, focusing the criteria 2; “maintenance of the productive capacity of forest ecosystems”. There were 33 sub-indicators of Criterion 2 of the Montréal, and only 52% (17 sub-indicators) were fulfilled in the concession management plan. This suggests that indicators related to growing stock for each of forest types and species group, plantations of native and exotic species and non-timber forest products should be included in forest concession management planning. Second, stand structure of natural evergreen forests in Preah Vihear, Northern Cambodia was evaluated using data from a total of 120 plots, obtained from large-scale inventory by a concession. The density, volume and basal area (BA) of trees ≥10cm diameter at breast height (DBH) were 220.3 trees/ha, 151.9 m3/ha and 11.0 m2/ha, respectively, in logged evergreen forest (LGFE) and 241.9 trees/ha, 185.8 m3/ha and 13.5 m2/ha, respectively, in unlogged evergreen forest. The density, volume and BA of harvested trees at DBH≥50cm in LGFE were 3.0 trees (22.4% of total), 22.2 m3 (29.5%), and 1.6 m2 per hectare (27.1%), respectively. The density, volume and BA of damaged trees at 10-49 cm DBH in LGFE were 12.6%, 25.3% and 40.4%, respectively.
  • 8. Third, stand dynamics of seasonal evergreen forest in central Cambodia were estimated from 20 plots measured in 1998 and 2003. Data for all trees with DBH≥ 10 cm and for commercial species DBH≥ 10 cm or DBH≥ minimum diameter cutting limit (MDCL) were evaluated. The mean DBH increment was 0.33 cm and 0.32 cm; mean mortality rates were 2.4% and 0.5%; mean recruitment rates were 2.5% and 1.4%; and volume increments were 1.09 and 0.86 m3/ha for all and commercial species, respectively. These values are similar to those reported from tropical rain forests in Amazon and Southeast Asia. Estimated volume increment 0.86 m3/ha/year for commercial trees with DBH≥MDCL was significantly larger than the figure 0.33 m3/ha/year previously used in Cambodian management systems. Finally, the Cambodian new guideline for estimating annual allowable cut (AAC) was evaluated using inventory data from a concession company in Northern Cambodia. Under this guideline, harvesting is allowed only for commercial species that fulfill recovery levels (RLs) of number of harvestable trees with size more than MDCL in 25 years after logging; 60% and 90% of RLs are currently adopted for unlogged and logged forests, respectively. Two scenarios (S1 and S2) were evaluated under different RLs from 60 to 100%. S1 is based on the guideline’s assumption; damaged rate 10.0%, DBH increment 5.0 mm and mortality 1.0%, and S2 is based on my new findings as in the previous chapters such as damaged rate 12.6%, DBH increment 3.2 mm and mortality 2.4%. The AACs tended to decrease with increasing RLs, and the values from the current guideline (S1) were always larger than those from S2. AACs Fig. 2 Annual allowable cut (AAC) under different recovery estimated from S1 were 35.5 levels (RLs). “None” indicates the results without accounting m3/ha/year (at RL 60%) and 39.1 RL. m3/ha/year (at RL 90%) for logged and unlogged forests, being much higher than growth potential (21.5 m3/ha/25years = 0.86 m3/ha/year×25 years) (Fig. 2).The results seek for updating information on stand dynamics used in the current guideline and reconsidering RLs to be fulfilled. In the case of this study sites, adapting more than 70% of RL is acceptable under the updated data in terms of growth potential. However, around 10 m3/ha of AAC is highly recommended to achieve the ideal RL of 100% that ensures sustainability of species diversity as well as growing stock. Interestingly, this 10 m3/ha of AAC is the same to one proposed by van Gardingen et. al (2006) for primary tropical rain forest in the Amazon, based on the modeling approach under the cutting cycle of 30 years. In conclusion, differences in some indicators of productive capacity, such as tree and stand growth, existed between the previous assumed values and ones found newly in this study, calling for revision of the Cambodian management planning guidelines. Especially, it should be noted that the current Cambodia’s allowable cut level is larger than growth potentials. Future evaluations on long-term dynamics of logged and unlogged sites may be critical for more accurate evaluation of sustainable productive capacity of tropical seasonal forests.
  • 9. Chapter 1: General Introduction 1.1. Background The biodiversity and complexities of natural tropical forests are known as the lives that depend on each other within ecosystems, species and genetics. Thus, the tropical forests provide variety of products and services for human over century (FAO, 2001) and play disproportionally important role in the global carbon cycle (Malhi and Grace, 2000; Clark et al., 2001) and biodiversity conservation (e.g. Myers et al., 2000). In developing countries, natural tropical forests provide a lot of benefits for indigenous people to use timber and nontimber products. Natural tropical forests also provide energy, food, medicine, shelter and livelihood (Menzies, 2002; Carter, 2005; FAO, 1986). Tropical forests are invaluable to protect fertile soil, to contribute general socio-economic development, to produce rain in the tropics and to increase overall productions (FAO, 1997). However, forest fragmentation results because the spatial scales of resource extraction do not match the scales of natural disturbance that shaped the evolution of the landscape (Hobbs, 2003). Tropical deforestation was still proceeding at 14.2 million hectares per annum in the 1990s, and only 5.5% of all forest in developing countries was under formal management plans in the year 2000 (FAO, 2001). This is because until the 1990s many tropical countries had no recent published, or stated, sustainable forest management (Poore, 1989; Poore and Thang, 2000); and also a stated yield or stock may not correspond to a government‘s actual forest management plan, i.e. its true attitude and intentions (Jianbang et al, 2001). Assessment of sustainability however, is often lacking or incomplete at the time a system is adopted (Dawkins and Philip, 1998; Southgate, 1998). Natural tropical forests can provide a wide range of essential economic, social and environmental goods and services for the benefit of current and future generations (Montréal Process, 2007). However, some developing countries are challenging to manage their forests at international standard. Criteria and indicators gained increasing international attention as a tool to monitor, assess and report on forest trends at national and global levels (Rio Earth Summit). Today, 150 countries are engaged in one or more regional and international criteria and indicators processes but most of developing countries do not have ability to implement to gain fully sound sustainable forest management. Especially, to manage forests to achieve sustainable productive capacity for future generation has not also enough but Southeast Asian countries cut forests illegally. Therefore, strategic implementation on the -1-
  • 10. uses of forest products should then be carefully considered. Strategic management planning according to available natural potential capacities should also evaluate with caution because natural stand structure will change after disturbances resulting in extend the rotation lengths. Maintenance of productive capacity is one of the most important criteria for sustainable forest management, but very little is known about productive capacity of tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia. All Cambodia forest was 59% of the total land and has a change rate of 0.6% per year (Table 1.1; FA, 2004; FA, 2007). About of 34% of Cambodia is classified into production forests, and a broad set of regulations and guidelines of forest management practices has been developed, but there have been lack of scientific evaluations of them. Fig. 1.1. Framework of this study 1.2. Objectives In respond to, tropical forests have been cut illegally without certification at a sustainable standard. In respond to emergent needs to improve production forest capacity of tropical forest ecosystems, the purpose of this study is to support criteria 2 of The Montréal Process (Fig. 1.1 and Fig. 1.2) and also to provide the strategic implementation of production forests in a large scale (forest concession level) and small scale (coupe level and -2-
  • 11. community forestry level). By identifying the main elements of sustainable forest management, this study provides a means of assessing the available resource at disturbed and undisturbed natural tropical forests in Northern Part and Central Part of Cambodia. This thesis enhances strategy to implement on the method uses to gain sustainable productive capacity of ecosystem of 7 criteria (Fig. 1.2). In order to ensure sustainable uses of forests for long-term uses, there are urgent needs to know the potential capacity and its dynamics of natural tropical forests, which are very important information for managers make plan and to decide rotation length for next harvestings. The below objectives would serve a framework within criteria 2 and indicators of Montréal Process, (2007) presented in Fig. 1.1 and Fig. 1.2. This dissertation aims at (1) assessing stand dynamics and structure of natural seasonal tropical forests (2) planning procedures and (3) selecting appropriate methods for estimating annual allowable cut at a suitable rotation length. This dissertation would be an important report for production forest management, which it is not available yet in this country and especially in the tropics of Main Land of Southeast Asia. The results of this study would be successful experimental indicators before they will be approved to go in to effect for harvesting. 1: Conservation and biological diversity 4: Conservation and maintenance of soil and water resources 2a: MAINTENANCE OF PRODUCTIVE CAPACITY OF FOREST ECOSYSTEMS SUSTAINABLE FOREST MANAGEMENT (SFM) 6: Maintenance and enhancement of longterm multiple socio-economic benefits to meet the needs of societies 3: Maintenance of forest ecosystem health and Vitality 5: Maintenance of forest contribution to global carbon cycles 7: Legal, policy and institutional framework Fig. 1.2. Seven criteria of sustainable forest management a The criteria that this dissertation was mainly focus on Source: Criteria and Indicators for the Conservation and SFM (Montréal Process, 2007) 1.3. Past studies In respond to the needs of products from natural tropical forests, Cambodia and the Southeast Asia should have forest certification for their sustainable production forest -3-
  • 12. management. The Sustainable Forest Criteria for managing natural forests; however, there have no enough strategic implementation. Some of examples on the needs of forest product are found as below. Markets and demand for Cambodian forest products are timber, fuelwood as nontimber forest products (NTFP) and other NTFPs. Wood is principle source of fuel of the Cambodian population and fuelwood is the largest use of wood harvested in Cambodia. Fuelwood extracted per person from the forests was estimated 0.6 m3/year (The WB, UNDP and FAO, 1996). Above ground biomass supply per person 0.142 Mg/year was estimated based on Top et al (2006). Cambodia people prefer wood fuel because of cheap price. In Cambodia, Abe et al. (2007) found that although biomass gasification provided cheaper power than diesel generators, consistent supply and barriers to growing wood were key constraints. Cambodia exported industrial round-wood reached 499 thousand m3 in 1992 declining to only 301 thousand m3 for 1994 (FAO, 1997). Fig. 1.3: General study sites There are good guidelines for sustainable forest managements such as Forest Stewardship Council, ITTO Policy Development Series No 15 (ITTO, 2005) and Criteria for the Conservation and Sustainable Management of Temperate and Boreal Forests (Montréal Process, 2007). In order to fulfill the Forest Stewardship Council performances, the dissertation aims, generally, to support some parts of the 10 principles: compliance with law, tenure and use rights and responsibilities, indigenous peoples‘ rights, community relations -4-
  • 13. and workers‘ rights, benefit from the forests, environmental impact, management plan, monitoring and assessment, maintenance of high conservation value forests and plantations. Fig. 1.4. Influence of water and temperature regimes on vegetation Source: FA, DANIDA, German Development Service, (2003) Fig. 1.5. Distribution of meteorological station in relation to elevation of Cambodia Source: Forestry Administration, Danida and German Development Service, (2003) -5-
  • 14. Fig. 1.2 presented the seven sustainable criteria: enabling conditions for sustainable forest management, forest resource security, forest ecosystem health and condition, flow of forest produce, biological diversity, soil and water, and economic, social and culture aspects. Another reason is that the forest resource is becoming scare since the population growth is increasing to be faster than natural growth. The most important relative objectives of this thesis are to support the indicators in criteria of Sustainable Productive Capacity, which proposed by a professional organization namely as the International Tropical Timber Organization and Montréal Process Working Group. 1.4. Study site Forests have always been a defining element of the economy, culture and environment of Cambodia. Until the middle of the century, forests totaled over 13 million ha, or over 73% of the country‘s land area in 1973 (The WB UNDP and FAO, 1996). The best data available indicate that 1.4 million ha of forests were converted and much of the remaining area has been negative affected from 1973 – 1993 (Fig. 1.10). As accessible forests have disappeared, the composition of demand for timber and nontimber forest products has also shifted. The more heavily populated areas of Cambodia, indications of possible fuelwood shortages are worsening and foreign demand for Cambodia logs and processed wood exported has grown faster than the regulatory capacity of the Cambodian government. The dissertation consists of 3 study sites (Fig. 1.3) locate in Cambodia, main land of Southeast Asia. Cambodia has the total area 181,035 km2 consisting of 24 provinces and cities, 185 districts, 1,621 communes, and 14,073 villages (The WB, UNDP and FAO, 1996; FA 2007; NIS, 2003). Total population was 13,388,910 (General Population Census of Cambodia 2008) with the population density 75 per km2. The annual population growth rate was 1.54% (NIS, 2003). Cambodia locates in tropical seasonal rain areas (Fig. 1.4). The minimum rainfall was 800 mm to maximum >3800 mm in coastal western part (Fig. 1.6) with the average annual rainfall is 1,604 mm. Humidity is often high through the year with a mean of 80.3% (FA, DANIDA, German Development Service, 2003). The elevation was zero to 10 m above sea level in central and southern parts (Fig. 1.5). The length of dry season was longer than 4 months in northern parts (Fig. 1.7) with temperature 34°C in April, 21°C in January and the annual average of 28°C (Fig. 1.8). Hence the highlands of the -6-
  • 15. Cardamom Mountains, sustain forests that are adapted to cool temperature from December to February at <16.5°C (Fig. 1.9). Fig. 1.6. Distribution of rainfall regimes in Cambodia in mm Source: Forestry Administration, Danida and German Development Service, (2003) Fig. 1.7. Length of dry season in Cambodia Source: Forestry Administration, Danida and German Development Service, (2003) -7-
  • 16. This study focuses largely on commercial forest resource evaluation of sustainable productive capacity of natural tropical forest ecosystems in three different provinces of Preah Vihear (northern part), Kampong Thom (central part) and Kampong Chhnang (central part) (Fig. 1.3). Fig. 1.3 shows the location and Table 1.1 present the canopy by year. The study site in northern part is in Preah Vihear Province, which has the highest forest cover of up to 94% of the total forest cover. The study sites in central part are in Kampong Thom and in Kampong Chhnang Province, which have a forest cover of 51% and 40% of the total forest cover, respectively (Table 1.1). The dominant forest type was evergreen forests in Kampong Thom, deciduous forest in Kampong Chhnang and Preah Vihear (Table 1.1). Table 1.1: Forest cover and other land use of Cambodia and province‘s study sites based on LandSat image shot in the year 2002 and 2006 in hectare Forest types Evergreen forest Semi-FEb Deciduous forest Wood SLDc Wood SFEd Bamboo Other forests Total forests Non forest Grand total Whole Cambodia Ya-2002 Y-2006 3,720,504 3,668,902 1,455,091 1,362,638 4,833,138 4,692,098 138,939 37,028 150,017 96,387 28,952 35,802 1,065,706 971,341 11,392,347 10,864,186 6,768,323 7,296,456 18,160,670 18,160,674 Kampong Thom Y-2002 Y-2006 348,971 374,233 26,025 20,120 85,119 78,649 7,396 0 8,483 25,738 16 16 180,047 145,677 656,057 644,432 588,706 600,331 1,244,764 1,244,763 Kampong Chhnang Y-2002 Y-2006 16,097 16,156 6,219 6,136 150,484 147,175 1,405 845 44 44 0 0 39,675 38,423 213,924 208,779 315,538 320,682 529,462 529,461 Preah Vihear Y-2002 Y-2006 222,425 254,451 156,800 143,431 927,343 901,295 11,436 914 1,157 556 0 408 17,907 9,626 1,337,068 1,310,680 66,023 92,407 1,403,091 1,403,087 Note: Cambodia forest cover was 12,711,100 ha in 1973 decreased to 11,284,200 ha in 1993 with annual changes – 0.6% of the total country area 18,153,500 ha (The WB, UNDP and FAO, 1996) Source: Forest cover in the year 2002 (FA, 2005) and forest cover in the year 2006 (FA, 2007) a Year b Semi-evergreen forest c Wood shrub land dry d Wood shrub evergreen forest In 1993, the total Cambodian forest area of 11.3 million ha is divided among 4.8 million ha of evergreen forest, 4.3 million ha of deciduous forest, 1 million ha of mixed forest, 0.5 million ha of secondary forest and 0.7 million ha of edaphic forest – refers to flooded, flooded secondary and mangrove forests (The WB UNDP and FAO, 1996). In 1973, the total forest area of 12.7 million ha is divided among 6.9 million ha of evergreen forest, 4.8 million ha of deciduous forest and 1.0 million ha of edaphic forest (Table 1.1). The 20year periodic annual change of land resource dynamics was - 0.6% (Table 1.1). In 2002/2003, the total forest area was 11.4 million ha (FA, 2005) but in 2006, the total forest was 10.9 million ha (FA, 2007; Table 1.1). Therefore, in response to the changed forest canopy, the Cambodian Government and its predecessors developed a broad set of -8-
  • 17. regulations and guidelines to control and safeguard forest management practice with funds and technical support from the FAO, ADB, World Bank and several bilateral donors since 1996 (RGC, 1996; 1999; 2000; 2002; 2003; DFW, 1998; 1999; 2000a;b; 2001a,b). Additionally, five handbooks, prepared by the technical assistance team of the World Bank supported Forest Concession Management and control pilot project, were issued (WB, 2004a;b;c;d;e). By using these publications, objectives for strategic sustainable forest management were set. 1.5. Methods of this thesis In order to fulfill this thesis‘s objectives, the forest inventory over large area – concession level (Kao et al., 2010b), permanent sample plots and small area (community forestry level) were conducted in 3 different provinces. Data from these measurements were sorted and processed for tabulations to reach the objectives of each study section. This thesis included 6 different technical studies out of general introduction and conclusion, representing Chapter 2 to 7. Each Chapter presented limitation of key concerns, objectives, methodologies, results and discussions of joint other scientific articles, which had recommendation to forest sector locally and internationally. In order to gain sustainable production forests, this study set 2 sub-frameworks one as structure and another as dynamics by following the sustainable criteria and indicator of capacity of ecosystem (Fig. 1.1). This classification was because the evaluation of productive capacity would realize on these subframeworks. Variability for evaluations was set together with case studies for sample as strategic implementation. Fig. 1.8. Monthly mean temperature in Cambodia in °C Source: Forestry Administration, Danida and German Development Service, (2003) -9-
  • 18. Note: Tav is the average temperature, Tmin is the minimum temperature and Tmax is the maximum temperature In the first sub-framework named as ―Structure‖, evaluation of forest resource mobilization was presented in Chapter 3, 4 and 6 by forest type over unlogged, logged and degraded forests, respectively. In the second sub-framework named as ―Dynamics‖, evaluation of forest resource was done at production forests in order to understand the mortality, recruitment, illegal-cut and increments (Chapter 5). Chapter 7 scaled sustainable yield by comparing between natural capacity and growth capacity for evaluating the best method for harvesting implanting in this country. This Chapter 7 reported about whether growth could reach expected harvesting intensity or not. Chapter 2 assessed 25-year strategic plan as a case study to be a sample for decision makers to select the best plan based on sustainable management criteria. Key recommendation of each findings are also summarized in each discussion and conclusion of each Chapter 2 – 7 for a policy matrix and for strategic implementing to gain sound sustainable standard at production forests that are organized around the strategic issue raise in the dissertation framework (Fig. 1.1). Fig. 1.9. Distribution of low-temperature regions of Cambodia in °C Source: Forestry Administration, Danida and German Development Service, (2003) To explore the challenge of commercial quality of forest structure changes and SFM implication, this dissertation summarize what can now be discerned on key criteria and indicators of productive capacity. Domestic energy and timber are the largest source of demand for wood in Cambodia; commercial logging has a considerably greater economic significance (The WB UNDP and FAO, 1996). One of the most crucial considerations for - 10 -
  • 19. production forest management and investment is cutting intensity or allowable cut. The methodologies for estimating annual allowable cut was shown in FA, (2001) and updated for new annual allowable cut equation in FA, (2004), by level of management system – long-term plan, medium term plan and annual operational plan. This dissertation also practice and evaluated the method of annual allowable cut estimation as well. Cambodian forest harvesting intensity is expressed in terms of the volume of commercial timber to be removed during each entry to the harvested area or in term of the percentage of the standing commercial volume to be removed (FA, 2001). Parts of this thesis have been published in various journals, i.e., Chapter 4 informed concerning the structural characteristics of forests after impact logging (Kao and Iida, 2006), Chapter 2 assessed on management plan of a forest concession (Kao et al., 2005a) and Chapter 5 estimated the stand dynamic at evergreen forest (Kao et al., 2010a). Some parts have also been published as proceeding in the international and Japanese national conferences and workshops, i.e., Chapter 7 evaluated the annual allowable cut methods vs. forest increments in evergreen forest (Kao et al., 2004; Kao et al., 2008a), Chapter 6 assessed the supply and demand of fuelwood at 2 selected community forestry (Kao et al., 2008b). Additionally, some parts were also published in the book chapters, i.e., Chapter 3 presented a case at concession management level (Kao et al., 2005b). Fig. 1.10. Generalized distribution of vegetation in Cambodia Source: Forestry Administration, Danida and German Development Service, (2003) This study expected to reach Cambodian important stakeholders such as forest concessionaires, land concessionaires, community forestry, local people, government, non- - 11 -
  • 20. government organizations and forest conservationists, who participate in sustainable forest management as obvious methodologies in solving mutual conflicts of interests. These results also expected to reach the end users in some parts of Southeast Asia that have not yet been evaluated the supply and demands from natural tropical forests. Future important silviculture treatment of sub-criterion 3 should then be studied (Fig. 1.1). Extrapolations of these methods to an anticipated acceptable cutting cycle must be interpreted with caution by forest types. Ongoing restudy of this and other criteria for receiving forest certification are necessary to provide a strong basis for how to manage the production of the natural tropical forests (Fig. 1.2). - 12 -
  • 21. Chapter 2: Assessment of Cambodian forest concession management planning based on criteria and indicators of Montréal Process: a case study of CFC Company Keywords: Cambodia, Sustainable forest management, Criteria and indicators, Scaling, Forest concession, Strategic management 2.1. Introduction Forest fragmentation results because the spatial scales of resource extraction do not match the scales of natural disturbance that shaped the evolution of the landscape (Hobbs, 2003). Tropical deforestation was still proceeding at 14.2 million hectares per annum in the 1990s, and only 5.5% of all forests in developing countries was under formal management plans in the year 2000 (FAO, 2001). Forest is the essential component for human life in term of economics and environment. There is a need to extend the findings from visual images and content analyses to a wider context and different types of media in order to further examine the role of forestry industry and organizations in the public sphere (Kohsaka and Flitner, 2004). As signatory nations negotiate the implementation of the Framework Convention on Climate Change (UNCED, 1992), the role of forestry-based options for mitigating carbon dioxide emissions continues to be debated (e.g. Kyoto Protocol). Globally agreed-upon elements of criteria for sustainable forest management are extent of forest resources, biological diversity, forest health and vitality, productive functions of forests, protective functions of forests, socio-economic benefits and needs, legal and policy and institutional framework. Considerable international efforts also have focused in recent years on criteria for assessing forest issues. The United States signed the Santiago Agreement (Anonymous 1995) defining criteria and indicators for conserving and sustainably managing. Other efforts in Europe (Helsinki Process), tropical countries (Tarapoto Proposal), and Africa (Dry Zone Africa Initiative) are helping to develop a worldwide consensus on these topics. These criteria are now being used to develop the Global Forest Resource Assessment 2000 by the United Nations, and they served as the program theme for the 1997 World Forestry Congress in Antalya, Turkey. The Santiago Agreement identifies seven criteria for assessing sustainable forest management: (1) Conservation of biological diversity, (2) Maintenance of productive capacity of forest ecosystems, (3) Maintenance of forest ecosystem health and vitality, (4) Conservation and - 13 -
  • 22. maintenance of soil and water resources, (5) Maintenance of forest contribution to global carbon cycles, (6) Maintenance and enhancement of long-term multiple, socioeconomic benefits to meet the needs of societies; and (7) Legal, institutional, and economic framework for forest conservation and sustainable management. A fundamental sustainable forest management increasingly debated in the past two decades has been the need for human actions that lead to sustainable development that meets the needs of the present without comprising the ability of future generations to meet their needs (WCED, 1987). This debate has broadened to include notions of sustainability as a normative concept reflecting the persistence over an indefinite future of certain necessary and desirable characteristics of both ecological and human parts of an ecosystem (modified from Hodge 1997). Forest sustainability is a goal of many forestry organizations throughout the world. Managing forests sustainably involves recognizing interconnections among ecological, social, and economic systems to preserve options for future generations while meeting the needs of the present. Sustainability, like many concepts, is difficult to define in concrete terms. Many organizations are turning to criteria and indicators approach to help describe forest sustainability. Under this approach, criteria define broad categories of sustainability and indicators are specific measurements of each category (USDA, 2002). There are a host of efforts underway using criteria and indicators to describe forest sustainability. Notable among these is an effort commonly called the Montréal Process. This work is an outgrowth of the 1992 Earth Summit in Rio de Janeiro, Brazil. In 1995, the United States joined 11 other countries in signing a document establishing a set of 7 criteria and 67 indicators to track forest sustainability. Definition of the sustainable forest management criteria is a category of conditions or processes by which sustainable forest management may be assessed. Each criterion is characterized by a set of 9 to 20 indicators. An indicator is a qualitative or quantitative measure of an aspect of the criterion that can be observed periodically (Montréal Process Working Group, 1998). In fiscal year 2003, the forest reformed program supported the Cambodia missions in conducting analyses and specific targeted interventions to mitigate conflicts over forest resources. These conflicts contribute to political destabilization and economic decline as well as environmental destruction (USAID, 2004). The Forest Administration (FA, 2000) requires concession companies to set out in their sustainable forest management planning - 14 -
  • 23. (SFMPs) clear objectives for sustainable forest management over the concession area for the duration of the license through policy statement to which management and employees are committed. The FA can be congratulated for the thorough consideration of this topic in the planning process. The Planning Manual gives examples for the policy statement and several management objectives, which serve as guidance to the concessionaires. The Cambodian forest of 2.1 million hectares (11%) was degraded from 1973 to 1997 (Fig. 2.1). Cambodian tropical forests include the only partly continuous tropical forest in the world. However, it has annually suffered serious deforestation at 0.6% because of road building, mining and agricultural improvement expansion (Kim Phat et al, 2002, Kao, 2004). A large deforestation area has affected the climate change, biological diversity, hydrological cycle, soil erosion and degradation (CTIA and Kao, 2004, Kim Phat et al, 2004, Top et al, 2004). In the past, logging was an integral part of the ecosystem in Cambodia, affecting wildlife habitats, forest stand dynamics, soil properties, and watershed hydrology. Therefore, assessment on the how concessions manage the forest needs to be studied for government and other concerned organizations to constrain forest harvesting and management. How do successional pathways differ throughout the region by site landform, and with susceptibility to disturbance? Fig. 2.1. Cambodian Land use Map Source: Cambodian forest statistics to 2002 - 15 -
  • 24. At the present, Cambodia has 26 forest concessions, who manage the natural forest. By early 2003, 2 companies had been cancelled, 1 dropped out and 2 missed the deadline; of the remaining 9 concessions. Twelve forest concessions were required to revise and resubmit their plans, for further review (Table 2.1). As a result, 6 concessions have been provisionally approved for advancement to the compartment level (5-year) planning stage: Cambodia Cherndar Plywood Manufacturing Co Ltd, Everbright CIG Wood Co. Ltd, Colexim Enterprise, TPP Cambodia Timber Product Pte. Ltd., Timas Resources Ltd. and Samrong Wood Industry Pte Ltd. The focus on problem of concession management is the subject of this paper. Specifically, the purpose of this paper is to evaluate the accomplishment of CFC forest Concession Company to assess sustainable timber production and adaptability in the context of the Montréal Process of Criterion 2 and Indicators number 10, 11, 12, 13 and 14 for sustainable forest management (Montréal Process Working Group 1998). Table 2.1: Valid forest concession area in Cambodia No 1 2 3 4 5 6 7 8 9 10 11 Name Cambodia Cherndar Plywood Mfg.Co., Ltd. Casotim Enterprise Colexim Enterprise Everbright CIG Wood Co., Ltd. King Wood Industry Pte. Co., Ltd. Mieng Ly Heng Investment Co., Ltd. Pheapimex Fuchang Cambodia Co., Ltd.(1) Pheapimex Fuchang Cambodia Co., Ltd.(2) Pheapimex Fuchang Cambodia Co., Ltd.(3) Samrong Wood Industry Pte., Ltd. Silveroad Wood Products Ltd.(1) Silveroad Wood Products Ltd.(2) Timas Resources Ltd. TPP Cambodia Timber Product Pte., Ltd. Yourysaco Company Approved Date Area (ha) Preah Vihear Kratie Kampong Thom, Preah Vihear Kratie, Stung Treng Krotie, Stung Treng, Modul Kiri Kampong Thom, Kampong Cham, Preah Vihear 3/2/1996 9/4/1996 12/2/1996 8/8/1996 15/1/1998 103,300 131,380 147,187 136,376 301,200 27/2/1996 198,500 Krotie, Kampong Thom 15/03/1996 137,475 Stung Treng 15/03/1996 221,250 Stung Treng, Ratanak Kiri Siem Reap, Otdor Meang Chey Koh Kong, Pursat Koh Kong Kampong Cham, Kratie, Preah Vihear Siem Reap, Preah Vihear, Pursat, Koh Kong Pursat, Battambang 8/4/1998 22/08/1996 8/3/1998 8/4/1998 350,000 200,050 215,460 100,000 14/4/1996 161,450 3/4/1998 2/3/1998 395,900 214,000 3,874,028 Provinces/Municipality 12 Total Source: Cambodian forest statistics to 2002 (FA, 2003) 2.2. Materials and Methods There are 5 indicators of criterion 2, which deals with maintenance of the productive capacity of forest ecosystems. The focus is on a single Criterion (commonly referred to as - 16 -
  • 25. indicators 10 to 14), which addresses the ―maintenance of the productive capacity of forest ecosystems‖. Data of 25-year strategic sustainable forest concession management level of CFC Company were selected for tabulation. For a more accurate evaluation of the CFC Company, the sections, which related to criterion 2, were sorted. 2.2.1 Data sources Most of the data in CFC Company and in the Montréal process were collected based on the question ―what is each indicator and why it is important?‖ and ―What does the indicator show?‖ Standard protocols for each indicator of Criterion 2 are available at www.fs.fed.us/research. Each of the selected indicators was assessed based on the results of the publication from the United States department of agriculture, European forest certification, ITTO report and FAO report and the result of acceptable indicator of Criterion 2 of the Montréal, existing records in the World Wide Web. In Cambodia, data were collected through a combination of individual and key informant interviews from the forest concessionaire in Cambodia, focus group (professor, FA officers, forest manager and the executive staff of CFC company), direct observation, and measurement of sheet 25-year strategic sustainable forest management plan of CFC Company, analysis of methodology work, result analyses and literature reviews. There are 8 criteria in 25-year sustainable forest management plan of CFC Company. In criteria number 4, 5 and 6 of the CFC Company was collected because of this relevance to Criterion 2 of Montréal process 1998 (Table 2.2). 2.2.2 Data analysis To evaluate the different indicators between CFC Company and Montréal, we first answered the question ―What does the indicator show?‖ and summarized them, and interpreted the indicators of Montréal. Then, we matched the each indicator of CFC Company and Montréal indicators. Indicators with negative or fluctuating trends were scored "0", while indicators with positive trends were rated "1". To evaluate the value of sustainable forest management of CFC Company, we finally graded each indicator of CFC based on the data collection, methodology and its objective. The analysis of indicators data goes beyond the direct measurement of grade by scaling the sub-indicators in each indicator as mentioned in Table 2.3. In this study, we - 17 -
  • 26. assessed the grade of each sub-indicator at four different ranks ―A‖ is high, ―B‖ is medium, ―C‖ is low and ―D‖ is poor in each sub-indicator or indicator, respectively. To examine the effect of CFC‘s sub-indicators, we sorted the sub-indicator descriptions of the data collection, the data analysis and the SFM objectives in each indicator for tabulation. The sub-indicator, which did not fulfill one of the three activities of accomplishment, was graded as ―C‖. The sub-indicator, which fulfilled the three activities of the data collection, the data analysis and the SFM objective, was graded as ―A‖. The sub-indicator, which fulfilled two of the three activities i.e., fulfilling of the data collection and the data analysis but without the SFM objective, was graded as ―B‖. Table 2.2: Summary of criteria and indicators of CFC Company Criteria 4. Environmental and social 4.2. Evaluation of impacts and mitigation measures 4.3. Special management areas 4.4. Environmental monitoring 5. Forest function zonation Indicators Conclusion of the ESIA document Table of the principal investigation and mitigation measures appropriate to forest concessions Guidelines for special management areas Monitoring measures tables Zoning according to the manual : - Production areas - Protection areas (>5%) - Local traditional use areas (>5%) Tables with non operable area and net operable working forest by major type Forest function zonation: production areas, sacred forests, protection, special management areas. 6. Resource and Yield calculation 6.1. Area information Forest types area tables Operable forest types Maps (1:100 000) Document verification undertaken – sources 6.2. Concession level inventory Description of the methodology of the inventory Tables, data available and correct with precision <20m3/ha Data verified on the field by the DFWb 6.3. Growth and yield information 6.4. Estimated Available Annual Yield 6.5. Plans Compartment level Guidelines will be developed by the DFW in the next months Calculation available and based on the main group of species (Group I, II and III) by forest types updated after Cambodia Maps (1:50 000) showing compartment layout based on a EAAYc production for a five years period 5 to 6 compartments according to contract between concessionaires and DFW Tables showing areas by forest types and estimated volumes in each compartment updated after Cambodia Arterial road network Proposal of an arterial road network Maps (1:50 000) Schedule of road construction per year Source: 25-year strategic sustainable forest management plan (CFC, 2003) Environmental and social impact assessment b Department of Forestry and Wildlife c Estimate of annual allowable yield - 18 -
  • 27. For the forest area estimation activity, we graded this sub-indicator by ―A‖ if there was information or ―D‖ if there was no information in the CFC‘s sustainable forest management plan. The CFC‘s area estimation source generally used Geographic Information System version 3.1 from the Forest Administration Office in Cambodia based on the imagery in the year 2000. Therefore, it was accurate enough for planning the sustainable forest management. Table 2.3: Summary of sustainable forest management sub-indicator data and rating CFC‘s sub-indicators Grade Ranking 1 Available a ―C‖ Low 2 Available ―B‖ Medium 3 Available ―A‖ High Area estimation by GIS ―A‖ High No information on area estimation ―D‖ Poor a Assessment on the available data from CFC Company on sub-indicator (1) Data collection, (2) Data analysis or (3) Sustainable Forest Management (SFM) objective 2.3. Results and Discussion Indicator 10: Area of Forest Land and Net Area of Forest Land Available for Timber Production. This indicator provides information fundamental to calculating the timber productive capacity of existing forests and shows how much forest is potentially available for timber production, compared with total forest area. Knowledge of the availability and capability of forest land to provide desired goods and services is a critical indicator of the balance of forest ecosystems relative to potential end uses. The comparison between Montréal‘s and CFC‘s sub-indicators showed that CFC‘s company fulfilled the forest land available for timber production in indicator 10 about 11 of 13 sub-indicators (Table 2.4). The community and conservation area estimation were not fulfill. Whereas, the other 11 sub-indicators were realized with the grade A because the area estimation used Geographic Information System (GIS) in the year 2000, which may provide the accurate area identification. Therefore, average of annual allowable cut and stock forests would be accurate because this plan has enough information for forest operation (Table 2.4). Indicator 11: Total Growing Stock of both Merchantable and Non-merchantable Tree Species on Forest Land Available for Timber Production. Growing stock is a fundamental element in determining the productive capacity of the area identified as forest available for timber production. Knowledge of growing stock of the various species that make up the forest and how growing stock changes over time is central to considerations of a sustainable supply of wood for products and the sustainability of the ecosystems that - 19 -
  • 28. provide them. The comparison between Montréal‘s and CFC‘s sub-indicators showed that CFC‘s company fulfilled the total growing stock of both merchantable and nonmerchantable tree species in indicator 11 about 2 of 7 sub-indicators (Table 2.5). Of the 2 sub-indicators, sub-indicator 11.1 was graded as A and sub-indicator 11.2 was graded as B because only data collection and data analysis were fulfilled and the objective of SFM is not mentioned. However, the other 5 sub-indicators were realized with the grade D because in the CFC‘s master plan, there was no information mentioned (Table 2.5). Table 2.4: Area of forest land and net area of forest land available for timber production Subindicators In.10.1d Subin.10.1.1e Subin.10.1.2 Subin.10.1.3 Subin.10.1.4 Subin.10.1.5 Subin.10.1.6 Subin.10.1.7 Subin.10.1.8 Subin.10.1.9 In.10.2 Subin.10.2.1 Subin.10.2.2 Title of sub-Indicator 10 Montréal's ref.a Area of forest land and its changed by forest, class and year type Unlogged evergreen forest Unlogged mix evergreen forest Unlogged deciduous forest Logged over evergreen forest Logged over mix evergreen forest Logged over deciduous forest Biodiversity forest Community forest Conservation forest Timber land area, by management class and region Gross area by forest type and management level (Strategic, compartment and annual) Net operable area by forest types and management level Total Source: Indicator number 10 of Montréal Process Working Group 1998 Montréal's reference b CFC's reference c This assessment was graded based on area estimation by GIS d Indicator number 10.1 e Sub-indicator number 10.1.1 CFC's ref.b Quality Grade c 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 A A A A A A A A D D A 1 1 A 1 13 1 11 A 11A, 2D Table 2.5: Total growing stock of both merchantable and non-merchantable tree species on forest land available for timber production Sub indicators Subin.11.1 Subin.11.2 Subin.11.3 Subin.11.4 Subin.11.5 Subin.11.6 Subin.11.7 Title of sub-Indicator 11 Merchantable volume by forest type and year Non merchantable volume by forest types and year Percentage for comparison by forest types and year Compare the evolution for decision making Trend of growing stock by year by region Growing stock volume on timber land by region and species group Growing stock volume per hectare on timber land by region Montréal's ref. 1 1 1 1 1 CFC's ref. 1 1 0 0 0 Quality Gradea A B D D D 1 0 D 1 0 D Total 7 2 1A,1B, 5D Source: Indicator number 11 of Montréal Process Working Group 1998 a This assessment was graded based on the three activities of (1) Data collection, (2) Data analysis or (3) Sustainable Forest Management (SFM) objective - 20 -
  • 29. Indicator 12: Area and Growing Stock of Plantations of Native and Exotic Species. This indicator is a measure of the degree to which forest plantations are being established in response to increasing demand for forest products and competing non-timber uses for forest land. The provision of forest products from intensively managed plantations can enhance the potential range and quantity of goods and services available from the remaining forest. The comparison between Montréal‘s and CFC‘s sub-indicators showed that CFC‘s company did not fulfill the area and growing stock of plantations of native and exotic species in indicator 11 (Table 2.5). Therefore, the whole indicator in this area should be restudied by CFC Company (Table 2.6). Table 2.6: The area and growing stock of plantations of native and exotic species Subindicators Subin.12.1 Subin.12.2 Subin.12.3 Subin.12.4 Title of sub-Indicator 12 Area of forest planting by forest type and species Area of tree planting by major geographic region (Specific period) Area of timber land plantations Area of timber planting by major geographic region (Specific period) Total Source: Indicator number 12 of Montréal Process Working Group 1998 a This assessment was graded based on area estimation by GIS Montréal's ref. 1 CFC's ref. 0 Quality Gradea D 1 1 0 0 D D 1 4 0 0 D 4D Indicator 13: Annual Removal of Wood Products Compared to the Volume Determined To Be Sustainable. This indicator compares the net growth of growing stock with wood harvest (removals) of products on timber land. This method is frequently used to assess whether wood harvesting is reducing the total volume of trees on forest available for timber production. Growth is the net annual increase in the volume of growing stock between inventories after accounting for effects of mortality and before accounting for the effects of harvest. Removals measure the average annual volume of living trees harvested between inventories. Timber land is the subset of forest land on which some level of harvesting is potentially allowed. The volume of trees on timber land is considered sustainable as long as growth (net of mortality) exceeds removals. The comparison between Montréal‘s and CFC‘s sub-indicators showed that CFC‘s company fulfilled the annual removal of wood products compared to the volume determined to be sustainable in the indicator number 13 approximately 4 of 5 sub-indicators (Table 2.7). For the sub-indicator number 13.4 the grade D (Table 2.7) was evaluated based on data rating in Table 2.3. There were two A graded in the sub-indicator number 13.1 and 13.5 because the growing stock by - 21 -
  • 30. species group class and current removal by forest types were studied with the clear objectives (Table 2.7). Sub-indicators number 13.2 and 13.3 was graded as B because there are only two activities were studied (Table 2.7). Indicator 14: Annual Removal of Non-timber Forest Products Compared to the level determined to be sustainable. This indicator shows the removal of non-timber forest products (NTFPs). As demand for these products grows, it becomes more important to monitor the products‘ flow and the effect of their removal on the viability of current and future forest ecosystems. Information is not currently available to compare the growth and removals of NTFPs to evaluate sustainable levels. The comparison between Montréal‘s and CFC‘s sub-indicators showed that CFC‘s company did not fulfilled the annual removal of non-timber forest products (NTFPs) in indicator 14 (Table 2.8). Therefore, the whole indicator in this area should be restudied by CFC Company (Table 2.8). Table 2.7: Annual removal of wood products compared to the volume determined to be sustainable Subindicators Subin.13.1 Title of sub-Indicator 13 Montréal's ref. CFC's ref. Quality Gradea Historic growth and removals of growing stock by group class, dbh and species Net growth and removals of each forest type by year Potential Growth by forest type Current growth by forest type Current removals by forest type 1 1 A Subin.13.2 1 1 B Subin.13.3 1 1 B Subin.13.4 1 0 D Subin.13.5 1 1 A Total 5 4 2A, 2B, 1D Source: Indicator number 13 of Montréal Process Working Group 1998 a This assessment was graded based on the three activities of (1) Data collection, (2) Data analysis or (3) Sustainable Forest Management (SFM) objective Table 2.9 summaries the comparison between Montréal‘s and CFC‘s 5 indicators in the whole Criterion 2. We found that CFC‘s plan accomplished only 3 indicators 85%, 29% and 80% in Table 2.4, Table 2.5 and Table 2.6, respectively. Indicator 12 and 13 were remaining blank (Table 2.9). There were 14 sub-indicator graded as A, 3 sub-indicator were graded as B and 16 sub-indicators were graded as D (Table 2.9). There were 33 subindicators of Criterion 2 in Montréal and only 52% equivalents amount of 17 sub-indicators were fulfilled (Table 2.9). The Montréal Process provides little guidance for defining annul allowable cut although the information that is available largely addresses sustainable forest management. The various technical notes on the subject refer to biodiversity generically. They stress the need to assess using quantitative and qualitative information of the trends on the status of maintenance of the productive capacity of forest ecosystems. Little guidance is available for - 22 -
  • 31. which scales need to be considered other than general direction to deal with national, regional, and local concerns. No guidance is provided for how to scale annual allowable cut information upward to broader spatial scales. Table 2.8: Annual removal of non-timber forest products (NTFPs) Subindicators Subin.14.1 Subin.14.2 Subin.14.3 Title of sub-Indicator 14 Montréal's ref. Popular use of medicinal plants, food and forage species Floral and horticultural species, resins and oils, Materials used for arts and crafts, and game animals and fur bearers. Annual periodic harvest of NTFPs CFC's ref. Quality Gradea 1 1 0 0 D D 1 0 D Subin.14.4 1 0 D Total 4 0 4D Source: Indicator number 14 of Montréal Process Working Group 1998 a This assessment was graded based on the three activities of (1) Data collection, (2) Data analysis or (3) Sustainable Forest Management (SFM) objective Table 2.9: Summary of Criterion 2 of maintenance of the productive capacity of forest ecosystems Indicator number 10 11 12 13 Montréal‘s CFC's CFC‘s (%) Quality Grade 13 11 85 11 A, 2D 7 2 29 1A,1B, 5D 4 0 0 4D 5 4 80 2A, 2B, 1D 4 33 0 17 0 52 4D 14A, 3B, 16D Title of indicators Area of forest land and net area of forest land available for timber production Total growing stock of both merchantable and nonmerchantable tree species on forest land available for timber production The area and growing stock of plantations of native and exotic species Annual removal of wood products compared to the volume determined to be sustainable Annual Removal of Non-timber Forest Products (NTFPs) 14 Total Fulfillments Source: Criterion number 2 of Montréal Process Working Group 1998 However, this study found that only 52% of Criterion number 2 was accomplished. We found that 48% of management indicators were not in the plan yet. Whenever the CFC‘s master plan will be approved, this estimation forecasted that indicator number 11, 12 and 14 will be endangered to the forest area of CFC Company. We suggested that growing stock of plantation and NTFPs have made the forest management into terrible condition because the forest area in CFC Company was mainly studied on the timber production. 2.4. Conclusion The analysis of trade data goes beyond direct measurement of Montréal Criterion number 2 and each sub-indicator of indicator number 10, 11, 12, 13 and 14. It is difficult to assess whether a 25-year sustainable forest management plan will fully support sustainable forest management if measures such as the conserved forest, annual growth rate and NTFPs - 23 -
  • 32. are not provided. Many of the current analytical approaches are designed to reflect, forest area and annual allowable cut on aggregate levels. 5 Indicators attempt to address the links among land management, the flow of growing stock, and plantation. In that sense it reflects the current scientific thinking of forest growth and harvesting rate. This study recommends to not approving this company to proceed to cut forest because the growth rate of this area is not studied yet. Sustainability is a human value, not a fixed, independent state of social, economic, and ecological affairs. As such it is not an ‗absolute‘ because it is dependent on social values and involves multiple dimensions and scales, including those of time and space. At the concession scale, a concession‘s concept of sustainability may be influenced by broad scale perspectives such as general trends in concessionaire‘s environmental conditions, concession social or institutional issues or the balance with other national priorities. At the concession scale, the criteria and indicators will focus on eco-regional conditions, provincial economies and program effectiveness. At the concession scale, conceptions of sustainability will vary from stakeholder to stakeholder and will vary with unique forest conditions, the importance of forest in the traditions and economies of the area, and the nature and type of land ownership. While at each scale and for each property owner or manager the land management objectives may vary, collectively their individual actions contribute to sustainability. For instance, the indicator number 14, which is mainly about the NTFPs, concessionaires may not need to use this information in their plan because of economic conditions. Regardless of the scale at which they are applied, however, Montréal criteria and indicator frameworks must be flexible and adaptable over time. As society‘s values around sustainability change over time, criteria and indicators frameworks will need periodic revision to ensure that they continue to accurately and efficiently report on progress towards concession sustainable forest management for timber production. For the indicator number 12, which is mainly about the growing stock of plantation of native and exotic species, concessionaires may need this in the plan when the commercial forest area is not enough for the current production. Montréal criteria and indicators programs represent complementary tools that can be used to show progress towards sustainability and there is no information regard to monitoring. Each tool helps answer a set of questions unique to that scale and provides feedback for different kinds of purposes and decisions at other scales. Monitoring on illegal - 24 -
  • 33. logging and reduce impact logging should be mentioned in the standard criteria and indicator in order for the manager to conduct and follow. Managing for sustainability requires thinking across all indicators of criterion 2, but monitoring and assessing sustainability must be based on the recognition that different questions and different methods are appropriate for different indicator. There is clear philosophical overlap and interdependence between the concession and Montréal indicators sustainability monitoring initiatives although the purposes, tools, and approaches are by intent different and therefore not easily translated one to the other. The CFC Company is not alone in facing the challenge of sustainable renewable resource management. Problems such as illegal logging by arm group, population growth, conflicting resource uses and subdivision of open spaces confront most of the other concessions that are employing criteria and indicators. Using criteria and indicators to assess and monitor forest conditions can aid in addressing these problems, but further action is necessary to effectively influence policies and decisions to achieve sustainable management of renewable resources. Cambodia must also integrate the information derived from the use of criteria and indicators into the development and implementation of the national forest programs. The policy statement should include an overall company goal and the willingness to: maintain long term productivity, maintain environmental and social-economic quality, sustain economic returns, work in compliance with laws and internationally recognized criteria for sustainable forest management, conduct regular monitoring, match downstream processing and forest production and formulate detailed management objectives derived from the policy statement. Defining management objectives is a key element of strategic planning. The results of this study on assessment of forest concession in Cambodia are applicable for tropical forest management. The assessment was more accurate using a forest concession planning and the Montréal. Because the sustainable forest management remedies are based on the specific knowledge of criteria and indicators, our results may be useful for the future establishment and management of sustainable yields in tropical forests. - 25 -
  • 34. Chapter 3: Stand structure of an ecosystem in Northern Cambodia: a case at concession management level in Preah Vihear Forests (25-year management level) Keywords: Stand structure, disturbance, stratification, evergreen forest 3.1. Introduction Forest fragmentation results because the spatial scales of resource extraction do not match the scales of natural disturbance that shaped the evolution of the landscape (Hobbs, 2003). Tropical deforestation was still proceeding at 14.2 million hectares per annum in the 1990s, and only 5.5% of all forest in developing countries was under formal management plans in the year 2000 (FAO, 2001). This is because until the 1990s many tropical countries had no recent published, or stated, sustainable forest management (Poore, 1989; Poore and Thang, 2000); and also a stated yield or stock may not correspond to a government‘s actual forest management plan, i.e. its true attitude and intentions (Jianbang et al, 2001). Assessment of sustainability however, is often lacking or incomplete at the time a system is adopted (Dawkins and Philip, 1998; Southgate, 1998). A government may also be unhappy if its original stated forest management was drastically modified during passage into legislation (Kim Phat et al, 2000). Forest is the essential component for human life in term of economics and environment. There is a need to extend the findings from visual images and content analyses to a wider context and different types of media in order to further examine the role of forestry industry and organizations in the public sphere (Kohsaka and Flitner, 2004). As signatory nations negotiate the implementation of the Framework Convention on Climate Change (UNCED, 1992), the role of forestry-based options for mitigating carbon dioxide emissions continues to be debated (e.g. Kyoto Protocol). In Europe for example, the role of forests should be no longer be only to sustain high wood production, but also to maintain the vitality and health of forests, biodiversity and protective functions of ecosystems, as well as to produce non-wood resources and to support socioeconomic development at multiple scales (Liaison Unit in Lisbon, 1998). Being a concern on the international market place, biodiversity maintenance has become an issue, especially in countries and regions, which are dependent on exporting wood products (Elliott and Schlaepfer, 2001). This development has been preceded by a long list of policy documents (United Nations, 1992; Work Program - 26 -
  • 35. on the Conservation, 1997; Liaison Unit Vienna, 2000). In the 1970s, when the fulfillment of the basic needs of the rural poor became an ingredient of rural development, the critical role of forests in the life of forest-dependent rural communities, which had been excluded from forest use, was reestablished (Barraclough and Ghimire, 1995; Poffenberger and McGean, 1996). The United Nations Conference on Human Environment (1972) brought environmental issues to the forefront, and since this time environmental movements have been strengthening in the developed as well as the developing world. Cambodian forest 2.1 million hectares 11% was degraded within the period 19731997 (Kao et al, 2004). The Cambodian Tropical Forests contain the partly continuous tropical forest in the world; however, it has annually suffered serious deforestation 0.6% because of road-building, mining and agricultural and illegal logging-raising expansion (Kao, 2004; KimPhat, 2000 and 2002). The large area deforestation has resulted in effects on climate change, biological diversity, hydrological cycle, soil erosion and degradation (Kim Phat, 2004; Top et al, 2004; CTIA and Kao, 2004). After deforestation, regeneration of vegetation is common and the resulting landscape often consists of patches of successional forests and agricultural lands. Stand structure is an important variable affecting habitat of wildlife and plays a key role for forest zonation. For tree species, recruitment of new individuals and death of old ones may be less important to the population dynamics than are the architectural consequences of sprouting on the persistence of already established individuals (Midglei, 1996). Moreover, an understanding of stand structure at the landscape level should take into account variability in sprouting patterns that may affect medium- and long-term forest structure (Rabinovitch-Vin, 1983; Pigott and Pigott, 1993; Gracia and Retana, 1996). In Mediterranean conditions, stand patterns are usually related to the variability in site quality conditions (Espelta et al., 1999). A plant community is not understood if it is known merely under what condition it is found. It is more important first to discover how it is built up, what is its structure. The science of vegetation is the study of the morphology of plant communities (Richards et al, 1996). Forest act in UK coined the definition stand structure: the distribution of trees in a stand, which can be described by species, vertical or horizontal spatial patterns, size of trees or tree parts, age, or a combination of these. The behavior of stand structure during and after disturbance is the basic information for preparing the forest planning and help to efficient - 27 -
  • 36. sustainable forest planning. Stand structure is important for forest zonation, which leads to guide the forest manager to scale the forest compartment of operation. Without stand structure, the forest owner may be useless expense from main road construction after year‘s indecision (Kao, 2003). Predicting stand dynamics and future yields in mixed-species complex structured stands cannot be easily accomplished with traditional field experiments (Coates et al, 2003). An indispensable way to explore relationships between management and future stand structure and function will be the use of stand structure information. This study could provide more reliable basic results on long-term monitoring stand structure of Cambodian forests in order for the government to make decision on forest concession agreement. This study aims to explore the stand structure of evergreen forests of Preah Vihear after disturbance. 3.2. Methods 3.2.1. Forest Inventory Fig. 3.1. Primary Sampling Unite allocation Note: This map is edited by FA-GIS office 2000 - 28 -
  • 37. With financial support of a timber company, an executive agency of World Bank and a counterpart of the Forest Administration of Cambodia, a two-year forest inventory project was initiated in 2000 and implemented enumeration from April 2001 to September 2001. This inventory project covered 96,714 ha of forests in Cambodia‘s three largest districts; Tbaeng Mean Cheay, Chhaep and Choam Khsant, Preah Vihear Province (Fig. 3.1). The inventory map was interpreted using satellite maps of 1996/97 and 2000 from GIS office, Forest Administration (FA) (Fig. 3.1 and Fig. 3.2). Forest types within the forest were divided into four forest types; Evergreen Forest (FE), Mixed Forest (FM), and Deciduous Forests (FD) Conserved Evergreen Forest (CSFE). Fig. 3.2. Preah Vihear Forest land cover map Under this inventory project, the procedure of the Forest Management Planning Manual was adapted. In each forest type, 100 Primary Sampling Unites (PSU) were set on the map with the detail UTM grid coordinates. PSU in FE had the average area of 301ha was measured (Table 3.4). Twenty PSUs were randomly selected from the 100 PSUs on the map (Fig. 3.1). Sample plots of 20m x 60m were set in the PSUs. Therefore, 160 sample plots of this forest type in total were selected from 20 PSUs. In each sample plot, four sub - 29 -
  • 38. plots with the different size were set 20 x 60m, 20 x 20m, 10 x 10m and 5 x 5m as shown in Table 3.1. Table 3.1: Tree measuring procedure in each plot Diameter Classes Plot dimensions (m) Above 30 cm. DBH 60 x 20 Above 10-30 cm. DBH 20 x 20 5 to 10 cm. (count only) 10 x 10 Below 5 cm. (count only) 5 x 5 Note: DBH is the diameter at 1.3 m Plot Size (ha) 0.12 0.04 0.01 0.0025 At the forest, the location of the PSU was found by means of GPS. Then, we moved to the sub plot and evaluated the trees in the plot; species stem form (good, medium and bad), diameter of breast height (dbh) and height. The criterion of dbh to be measured was different in each sub plot as shown in Table 3.1. All condition of forest type survey and inventory data together with general comments were recorded by the team leaders (Fig. 3.1). 3.2.2. Data Processing To calculate the stand structure; we first calculated the stand volume using formula available in Forest Administration (2001). The dipterocarp species in evergreen forest is V = 0.121+5.422*(DBH) ^2*H/100,000, Non-dipterocarp species in evergreen forest is V = 0.226+4.750*(DBH) ^2*H/100,000. We then sorted the average volume in the dbh class above dbh 10 cm by royalty class I, II, III, LUX and OTHER. n VN  {[0.121  5.422 * (DBHi ) ^2 * H i /100,000] /P ft /PSU ft } i 1 m VD  {[0.226  4.750 * (DBH j ) ^2 * H j /100,000] /P ft /PSU ft } j 1 where: VN is volume of nondipterocarp species, VD is volume of dipterocarp species, Pft is subplot area by forest type and PSUft is primary sampling unite area by forest type 3.2.3. Overview of study area Preah Vihear Province is situated in the northern part of Cambodia, and has a total area of 14,013.61 km2 including land areas of 13,788 km2. This province has 7 districts, Choam Khsant, Chhaeb, Chey Saen, Rovieng, Sankom Thmei, Kulean and Tbaeng Mean Chey. According to the meteorology data, the average of rainfall within the area mostly falls - 30 -
  • 39. within the range of >1,500 mm to <2,000 mm, around the province of Preah Vihear. In summary, yearly maximum temperature is 32.11ºC, yearly average temperature is 28.15ºC and yearly minimum temperature is 24.20ºC. This province has a 1998 population of 119,261 people of whom 59,333 were males. Nearly 80% of the populations were engaged in farming and forestry for their livelihood. There were 21,007 households of whom 18.7% are females headed household. The population density is 8.6 people per km2 and total urban area is 18.6% (NIS, 1998). The study side forest areas (both in the core and buffer zones) have 2,635 families under the administrative control of Choam Khsant, Chhaeb and Tbaeng Mean Chey Districts. These 2,635 households come from 16 villages within 06 communes. The mean annual temperature in the area is 24.7C, lower than the national mean annual temperature of 26.7C. The highest temperature was 41C while the lowest was 19.4C. Humidity varies from 72.3% in January to 86.9% in October, with an annual average of 80.3%. The study site is situated within the province of Preah Vihear, covering an area of approximately 103,058 hectares (Table 3.3) of different forest formations (FA/GIS office, 2000). Geographically, it is located within latitude 104º 58‘ E to 105º 2‘E and longitude 13º 48‘ N to 14º 9‘ N. The area is presently accessible from Phnom Penh using National Route No. 6 thence following National Road No. 127 and 128 to reach the Preah Vihear area. It is about 5 hours ride by car to reach Preah Vihear Forest. The boundary is defined mostly by using natural features like roads, bridges, rivers, streams, or villages… etc. Northern boundary: Starting from point A (UTM: 500000.08, 1566224.68), at the junction of route No 69 and 6931 near Chaep village, along route No. 69 to Chuon village continuing to point B (UTM: 528584.51, 1549094.81) on route No. 69. Eastern boundary: From point B (UTM: 528584.51, 1549094.81 along route No. 69 to point C (UTM: 528367.79, 1546586.9), to point D (UTM: 540109.76, 1537536.97) where is the connection of route No. 69 and route No. 695, and then continue from route 695 to point E (UTM: 530340.97, 1526447.14) at the connection of route No. 6931 and route No. 695 near Molu Prey village. Southern boundary: from point E (UTM: 530340.97, 1526447.14) near Molu Prey village, along route No 6931 to point F (UTM: 519063.03, 1527527.73) and continue through Bos Thom village to point G (UTM: 502559.43, 1532069.96) near Pou village, Prame commune. Western boundary: from point G (UTM: 502559.43, 1532069.96) near Pou village along route No 6931 passing through O Kak village and Sre Phong village - 31 -
  • 40. to point H (UTM: 498057.29, 1545002.04) at Khnat village and continue along this route No. 6931 to meet the starting point of point A (UTM: 500000.08, 1566224.68) where is the junction of route No 69 and 6931 near Chaeh village (Kao, 1999). During field inventory work in the projected area, an ancient temple known as ―Daun Chrom‖ with the size of 100m x 100m has been discovered in the upper northern part of the concession at UTM: 505054, 1559394. Savannah-type brush land with scattered trees occurs mainly in the intermediate regions in the northern parts of the studied site. Along the Stoeng Sen boundary of the studied site are scattered pockets of bamboo and cultivated crops. Cultivated crops are also extensive in the vicinities around Choam Khsan district and Pau Commune. The forest vegetation over the area is composed of three major forest types. These are the evergreen forests, mixed evergreen forests and dry deciduous forests. These are further stratified into 4 sub-types (FE, FM, FD and CSFE) as interpreted by the GIS Unit of FA based on 1996/97 satellite imageries, and is further updated based on 1999/2000 satellite imageries, field assessment and forest inventory during the current analysis processes. After comparing the ground assessment with the satellite imageries 2000, forest typing and forest zonation, the identified forest area is 96,714 hectares (Table 3.2 and Fig. 3.2). Based on the 1999/2000 satellite imageries interpreted by FA, and actual ground survey and field verification, the vegetation cover in the concession is classified to include the above mentioned forest typing according to sub types as shown in Table 3.3. Table 3.2: Change of forest types in Preah Vihear Forest 1996-2000 Forest type 1996 area 2000 area Difference Change Annual Change (ha) (ha) (ha) (%) (%) Evergreen forest 34,250 30,128 -4,122 -12.0 -3.0 Mixed forests 32,795 19,968 -12,827 -39.0 -9.8 Deciduous forest 25,617 41,083 15,466 60.0 15.1 Conserved forest 6,517 5,535 -982 -15.0 -3.8 Total 99,179 96,714 -2,465 -2.0 -0.6 Percentage 96.24% 93.84% Note: This data is based on Landsat TM imagery 2000 interpreted by Forestry Administration-GIS Between the period 1995 and early 1998, extensive depletion of merchantable timber in the Preah Vihear Forest area occurred. Portion of the original operable areas has been illegally logged by armed group and village-based illegal logging activities. It is widely known that the Thai-owned company conspired by former Khmer Rouge returnees and local - 32 -
  • 41. gunmen had illegally logged hundred thousands cubic meter of timber in the area and sent to Thailand between that period (Kao, 2003). Table 3.3: Forest land use classification in Preah Vihear Forest Studied site area in hectares Total Forest types Map code Total area Conserved Unlogged (%) Evergreen forest Evergreen dense A 0 0 0 0 Evergreen disturbed B 30749 4481 26707 30 Evergreen mosaic C 5062 1054 3421 5 Sub-total 35811 5535 30128 35 Mixed evergreen forest 0 0 0 0 Mixed evergreen dense D 846 0 846 1 Mixed evergreen disturbed E 18059 0 18102 18 Mixed evergreen mosaic F 1146 126 1020 1 Sub-total 20051 126 19968 19 Deciduous forest Deciduous G 40850 710 41083 40 Sub-total 40850 710 41083 40 Total production area 96712 6371 91179 94 Non production forest Sub-total 3039 11 3028 3 Non forest or other land uses Sub-total 3307 336 2971 3 Total non-production area 6346 347 5999 6 Grand total of study side 103058 6718 97178 100 Note: This data is based on Landsat TM imagery 2000 interpreted by FA-GIS office 2000 As shown in the originally approved "Master Plan" and the "Annual Logging operational Plan, the first compartment has seven coupes that is coupe: 1, 2, 3, 4, 5, 6 and 7 (CCP, 1996). The concessionaire, at the time of making the previous approved plan, supposed to operate this first compartment's coupes sequentially by numbered. Not so long before and after the Master Plan was approved, this forest area was conquered and illegally logged by the Thai owned timber company. These illegal logs were sent to Thailand. Thai company built a direct road from within the Preah Vihear Forest to Thai border. The terrain consists of mostly flat alluvial plain from the Tonle Sap basin in the south gently rising to moderately rolling terrain to the north. The three major forest types (evergreen, mixed and deciduous) occur on five major soil types. The evergreen forests show a distinctive preference for Acid Lithosols and Red-Yellow Podsols. The mixed forests prefer Acid Lithosols and Plinthite Podzols while the deciduous forests are found almost equally in Acid Lithosols, Plinthite Podsols and Grey hydromorphics. Acid Lithosols type – most of the project area is covered by this soil family particularly in the northwestern part of the area. It covers about 45,611 hectares equal to 44.3%. The parent material at depth - 33 -
  • 42. is decomposed rock and acidic (pH 4.5 – 6.5). The project area covers a very small area of Alluvial soil type, less than 200 hectares (0.2%.) at the southern tip of the studied site near the main road entering the studied site. Grey Hydromorphic soil over the area covers about 12,856 hectares equal to 12.5% of the total project area. The Plinthite Podzols soil covers about 28,989 hectares equal to 28%. Red-Yellow Podzols soil covers about 15,406 hectares equal to 15% (Kao, 2003). Table 3.4: Sampling parameters for evergreen forest of dbh above 10 cm Forest types/ Sampling parameters FE Total area (ha) 30,128 Total number of PSU: 20 Total area of PSU (ha) 6,026 Average area of PSU (ha) 301 Total number of sampling units: 160 Dimension for dbh 10-30 cm (m) 20x20 Dimension for dbh above 30 cm (m) 20x60 Sub plot area (ha) 0.12 Plot area per PSU (ha) 0.96 Total sampled area (ha) 19.20 Number of plots per sampled PSU: 8 (+ or -)10% sampling error @ 95% confident level: 1.96 3.3. Results and discussion 3.3.1 Density and dispersion of trees Data used in this study were taken from 160 sample plots in evergreen forest. The density of the trees in evergreen forests varies within wide limits and depends on many factors. For all trees with dbh greater than 10 cm, the average density of tree, volume and basal area was 364.3 trees/ha, 286.1m3/ha and 21.4m2/ha (Table 3.5) within the area of 30,128 ha, respectively (Table 3.4). In mature forest with few gaps on more or less level, free-draining low land sites (center of the studied site in Fig. 3.3) the density of trees, volume and basal area per hectare with a dbh greater than or equal to 10-59 cm is 344 trees/ha, 172.8m3/ha and 12.6m2/ha (10 cm is an arbitrary limit roughly corresponding to trees about 15-30 m high) (Table 3.8 and inventory plots observation). - 34 -
  • 43. 220 200 180 2 Basal area (m /ha) 160 Volume (m3/ha) 140 Stem (Trees/ha) 120 100 80 60 40 20 0 I II III LUX OTHER Royalty class Fig. 3.3. Density of stem, volume and basal area of dbh above 10 cm by royalty class The factors controlling tree density in rain forests are complex and not well understood. A part from the effects of natural and anthropogenic disturbances, they certainly include drainage, illegal logging and other soil conditions, as is well shown in the over view of the studied site section 3.2. In the studied site area, the density of trees is often strikingly greater on the flat area 200- 800 m above sea level (GIS/FA office, 2000 and field observation using GPS, 2001). In hilly country the density of trees is often markedly greater on ridge tops than on the slops, as (Wyatt-smith, 1960) found in Malaya and (Ashton, 1964) in Brunei. Like density, the diameter-class distribution of the trees is very variable, some mature trees having relatively large number of 10-29 cm dbh or more and other comparatively few; however, volume and basal area density of dbh above 30 cm are higher and other comparatively few (Table 3.8). In tropical rain forest country, some mature trees of dbh 40-60 cm is very variable and other comparatively few (Richards et al, 1996). It also shows that there is little correlation between the numbers of trees or very large dbh and the total number above some fairly small arbitrary lower dbh limit such as above 10 cm (Richards et al, 1996). Since many large evergreen forest trees (over about 30 cm dbh), are buttressed and most of the smaller trees unbuttressed (forest inventory observation), the area - 35 -
  • 44. of the forest floor effectively occupied by this study is considerably larger than the basal area calculated from their dbh (Table 3.8). Table 3.5: Density of stem, volume and basal area in dbh class above 10 cm Class Stem Volume Basal area Stem Volume Basal area (Trees/ha) (m3/ha) (m2/ha) (%) (%) (%) I 79.7 90.3 7.1 22 32 33 II 103.2 95.4 7.0 28 33 33 III 51.2 28.7 2.1 14 10 10 LUX 8.2 6.3 0.5 2 2 2 OTHER 121.9 65.4 4.7 33 23 22 Total 364.3 286.1 21.4 100 100 100 Note: LUX is luxury tree class and OTHER is tree without scientific name 3.3.2. Stratification Some writer gives the impressions that the strata of the evergreen forest are as well defined and as easy to recognize as ―coppice-with-standard‖, (Richards et al, 1996) but the presence of the three story of difference trees is not evident on casual observation, for the composition of all stories is very complex and few of the trees present any stinking peculiarities, while smaller tree of a higher story always occur in a lower story and between the different sorties (Brown and Whitmore, 1992). In Table 3.6, the first or dominant story forms a complete canopy of dbh above 60 cm (13.2 trees/ha) with the average of 30-40 m of high; under this there is another story of large trees, which also form a complete canopy of dbh 30-59 cm (52.1 trees/ha) with the average of 15-30 m of high (Table 3.8). Still lower there is a story of small scattered trees of dbh 10-29 cm (299.3 trees/ha) with average of 515 m of high (Table 3.5 and Table 3.6). In this study, the result of our analysis is similar to Brown (1992). 3.3.3. Species density It consists of three stories of trees at the studied site at 30 m and upwards, 15-30 m and 3-15 m, respectively (Inventory observation). So that it is somewhat lower and less luxuriant (Table 3.5, Table 3.7, Table 3.8 and Fig. 3.6) than the best developed ―true‖ evergreen forest. Apart from the lower height of all the stories, the highest tree is even more discontinuous (Richards et al, 1996). Structurally the original evergreen forest have a dense closed canopy with the emergent layer attaining a height up to 40 meters and the trees reaching a diameter of 200 cm In Fig. 3.4 and Table 3.6, many of these emergent trees are buttressed (Inventory data). In Table 3.7, dipterocarps species are commonly encountered - 36 -
  • 45. including Shorea vulgaris (Chorchong) 20.3%, 10.3% and 10% of stem, volume and basal area density, Shorea cochinchinensis (Popel) 5%, 6.6% and 6.6% of stem, volume and basal area density, Anisoptera costata (Phdeak) 3.7%, 10.8% and 10.7% of stem, volume and basal area density, and Dipterocarpus turbinatus (Sokomdoray) 1.4%, 3.1% and 3.1% of stem, volume and basal area density. Lagerstroemis sp in Lythraceae family was found 9.1%, 10.6% and 11.7% of stem, volume and basal area density in this forest type. Eugenia sp. in Myrtaceae family was found 7.2%, 5.4% and 5.5% of stem, volume and basal area density. Total density of tree was 44.5 % of the top story equivalent amount of 175.8 trees/ha (Fig. 3.5). Table 3.6: Stand structure of evergreen forest above 50 cm dbh Royalty Class I II III LUX OTHER Total Stem (Trees/ha) 8.3 7.5 0.9 0.6 2.9 20.3 Volume (m3/ha) 44.2 51.5 3.4 2.9 11.2 113.3 Basal area (m2/ha) 3.5 3.8 0.3 0.3 1.0 8.8 Stem (%) 41 37 4 3 14 100 Volume (%) 39 45 3 3 10 100 Basal area (%) 40 43 3 3 11 100 Note: LUX is luxury tree class and OTHER is tree without scientific name 100 90 80 70 Royalty class I 60 Royalty class II 50 Royalty class III 40 Royalty class luxury 30 Royalty class other 20 10 0 Stem Volume Basal area Fig. 3.4. Percentage of tree, volume and basal area density by royalty class The next tree layer stands at 15-30 meters. This layer is floristically very mixed and species dominance may depend on the soil conditions. Hopea odorata, Shorea obtusa, Sindora cochinchinensis, Xylia dolabriformis, Hassia cuneata, Kayea engeniafolia, Melaleuca leucadendron, Terminalia mucronata and Diospyros crumenata (Table 3.7). - 37 -
  • 46. Table 3.7: Projected distribution of species of dbh above 10 cm in evergreen forest by royalty class Local name Krolanch Korki Srolao Trosek Rang Phnom Popel Pcheck Korkosh Donchem Chlick Popol Sokrom Sub-total Kvav Phdeak Tbeng Trach Chertealteak Chertealpreng Chertealbongkuy Sokomdoray Srol Lombor Chorchong Chromas Sub-total Bongkov Kondol Pring Pros Tromong Kray Smarkrobay Smach Tlok Svay Pramdomleng Sub-total Beng Neannon Ankotkhmao Cherkmao Troyeing Tartrav Krel Tnoung Sub-total Other names Sub-total Total Scientific name Dialium cochinchinensis Hopea odorata Lagerstroemis sp Peltophorum ferrugineum Pentacme suavis Shorea cochinchinensis Shorea obtusa Sindora cochinchinensis Tarrietia javanica Terminalia tomentosa Vitex sp. Xylia dolabriformis Family Caesalpiniaceae Dipterocarpaceae Lythraceae Caesalpiniaceae Dipterocarpacees Dipterocarpacees Dipterocarpaceae Caesalpiniaceae Sterculiaceae Combretaceae Verbenaceae Mimosaceae Royalty Class I I I I I I I I I I I I Adina cordifolia Anisoptera costata Diptercapus obtusifolius Dipterocarpus intricatus Dipterocarpus alatus Dipterocarpus turbinatus Dipterocarpus costatus Payena elliptica Poducarpus cupressina Shorea hypochrea Shorea vulgaris Vatica astrotricha Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae Sapotaceae Podocarpaceae Dipterocarpaceae Dipterocarpaceae Dipterocarpaceae II II II II II II II II II II II II Aglaia gigantia Careya sphaerica Eugenia sp. Garcinia ferrea Garcinia schomburghiana Kayea engeniafolia Knema corticosa Melaleuca leucadendron Parinarium annamensis Swintonia pierri Terminalia mucronata Meliaceae Myrtaceae Myrtaceae Guttiferes Guttiferes Guttiferes Myristicaceae Myrtaceae Rosaceae Anacardiaceae Combretaceae III III III III III III III III III III III Afzelia xylocarpa Delbergia beriensis Diospyros bejaudi Diospyros crumenata Diospyros helferi Fagraea fragrans Melaleuca laccifera Pterocarpus cambodianus Caesalpiniaceae Papilionaceae Ebenaceae Ebenaceae Ebenaceae Loganiaceae Anacardiaceae Papilionaceae LUX LUX LUX LUX LUX LUX LUX LUX Not Available Not Available OTHER Stem (%) 0.3 0.9 9.1 0.2 0.6 5.0 1.8 1.3 0.3 0.3 0.6 1.3 21.9 0.3 3.7 0.0 0.0 0.3 1.5 0.9 1.4 0.0 0.0 20.3 0.0 28.3 0.5 0.1 7.2 1.1 0.4 1.5 0.1 1.3 0.4 0.4 1.0 14.1 0.1 0.2 0.9 0.4 0.4 0.2 0.1 0.1 2.3 33.5 33.5 100 Volume (%) 0.5 6.7 10.6 0.4 0.6 6.6 1.8 1.7 0.3 0.3 0.4 1.6 31.5 0.2 10.8 0.1 0.0 0.2 8.1 0.5 3.1 0.0 0.0 10.3 0.0 33.4 0.3 0.1 5.4 0.6 0.3 0.8 0.1 0.8 0.5 0.2 0.8 10.0 0.9 0.2 0.5 0.2 0.2 0.1 0.1 0.1 2.2 22.9 22.9 100.0 Basal area (%) 0.5 6.6 11.7 0.5 0.6 6.6 1.8 1.9 0.0 0.3 0.4 1.9 32.9 0.2 10.7 0.2 0.0 0.2 7.9 0.5 3.1 0.0 0.0 10.0 0.0 32.8 0.3 0.1 5.5 0.6 0.3 0.7 0.1 0.7 0.6 0.2 0.9 10.0 1.0 0.2 0.4 0.1 0.2 0.1 0.1 0.2 2.3 22.0 22.0 100.0 Source of scientific names: National priority tree species workshop, Cambodia Tree Seed Project/DANIDA, (2000) Note: LUX is luxury tree class and OTHER is represented 102 species without scientific name, which found in 160 sample plots of evergreen forest The other 102 species were found in evergreen forest, which there is no scientific name. This analysis used Fig. 3.5 to describe the strand structure. The total number of tree - 38 -
  • 47. dbh class of 10 to 59 cm was decline in all royalty class (Table 3.8). The volume of trees in dbh above 60 cm increased. Royalty class I and II, which represented the dipterocarp species were also high (Fig. 3.5). 3.4. Conclusion Table 3.8: Projected distribution of dbh class of evergreen forest by royalty class Royalty class I I I I I I Sub-total II II II II II II Sub-total III III III III III III Sub-total LUXURY LUXURY LUXURY LUXURY LUXURY LUXURY Sub-total OTHER OTHER OTHER OTHER OTHER OTHER OTHER Sub-total Total DBH (cm) 10–19 20–29 30–39 40–49 50–59 60–UP 10–19 20–29 30–39 40–49 50–59 60–UP 10–19 20–29 30–39 40–49 50–59 60–UP 10–19 20–29 30–39 40–49 50–59 60–UP 10–19 20–29 30–39 40–49 50–59 60–UP 10–UP Stem Trees/ha 31.1 22.0 11.7 6.6 3.3 5.1 79.7 60.5 25.5 6.8 3.0 1.9 5.6 103.2 26.7 17.8 4.2 1.6 0.4 0.5 51.2 4.8 2.3 0.3 0.2 0.3 0.4 8.2 82.0 26.6 7.3 3.2 1.3 1.6 121.9 121.9 364.3 Volume m3/ha 9.5 12.9 12.4 11.3 8.7 35.5 90.3 16.3 14.1 7.9 5.7 5.8 45.7 95.4 8.8 9.9 4.1 2.5 1.0 2.4 28.7 1.6 1.3 0.3 0.2 0.7 2.3 6.3 26.6 15.2 7.3 5.0 3.1 8.2 65.4 65.4 286.1 Basal area m2/ha 0.5 1.0 1.1 1.0 0.7 2.7 7.1 1.0 1.1 0.6 0.5 0.4 3.3 7.0 0.5 0.8 0.4 0.2 0.1 0.2 2.1 0.1 0.1 0.0 0.0 0.1 0.2 0.5 1.3 1.2 0.7 0.5 0.3 0.7 4.7 4.7 21.4 Stem (%) 8.5 6.0 3.2 1.8 0.9 1.4 21.9 16.6 7.0 1.9 0.8 0.5 1.5 28.3 7.3 4.9 1.2 0.4 0.1 0.1 14.1 1.3 0.6 0.1 0.1 0.1 0.1 2.3 22.5 7.3 2.0 0.9 0.4 0.4 33.5 33.5 100 Volume (%) 3.3 4.5 4.3 3.9 3.0 12.4 31.6 5.7 4.9 2.8 2.0 2.0 16.0 33.3 3.1 3.5 1.4 0.9 0.3 0.8 10.0 0.6 0.5 0.1 0.1 0.2 0.8 2.2 9.3 5.3 2.6 1.7 1.1 2.9 22.9 22.9 100 Basal area (%) 2.3 4.7 5.1 4.7 3.3 12.6 33.2 4.7 5.1 2.8 2.3 1.9 15.4 32.7 2.3 3.7 1.9 0.9 0.5 0.9 9.8 0.5 0.5 0.0 0.0 0.5 0.9 2.3 6.1 5.6 3.3 2.3 1.4 3.3 22.0 22.0 100 The calculation serves to illustrate discrepancies between several alternatives such as forest type‘s identifications using GIS has been highlighted. GIS and ground reconnaissance could show differences in forest structure at different scales before forest inventory project starting. These indicate the useful analysis of stand structure referenced land use limitation and tree density. This study may be the best alternative, particularly as it provides locationspecific harvestable zonation after the reconnaissance survey based on forest inventory and - 39 -
  • 48. invites comparisons between predicted disturbed area and undisturbed area in other parts of the country. For more accurate assessments on the sustainable forest operation based on stand structure and use, further research is needed on the size and dynamic of trees. 680 640 600 560 520 480 440 400 360 320 280 240 200 160 120 80 40 0 Stem density (Trees/ha) Volume density 3 (m /ha) Basal area density 2 (m /ha) Adina cordifolia Afzelia xylocarpa Aglaia gigantia Anisoptera costata Careya sphaerica Delbergia beriensis Diospyros bejaudi Diospyros crumenata Diospyros helferi Diptercapus obtusifolius Dipterocarpus intricatus Dipterocarpus tuberculatus Dipterocarpus turbinatus Eugenia sp. Fagraea fragrans Garcinia ferrea Garcinia schomburghiana Hassia cuneata Hopea odorata Kayea engeniafolia Knema corticosa Lagerstroemis sp Melaleuca laccifera Melaleuca leucadendron Parinarium annamensis Payena elliptica Peltophorum ferrugineum Pentacme suavis Poducarpus cupressina Pterocarpus cambodianus Shorea cochinchinensis Shorea hypochrea Shorea obtusa Shorea vulgaris Sindora cochinchinensis Swintonia pierri Tarrietia javanica Terminalia mucronata Terminalia tomentosa Vatica astrotricha Vitex sp. Xylia dolabriformis Not Available Fig. 3.5. Average stand structure of dbh above 10 cm by species Note: Not Available is represented 102 species without scientific name, which found in 160 sample plots of evergreen forest - 40 -
  • 49. 140 120 Royalty class I 100 Royalty class II 80 Royalty class III 60 Royalty class Luxury Royalty class other 40 20 0 Trees/ha Stem 3 m /ha Volume 2 m /ha Basal area Fig. 3.6. Density of stem, volume and basal area of trees dbh above 10 cm in forest evergreen by royalty class We are not the first to register that it is possible to significant of forest structure in Cambodia. Other work in nearby Preah Vihear Province Kim Phat et al (2000) has found that the poor, medium and rich forest in dipterocarp species and Top et al (2004) has found biomass need and demand in Kompong Thom Province can also be the basic information together with this study to provide for Cambodia in preparing its new forest zonation in the region. In order to support this analysis more effectively and efficiently, since tree scientific names have remained unknown, a big proportion in the Preah Vihear Forest, any study on such species should be urged. Identification of species is not important either for the forest sustainable planning but also for settling disputes between the concessionaires and the government in taxation. Whenever this result will have applied, illegal logging monitoring during forest operation should be promoted in Cambodia. This result is hopefully to apply for compartment identification and other forest zonations for sustainable forest management respond to the local community needs and demands for the protection of endanger species and resin trees. - 41 -
  • 50. Chapter 4: Structural characteristics of logged evergreen forests in Preah Vihear, Cambodia, three years after logging at coupe management level (annual small size management level) Keywords: Cambodia; Stand structure; Disturbances; Selective cutting; Forest management 4.1. Introduction The Cambodian natural forests extended over 10.6 million hectares at 62.2% of the total land area in the year 1996/97 (DFW, 2003). These forests of 2.1 million hectares (11.0%) were degraded from 1973 to 1997 (Kao, 2004). They have annually suffered serious deforestation at 0.6% because of road building, mining and agricultural improvement expansion (Kim Phat et al., 2002; Kao, 2004). A large deforestation area has affected the climate change, biological diversity, hydrological cycle, soil erosion and degradation (CTIA and Kao, 2004, Kim Phat et al., 2004, Top et al., 2004). In the past, logging was an integral part of the ecosystem in Cambodia, affecting wildlife habitats, forest stand dynamics, soil properties, and watershed hydrology. Therefore, in response to the changed forest canopy, the Cambodian Government and its predecessors developed a broad set of regulations and guidelines to control and safeguard forest management practice with funds and technical support from the FAO, ADB, World Bank and several bilateral donors since 1996 (RGC, 1996; 1999; 2000; 2002; 2003; DFW, 1998; 1999; 2000a;b; 2001a,b). Additionally, five handbooks, prepared by the technical assistance team of the World Bank supported Forest Concession Management and control pilot project, were issued (WB, 2004a;b;c;d;e). By using these publications, objectives for strategic sustainable forest management were set. The most appropriate sustainable forest management adopted by the Royal Government of Cambodia for production forest zones is: management of forest resources that ensures that commercial forest harvestings are carried out efficiently (DFW, 1999); preserves soil value; identifies and protects sites of high traditional, historical and archaeological value (RGC, 1996; 1999); maintains the logging productivity of those sites designated for logging over many cutting cycles (RGC, 2000); identifies, maintains and protects a broad range of natural habitats with potential scientific and ecological values (RGC, 2002); protects water resources; allows continued exploitation of non-timber forest resources in a way that permits continued - 42 -
  • 51. productivity of these resources (DFW, 2000b; 2001); ensures that forest activities are carried out safely and legally; allows existing recreational use and new recreation uses as appropriate and minimizes the adverse effects of forest operations on people and the environment (RGC, 1996; 1999; 2002; 2003). The evergreen forests extend over 8,553 ha in Preah Vihear Province, Cambodia (DFW, 2003). The evergreen forest type in this ecozone is a major source for industry and is a habitat for numerous wildlife species. However, little is known of the structure, composition, process and dynamics of these ecosystems. More specifically, evergreen forest is widely distributed in Preah Vihear Province. It is among the most productive forests types in this province. Commercial timber in the Preah Vihear Forest area was extensively depleted between 1995 and early 1998. Part of the original logging areas has been illegally logged by armed groups and village-based illegal logging activities. Widely known is that a company conspired with former Khmer Rouge returnees and local gunmen and illegally logged hundreds of thousands of cubic meters of timber over a wide area, which was sent to Thailand during that period (CTIA and Kao, 2004) Until recently, selective cutting was a common logging practice in Cambodia. This harvesting method is generally not suitable for forests because Cambodia needs more knowledge to control and manage. Very little detailed information on stand structure and degree of disturbance is available on vegetation development after cutting in this forest type. Forest concessionaires still seem to lack a full understanding on how to achieve successful implementation of the silvicultural system, especially related to stand structure development needs, despite their clear commitment to follow the Cambodian harvesting code (Hinrichs and Mckenzie, 2004). The development of better forestry practice requires knowledge of system responses to natural man-made disturbance, including patterns of succession. Information on the effects of silvicultural treatment on future site conditions, vegetation species composition, structure and spatial distribution is a required strategy to achieve sustainable forest management (Archambault et al., 1998). Stand structures have a key role in preparing a sustainable forest management plan and are important in forest zonation to guide a forest manager to scale the forest into areas of operation. Forest stand structures over time, including stand characteristics during and after disturbance, provide basic information to - 43 -
  • 52. identify forest types in preparing a sustainable forest management plan. Ecosystem and landscape management approaches are already becoming more widely accepted and should be put into practice by using stand structure as basic information. We addressed these concerns by analyzing logged evergreen forest (LGFE) and unlogged evergreen forest (UNFE) areas by using their stand structure, the harvested rate of logged forests and the damage rate after forest loggings. Our aim was to provide information that will guide sustainable timber production in an ecosystem management context by evaluating previous logging systems that may be practical alternatives to manage trees of various ages with selective cutting in northern Cambodia by using forest inventories. The specific study aims were to: (1) increase our understanding of a logged stand structure and dynamics in Preah Vihear Province including the density of harvestable trees and levels of tree harvested; (2) determine tree damage during timber harvesting. Fig. 4.1. Geographic location of the study site Source: Cambodian Forest Administration- GIS/Office 2000 The study site forest areas (both in the core and buffer zones) have 2,635 families 4.2. Methods 4.2.1. Overview of study site Preah Vihear Province is situated in northern Cambodia and has a total area of 14,013.61 km2 including a land area of 13,788 km2 (NIS, 1998). This province has seven - 44 -
  • 53. districts: Choam Khsant, Chhaeb, Chey Saen, Rovieng, Sankom Thmei, Kulean and Tbaeng Mean Chey. According to meteorology data, the average rainfall within the area mostly falls within >1,500 mm to <2,000 mm in the province of Preah Vihear. The yearly maximum temperature is 32.11ºC, the yearly average temperature is 28.15ºC and the yearly minimum temperature is 24.20ºC. This province has a 1998 population of 119,261 of whom 59,333 were males. Nearly 80% of the population was engaged in farming and forestry for their livelihood. The number of households among which 18.7% were female household heads was 21,007. The population density is 8.6 people per km2 and the total urban area is 18.6% (NIS, 1998). Under the administrative control of Choam Khsant, Chhaeb and Tbaeng Mean Chey Districts, these 2,635 households come from 16 villages within 6 communes. The mean annual temperature in the area is 24.7C, lower than the national mean annual temperature of 26.7C. The highest temperature was 41C and the lowest temperature was 19.4C. The humidity varies from 72.3% in January to 86.9% in October, with an annual average of 80.3% (NIS, 1998). The study area of approximately 103,058 hectares of different forest formations was at longitude 104º 58‘ E to 105º 2‘E and latitude 13º 48‘ N to 14º 9‘ N within the province of Preah Vihear (Fig. 4.1) . It is accessible from Phnom Penh by using National Route No. 6 and then following National Roads No. 127 and 128 to reach the Preah Vihear area, and takes about 5 hours by car to reach Preah Vihear Forest. Fig. 4.2. Preah Vihear Forest land cover map Source: Cambodia Forest Administration-GIS/Office 2000 - 45 -
  • 54. The terrain consists of mostly flat alluvial plain from the Tonle Sap basin in the south and gently rises to a moderately rolling terrain in the north. Three major forest types of evergreen, mixed and deciduous are on five major soil types. Evergreen forests have a distinct preference for Psamments and Udults. Mixed forests prefer Psamments and Aquults, and deciduous forests grow almost equally in Psamments and Aquults, Aquents and Psamments cover most of the area at about 45,611 hectares (44.3%), especially in the northwest of the area. The parent material is decomposed rock and is acidic (pH 4.5 – 6.5). The study site included a very small area of alluvial soil, less than 200 hectares (0.2%) at the southern tip of the concession near the main road entering the concession. Aquents covered about 12,856 hectares (12.5%) of the total study site area; Aquults covered about 28,989 hectares (28.0%); and Udults covered about 15,406 hectares (15.0%) (Kao, 2003). The forest vegetation over the area comprised two major forest types: UNFE and LGFE, as interpreted by the Geographic Information System (GIS) Unit of the Forest Administration (FA) from satellite images in the year 2000, and was further updated from a field reconnaissance survey and field assessment during the forest inventory recording (Fig. 4.2). After comparing the ground assessment with the satellite images in the year 2000, forest typing and forest zonation, the identified forest area was 7,644 hectares (Table 4.1, Fig. 4.2). Table 4.1: Sampling characteristics for unlogged (UNFE) and logged (LGFE) evergreen forest trees above dbh 10 cm Sampling characteristic UNFE LGFE Total area (ha) 4,134 3,510 Total number of PSUa: 10 10 Total area of PSU (ha) 827 702 Average area of PSU (ha) 83 70 Total number of sampling units: 60 60 Area of trees dbh 10 cm to 29 cm (m) 20x20 20x20 Subplot area of trees dbh 10 cm to 29 cm (ha) 0.04 0.04 Area of trees dbh above 30 cm (m) 20x60 20x60 Subplot area of trees dbh above 30 cm (ha) 0.12 0.12 Plot area per PSU (ha) 0.96 0.96 Total sampled area (ha) 9.6 9.6 Number of plots per sampled PSU 6 6 (+ or -)10% sampling error @ 95% confident level 1.96 1.96 a Primary sampling unit Since 1998, the Preah Vihear Forest has been operated only in one coupe. According to the originally approved "Master Plan" and the "Annual Logging Operational Plan‖ by a forest concession company, the first compartment has seven coupes: 1 - 7 (CCP, 1996). - 46 -
  • 55. When the previously approved plan was made, the concessionaire was supposed to operate the coupes of this first compartment sequentially by numbers. Coupe 2 (UNFE) of 4,134 ha was not harvested (Fig. 4.3). Only coupe 1 (LGFE) of 3,510 ha was harvested (Fig. 4.3). 4.2.2. Forest Inventory With technical support of an executive agency of the World Bank, and a counterpart of the Forest Administration of Cambodia, a two-year forest inventory project was introduced in 2000 and enumeration was from April 2001 to September 2001. This inventory project covered 7,644 ha of forests in Preah Vihear Province (Fig. 4.3). The inventory map was interpreted by using satellite images in the year 2000 from the GIS office, Forest Administration. Forest types within the permanent production forest were divided into two major forest types: UNFE and LGFE. Under this inventory project, the procedure of the Cambodian Forest Management Planning Manual was used (DFW, 2001a). In each forest type, 50 Primary Sampling Units (PSU) were delineated on a map with UTM grid coordinates. The PSU in UNFE and LGFE had average areas 70 and 83 ha, respectively (Table 4.1). Ten PSUs were randomly selected from the 50 PSUs in each forest type on the map (Fig. 4.3). Sixty sample plots were formed in UNFE and sixty sample plots were formed in LGFE (Fig. 4.4). In each sample plot, a subplot was formed at 20 x 20m (Table 4.1). Fig. 4.3. Primary Sampling Unit allocation Source: 25-year strategic sustainable forest management plan (Kao, 1999) - 47 -
  • 56. The PSU in the forest was found by using a Global Positioning System. We first demarcated the boundaries of the plot (20m x 60m) and subplot (20m x 20m), and then evaluated the trees in the plot: tree species, measured diameter at breast height (dbh) and height (Kao, 1999). The data collected were species, diameter at breadth height (or diameter above the buttress) and height. All trees at dbh 10 cm to 29 cm, species and height were recorded in each subplot (Table 4.1, Fig. 4.4). All trees at dbh above 30 cm, species and height were recorded in each sample plot (Table 4.1, Fig. 4.4). Fig. 4.4. Plot allocation Note: This map is edited by FA-GIS office 2000 Tree heights were measured in meters by using Suunto Clinometers (Fig. 4.5) only to the highest point along the trunk of the tree, which was just below the first branch (Fig. 4.5). Fig. 4.5 shows the method used to calculate tree heights in the field: TH = (a% x hd) + (b% x hd) where, TH is tree height, a% is the positive clinometer reading in percentage, b% is the negative clinometer reading (%) and hd is the horizontal distance from tree to Suunto Clinometer in meters. - 48 -
  • 57. Fig. 4.5. Net tree height calculation in the field (Kao, 2003) 4.2.3. Data processing We summarized the following information from the inventory data by dbh range: total number of tree species, including the number of native, unknown, and endemic species; basal area (BA), tree density, and volume by species or forest type or both; and species importance commercial values. The importance value was the sum of the relative density (percent of the stand total density) and relative BA (percent of the stand total BA). The minimum diameter at breast height (dbh) for harvested trees was above 50 cm and above 10 cm for regenerating trees. The information collected from the 60 sample plots each of UNFE and LGFE was analyzed and was integrated into a usable classification of tree species and tree dbh range by sorting and coding the trees by family name and selecting the dbh class for tabulation. To calculate the stand volume of tree species in each family, we first calculated the stand volume by using formula of the Forest Administration (DFW, 2001b): dipterocarp species in evergreen forest, V = 0.121+5.422*(DBH)^2*H/100,000; non-dipterocarp species in evergreen forest, V = 0.226+4.750*(DBH)^2*H/100,000. For each plot, we calculated tree density, volume and BA by number of individuals of each species for all trees at dbh above 10 cm. Average values were calculated for logged and unlogged area. The analysis was done for the number of trees of each species in each plot. Trees in the lower diameter class at dbh 5-9 cm were not included. We then calculated the average volume of inventory plots in UNFE and LGFE to characterize the main variability by using: n VN  {[0.121  5.422 * (DBHi ) ^2 * H i /100,000] /P ft /PSU ft } i 1 m VD  {[0.226  4.750 * (DBH j ) ^2 * H j /100,000] /P ft /PSU ft } j 1 - 49 -
  • 58. where, VN is the average volume of non-dipterocarp species (m3/ha), VD is the average volume of dipterocarp species (m3/ha), Pft is the subplot area by forest type, PSUft is the number of primary sampling unit by forest type, i is dipterocarp species, j is nondipterocarp species, n is the number of dipterocarp species and m is the number of nondipterocarp species. To calculate the harvested rate, we first sorted the trees into dbh class and selected the dbh above 50 cm (harvestable trees dbh in Cambodia) in UNFE and LGFE. We then evaluated and subtracted the average volume harvested in LGFE from unlogged trees in UNFE. It must be clearly understood that the damage rate caused by forest harvesting is higher than the number of small trees and damage rates caused by wildlife disturbance and natural death (mortality). This study calculated the damaged rate based on tree felling, road construction, skid trails and clearing surround the stump after cutting, but natural disturbances and death were not included because natural disturbances affected sites in both UNFE and LGFE. To calculate the damage rate, we first sorted trees of dbh 10 to 49 cm (trees that remain after harvesting in Cambodia or trees that are not allowed to be harvested in Cambodia) in LGFE and UNFE sites. We then evaluated and compared the average volume of the trees in UNFE with the remaining trees in LGFE. The damaged rate was calculated by subtracting the tree density, volume and BA at dbh 10 to 49 cm in LGFE from UNFE. Because the condition of environment, soil and temperature are similar at UNFE and LGFE (Kao, 2003), to assess the characteristics of emerging forests, we summarized UNFE stand density, volume density and BA density and compared them with LGFE stand density, volume and BA. When making comparisons, we took the precaution of comparing stands in UNFE and LGFE. We focused our attention both on state variables (e.g., stand structure, tree species composition and soil organic matter) and functional, or rate, variables. 4.3. Results 4.3.1. Tree family stand structure LGFE had a lower tree density, smaller volume and BA than UNFE (Table 4.2). As predicted, LGFE density, volume and BA gradually declined with marked differences between tree families. Total density, volume and BA differences were also marked between - 50 -
  • 59. LGFE and UNFE. These differences were related to intensity of trees harvested at dbh above 50 cm and trees damaged from forest logging at dbh 10 to 49 cm. In UNFE, about 54% of stand BA above 10 cm dbh comprised 25 families. Of these families, 10 were changed from 0.1 to 2.1m2/ha and 15 were not in BA. Most species of Dipterocarpaceae (of BA) were commercial (Government of Cambodia, 1986). Most commercial species of Hopea odorata (Korki), Shorea roxburghii (Popel), Anisoptera costata (Phdeak), Dipterocarpus alatus (Cherteal), Dipterocarpus intricatus (Trac), Dipterocarpus turbinatus (Krochas), Shorea hypochrea (Lombor), Shorea vulgaris (Chorchong) and Vatica astrotricha (Chromas) dominated this study site. In LGFE, 54% of the stand BA comprised the same families, but the range changed: Meliaceae ranked tenth. Rosaceae, a fast growing tree that may benefit from canopy opening, ranked ninth in BA, followed by another pioneer, Caesalpiniaceae (Table 4.2). Most tree families in UNFE had the highest density, volume and BA greater than LGFE. The family composition in logged and unlogged area (34.3m3/ha or 2.5m2/ha were extracted) in LGFE showed no major changes in families and species ranking. Dipterocarpaceae and Meliaceae ranked first and second in the unlogged area and the same Dipterocarpaceae ranked first, but Myrtaceae ranked second in the logged area and dominated for three years after logging. Comment families, which were not highly changed in BA, such as Irvingiaceae and Lythraceae ranked third (Table 4.2). Generally, plots increased in density, volume and BA of trees during the three years (Table 4.2). The stand BA in LGFE was about 81.4% of an unlogged area, which on average was about 11.0m2/ha. Dominant species in Dipterocarpaceae did not lose trees, but only declined in BA, volume and density. For the remaining families during the three years after logging in LGFE, tree volume may grow the same as for UNFE because of the canopy opening. Some families had no change in LGFE during the three years (1998-01) because tree dbh 10-29 cm may grow slowly under a closed canopy. Selective logging cannot cause forest degradation. Meliaceae family was harvested and damaged more than the other families (Table 4.2). In the future, we recommend not to cut trees in this family. Aglaia gigantia species in this family was harvested and damaged more than other species in the study site. In the future this species might become endangered. The analysis indicated that forest structure after three-year harvesting was most predictable. Approximately 64% of the study site (16 - 51 -
  • 60. families) changed after cutting. Although we did not find a strong correlation between preand post-cut LGFE in these families, the logged area density was more likely to increase after the forest canopy opened. Table 4.2: Distribution of the density of trees, volume and basal area at dbh above 10 cm by family in UNFE and LGFE Family LGFE UNFE Change Name DEa VOb BAc DEa VOb BAc DEa VOb BAc Dipterocarpaceae 75.2 69.2 5.1 62.3 68.7 5.2 12.9 0.5 -0.1 Meliaceae 1.5 0.9 0.1 19.4 30.9 2.2 -17.9 -30.0 -2.1 Myrtaceae 34.0 16.2 1.1 40.1 20.6 1.5 -6.1 -4.4 -0.4 Irvingiaceae 7.8 12.4 1.0 7.9 8.5 0.7 -0.1 3.9 0.3 Lythraceae 9.4 4.9 0.4 8.9 6.1 0.5 0.5 -1.2 -0.1 Caesalpiniaceae 5.1 6.0 0.5 3.8 4.4 0.4 1.3 1.6 0.1 Melastomaceae 19.4 7.1 0.4 15.6 6.5 0.4 3.8 0.6 0.0 Guttiferes 11.1 4.8 0.3 10.6 4.3 0.3 0.5 0.5 0.0 Ebenaceae 11.8 4.6 0.3 12.6 4.8 0.2 -0.8 -0.2 0.1 Anacardiaceae 1.5 0.6 0.0 4.5 1.9 0.1 -3.0 -1.3 -0.1 Annonaceae 4.2 1.6 0.1 5.1 2.0 0.1 -0.9 -0.4 0.0 Clusiaceae 2.6 1.4 0.1 1.7 1.1 0.1 0.9 0.3 0.0 Combretaceae 0.0 0.0 0.0 0.8 1.0 0.1 -0.8 -1.0 -0.1 Dilleniaceae 0.7 0.3 0.0 1.3 0.7 0.1 -0.6 -0.4 -0.1 Hypericaceae 1.1 0.5 0.0 3.3 1.5 0.1 -2.2 -1.0 -0.1 Mimosaceae 0.5 0.9 0.1 2.2 1.2 0.1 -1.7 -0.3 0.0 Moraceae 0.6 0.2 0.0 2.3 1.4 0.1 -1.7 -1.2 -0.1 Rosaceae 1.0 2.3 0.2 1.0 1.2 0.1 0.0 1.1 0.1 Sterculiaceae 5.4 2.4 0.1 2.2 1.0 0.1 3.2 1.4 0.0 Bombacaceae 0.6 0.3 0.0 1.0 0.4 0.0 -0.4 -0.1 0.0 Euphorbiaceae 1.0 0.3 0.0 1.0 0.4 0.0 0.0 -0.1 0.0 Myristicaceae 1.6 0.8 0.1 0.6 0.2 0.0 1.0 0.6 0.1 Podocarpaceae 0.6 0.3 0.0 0.3 0.3 0.0 0.3 0.0 0.0 Sapindaceae 0.3 0.6 0.1 0.6 0.3 0.0 -0.3 0.3 0.1 Sapotaceae 0.3 0.1 0.0 0.3 0.3 0.0 0.0 -0.2 0.0 NAd 23.1 13.0 1.0 32.4 16.3 1.1 -9.3 -3.3 -0.1 Total 220.4 151.7 11.0 241.8 186.0 13.5 -21.4 -34.3 -2.5 Source of scientific family names: Cambodia Tree Seed Project/Danida., (2000) a Density (tree/ha) b Volume (m3/ha) c Basal area (m2/ha) d 80 tree species, which having no scientific name in UNFE and LGFE in local name: Ambeakchan, Ambeakpreash, Andeark, Angkeasel, Archkondol, Archsat, Arlok, Bakdork, Bakdorng, Baktongdomray, Bayarm, Beak, Beck Chan, Blokreach, Bongkorng, Char, Charsh, Chearnmloush, Chket, Chomleang, Chompoung, Chongangkor, Chongkongandark, Chongkorm, Chongkotro, Chongvapich, Creayprey, Dokdol, Dokreach, Dongreak,, Donkeapkdarm, Donkovesvar, Dorkpor, Eang, Eil, Enternail, Kbe, Keov, Kheades, Komouy, Kreang, Krol, Leankong, Leay, Lvay, Maykav, Mdeng, Meanpreay, Menkong, Pang, Peak, Pleak, Plear, Plearng, Plearpreash, Plong, Ploo, Plor, Plovsompoch, Pnak, Pneav, Poldeak, Pongro, Ponsomlay, Porl, Porlarpras, Posveanarp, Preash, Role, Sdaovprey, Seang, Semon, Sengkam, Seset, Sneang, Srol, Tkovsva,, Vayveak and Vongprey. 4.3.2. LGFE tree species structure The density of LGFE tree species of dbh above 10 cm that were common included Vatic astrotricha at 16.3 %, Eugenia sp. at 12.2%, A. costata at 8.9% and Memecylon edule - 52 -
  • 61. at 8.8%, Lagerstroemis sp, Irvingia malayana, Melaleuca leucadendron, Garcinia ferrea, D. intricatus, D. alatus, S. roxburghii and Kayea engeniafolia at 2.0% to 4.3% and Melodoum fructicosum, Diospyros sylvatica, Sindora cochinchinensis, Grewia paniculata, Diospyros bejaudi, Diospyros crumenata and H. odorata at 1.0% to 1.9%. Thirty-one species in LGFE that had no scientific name were equivalent to 23.1 trees/ha (10.5%) density, 13.0m3/ha (8.65%) volume and 1.0m2/ha (8.7%) BA (Fig. 4.6). The density of LGFE tree species dbh above 50 cm that were common included A. costata at 23.5%, I. malayana at 12.8%, D. alatu at 10.1%, S. roxburghii at 9.4 %, S. cochinchinensis at 8.75 and H. odorata at 8.1% , Parinari annamensis, D. intricatus, L. sp, E. sp. and V. astrotricha at 2.0% to 4.0% and M. edule, Xylia dolabriformis at 1.3%. Seven species in LGFE that had no scientific name were equivalent to 0.7 trees/ha (6.7%) density, 2.3m3/ha (4.5%) volume and 0.2m2/ha (4.9%) BA (Fig. 4.6). The endangered species composition at dbh above 10 cm in LGFE showed major changes in species ranking (Fig. 4.6). S. hypochrea and Terminalia mucronata ranked first as endangered species because these two species were not found in LGFE after the forests were harvested. S. vulgaris, A. gigantia, X. dolabriformis, H. odorata and Peltophorum ferrugineum ranked second because trees at density 70-99% were harvested and damaged. Diospyros helferi, Artocarpus communis, Euphoria longan, Swintonia pierri, Cratoxylon cochinchinensis and Dillenia ovata ranked third because trees at density 40-69% removed. Comment species, which is not highly damaged, such as the remaining species in Fig. 4.6, ranked fourth because the species structure had no changes and the tree density was the same as the UNFE structure. At the next cutting cycle, these endangered species should be prohibited from cutting in the LGFE site. 4.3.3. UNFE tree species structure The UNFE had three tree stories at 30 m and above, 15-30 m and 3-15 m. Structurally, UNFE had a dense closed canopy, with the emergent layer at height up to 40 meters and trees at diameter 150 cm (inventory recording sheets). Many of these emergent trees were buttressed. The middle tree layer was 15-30 meters and was floristically very mixed. The species dominance may depend on the soil conditions. UNFE tree species of dbh above 10 cm that were common included S. vulgaris at 13.9%, E. sp. at 11.3%, A. gigantia at 8.0%, M. edule at 6.5% and M. leucadendron at 5.2%, - 53 -
  • 62. L. sp, H. odorata, I. malayana, S. roxburghii, G. ferrea, D. alatus and M. fructicosum at 2.1% to 3.7% , and S. pierri, A. costata, K. engeniafolia, D. crumenata, D. helferi, D. bejaudi and C. cochinchinensis at 1.0% to 1.9%. Fifty-seven species in UNFE that had no scientific name were equivalent to 32.4 trees/ha (13.4%) density, 16.3m3/ha (8.8%) volume and 1.1m2/ha (8.3%) BA. UNFE tree species of dbh above 50 cm that were common included A. costata at 20.8%, H. odorata at 20.3%, S. roxburghii at 14.1%, D. intricatus at 10.4% and D. alatus at 8.3%, I. malayana, E. sp., S. cochinchinensis, and L. sp. at 2.6% to 5.7% , and Garcinia delpyana at 1%. Three species in UNFE had no scientific name, equivalent to 0.6 trees/ha (4.1%) density, 2.3m3/ha (3.0%) volume and 0.2m2/ha (3.5%) BA (Fig. 4.6). 4.3.4. Tree harvested The UNFE structure was similar to that of the LGFE, with comparable tree densities, volumes and BA by dbh range, although the LGFE had lower tree density, volume and smaller BA, especially in all dbh class (Table 4.3). UNFE total and commercial densities were markedly higher than LGFE. We found that in the 3,510 ha LGFE, the harvested density of trees, volume and BA were 3.0 trees/ha, 22.2m3/ha and 1.6m2/ha, respectively, equivalent to 22.4%, 29.5% and 27.1% of the total forest area, respectively (Table 4.4). The density, volume and BA of trees at dbh above 50 cm in LGFE that remained unlogged were 10.3 trees/ha, 53.0m3/ha and 4.2m2/ha, respectively, equivalent to 77.6%, 70.5% and 72.9% of the total forest area, respectively (Tables 13, 14). Table 4.3: Distribution of density, volume and basal area of trees at dbh above 10 cm in LGFE and UNFE by dbh class Dbha class LGFE Density (Tree/ha) Volume (m3/ha) 10 – 19 138.7 43.0 20 – 29 48.8 27.0 30 – 39 15.3 16.2 40 – 49 7.1 12.6 50 – UP 10.3 53.0 Total 220.3 151.9 c SE 1.0 0.7 a Diameter at bread high b Basal area c Standard error BAb (m2/ha) UNFE Density (Tree/ha) Volume (m3/ha) BA (m2/ha) 2.2 2.2 1.4 1.1 4.2 11.0 0.0 148.3 53.3 19.0 7.9 13.3 241.9 1.0 46.2 30.0 20.2 14.1 75.2 185.8 0.8 2.5 2.4 1.7 1.2 5.7 13.5 0.1 - 54 - Damage and Harvested rate Density Volume BA (Tree/ha) (m3/ha) (m2/ha) 9.6 4.5 3.7 0.8 3.0 21.6 3.2 3.0 4.0 1.5 22.2 33.9 0.3 0.2 0.3 0.1 1.5 2.4
  • 63. 100% 98% 96% 94% 92% 90% 88% 86% 84% 82% 80% 78% 76% 74% 72% 70% 68% 66% 64% 62% 60% 58% 56% 54% 52% 50% 48% 46% 44% 42% 40% 38% 36% 34% 32% 30% 28% 26% 24% 22% 20% 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% LGFE UNFE Forest type Other species Afzelia xylocarpa Aglaia gigantia Anisoptera costata Artocarpus communis Bombax ceiba Cratoxylon cochinchinensis Dialium cochinchinensis Dillenia ovata Diospyros bejaudi Diospyros crumenata Diospyros helferi Dipterocarpus alatus Dipterocarpus intricatus Dipterocarpus turbinatus Dispyros sylvatica Eugenia sp. Euphoria longan Garcinia delpyana Garcinia ferrea Garcinia oliveri Grewia paniculata Grewia paniculata Hopea odorata Irvingia malayana Kayea engeniafolia Knema corticosa Lagerstroemis sp Melaleuca leucadendron Melodoum fructicosum Memecylon edule Pantadenia aldenanthera Parinari annamensis Payena elliptica Peltophorum ferrugineum Podocarpus cupressina Shorea hypochrea Shorea roxburghii Shorea vulgaris Sindora cochinchinensis Swintonia pierri Tarrietia javanica Terminalia mucronata Vatica astrotricha Xylia dolabriformis Fig. 4.6. Average species stand structure at dbh above 10 cm by forest type 4.3.5. Tree damaged After logging, the LGFE total and commercial density, volume and BA decreased substantially (Table 4.3). Trees at most regeneration densities at dbh 10-19 were damaged - 55 -
  • 64. by forest harvesting at 9.6 trees/ha. As expected, the damage decreased in density when the dbh increased. The LGFE regeneration damage volume at dbh 30-39 cm was 4m3/ha and at dbh 40-49 cm was only 1.5m3/ha. At dbh above 50 cm forest harvesting damaged no trees. To cut three commercial trees in each hectare, the forest damaged together with the road constructions and skid trail destroyed 11.7m3/ha or 18.6 trees at dbh 10-49 cm (Table 4.3). Table 4.4: Density, volume and basal area of unlogged trees, harvested trees and damage rate Density Volume Basal area Density Volume Basal area Density 3 2 (Tree/ha) (m /ha) (m /ha) (%) (%) (%) 10.3 53.0 4.2 Unlogged trees in LGFE 65.0 45.2 32.5 Harvested trees in LGFE 3.0 22.2 1.5 22.4 29.5 27.1 13.3 75.2 5.7 Total trees in unlogged area 100.0 100.0 100.0 Damage of trees at dbh 10-49 cm in logged area 18.7 11.7 1.0 12.6 25.3 40.4 4.4. Discussion Conventionally, succession has been considered as a directional process in time after a disturbance that affects both species composition and community structure (see, for example, Odum, 1969; Miles, 1987; Chinea, 2002). The species composition of natural communities is influenced by the biogeographical characteristics of each region and, therefore, comparing data sets from widely separated geographical localities is difficult (Garcı´a-Montiel and Scatena, 1994; Garcı´a-Ferna´ndez et al., 2003, 2005). In contrast, changes in forest structure depend less on the geographical location of the sites and generate patterns that allow comparison between different locations. Multivariate analyses of the data sets of the logged and unlogged areas show variation of species composition by tree family that also correspond to changes in forest structure. Some species from unlogged forest areas replace species of logged forest areas (Figs. 6). Also, the number of tree families, tree species, tree density, BA and species change according to patterns similar to those described during succession in other studies in North Sumatra and East Kalimantan, Indonesia (Garcı´a-Ferna´ndez et al., 2005) and in Brazilian Amazon (Mesquita, 2000). The composition of all stories is complex, few trees have distinctive characteristics, and the smaller trees in higher stories always also occur in lower stories and between the stories (Brown and Whitmore, 1992; Richards et al., 1996). Our results agree more or less with the stand structure of Brown and Whitmore (1992). In this study, the composition of all stories was complex with trees at dbh 10-19 cm in higher stories always in lower stories: - 56 -
  • 65. 138.7 trees/ha in LGFE and 148.3 trees/ha in UNFE. Our results may also aid in interrelating the results of other studies. For example, in a study of the stand structure of Dipterocarp tree density, Dipterocarpaceae were 50 m3, 109 m3 and 163 m3 in poor, medium and rich forests, respectively, in Sandan District, Kampong Thom Province, Cambodia (Kim Phat et al., 2000). If comparisons are restricted to harvested estimates calculated from forest inventory data, our mean result is similar to the central province and to others. The harvested trees of forests in some ASEAN countries are 25-40 m3 (KimPhat et al., 2000, 2002), 24 m3 (Van, 1998), 30 m3 (World Bank, 2002), 30 m3 (ITTO, 1994), 30-40 m3 (ITTO, 1994) in Cambodia, Vietnam, Laos, Thailand and Malaysia, respectively. Harvested trees of Indonesian forests were estimated at 30m3/ha (FAO and UNEP, 1981). Two main factors influence the forest structure, such as natural disturbance and human disturbance. In the hotter countries, forest fire is the greatest problem because it destroys thousands of hectares in a short period and is always during summer. Disturbance by wildlife is not the greatest problem, but for accurate disturbance evaluation it may need to be studied. However, in ASEAN countries and developing countries, forests have been destroyed by human activities by cutting trees to improve their economic needs. Forest harvesting is the greatest factor affecting the forest structure. This study only used forest logging as the cause of the forest structural change where the mortality was assumed to be the same rate in these evergreen forests. In this study, the rate of damaged trees at dbh 10-49 cm was 12.6% by trees, 25.3% by volume and 40.4% by BA. In the 60 LGFE sample plots, the number of damaged trees was 18.7 trees/ha (Table 4.4). In Indonesia, trees destroyed by forest logging were more than 40%, equivalent to 60 trees/ha (Sist et al., 2003). After logging was reduced in Indonesia, tree damage during forest logging was 25% (Sist et al., 2003). In the highly productive dipterocarp forests of Borneo, where harvesting intensities commonly exceed 100m3/ha and are more than 10 trees/ha, conventional logging generally damages more than 50% of the original stand (Nicholson, 1958; Kartawinata, 1978; Tinal and Palinewen, 1978; Abdulhadi et al., 1981; Cannon et al., 1994; Pinard and Putz, 1996; Bertault and Sist, 1997; Sist et al., 1998). The damage rate percentage of trees at dbh above 35 cm was 20.0%, 29.0%, 28.0%, 30.5% and 29.0% in Cambodia (DFW, 2000a), Sabah in Malaysia (Costa and Tay, 1996), Sarawak in - 57 -
  • 66. Malaysia (FAO, 2001), East Kalimantan in Indonesia (Sist and Saridan, 1998), West Kalimantan in Indonesia (Cannon et al., 1994), respectively. 4.5. Conclusion The relationship of stand structure by each family and species by forest type to evaluate the BA was examined in logged and unlogged areas in northern Cambodia. Logging and the resulting change in species structure altered the composition of the stand, reducing the density for balancing the natural value of the forest by family and species and endangering species because the natural canopy had changed. This study tested a relatively logged forest area for three years after harvesting and an unlogged forest area to measure the general status of individual species and structural complexity of the forest family canopy. This analysis provides basic information for sustainable forest managers to identify the forest type zonation and it will be important for forest concessionaires to decide the road construction cost before harvesting because of rare commercial tree species in the next harvesting plan. Silvicultural treatment to reduce the damaged rate and improve the selective cutting rate in the forest disturbance zoned for timber production should be considered as a managed viability option. Structural characteristics are also most important for wildlife conservationists to identify protected and environmental habitat areas. Ongoing restudy of this and other plots at unlogged sites for the next cutting cycle are necessary to provide a strong basis for how to reduce the impact of logging causes. Therefore, the impact of reduced logging should have been included to make the presence investigation more comprehensive and meaningful. The harvested and damaged rates are tools to assess the previous harvesting history to find if an area is well managed. Governments can use the result to revise previous plans or to change their policy. The comprehensive damage rate is the most effective way to calculate the sustainable cutting cycle. Extrapolations of these results to an anticipated acceptable cutting cycle must be interpreted with caution. Therefore, we hope this result will reach the end users in Cambodia to recalculate and monitor their current cutting cycle by comparing the damage rate to the new growth to improve forest generation. The fact is therefore important that stand structure and harvest and damage rate information are available to Cambodia now because Cambodia is now learning to manage its natural resources into forest quality management certification by criteria and indicators. - 58 -
  • 67. Chapter 5: Stand dynamics of tropical seasonal evergreen forest in, Central Cambodia Keywords: tropical seasonal forests, increment, recruitment, mortality, commercial species 5.1. Introduction There is increasing concern about the effect of selective logging in tropical natural forests on sustainability, the global carbon budget (e.g., Malhi and Grace, 2000) and biodiversity conservation (e.g., Myers et al., 2000). Information on tree and stand dynamics is required to evaluate silvicultural options for sustainable timber yield. Cutting cycles and minimum diameter cutting limits are often based on diameter increment and/or volume increment of commercial species (e.g., Silva et al., 1995; Sist et al., 2003; Sist and Ferreira 2007). Although there are data for some tropical rain forests, especially in Brazilian Amazonia (e.g., Silva et al., 1995; van Gardingen et al., 2006; Valle et al., 2006) and in Borneo (e.g., Sist and Nguyen- Thé, 2002; Phillips et al., 2002; Kammesheidt et al., 2003), very little is known about the stand dynamics of tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia, where strong seasonality of precipitation is found (Kumagai et al., 2005 and Kumagai et al., 2009). About 59% of Cambodia is covered by forest. There are three dominant forest types, evergreen (22.2%), deciduous (25.8%) and semi-evergreen forest (7.5%) (FA, 2007), in two classes, production forest (34% of total land area) and protection forest (25%). A selective logging system with a 25- to 30-year cutting cycle has been adopted in evergreen and semievergreen forests (Kimphat et al., 1999) and the annual allowable cut has been calculated using an assumed volume increment of 0.33 m3/ha/year (DFW, 2001). This value was derived from the average of virgin forest studies reported by the FAO in 1962 (DFW,2001) and is considered to be too low (DFW, 2001). However there is no data to verify the volume increment value. The present study was designed to measure stand dynamics of seasonal evergreen forest in Kampong Thom Province, central Cambodia using two consecutive measurements of 20 permanent sample plots (PSPs) in 1998 and 2003. The main questions are: 1) whether tree growth, mortality and recruitment in Cambodian forests differ from tropical rain forests - 59 -
  • 68. elsewhere, especially in Amazon and Southeast Asia; and 2) whether volume increment is significantly higher than 0.33 m3/ha/year. 5.2. Methods 5.2.1. Study Site and Data Collection Kampong Thom Province in central Cambodia lies between 12°11' and 13°26' north and 104°12' and 105°44' east. The total area is 1,244,763 ha, about 7% of the country (FA, 2007). The climate is tropical monsoon; the rainy season extends from May to October and the dry season from November to April. Between 1996 and 2000, the mean annual rainfall and temperature were 1,700 mm and 28°C (Top et al., 2009). Twenty PSPs were located in dense evergreen forests on flat terrain 9-100 m above sea level (Fig. 5. 1). Although these PSPs in this evergreen forest have not been heavily disturbed, they have been subject to some illegal extractions of fuelwood and timber (Top et al., 2009). The plots were established in April 1998 and the trees measured in 1998 and December 2003. Each main plot was 50 × 50 m and contained a 20 × 20 m sub-plot. All trees with diameter at breast height (DBH) of 7.5-29.9 cm in the sub-plot and ≥30 cm in the main plot were measured and recorded. In 2003, new trees in each of the main plot and subplot with DBH ≥30 cm and ≥ 7.5 cm were also measured. Missing or dead trees were recorded as natural death or human disturbance (illegal logging). 5.2.2. Data analysis As with selective logging systems in other tropical countries, only commercial species with DBH more than the predetermined Minimum Diameter Cutting Limit (MDCL) may be harvested. A Cambodian Government decree (Rgc, 2005) sets different MDCLs for each commercial species ranging from 30 to 60 cm. The stand-level attributes (stand structure in 1998 and 2003, mortality, recruitment, illegal cut and volume increment) for the two sampling years were examined separately for all trees with DBH ≥ 10 cm and all commercial trees with DBH ≥ MDCL. The annual rates of mortality, recruitment and illegal cut were estimated by using the widely used logarithmic equation (e.g. Lewis et al., 2004 a): Y = 100*{ln N1 – ln (N1 – X)}/t, - 60 -
  • 69. where Y is the rate of mortality, recruitment or illegal cut, N1 is the number of trees measured in 1998, X the number of mortality, recruitment or illegal cut, and t the time (5.75 years = December 2003 – April 1998). Diameter increments of individual trees were examined for all trees and commercial trees with DBH ≥ 10 cm. Although the minimum DBH of field measurements was 7.5 cm, a DBH of 10 cm was selected to be consistent with other studies (Valle et al., 2006; Silva et al., 1995; Rice et al., 1998). Two outliers with unrealistically large annual diameter increments (10.3 and 10.4 cm/year) were excluded from the analysis. These unrealistic values may have been due to misidentification of the trees to be measured or mistakes in data recording. Volume increment is defined as the net annual production of the forest from growth, mortality and recruitment (Valle et al., 2006). In the present study, we calculated volume increment for all trees with DBH ≥ 10 cm and commercial trees with DBH ≥ MDCL, defined by: I = (V2 - V1 +C)/(t2 - t1) where I is the volume increment (m3/ha/year), V2 the volume at measurement in 2003 (m3/ha), V1 the volume at measurement in 1998 (m3/ha), C the volume of illegally logged trees (m3/ha) and t2-t1 the time (in years) between the 2003 and 1998 measurements. In this formula, volume gains from the growth of existing stems and recruitment into the size class of interest (≥10 cm or ≥MDCL), as well as losses due to mortality, are condensed into one increment value for the entire observation period (Valle et al., 2006), while excluding illegally logged trees from the calculation. Volume (m3) of individual trees was estimated as a function of DBH (cm) developed for different DBH classes and species groups (Table 5.1, FA, 2003). 5.3. Results and Discussion 5.3.1. Stand Structure For all trees with DBH ≥ 10 cm in 1998, 67 species were found across all of 20 0.25ha sized plots (a total of 5 ha), and the mean values (± SD; standard deviation) of the 20 plots were 544.5 ± 106.3 trees/ha of tree density, 23.8 ± 5.1 m2/ha of basal area and 192.9 ± 46.4 m3/ha of stem volume (Table 5.2). For commercial trees with DBH ≥ MDCL in 1998, 19 species were found across all the plots, resulting in 23.4 ± 9.7 trees/ha of tree density, 6.3 - 61 -
  • 70. ± 3.4 m2/ha of basal area, and 64.3 ± 36.9 m3/ha of stem volume. There was no significant difference (P>0.05, the paired t-test) in the mean values of stand structure between 1998 and 2003 (Table 5.2). Fig.5.1. Location of 20 permanent sample plots (PSPs) distributed in 5 different places, each of which includes 4 plots. The sequence plot number of each location is shown; e.g., PSP25-28 indicates the plot number 25, 26, 27 and 28. Source: Forestry and Wildlife Research Institute, Forestry Administration, Cambodia Table 5.1: Volume equations by species group, DBH range and forest type (Forestry Administration, 2003) Tree Species Diameter class Evergreen forest Dipterocarp Below 15 cm Volume = 0.022 + 3.4 DBH2 Above 15 cm Volume = –0.0971 + 9.503 DBH2 Non-dipterocarp Below 30 cm Volume = 0.03 + 2.8 DBH2 Above 30 cm Volume = –0.331 + 6.694 DBH2 DBH is diameter at breast height There were fewer species and a lower stocking rate (basal area/ha) in this seasonal forest than in other primary tropical rain forests, despite the similar tree density recorded in the present study. About 200 species/ha are reported from primary lowland dipterocarp - 62 -
  • 71. forests in Borneo (Sist and Saridan, 1999) and Amazonian rain forests (Phillips and Gentry, 1994; Brewer and Webb 2002) compared with 67 in 5 ha in the present study. Similarly, the mean basal area (23.8 m2/ha) in this study is lower than reports from primary tropical rain forests; 31.5 ± 4.2 m2/ha in East Kalimantan (Sist and Nguyen-Thé, 2002), 35.5 ± 2.8 ( ± SE; Standard Error) m2/ha for 11 locations in Borneo and Peninsular Malaysia, 34.4 ± 1.4 (±SE) m2/ha for 15 plots in Central Kalimantan (van Gardingen et al., 2003) and 28.1 ± 12.0 (95% CI; Confidence Intervals) m2/ha in Amazonia (Lewis et al., 2004), while being closer to values reported for logged-over forests; 25.2 m2/ha in East Kalimantan (van Gardingen et al., 2003), 26.0 ± 6.4 m2/ha and 24.1 ± 7.1 m2/ha in Sarawak, Malaysia (Kammesheidt et al., 2003), 20.3 and 25.9 in Brazilian Amazon (Silva et al., 1995). On the other hand, tree densities of all trees with DBH ≥ 10cm in this study were similar to values documented for primary lowland dipterocarp forests elsewhere in Southeast Asia; 521±36 (±SE) trees/ha in Borneo and Penisular Malysia, and 583±19 (±SE) trees/ha in Central Kalimantan (van Gardingen et al., 2003), 531 trees/ha in East Kalimantan (Sist and Nguyen-Thé, 2002), as well as to 581±16 (±95%CI) trees/ha obtained from 50 plots distributed over rain forests in South America (Lewis et al.,, 2004). Table 5.2: Stand structure in 1998 and 2003 Year 1998 2003 a b Group All trees ≥ 10 cm Commercial ≥ MDCLb All trees ≥ 10 cm Commercial ≥ MDCL Number of species 67 19 67 20 Density (trees/ha) Mean ± SDa 544.5 ± 106.3 23.4 ± 9.7 531.6 ± 147.0 24.4 ± 9.8 Range 408.0 ~ 814.0 8.0 ~ 44.0 185.0 ~ 793.0 8.0 ~ 44.0 Basal Area (m2/ha) Mean ± SD Range 23.8 ± 5.1 14.6 ~ 32.8 6.3 ± 3.4 1.3 ~ 13.0 23.9 ± 5.4 15.9 ~ 34.8 6.5 ± 3.6 1.4 ~ 14.2 Volume (m3/ha) Mean ± SD 192.9 ± 46.4 64.3 ± 36.9 193.9 ± 49.1 66.3 ± 39.2 Range 103.8 ~ 259.1 11.1 ~ 127.4 102.1 ~ -274.9 12.0 ~ 137.9 SD: standard deviation MDCL: Minimum diameter cutting limit 5.3.2. Diameter Increment Table 5.3 shows the periodic annual diameter increment, which was calculated from individual trees and summarized for all trees and only commercial trees. There are not large differences in the results between all trees and commercial trees, with the total mean values (± SD) being 0.33 ± 0.09 and 0.32 ± 0.08 cm/year, respectively. There was no significant difference between growth rates for commercial and all trees (Table 5.3). The lowest increment values were recorded from the smallest DBH classes (10-19 cm and 20-29 cm), and there was no significant correlation between DBH class and increment for classes with DBH ≥ 30 cm (Table 5.3). - 63 -
  • 72. In tropical forests, diameter increments in any class of trees may vary greatly due to environmental conditions (Silva et al., 1995), silvicultural treatments (de Graaf et al., 1999; Kammesheidt et al., 2003) and other reasons. Nevertheless, the mean values found in this study are similar to reported values for tropical rain forests. For example, Silva et al. (1995) reported 0.3 and 0.4 cm/year for all trees and commercial species 11 years after logging and 0.2 cm/year for unlogged trees in Brazilian Amazonian rain forest. In East Kalimantan, Sist and Nguyen-Thé (2002) reported trees grew about 0.39 cm/year in logged dipterocarp forest and 0.22 cm/year in unlogged control plots. Dauber et al. (2005) reported a mean annual diameter increment of between 0.22 and 0.41 cm/year from PSPs in different eco-regions of Bolivia. Table 5.3: Annual diameter increment (cm/year) for diameter classes DBH class Commercial species trees at DBH ≥ 10 cm All species trees at DBH ≥ 10 cm (cm) n Max Mean Min SD CV% n Max Mean Min SD 10 - 19 129 0.85 0.21 0.00 0.10 45 258 0.85 0.22 0.00 0.07 20 - 29 36 1.17 0.25 0.02 0.17 70 65 1.17 0.31 0.00 0.25 30 - 39 60 1.10 0.42 0.00 0.19 44 156 2.94 0.46 0.00 0.20 40 - 49 46 1.39 0.44 0.00 0.39 87 77 1.39 0.39 0.00 0.32 50 - 59 17 1.32 0.36 0.00 0.27 76 24 1.32 0.35 0.00 0.21 60 - UP 40 1.18 0.41 0.03 0.22 546 67 1.98 0.42 0.00 0.17 Total 328 1.39 0.32 0.00 0.08 26 647 2.94 0.33 0.00 0.09 n, number of observations; CV, coefficient of variation; SD, standard deviation. CV% 31 81 42 82 62 41 28 5.3.3. Recruitment, Mortality and Illegal Cut Table 5.4 presented the annual density and percentage of recruitment, mortality and illegal cut for all trees ≥10 cm and ≥MDCL. For all trees, mean annual mortality ±SD was 12.2 ± 14.6 trees/ha (2.4±4.3% of total number of trees in 1998), similar to the recruitment rate of 12.6 ± 9.3 trees/ha (2.5±2.2%). On the other hand, the recruitment of commercial trees with DBH ≥ MDCL, 0.3 ± 0.4 trees/ha (1.4 ± 4.9%), was larger than the mortality of 0.1 ± 0.3 trees/ha (0.5 ± 1.3%). Human disturbances were 1.0 ± 1.8 trees/ha (0.2 ± 0.4%) and 0.03 ± 0.2 trees/ha (0.1 ± 0.9%) annually for all trees with DBH ≥ 10 cm and commercial trees with DBH ≥ MDCL, respectively, due to the collection of timber and/or non-timber forest products. Although mortality and recruitment may vary between species and diameter class, the mean rates for the present study were very similar to or well within the range of reported values from tropical rain forests in Amazon and Southeast Asia (Clark and Clark, 1992; - 64 -
  • 73. Connell et al., 1984; Kammesheidt et al., 2003; Sist et al., 2003; Bunyavejchewin, 1999). Phillips et al. (2004) compiled data for tree mortality in mature rain forests throughout the Amazon Basin, reporting mean values (±SE) of 2.30 ± 0.14% per year (number of sample (n)=31) for mortality and 2.33 ± 0.13 % per year (n=32) for recruitment. Phillips and Gentry (1994) collected data from mature South East Asian rain forests, reporting mean values (± SD) of 1.722 ± 0.70% per year (n=9) for mortality and 1.75 ± 0.66 % per year (n=9) for recruitment. Sist and Nguyen-Thé (2002) found that logging and yarding increase mortality in undisturbed primary at a rate of 1.5% per year. Table 5.4: Annual values of recruitment, mortality and illegal cut Species group All trees ≥ 10 cm Recruitment Mortality Illegal cut Commercial trees ≥ MDCLb Recruitment Mortality Illegal cut a b Density (trees/ha/year) Mean ± SDa Range Percentage of 1998 (% of 1998) Mean ± SD Range 12.6 ± 9.3 12.2 ± 14.6 1.0 ± 1.8 0.0 ~ 30.4 0.0 ~ 54.3 0.0 ~ 5.0 2.5 ± 2.2 2.4 ± 4.3 0.2 ± 0.4 0.0 ~ 6.5 0.0 ~ 17.2 0.0 ~ 1.1 0.3 ± 0.4 0.1 ± 0.3 0.03 ± 0.2 0.0 ~ 1.4 0.0 ~ 1.4 0.0 ~ 0.7 1.4 ± 4.9 0.5 ± 1.3 0.1 ± 0.9 0.0 ~ 19.1 0.0 ~ 4.4 0.0 ~ 3.9 SD: standard deviation MDCL: Minimum diameter cutting limit 5.3.4. Volume Increment The mean (± SD) volume increment for all trees with DBH ≥ 10 cm was 1.09 ± 3.35 m3/ha/year and that for commercial trees with DBH ≥ MDCL was 0.86 ± 1.33 m3/ha/year. The value for commercial trees (0.86 m3/ha/year) was significantly greater (P < 0.05, one tailed t-test) than the value (0.33 m3/ha/year) presently used in Cambodia as the standard figure for the calculation of cutting level. However, the value for all trees with DBH ≥ 10 cm (1.09 m3/ha/year) was not significantly larger than 0.33 (P > 0.05, one tailed t-test). The coefficient of variation for all trees among different plots was 300%. Volume increment may change substantially depending on minimum threshold DBH used for measurements or calculations, monitoring length (Valle et al., 2006) and species (Silva et al., 1995). Therefore, data from the present study cannot be directly compared to other studies. Nevertheless, our mean values (1.09 and 0.86 m3/ha/year) are well within the range between 0.5 and 2.0 m3/ha/year reported from most tropics mixed forests (Rice et al., 1998) and the ranges obtained from the Brazilian Amazon (Valle et al., 2006). - 65 -
  • 74. 5.4. Conclusion Information on forest stand dynamics is essential to ensure sustainable yield, and there are abundant data for tropical rain forests, especially those in mainland of Southeast Asia; however, there have been few reports on tropical seasonal evergreen forest. From the preliminary results presented here, we conclude: 1) While species richness and stocking level in terms of basal area are smaller in tropical seasonal forest than in tropical rain forest, tree density, recruitment, mortality and volume increment are similar. 2) The measured mean annual volume increment (0.86 m3/ha/year) for commercial trees with DBH ≥ MDCL was significantly larger than the value (0.33 m3/ha/year) that has been used in Cambodian management systems; however, this cannot be confirmed for the values for all trees with DBH ≥ 10 cm. Further data from longer periods and other locations are required to provide reliable estimates of sustainable yield to forest managers and planners. - 66 -
  • 75. Chapter 6: Potential woodfuel supply and demand of two community forestry in Kampong Chhnang, central Cambodia Keyword: Community natural-based management, Woodfuel, Biomass, supply and demand 6.1. Introduction Social or community forestry program was found under a variety of names: social, rural village, communal and community forestry (CF) (FAO, 1986). CF is an attempt to match simultaneous environmental, economic, and social objectives related to forest resources (Leach et at., 1999). Since CF has been providing a lot of benefits for local members to use forests and non-forest products and providing benefits for global carbon stock, many organizations and governments are increasingly devolving authority for managing forest to the local people to increase participation in sustainable forest management (Menzies, 2002; Carter, 2005; FAO, 1986). FAO (1987) also set the why-CF was to provide rural people could use resources for the basic needs, to increase the participation in managing forests, to manage degraded lands, to contribute to the general socio-economic development and to increase the overall productions. Because of forests play a vital role in supplying people‘s livelihood, Cambodian CF defined objectives to be similar to FAO (1987) to group people to assist to protect forest degradation, to share benefits of interest among stakeholders and to involve in the decision making process. The Cambodian CF was introduced in the early 1990s in this Kampong Chhnang Province, central part Cambodia (FA, 2006). Until 2005 officially and unofficially, Cambodia has 264 CF areas, which are located in 19 of 24 provinces, (CFO 2006), in the area 309,354 ha (AFW, 2008). On the other hand, local participation is low in this country. In referring to the CF expansion and to increase resources in developing countries, sustainable woodfuel supply and demand would be a critical indicator to understand in advance for balancing ecosystem before cutting forests. If the available resources are not enough for sustainable use, there is an urgent need for protecting, afforestation and calling for supporting in managing resources. A key issue is the ecology sustainability and lack of resources for local people, so that the participation in controlling and managing forests will decrease. Most well studies were concerned only on the sustainable ecology in Bhutan (Buffum et al., 2008) and Central Europe (O‘Hara et al., 2007); however, the demand link - 67 -
  • 76. with ecological sustainability is rare. There is also limited understanding of the ecological structure communities and their response to human pressures (Pote et al., 2006). There was a clear evident that the CF Southeast Asia Systems have been affecting forest cover, biodiversity and rural livelihood (Poffenberger, 2006). If we do not understand the consumption and supply rate for long-term policymaking, our resource may degrade. Any outlook assessment of the Asia Pacific Region must seriously incorporate and reflect the realities of the fuelwood component within the context of forest resource management and the industrial driven activities (FAO, 1997). The woodfuel potential in many Southeast Asia forests is uncertain and therefore needs to be evaluated for policy intervention can be set in the context of national and international negotiation on climate changes. This study assesses the woodfuel supply and demand for the purposes to report to the governments, local CF and other stakeholders to understand the current and future available resources for the young generation to increase participation in managing resource, sustainably. This research also aims to report to other regions and other developing countries about the shortage of forest resources and the way to understand the sustainable use of resources. To attain these needs, conflict of interests among the local people and conservationists over the long term must be made. The specific aims are (1) to estimate stand structure of forest and non-timber forest products and (2) to evaluate long-term woodfuel potential to compare with consumption in two CF sites, Svaybakav (SBK) and Boeng Kok (BK), in this province. These results would answer of why-less participation. 6.2. Methodologies 6.2.1. Study site and history The study sites are located in community forests, Kampong Tralach District, Kampong Chhnang province. It has 8 districts, 69 communes, and 538 villages (NIS, 2003).This province is located in the central part of Cambodia between UTM grit coordination 1295000 – 1390000 and 410000 – 490000. The provincial total land area is 529,461 ha about 3% of the country (FA, 2007). The local topography is very flat on gently terrain from Tonle Sap Lake 10 m to southwest 151 m above sea level (Fig. 6.1 and FA, DANIDA, German Development Service, 2003). There are 9,557 of 82,638 families (total 417,693 population) being involved in community forest activities in the province (CFO, - 68 -
  • 77. 2006). This province consists of evergreen 16,156 ha, mixed-evergreen 6,136 ha deciduous 147,175 ha, wood shrub evergreen 39,312 ha and other forests 145,693 ha, equivalent to 3, 1, 28 and 8% of the province, respectively (Fig. 6.1 and FA, 2007). This tropical ecozone is often high trough out the year with a mean of atmospheric humidity 80.3%, mean annual rainfall 1400 - 2000 mm and mean monthly temperature 21 – 25 ⁰C (FA, DANIDA, German Development Service, 2003). These forests located on Tone Sap alluvial plain of the wetland system at elevation reached 5 m northern to 30 m southern part (FA, DANIDA, German Development Service, 2003) and some parts of these forests were flooded in the rainy season. Fig. 6.1. Study site history in the Cambodian community forestry and Kampong Chhnang forest cover The forest areas in this province decreased from 59.6% in 1970s to 40.4% in 2003 of the total provincial land cover (FA, 2005) because of land encroachment for agriculture and population growth. According to FA (2004 and 2005) and the field survey observations and data recording sheets, these forests have long been available in these areas. Before 1975, these forests were evergreen and mixed evergreen forests consisting of luxury-trees, wildlife and diversity. Until 1975 – 1978, these forests started degrading by Pol Pot regime to clear some parts for rice plantations. In 1980 due to the population growth very fast after Pol Pot - 69 -
  • 78. regime, these forests were clear and selected cut for agriculture and for construction. These forest communities were official under an agreement with the government in 2003 due to they are continuing to degrade. Currently, there are few trees with an open canopy with some parts are clear-cut for land ownership and agriculture. The study site Svaybakav (SBK) community forest 71.2 ha is between UTM grit coordination 1324700 – 1325700 and 472000 – 473300. 237 of 435 households are members in this CF, using forests and farming for their daily livelihood. It was first established in 1995 by CONCERN non-government organization. Until 2005, it was transferred to Forestry Administration (Fig. 6.2a). The study site Boeng Kok (BK) community forest 107.3 ha is between UTM grit coordination 1314100 – 1315900 and 470600 – 472500. 187 of 212 households are members, using forests for their daily livelihood. It was first established in 1997 by CONCERN non-government organization. Until 2006, it was transferred to Forestry Administration (Fig. 6.2b). 6.2.2. Data collection The inventories were at both sites in 2007, aimed at finding the quantity and quality of these forests. This thesis followed the procedure of the Cambodian CF guideline and its relevant policies to enumerate trees (FA, 2006). 8 and 8 sample plots were randomly selected in the SBK and BK site, respectively. Each sample plot had the area 0.250 ha (50 × 50 m) for trees at diameter at breast height 1.3 m (DBH) ≥30cm. Each subplot had the area 0.125 ha (25 × 50 m) of non-timber forest products (NTFP) and trees DBH10 – 30 cm at diameter 1.3 m (DBH10-30cm). Each subplot had the area 0.062 ha (25 × 25 m) of tree seedlings with diameter <10 cm and height ≥1 m (Seedling<10.H>1). In each plot and subplot, this thesis evaluated and measured NTFP, Seedling DBH<10.H>1, trees at DBH1030cm and DBH≥30cm in both sites SBK and BK. The NTFP was defined as the tree seedlings in height ≥1 m and < DBH10 cm that could not growth to be tree ≥ 30 cm for the whole life. We evaluated and selected NTFP-species from some experience local people, who have long been familiar with tree species and collected trees for multiple purposes. Some NTFP species in these study sites were collected for firewood, resin, leaf for making roof, fruit trees and food for animal etc. The NTFP and tree seedlings were evaluated and count to record at difference columns in the field according species, plots and sites. The - 70 -
  • 79. trees ≥ DBH10cm were also evaluated on species and measured DBH at 1.3 m or DBH above the buttress, height and total height. Fig. 6.2. (a) Geographical location of Svaybakav (SBK) and (b) Geographical location of Boeng Kok (BK) Source: Community forest office, Forestry Administration - 71 -
  • 80. We interviewed the community forestry managers to collect the numbers of population member who use trees as woodfuel. There were 1101 persons of community members who currently participating in managing SBK site but there were only 946 persons of community members who currently participating in managing BK site. The total population was 2021 and 1073 persons in SBK and BK site, respectively. There are 237member household of 435 households in SBK. There are 946 187 households of 212 households in BK site. 6.2.3. Data processing and analysis Individual species was classified according to DBH class and site. We counted the species richness of NTFP and tree seedling<10.H>1 for tabulation. Because of these forests were nearly destroyed and trees ≥30 cm were not found in the inventory raw data, we evaluated these as the deciduous forest based on field observations and inventory recording sheets as canopy open with scatter trees and non-dense and non-mixed density. Individual tree volume was estimated by using the following FA, (2006) equation: V = 0.02756 + 1.49511.D2.H (1) where V was the volume in deciduous forest at DBH10-30 (m3/ha), D was the diameter at 1.3m (cm) and H was the bole height at diameter 1.3m (m). Individual tree above ground biomass was estimated using Brown, (1997) equation: ABB = 42.69 – 12.800.D + 1.242.D2 (2) where ABB was the above ground biomass (Mg) and D was the diameter at 1.3 m (cm). The sustainable theoretical concept of this study was defined as cumulative potential of woodfuel supply (WS) ≥ cumulative woodfuel demand (WD) at time t or annual ABB increment ≥ annual consumption increment. Biomass supply increment was estimated by: BS(t0)= 0.2624CB0.5543 FA BS(t1)= 0.2624[BS(t0)+CB]0.5543 FA BS(t2)= 0.2624[BS(t0)+ BS(t1)]0.5543 FA (3) BS(t3)= 0.2624[BS(t0)+ BS(t1)+BS(t2)]0.5543 FA … BS(tn)= 0.2624[BS(t0)+ BS(t1)+BS(tn-1)+…+BS(tn)]0.5543 FA where BS(tn) is the total biomass supply in year n (Mg/ha), CB the current biomass supply (Mg/ha), BS(t0) the current biomass supply increment in year 0 (Mg/ha), BS(t1) the biomass - 72 -
  • 81. supply increment supply in year 1 (Mg/ha) and BS(tn-1) the biomass supply increment in year n-1. FA is the forest area (ha). SBK CP is 1101 population members and BK CP is 946 members. For the reasons of natural dead trees were collected for woodfuel supply, this study was excluded the mortality rate out of the estimating the annual biomass supply and demand at year t. Annual ABB increment per ha was estimated by using equation: y = 0.2624 x0.5543 (R2 = 0.6919) (Fig. 6.3). This equation was estimated based on permanent plots in Kampong Thom (1998-2003). This study limit to estimate woodfuel supply for all species of trees at DBH>10cm; however, Top et al., (2004) found householders were more selective of species for fuel wood. Grundy et al., (1993) found the dominant species of the woodland were used for fuel wood. Fig. 6.3. Re-estimation above grown biomass increments based on permanent sample plots in Kampong Thom Province by Mizoue (2006) and Top et al, (2006) data 1998 – 2003 Biomass demand increment for community members was estimated by: BD(t0)= 0.152 × CB × Pgr% × PD% BD(t1)= 0.152 × BD(t0) +CB × Pgr%× PD% BD(t2)= 0.152 × BD(t0) + BD(t1) × Pgr%× PD% (4) BD(t3)= 0.152 × BD(t0) + BD(t1) + BD(t2) × Pgr% × PD% … BD(tn)= 0.152 × BD(t0) + BD(t1) + BD(tn-1) + … + BD(tn) × Pgr%× PD% - 73 -
  • 82. where BD(tn) is the total biomass demand in year n (Mg/ha), CD the current biomass demand of community member (Mg/ha), BD(t1) the biomass demand increment in year 1 (Mg/ha) and BD(tn-1) the biomass demand increment in year n-1 (Mg/ha). Pgr% is the 2% population growth rate of community member (NIS, 2003) and PD% the 95% population of community member who used forest as fuel wood (NIS, 2003). ABB supply per person 0.142 Mg/year at time t was estimated based on Top et al (2006), who conducted this research in Kampong Thom Province, where the people standard of living and levels of using fire wood for cooking was also similar to this study site (NIS, 2003). In Rajasthan region of India, the mean fuelwood consumption was 0.82 kg/person/day of 65% of the overall household energy demand from forests (Nagothu, 2001). Total fuel wood consumption was estimated at nearly 7 t per household per year (Grundy et al., 1993). Our study estimated biomass consumption at 0.142 Mg/year/person (Top et al., 2006) with current population density 5 persons per household (NIS, 2003). The comparison between biomass supply and demand was estimated by: SvsD(t0) = BS(t0) – BD(t0) SvsD(t1) = BS(t1) – BD(t1) SvsD(tn-1) = BS(tn-1) – BD(tn-1) (5) … SvsD(tn) = BS(tn) – BD(tn) where SvsTD(tn) is the total biomass supply vs. demand in year n (Mg/ha), SvsD(t0) the current biomass supply vs. demand at the time after inventory (Mg/ha), SvsD(t1) the biomass supply vs. demand increment in year 1 (Mg/ha) and SvsD(tn) the biomass supply vs. demand increment in year n (Mg/ha). 6.3. Result 6.3.1. Species and stand structure In SBK and BK forest structure (Table 6.1, Fig. 6.4 and Fig. 6.5), we found trees were available only DBH<30 cm and many NTFPs. The NTFP richness were 26 and 29 species (Fig. 6.4) with 2451 and 978 clump/ha (Fig. 6.6), respectively in SBK and BK site. For trees DBH<10cm in height ≥1 m, the sapling richness were 66 and 71 species (Fig. 6.4) with 3192 and 3062 tree/ha (Fig. 6.6), respectively in SBK and BK site. For immature trees DBH≥10 cm, the richness were 33 and 6 species with 593 and 51 tree/ha, respectively in - 74 -
  • 83. SBK and BK site (Table 6.1). For trees DBH≥10 cm, volumes were 142.3 and only 8.6m3/ha, respectively in SBK and BK site (Table 6.1). For trees DBH≥10 cm, biomasses were 45.5 and 3.7 Mg/ha, respectively in SBK and BK site (Table 6.1). Two species Dipterocarpus obtusifolius and Shorea roxburgshii were the highest density 292.0 and 171.0 trees/ha, respectively, whereas the other species ranked from 1.0 – 26.0 trees/ha, in SBH (Table 6.1). The highest BK density was Dipterocarpus obtusifolius 44.0 trees/ha and the other species were 1.0 – 4.0 trees/ha (Table 6.1). Fig. 6.4. Svaybakav (SBK) and Beong Kok (BK) species richness of non-timber forest product and trees Fig. 6.5. Svaybakav (SBK) and Beong Kok (BK) stand density of non-timber forest product and trees Note: This forest have no tree at DBH>30cm. DBH<10.H≥1 is trees DBH<10cm with height ≥1 m. 6.3.2. Supply and demand increments Fig. 6.6 showed the increment of biomass supply and demand in SBK Community. The cumulative biomass supply increments in the year t0 – t19 were 2.2 – 3.3 Mg/ha/year from current biomass 45.5 Mg/ha (Increment = 0.2624CB0.5543). The population member increments were 22.0 – 32.1 persons/year in the year t0 – t19. The SBK current biomass supply 45.5 Mg/ha grew 155.1 – 235.9 Mg/ha in year t0 – t19. The SBK current biomass - 75 -
  • 84. demand 148.5 Mg/ha in the year t0 for current member 95%, who used biomass as wood fuel of 1,101 people. As estimated by NIS (2003), the annual population growth in this community would be 2%. The demand increased to 216.4 Mg/ha in 20 years later. Table 6.1: Current density, volume and biomass by species and site for trees at DBH≥ 10 cm Density Volume Biomass No. Scientific name (Tree/ha) (m3/ha) (Mg/ha) Svaybakav Site (SBK) 1 Acasia spp 6.0 2.5 0.6 2 Bombax ceiba 5.0 1.5 0.7 3 Dillenia ovata 1.0 0.2 0.0 4 Diospyros hrlfer 2.0 0.3 0.1 5 Dipterocarpus intricatus 4.0 1.2 0.3 6 Dipterocarpus obtusifolius 292.0 64.3 20.8 7 Eucalyptus spp 1.0 0.8 0.2 8 Eugenia spp 8.0 1.6 0.5 9 Irvingia malayana 1.0 0.2 0.1 10 Kayea engeniafolia 1.0 0.5 0.2 11 Melanorrhea laccifera 21.0 5.1 1.7 12 Parinarium anamensis 7.0 2.4 1.0 13 Peltophorum feruginrum 5.0 1.4 0.4 14 Pentacme siamenesis 3.0 0.5 0.2 15 Pterocarpus pedatus 4.0 1.2 0.3 16 Shorea otusa 6.0 1.2 0.3 17 Shorea roxburgshii 171.0 44.4 14.4 18 Sindora cochinchinensis 26.0 6.8 1.8 19 Sterospernum chelonoides 2.0 0.4 0.1 20 Terminalia chebula 1.0 0.2 0.0 21 Vatica philastreana 8.0 1.4 0.5 22 Vitex pubescens 1.0 0.2 0.1 22 Xylia dolabriformis 4.0 0.9 0.2 Total 23 species with name 580.0 139.4 44.6 Total 5 other species in local names 8.0 1.7 0.5 Total 5 unknown species 5.0 1.2 0.5 Grand total SBK 593.0 142.3 45.5 Beong Kok Site (BK) 1 Bombax ceiba 1.0 0.2 0.1 2 Dipterocarpus obtusifolius 44.0 6.9 2.7 3 Melanorrhea lacciferra 1.0 0.2 0.1 4 Parinarium anamensis 4.0 1.2 0.7 Total 4 species with name 50.0 8.5 3.6 Total 2 unknown species 1.0 0.2 0.1 Grand total in Beong Kok Site 51.0 8.6 3.7 Note: Other species in local names Svaybakav Site: Khmeas, Lat, Mrak, Rom denh and Sleng Unknown species are the species that we could not recognize in local name or scientific names Fig. 6.6 also showed the increment of biomass supply and demand in BK Community. The cumulative biomass supply increments in the year t0 – t19 were 0.5 – 1.5 Mg/ha/year from current biomass 3.7 Mg/ha (Increment = 0.2624CB0.5543). The population member increments were 18.9 – 27.6 persons/year in the year t0 – t19. The BK current biomass supply 3.7 Mg/ha grew 58.1 – 155.7 Mg/ha in year t0 – t19. The BK current biomass demand 127.6 Mg/ha in the year t0 for current member 95%, who used biomass as wood - 76 -
  • 85. fuel of 946 people. As estimated by NIS (2003), the annual population growth in this community would be 2%. The demand increased to 185.9 Mg/ha in 20 years later. 6.3.3. The comparison between supply and demand Fig. 6.7 showed the annual comparison of SBK supply and demand increment within the next 20 years. The supply increment in this site was higher than demand decrements 6.6 Mg/year. Therefore, local people could cut this forest for fuelwood based on the biomass increment 1.42Mg/person/year plus the dead trees 1%, which was widely known as the tropical mortality rate, sustainably. The supply would increase to 19.5Mg/year higher than demand increment. However, cutting 6.6 Mg/years would be unknown as the sustainable yield or not since the cutting impact may exist highly on this complex density of this ecosystem. Annual allowable cut should then be studied to increase number of population participation. Fig. 6.8 showed the annual comparison of BK supply and demand increment within the next 20 years. Because of this structure were very poor 3.7Mg/ha, local people in this community did not have a chance to use this forest fuel wood. The increment of supply was slower than the demand increment 69.5Mg/year, in the year t0. In the 20-year later (t19), the supply increment was lower than demand increment 30.2 Mg/year. 6.4. Discussion 6.4.1. Species and stand structure There were 66 and 71 species richness for all trees at DBH< 10 cm in height > 1m in SBK and BK, respectively, (Fig. 6.4). There were 33 species DBH> 10cm in SBK (Table 6.1 and Fig. 6.4) , more or less similar to other tropical forests: 37-54, 44-57, 106, 64–89 and 39 in central Cambodia, north Cambodia, Costa Rican, South India and Bhutan, respectively (Top et al., 2009; Kao and Iida, 2006; Finegan et al., 1999; Pélissier et al., 1998; Buffum et al., 2008). However, the BK site was very poor in density (Table 6.1), which could not compare with other studies. As the history statements, these forests were high in densities including luxury species. Because of population growth and poor after returning from killing fields, these community resources are now fall far behind the richness of diversity with volume 8.6 – 142.3m3/ha and biomass 3.7 – 45.5 Mg/ha for only trees at DBH< 30 cm. The evergreen structure converted to deciduous structure with much opened - 77 -
  • 86. in canopies. Our study estimated woodfuel for tree at DBH< 30cm, which was similar to the case in Kampong Thom Province, Cambodia (Top et al., 2003 and Top et al., 2009). In Kampong Thom Province, Cambodia, biomass for trees at DBH< 30 cm were 59.9 Mg/ha (Top et al., 2009) to be a little higher than these community forestry 45.5 and 3.7 Mg/ha in SBK and BK, respectively (Table 6.1). 6.4.2. Biomass supply increment The biomass increased 2.2 – 3.3 Mg/ha/year (Increment in year 0 = 0.2624×45.50.5543) for SBK and 0.5 – 1.5 Mg/ha/year (Increment in year 0 = 0.2624×3.70.5543) for BK site were lower than in Kampong Thom Province 4.59 Mg/ha/year (Top et al., 2004a) at the same deciduous forest of trees at DBH>10cm. The low biomass increment were because the current density of biomass 3.7 – 45.5 Mg/ha in our study sites (Table 6.1) were lower than in Kampong Thom deciduous forest 189 Mg/ha (Top et al., 2004a). Our current study sites found only trees at DBH10-30 cm have annual increment to be similar to 2.5 Mg/ha/year (Top et al., 2006). In these deciduous forests of trees at DBH10-30 cm, the average of biomass growth was estimated to be 4.0 % of SBK site and 9.7 % of BK site within the year 2007 - 2027. Top et al., (2004) found the average biomass increment for trees DBH> 10 cm in deciduous forest was 2.4 %. 6.4.3 Biomass demand increment Energy consumption in developing countries is projected to grow at an average annual rate of 3 percent from 2004 to 2020 (FAO, 2008). In industrialized countries, where national economies are mature and population growth is expected to be relatively low, the demand for energy is projected to grow at the lower rate of 0.9% per year, albeit from a much higher starting point (FAO, 2008). Energy demand in the developing countries of Asia is projected to grow at an average rate of 3.7% per year, far higher than any other regions (FAO, 2008). Our study biomass demand increment was estimated based on population growth 2% (projected until 2020) with 95% of the total population who used trees as fuelwood (NIS, 2003). In Cambodia, around 76% of the 10,452 villages of Cambodia will still be without electricity in the year 2010 and need land for tree planting 0.02 ha/household for electricity (Abe et al., 2007). In Valley Thicket of South Africa, there were 88% of households, who - 78 -
  • 87. used fuelwood for cooking (Pote et al., 2006). In Cambodia, 95% of the population is dependent on woodfuel for cooking (NIS, 1998) and also Top et al., (2003) also found woodfuel consumption rates was 94.3% of the total woodfuel consumption, in Kampong Thom Province, Cambodia. Therefore, this study used consumption rate 95% for predicting woodfuel demand. Currently, the standard of living surround these community are poor (without electricity or gas for cooking), therefore, local people used woodfuel for cooking. Cambodia has a population of 13.6 million and was classified as a low-income country with a gross national income per capita in 2004 of US$320 (Abe et al., 2007). Fig. 6.6. Biomass supply and demand increment by community forestry site 6.4.4. Woodfuel supply and demand As predicted, when the population growth 2% within 20 years later (NIS, 2003), the BK forest may degrade if the members of the communities are continuing to cut the forest for cooking (Fig. 6.7). For SBK forest, local can use 0.142 Mg/person/year for cooking since the supply increment is higher than demand increment (Fig. 6.7). At the present, the SBK and BK forests were banned to harvest for any purposes, thus, local people are using agriculture wastes, collecting dead fruit-trees branches, collecting dead trees in these study sites for cooking and buying woodfuel from outside sources. These forests are in the issue to compromise because each person has a forest area supply 0.06 and 0.1 ha for cooking in SBK and BK site, respectively. However, these forests would be degraded, if all 2021 - 79 -
  • 88. persons (member and non-member) in SBK site and 1073 persons in BK site who are living around them, who were cutting these forests for fuelwood. In Kampong Thom, each person has a forest area supply 1.14 ha with a high density of evergreen, mix-evergreen and deciduous forest trees (Top et al., 2003). However, the case in Kampong Thom Province Forests, cutting forest for fuelwood alone, may not cause deforestation because the local people preferred only on the trees below DBH30 cm but the density above DBH30 cm remain high enough to survive (Top et al., 2006). Also in Rajasthan of India, the current extraction of forest resource by local people for fuelwood may not be the major reason for deforestation in the area, since it largely involves collection of dry and fallen wood rather than cutting of trees (Nagothu, 2001). Biomass increment (Mg/year) 25 20 15 10 5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Supply minus Demand (year) Fig. 6.7. Svaybakav (SBK) woodfuel supply and demand at time t We found the biomass supply increment from the year 1 to year 20 was a little higher than demand increment for SBK site; however, BK site biomass demand increment was higher than supply increment in each year since the current biomass was poor (Fig. 6.6). In South Africa, biomass demand 3% would cause woodland stocks to decline after 20 years; and continuation of current harvesting practice would lead to severe deforestation within 15 years (Banks et al., 1996). Regional wood energy development program in Asia found Cambodian potential supply 81,565 kton higher than consumption 5,375 kton in the year 1994; however, the supply decreased to 43,827 kton with the consumption increased to 7,553 kton in the year 2010 (FAO, 1997a). Therefore, this study would be an example to report the lack of resources for the next generation in these communities. Even though, the - 80 -
  • 89. WB, UNDP and FAO, (1996) assumed in its report that 50% of all fuelwood was extracted from the forests, BK forest resource was still not enough supply for the local members of this community. Local people would wait at least 3-year for forest growth to be higher than demand growth [58.1 – (127.6 ×0.5)]. Supply minus Demand (year) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Biomass increment (Mg/year) 0 -10 -20 -30 -40 -50 -60 -70 -80 Fig. 6.8. Beong Kok (BK) woodfuel supply and demand at time t 6.5. Conclusion We understood that the research on current supply was lower than demand increment in BK site, which was the fundamental cause to destroy the ecology of the forests. Therefore, the results have benefit from the new perspective such as consideration of supporting these ecosystems and local people. The solutions to these problems should be at both sites, all local people have less chance to use this forest resource, so it is important to motivate villagers to participate in managing and monitoring these resources. Sustainable annual cut should be estimated for woodfuel to encourage CF members to take responsibility. In replying to the international emergent need to increase the canopy program, this study provides the strategic to implement sustainable use of forest resources by calling new project funds to reforest at both sites. Estimate carbon credit to look for funds to support these forests, since currently, there is a Reducing Emission from Deforestation and Degradation project under the Global Canopy Program has just started. The best and effected ways are to call for cooperation between governments and academic research institutions to assist these forests, immediately. The final solution is to explain the local people to understand the roles of forests for their daily livelihood not only for the present - 81 -
  • 90. but also for their young generations. Each community can also be viewed as an end-result of one or more adaptive radiation to control these ecosystems. This study method would be important for any communities or regions where conflict of interest on resource use is practiced. This study provides basic information as a sample for other communities in the country and it may be a useful method for solving conflicts of interest, internationally. Using current biomass without waiting for the growth can cause deforestation and lead to change the structure and composition within the long period, when the forest will be heavily disturbed. At the present, cutting trees for woodfuel in the BK site is impossible because the current population is higher than the current resources. However, all members can cut the forest for fuelwood in the SBK site based on biomass increment. Cutting forest without realizing on annual increment lead to disturb biodiversities and degrade. Local people are now using woodfuel from different sources such as fruit trees from their own villages, agriculture wastes from their own farms, collecting the dead branch trees from this study site, buying charcoal from the market sources nearby and the expensive gas that most of the people could not afford. Currently, local people can use dead trees only after the government of Cambodia banned to cut these forests, which are now endangering. The death was widely known as 1 % in the tropics, the SBK current biomass 45.5 Mg/ha provided dead biomass 0.5 Mg/year. At the time of the numbers of households start using electricity and gas, the consumption of fuelwood and demand should be restudied for managing these forests. This study provides important information profit to reach an agreement between community-based forest managers and stockholders together with increasing local participants to improve these resources, sustainably. - 82 -
  • 91. Chapter 7: Evaluating of the Cambodian yield regulation for tropical natural forest management Keywords: Cambodia, AAC, Yield regulation, Commercial species, Damage 7.1. Introduction There have been increasing concerns on sustainable forest management (SFM) in tropical natural forests, being disproportionately important in the global carbon budget (e.g. Malhi and Grace, 2000) and biodiversity conservation (e.g. Myers et al., 2000). Selective logging is a common production system in tropical forests, where the yield regulations are mostly based on one universal criterion: a minimum diameter cutting limit (MDCL) for all commercial timber species (Sist et al., 2003, Environmental Conservation 30: 364-374). In this, all or part of trees > MDCL are allowed to be harvested. Studies indicated this MDCL rule tends to result in over logging. For example, Sist et al (2003) indicated that MDCLs in mixed dipterocarp forests of the Malaysia region lead to high felling intensities (10-20+ tree ha-1), resulting in stand damage with >50% of the remaining tree population. Van Gardengen et al (2006) used the growth and yield simulation model to conclude the maximum extracted volume of 35 m3/ha with a 30-year cutting cycle was unsustainable for the Tapajos region of the Brazilian Amazon, suggesting an extraction 10 m3 /ha every 30 years. Most of the previous studies on the yield regulations of tropical forests were for seasonal tropical rain forest forests especially in Brazilian Amazonia and in Borneo island, and however, very little is known about sustainability of selective logging for tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia. About 59% of Cambodia is covered by forest. There are three dominant forest types, evergreen (22.2%), deciduous (25.8%) and semi-evergreen forest (7.5%) (FA, 2007), in two classes, production forest (34% of total land area) and protection forest (25%). A selective logging system with a 25- to 30-year cutting cycle has been adopted in evergreen and semievergreen forests (KimPhat et al., 1999). Traditionally, there have been two roles of yield regulation in Cambodia; 1) Annual allowable cut should be based on the assumption of volume increment at 0.33m3/ha/year, resulting in 8.25 m3/ha (=0.33*25) of harvestable volume under 25-year cutting cycle, and 2) felling volume should be restricted to 30% of available commercial species greater than MDCL. However studies found that the - 83 -
  • 92. concession companies tended to over-cut their forests, under these rules (KimPhat et al., 1999; DFW, 2001). It was also said that the rule based on the volume increment 0.33 m3/ha/year was too conservative (DFW, 2001), since this increment value is the average of virgin forest studies reported by the FAO in 1962 (DFW, 2001). Indeed, Kao et al. (2010) have recently found the mean volume increment of 0.86 m3/ha/year using permanent sample plot measurements in central Cambodia. Recently, the Cambodian Government has proposed a new yield regulation system; it is an advanced point for this system that takes into account sustainability of each of commercial species, although the MCDL rule is basically used as in many other yield regulations. This new system considers recovery levels (RLs) of each commercial species, which is ratio of the estimated number of trees >MCDL after the 25-year cutting cycle against the tree number before harvesting. The current guideline requires each commercial species to achieve the RLs of 60% and 90% for unlogged and logged forests, but the reasons of adopting these thresholds are unknown. In strict sense of sustainability, more than 100% RL should be achieved. This study aims to evaluate how the Cambodian new yield regulation performs well as compared with traditional ones, growth potential and others adopted in other countries, toward further improvement. Specifically, it is to evaluate the Cambodian new rule of estimating sustainable yield (annual allowable cut) under different scenarios. 7.2. Methods 7.2.1. Study site Under the administrative control of Choam Khsant, Chhaeb and Tbaeng Mean Chey Districts. These 2,635 households come from 16 villages within 6 communes. The mean annual temperature in the area is 24.7C, lower than the national mean annual temperature of 26.7C. The highest temperature was 41.0C and the lowest temperature was 19.4C. The humidity varies from 72.3% in January to 86.9% in October, with an annual average of 80.3% (NIS, 1998). The study area of approximately 103,058 hectares of different forest formations was at longitude 104º 58‘ E to 105º 2‘E and latitude 13º 48‘ N to 14º 9‘ N within the province of Preah Vihear (Fig. 7.1) . It is accessible from Phnom Penh by using National Route No. 6 - 84 -
  • 93. and then following National Roads No. 127 and 128 to reach the Preah Vihear area, and takes about 5 hours by car to reach Preah Vihear Forest. Table 7.1: Sampling characteristics for unlogged (UNFE) and logged (LGFE) evergreen forest trees above dbh 10 cm Sampling characteristic UNFE LGFE Total area (ha) 4,134 3,510 Total number of PSU : 10 10 Total area of PSU (ha) 827 702 Average area of PSU (ha) 83 70 Total number of sampling units: 60 60 Area of trees dbh 10 cm to 29 cm (m) 20x20 20x20 Subplot area of trees dbh 10 cm to 29 cm (ha) 0.04 0.04 Area of trees dbh above 30 cm (m) 20x60 20x60 Subplot area of trees dbh above 30 cm (ha) 0.12 0.12 Plot area per PSU (ha) 0.96 0.96 Total sampled area (ha) 9.6 9.6 Number of plots per sampled PSU 6 6 (+ or -)10% sampling error @ 95% confident level 1.96 1.96 a a Primary sampling unit Fig. 7.1. Preah Vihear Forest land cover map Source: Cambodia Forest Administration-GIS/Office 2000 - 85 -
  • 94. The terrain consists of mostly flat alluvial plain from the Tonle Sap basin in the south and gently rises to a moderately rolling terrain in the north. Three major forest types of evergreen, mixed and deciduous are on five major soil types. Evergreen forests have a distinct preference for Psamments and Udults. Mixed forests prefer Psamments and Aquults, and deciduous forests grow almost equally in Psamments and Aquults, Aquents and Psamments cover most of the area at about 45,611 hectares (44.3%), especially in the northwest of the area. The parent material is decomposed rock and is acidic (pH 4.5 – 6.5). The study site included a very small area of alluvial soil, less than 200 hectares (0.2%) at the southern tip of the concession near the main road entering the concession. Aquents covered about 12,856 hectares (12.5%) of the total study site area; Aquults covered about 28,989 hectares (28.0%); and Udults covered about 15,406 hectares (15.0%) (Kao, 2003). The forest vegetation over the area comprised two major forest types: UNFE and LGFE, as interpreted by the Geographic Information System (GIS) Unit of the Forest Administration (FA) from satellite images in the year 2000, and was further updated from a field reconnaissance survey and field assessment during the forest inventory recording (Fig. 7.1). After comparing the ground assessment with the satellite images in the year 2000, forest typing and forest zonation, the identified forest area was 7,644 hectares (Table 7.1, Fig. 7.1). Since 1998, the Preah Vihear Forest has been operated only in one coupe. According to the originally approved "Master Plan" and the "Annual Logging Operational Plan‖ by a forest concession company, the first compartment has seven coupes: 1 - 7 (CCP, 1996). When the previously approved plan was made, the concessionaire was supposed to operate the coupes of this first compartment sequentially by numbers. Coupe 2 (UNFE) of 4,134 ha was not harvested (Fig. 7.2). Only coupe 1 (LGFE) of 3,510 ha was harvested (Fig. 7.2). With technical support of an executive agency of the World Bank, and a counterpart of the Forest Administration of Cambodia, a two-year forest inventory project was introduced in 2000 and enumeration was from April 2001 to September 2001. This inventory project covered 7,644 ha of forests in Preah Vihear Province (Fig. 7.2). The inventory map was interpreted by using satellite images in the year 2000 from the GIS office, Forest Administration. Forest types within the permanent production forest were divided into two major forest types: UNFE and LGFE. - 86 -
  • 95. Under this inventory project, the procedure of the Cambodian Forest Management Planning Manual was used (DFW, 2001a). In each forest type, 50 Primary Sampling Units (PSU) were delineated on a map with UTM grid coordinates. The PSU in UNFE and LGFE had average areas 70 and 83 ha, respectively (Table 7.1). Ten PSUs were randomly selected from the 50 PSUs in each forest type on the map (Fig. 7.2). Sixty sample plots were formed in UNFE and sixty sample plots were formed in LGFE (Fig. 7.3). In each sample plot, a subplot was formed at 20 x 20m (Table 7.1). Fig. 7.2. Primary Sampling Unit allocation Source: 25-year strategic sustainable forest management plan (Kao, 1999) The PSU in the forest was found by using a Global Positioning System. We first demarcated the boundaries of the plot (20m x 60m) and subplot (20m x 20m), and then evaluated the trees in the plot: tree species, measured diameter at breast height (dbh) and height (Kao, 1999). The data collected were species, diameter at breadth height (or diameter above the buttress) and height. All trees at dbh 10 cm to 29 cm, species and height were recorded in each subplot (Table 7.1, Fig. 7.3). All trees at dbh above 30 cm, species and height were recorded in each sample plot (Table 7.1, Fig. 7.3). 7.2.2. Data processing We summarized the following information from the inventory data by dbh range: total number of tree species, including the number of native, unknown, and endemic species; - 87 -
  • 96. basal area (BA), tree density, and volume by species or forest type or both; and species importance commercial values. The importance value was the sum of the relative density (percent of the stand total density) and relative BA (percent of the stand total BA). The minimum diameter cutting limit (MDCL) at breast height (dbh) for harvested trees was above 30, 35, 40, 45, 50, 55 and 60 cm and above 10 cm for regenerating trees. Fig. 7.3. Plot allocation Note: This map is edited by FA-GIS office 2000 The information collected from the 60 sample plots each of UNFE and LGFE was analyzed and was integrated into a usable classification of tree species and tree dbh range by sorting and coding the trees by family name and selecting the dbh class for tabulation. To calculate the stand volume of tree species in each family, we first calculated the stand volume by using formula of the Forest Administration (Table 7.2). For each plot, we calculated tree density, volume and BA by number of individuals of each species for all trees at dbh above 10 cm. Average values were calculated for logged and unlogged area. The analysis was done for the number of trees of each species in each plot. Trees in the lower diameter class at dbh 5-9 cm were not included. We then calculated the average - 88 -
  • 97. volume of inventory plots in UNFE and LGFE to characterize the main variability by using the equation proposed by Kao and Iida (2006): n V   (Vi /P ft /PSU ft ) i 1 where, V is the average volume by species (m3/ha), Vi is the volume (m3), Pft is the subplot area by forest type, PSUft is the number of primary sampling unit by forest type, i is species and n is the number of species. To estimate the recovery level, first I followed the Cambodian new rule for yield estimations (FA, 2004) by selecting only commercial trees >MCDL, rotation length is 25 years, cutting only 50% of commercial trees and considering recovery levels after logging for each commercial species. Then estimated the recovery level (RL) by selecting number of harvestable trees in 25 years after logging divided by number of harvestable trees before logging. The RL(%) was estimated as following: RL(%)  (N  MCDL  N  MCDL (DI)(1 - D%)(1 - M)CC  100 N  MCDL where, D% is damaged rate (%), M%, mortality rate (%) and DI, diameter increment (cm). The selection process of RL(%) was based on Fig. 7.4. Yields were estimated under 2 scenarios in 5 recovery levels of 60, 70, 80, 90 and 100. Scenario 1 was based on the D% = 10.0%, M%= 1.0% and DI = 0.5 cm. Scenario 2 was based on the D% = 12.6% (Kao and Iida, 2006), M%= 2.4% (Chapter 5) and DI = 3.2 cm (Chapter 5). The Cambodian new guideline for estimating annual allowable cut (AAC) was evaluated using this inventory data. Under this guideline, harvesting is allowed only for commercial species that fulfill recovery levels (RLs) of number of harvestable trees with size more than MDCL in 25 years after logging; 60% and 90% of RLs are currently adopted for unlogged and logged forests, respectively (Fig. 7.4). - 89 -
  • 98. Fig. 7.4. Cambodian new rule for yield estimations (FA, 2004) Table 7.2: Volume equations by species group, DBH range and forest type (Forestry Administration, 2003) Tree Species Diameter class Evergreen forest Dipterocarp Below 15 cm Volume = 0.022 + 3.4 DBH2 Above 15 cm Volume = –0.0971 + 9.503 DBH2 Non-dipterocarp Below 30 cm Above 30 cm Volume = 0.03 + 2.8 DBH2 Volume = –0.331 + 6.694 DBH2 DBH is diameter at breast height 7.3. Results and discussion Two scenarios (S1 and S2) were evaluated under different RLs from 60 to 100%. S1 is based on the guideline‘s assumption; damaged rate 10.0%, DBH increment 5.0 mm and mortality 1.0%, and S2 is based on my new findings as in the previous chapters such as damaged rate 12.6%, DBH increment 3.2 mm and mortality 2.4%. The AACs tended to decrease with increasing RLs, and the values from the current guideline (S1) were always larger than those from S2. AACs estimated from S1 were 35.5 m3/ha/year (at RL 60%) and 39.1 m3/ha/year (at RL 90%) for logged and unlogged forests, being much higher than growth potential (21.5 m3/ha/25years = 0.86 m3/ha/year×25 years) (Fig. 7.5).The results seek for updating information on stand dynamics used in the current guideline and reconsidering RLs to be fulfilled. In the case of this study sites, adapting more than 70% of RL is acceptable under the updated data in terms of growth potential. However, around 10 m3/ha of AAC is highly recommended to achieve the ideal RL of 100% that ensures sustainability of species diversity as well as growing stock. Interestingly, this 10 m3/ha of - 90 -
  • 99. AAC is the same to one proposed by van Gardingen et. al (2006) for primary tropical rain forest in the Amazon, based on the modeling approach under the cutting cycle of 30 years. Fig. 7.5. Annual allowable cut (AAC) under different recovery levels (RLs). ―None‖ indicates the results without accounting RL. In conclusion, differences in some indicators of productive capacity, such as tree and stand growth, existed between the previous assumed values and ones found newly in this study, calling for revision of the Cambodian management planning guidelines. Especially, it should be noted that the current Cambodia‘s allowable cut level is larger than growth potentials. Future evaluations on long-term dynamics of logged and unlogged sites may be critical for more accurate evaluation of sustainable productive capacity of tropical seasonal forests. - 91 -
  • 100. Chapter 8: General discussion and conclusion 8.1. Usefulness and limitation In order to manage an ecosystem sustainably, the Forest Stewardship Council designated 10 principles with many supported criteria. Also, the International Tropical Timber Organization made guideline in its policy development series 1 to manage tropical forest ecosystems. In 2007, the Montréal Process reviewed and is reviewing on criteria and indicators to manage ecosystems as well. Therefore, the whole studies were completely to support FSC, ITTO and the Montréal Process. The maintenance of productive capacity of ecosystems was evaluated to provide the strategic implementation on sustainable yield evaluation based on structure (Chapter 4, 5 and 7) and dynamics (Chapter 6). The main advantages of this criterion are to manage yield for long-term uses and to reduce the impact on forest structure loggings. This criterion consists of five indicators: (1) Area and percent of forest land and net area of forest land available for wood production; (2) Total growing stock and annual increment of both merchantable and non-merchantable tree species in forests available for wood production; (3) Area, percent, and growing stock of plantations of native and exotic species; (4) Annual harvest of wood products by volume and as a percentage of net growth or sustained yield; and (5) Annual harvest of non-wood forest products. In replying to the urgent needs from developing countries to test criteria and indicators for managing their forests to be qualified as the international standard, specifically, each chapter worked closely to give strategic implementation on each indicator of criteria 2 of Montréal Process. Indicator 1 was at Chapter 3 that tested the unlogged stand structure, which plays a key role in forest zonation before sustainable forest management starting. Indicator 2 was at Chapter 5, which was critical for evaluating the forest rotation length and was the most fundamental to ensure sustained timber yield. Indicator 3 was at Chapter 3, 4 and 5, which was indentified the native and exotic species that need to conserve or to harvest. The information by species needed to effectively plan the number of trees remaining after logging in logged areas for the next cutting cycle, and to increase the likelihood of meeting long-term management goals for logged areas. Indicator 4 and 5 were at Chapter 4 and 7 that tested and assessed the damages and AAC vs. annual increments. Chapter 6 addressed the problems that mentioned about over degraded forests and impacted - 92 -
  • 101. to be decreased participation from local member to manage and to have not enough resource for future generation. More importantly, Chapter 6 provided information on biomass carbon management as well. Chapter 2 expressed the lack of knowledge on strategic planning as an example but it was important for a sample of methods for well plan to claim certification. This thesis limited the data collection for evaluating stand structure on three main forests of unlogged, logged and degraded forests at the large scale in forest concession approximately 100,000 ha (Chapter 3), on small scale in coupe level 3,000 – 4,000 ha (Chapter 4) and on small scale in community level around 70 – 100 ha (Chapter 6). The evaluation on stand dynamics was from 5 ha permanent sample plot (Chapter 5) at production area namely evergreen forest. Therefore, results of this report would be critical to test on the ecosystems for long-term yield in Chapter 7 and Chapter 2 that provided strategic implementation to fit with the actual natural density (High growth is high yield and/or high density is high yield). 8.2. Recommendation and conclusion The structures and dynamics information from logged and unlogged site at big and small forests would be more important for evaluating rotation length and productive capacity of forest ecosystems. This thesis recommends and concludes as following: o Chapter 2: Because the sustainable forest management remedies are based on specific knowledge of criteria and indicators, this assessment may be useful for the future establishment and management of sustainable yields at tropical forests. On the other hand, planning based on international standard criteria and indicators would be an asset for friendly environment, globally, because harvesting planning would be critical to improve productive capacity and carbon when the canopy will be opened to young trees to improve stand growths. Too dense of forests may destroy quality of timber or may lead big trees to die naturally at old age of forests. o Chapter 3: For more accurate assessments on the sustainable forest management based on stand structure of the unlogged forest to conduct forest zonation and use, further research is needed on the size and dynamic of trees in each forest type. With this flexibility and demonstrated accuracy, we believe stand structure at unlogged - 93 -
  • 102. area will provide the accessible and effective information for forest stand management, regeneration modeling and forest zonation. o Chapter 4: Extrapolations of these results to an anticipated acceptable cutting cycle must be interpreted with caution. Silvicultural treatment to reduce the damaged rate and improve the selective cutting rate in the forest disturbance zoned for timber production should be considered as a managed viability option. Ongoing restudy of this and other plots at unlogged sites for the next cutting cycle are necessary to provide a strong basis for how to reduce the impact of logging causes. Therefore, the impact of reduced logging should have been included to make the presence investigation more comprehensive and meaningful. o Chapter 5: Interestingly, our findings of stand dynamics from tropical seasonal forests in Cambodia are relatively similar to many values reported from tropical rain forests in Neotropics and in Southeast Asia. New strategic long-term, medium-term and annual operational plans at production forests should then be reviewed to fit only with increments and damages. Setting permanent sample plots and repeating inventories at logged sites should have been established and conducted to make the current estimations more meaningful and useful for SFM practice. o Chapter 6: Sustainable annual cut should be estimated for timber and woodfuel to encourage and to increase CF members to take responsibility at degraded land. Disseminate this result to local people should be important for motivation in managing. However, the dynamic of structure caused from cutting forest for woodfuel after 2027, should then be restudied because the standard of living and the number of participants may changes in this province. Estimate biomass carbon at below and above grounds should also be an asset to look for fund to enlarge density and improve forest quality at this degraded lands. o Chapter 7: Reviewing and reediting new management plans using new methods from this study that fit to forest increments should be conducted effective and efficient SFM for claiming certification in this country as well as in Southeast Asia. - 94 -
  • 103. Policy and decision makers and managers should take into account the results found in these studies to make a new plan based on this testing on this criterion of maintenance productive capacity. This study found complete section to support all indicators 1 – 5 of the criterion to manage timber and non-timber forest products and to manage commercial and non-commercial species. However, this study did not convert biomass and volume into carbon management that currently the hot topics for climate changes. The well management of production forest would be already the best options to gain carbon stock in the forests for today and the future. Therefore, further researches on productive capacity to gain carbon and timber stocks are needed for environmental and economic benefits./. - 95 -
  • 104. Summary Keyword: Cambodia, Tropical Seasonal Forest Ecosystems, Productive Capacity, Criteria, Forest Management, Forest policy, Montréal Process There have been increasing concerns on sustainable forest management (SFM) in tropical natural forests, being disproportionately important in the global carbon budget and biodiversity conservation. Maintenance of productive capacity is one of the most important criteria for SFM, but very little is known about productive capacity of tropical seasonal forests in mainland Southeast Asia, such as those in Cambodia. About of 34% of Cambodia is classified into production forests, and a broad set of regulations and guidelines of forest management practices has been developed, but there have been lack of scientific evaluations of them. This study aims at evaluating indicators of productive capacity of tropical seasonal forests in Cambodia, mainly focusing on stand structure, dynamics and sustained yield of unlogged and logged evergreen forests. First, the 25-year strategic forest concession management plan for a company was evaluated based on criteria and indicators of Montréal Process, focusing the criteria 2; ―maintenance of the productive capacity of forest ecosystems‖. There were 33 subindicators of Criterion 2 of the Montréal, and only 52% (17 sub-indicators) were fulfilled in the concession management plan. This suggests that indicators related to growing stock for each of forest types and species group, plantations of native and exotic species and nontimber forest products should be included in forest concession management planning. Second, stand structure of natural evergreen forests in Preah Vihear, Northern Cambodia was evaluated using data from a total of 120 plots, obtained from large-scale inventory by a concession. The density, volume and basal area (BA) of trees ≥10cm diameter at breast height (DBH) were 220.3 trees/ha, 151.9 m3/ha and 11.0 m2/ha, respectively, in logged evergreen forest (LGFE) and 241.9 trees/ha, 185.8 m3/ha and 13.5 m2/ha, respectively, in unlogged evergreen forest. The density, volume and BA of harvested trees at DBH≥50cm in LGFE were 3.0 trees (22.4% of total), 22.2 m3 (29.5%), and 1.6 m2 per hectare (27.1%), respectively. The density, volume and BA of damaged trees at 10-49 cm DBH in LGFE were 12.6%, 25.3% and 40.4%, respectively. - 96 -
  • 105. Third, stand dynamics of seasonal evergreen forest in central Cambodia were estimated from 20 plots measured in 1998 and 2003. Data for all trees with DBH≥ 10 cm and for commercial species DBH≥ 10 cm or DBH≥ minimum diameter cutting limit (MDCL) were evaluated. The mean DBH increment was 0.33 cm and 0.32 cm; mean mortality rates were 2.4% and 0.5%; mean recruitment rates were 2.5% and 1.4%; and volume increments were 1.09 and 0.86 m3/ha for all and commercial species, respectively. These values are similar to those reported from tropical rain forests in Amazon and Southeast Asia. Estimated volume increment 0.86 m3/ha/year for commercial trees with DBH≥MDCL was significantly larger than the figure 0.33 m3/ha/year previously used in Cambodian management systems. Finally, the Cambodian new guideline for estimating annual allowable cut (AAC) was evaluated using inventory data from a concession company in Northern Cambodia. Under this guideline, harvesting is allowed only for commercial species that fulfill recovery levels (RLs) of number of harvestable trees with size more than MDCL in 25 years after logging; 60% and 90% of RLs are currently adopted for unlogged and logged forests, respectively. Two scenarios (S1 and S2) were evaluated under different RLs from 60 to 100%. S1 is based on the guideline‘s assumption; damaged rate 10.0%, DBH increment 5.0 mm and mortality 1.0%, and S2 is based on my new findings as in the previous chapters such as damaged rate 12.6%, DBH increment 3.2 mm and mortality 2.4%. The AACs tended to decrease with increasing RLs, and the values from the current guideline (S1) were always larger than those from S2. AACs estimated from S1 were 35.5 m3/ha/year (at RL 60%) and 39.1 m3/ha/year (at RL 90%) for logged and unlogged forests, being much higher than growth potential (21.5 m3/ha/25years = 0.86 m3/ha/year×25 years).The results seek for updating information on stand dynamics used in the current guideline and reconsidering RLs to be fulfilled. In the case of this study sites, adapting more than 70% of RL is acceptable under the updated data in terms of growth potential. However, around 10 m3/ha of AAC is highly recommended to achieve the ideal RL of 100% that ensures sustainability of species diversity as well as growing stock. Interestingly, this 10 m3/ha of AAC is the same to one proposed by van Gardingen et. al (2006) for primary tropical rain forest in the Amazon, based on the modeling approach under the cutting cycle of 30 years. - 97 -
  • 106. In conclusion, differences in some indicators of productive capacity, such as tree and stand growth, existed between the previous assumed values and ones found newly in this study, calling for revision of the Cambodian management planning guidelines. Especially, it should be noted that the current Cambodia‘s allowable cut level is larger than growth potentials. Future evaluations on long-term dynamics of logged and unlogged sites may be critical for more accurate evaluation of sustainable productive capacity of tropical seasonal forests. - 98 -
  • 107. Acknowledgements I am particularly grateful my adviser Associate Professor MIZOUE Nobuya and Professor YOSHIDA Shigejiro of Kyushu University for their many valuable suggestions in all chapters, encouragement and support during this study. I furthermore thank Dr. NAGASHIMA Keiko, Dr. KAJISA Tsuyoshi, Dr. KITAHARA Fumiaki and all colleagues, who share idea and comments in the Laboratory of Forest Management, Kyushu University, Japan. I thank the Cambodian 1994-Group Foresters, especially Dr. TOP Neth, who keeps to give many good communications and advises to succeed. I also thank the head of the Cambodia‘s Forestry Administration, for his approval to study in Japan. My special thanks would go to Japanese Government and Japanese People, who provide fund for this study and Committee Advisors of Kyushu University, who review this thesis. I am indebted to my family and parents, who keep calling to give encouragements to me from Cambodia. My special thank to EITO San and his family members, who gave value relationship to my family members in Japan with many entertainments during my stays in Japan. - 99 -
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  • 121. List of tables Table 1.1: Forest cover and other land use of Cambodia and province‘s study sites based on LandSat image shot in the year 2002 and 2006 in hectare Table 2.1: Valid forest concession area in Cambodia Table 2.2: Summary of criteria and indicators of CFC Company Table 2.3: Summary of sustainable forest management sub-indicator data and rating Table 2.4: Area of forest land and net area of forest land available for timber production Table 2.5: Total growing stock of both merchantable and non-merchantable tree species on forest land available for timber production Table 2.6: The area and growing stock of plantations of native and exotic species Table 2.7: Annual removal of wood products compared to the volume determined to be sustainable Table 2.8: Annual removal of non-timber forest products (NTFPs) Table 2.9: Summary of Criterion 2 of maintenance of the productive capacity of forest ecosystems Table 3.1: Tree measuring procedure in each plot Table 3.2: Change of forest types in Preah Vihear Forest 1996-2000 Table 3.3: Forest land use classification in Preah Vihear Forest Table 3.4: Sampling parameters for evergreen forest of dbh above 10 cm Table 3.5: Density of stem, volume and basal area in dbh class above 10 cm Table 3.6: Stand structure of evergreen forest above 50 cm dbh Table 3.7: Projected distribution of species of dbh above 10 cm in evergreen forest by royalty class Table 3.8: Projected distribution of dbh class of evergreen forest by royalty class Table 4.1: Sampling characteristics for unlogged (UNFE) and logged (LGFE) evergreen forest trees above dbh 10 cm Table 4.2: Distribution of the density of trees, volume and basal area at dbh above 10 cm by family in UNFE and LGFE Table 4.3: Distribution of density, volume and basal area of trees at dbh above 10 cm in LGFE and UNFE by dbh class Table 4.4: Density, volume and basal area of unlogged trees, harvested trees and damage rate Table 5.1: Volume equations by species group, DBH range and forest type (Forestry Administration, 2003) Table 5.2: Stand structure in 1998 and 2003 Table 5.3: Annual diameter increment (cm/year) for diameter classes Table 5.4: Annual values of recruitment, mortality and illegal cut Table 6.1: Current density, volume and biomass by species and site for trees at DBH≥ 10 cm Table 7.1: Sampling characteristics for unlogged (UNFE) and logged (LGFE) evergreen forest trees above dbh 10 cm Table 7.2: Volume equations by species group, DBH range and forest type (Forestry Administration, 2003) - 113 -
  • 122. List of figures Fig. 1.1: Framework Fig. 1.2. Seven criteria of sustainable forest management Fig. 1.3: General study sites Fig. 1.4. Influence of water and temperature regimes on vegetation Fig. 1.5. Distribution of meteorological station in relation to elevation of Cambodia Fig. 1.6. Distribution of rainfall regimes in Cambodia in mm Fig. 1.7. Length of dry season in Cambodia Fig. 1.8. Monthly mean temperature in Cambodia in °C Fig. 1.9. Distribution of low-temperature regions of Cambodia in °C Fig. 1.10. Generalized distribution of vegetation in Cambodia Fig. 2.1. Cambodian Land use Map Fig. 3.1. Primary Sampling Unite allocation Fig. 3.2. Preah Vihear Forest land cover map Fig. 3.3. Density of stem, volume and basal area of dbh above 10 cm by royalty class Fig. 3.4 Percentage of tree, volume and basal area density by royalty class Fig. 3.5. Average stand structure of dbh above 10 cm by species Fig. 3.6. Density of stem, volume and basal area of trees dbh above 10 cm in forest evergreen by royalty class Fig. 4.1. Geographic location of the study site Fig. 4.2. Preah Vihear Forest land cover map Fig. 4.3. Primary Sampling Unit allocation Fig. 4.4. Plot allocation Fig. 4.5. Net tree height calculation in the field (Kao, 2003) Fig. 4.6. Average species stand structure at dbh above 10 cm by forest type Fig.5.1. Location of 20 permanent sample plots (PSPs) distributed in 5 different places Fig. 6.1. Study site history in the Cambodian community forestry and Kampong Chhnang forest cover Fig. 6.2. (a) Geographical location of Svaybakav (SBK) and (b) Geographical location of Boeng Kok (BK) Fig. 6.3. Re-estimation above grown biomass increments based on permanent sample plots in Kampong Thom Province Mizoue (2006) and Top et al, (2006) data 1998 – 2003 Fig. 6.4. Svaybakav (SBK) and Beong Kok (BK) species richness of non-timber forest product and trees Fig. 6.5. Svaybakav (SBK) and Beong Kok (BK) stand density of non-timber forest product and trees Fig. 6.6. Biomass supply and demand increment by community forestry site Fig. 6.7. Svaybakav (SBK) woodfuel supply and demand at time t Fig. 6.8. Beong Kok (BK) woodfuel supply and demand at time t Fig. 7.1. Preah Vihear Forest land cover map Fig. 7.2. Primary Sampling Unit allocation Fig. 7.3. Plot allocation Fig. 7.4. Cambodian new rule for yield estimations (FA, 2004) Fig. 7.5. Annual allowable cut (AAC) under different recovery levels (RLs) - 114 -
  • 123. List of acronyms AAC ABB ADB AFW BA BK CC CCP CF Class I Class II Class III Class LUX Class OTHER CSFE CTIA D DBH DFW FA FAO FE GIS GPS H ITTO LGFE MDCL NIS NTFP PSU RGC SBK SFM UNDP UNFE USAID V WB Annual Allowable Cut Above ground biomass Asian Development Bank Asian Forest Workshop Basal area in square meter Boeng Kok Community Forestry Cutting cycle Cambodia Cherndar Plywood Mfg. Co. Ltd Community Forestry Quality of trees in grade one or tax class one Quality of trees in grade two or tax class two Quality of trees in grade three or tax class three Quality of trees in grade luxury or tax class luxury Quality of trees in non-graded system or non-commercial trees Conserved evergreen forest Cambodian Timber Industrial Association Diameter at breath height Diameter at breath height or diameter at 1.3 m Department of Forestry and Wildlife of Cambodia Forestry Administration of Cambodia Food and Agriculture Organization of the United Nations Evergreen forest Geographic Information System Geographic Positioning System Height International Tropical Timber Organization Logged evergreen forest Minimum diameter cutting limit National Institute of Statistics Non-timber forest product Primary Sampling Unit Royal Government of Cambodia Svaybakav Community Forestry Sustainable Forest Management United Nation Development Program Unlogged evergreen forest United States Agency for International Development Volume in cubic meter The World Bank - 115 -
  • 124. Laboratory of Forest Management
  • 125. Background • The tropical forests are important for:  Local people livelihood(e.g. Poffenberger, 2006)  Global carbon budget (e.g. Malhi and Grace, 2000)  Biodiversity conservation (e.g. Myers et al., 2000) • Deforestation and forest degradation in tropics is one of the most critical environmental problems, due to e.g. Agricultural expansion, Illegal logging, No sound management Increasing Global and Local Concerns and Needs on “Sustainable Forest Management” in the Tropics
  • 126. Background “Sustainable Forest Management (SFM)”? 7 Criteria of SFM in Montreal Process (1998) 1 - Conservation of biological diversity 2 - Maintenance of productive capacity of forest ecosystems 3 - Maintenance of forest ecosystem health and vitality 4 - Conservation and maintenance of soil and water resources 5 - Maintenance of forest contribution to global carbon cycles 6 - Maintenance and enhancement of long-term multiple socioeconomic benefits to meet the needs of societies 7 - Legal, policy and institutional framework
  • 127. Background Indicators of Productive capacity of forest ecosystem (Montreal Process, 1998) 1: Area available for timber production 2: Growing stock for commercial trees 3: Area and stock of plantation 4: Sustainable yield (Annual allowable cut) 5: Annual remove of Non-timber forest products However; very little is known about tropical seasonal forests in mainland Southeast Asia, like in Cambodia,
  • 128. Background Cambodia, Southeast Asia - Cambodian Forests: 59% (2007) = Production forests (34%) + Conservation (25%) - Forest Types: Evergreen and Deciduous Forests
  • 129. Background: Deciduous Forests
  • 130. Background: Deciduous Forest
  • 131. Background: Evergreen Forest
  • 132. Background Production forests - Evergreen forests - Selective logging (cutting only selective trees of big and commercial species)
  • 133. Problems Tropical seasonal forests of Cambodia and some other countries are having not enough: - Information of productive capacity - Scientific evaluation on management guidelines Thesis Objectives To evaluate productive capacity of tropical seasonal forest in Cambodia with focusing on 1) Stand structure 2) Stand dynamics 3) Sustainable yield (Annual Allowable Cut)
  • 134. Chapter 4 Structural characteristics of logged evergreen forests in Preah Vihear, Cambodia, 3 years after logging The development of better forestry practice and strategy to achieve sustainable forest management require: -Knowledge of system responses to natural man-made disturbance, including patterns of succession. -Information on the effects of silvicultural treatment on future site conditions, vegetation species composition, structure and spatial distribution (Archambault et al., 1998)
  • 135. Chapter 4 Stand structures have a key role in preparing a sustainable forest management plan and are important in forest zonation However, very little is known about impacts of logging on stand structure of tropical seasonal forests Objectives: 1) To understand stand structure of unlogged forest and logged forests 2) To know effect of logging (damaged rates)
  • 136. Chapter 4 Data
  • 137. Chapter 4 Field Work
  • 138. Chapter 4 Inspection
  • 139. Chapter 4 Data analysis Inventory data by diameter range were summarized: oTotal number of tree species, oThe number of native, unknown, oBasal area (BA), tree density, and volume by species or forest type or both; and o Species importance commercial values.
  • 140. Chapter 4 Data analysis To estimate the damage and harvested trees, I compared the following information in Logged and unlogged site: - Density, - Volume density and - Basal area
  • 141. Chapter 4 Results: Structure DBH Class 10 – 19 20 – 29 30 – 39 40 – 49 50 – UP Total Logged Site Unlogged site Density Volume Density Volume (Tree/ha) (m3/ha) (Tree/ha) (m3/ha) 138.7 43.0 148.3 46.2 48.8 27.0 53.3 30.0 15.3 16.2 19.0 20.2 7.1 12.6 7.9 14.1 10.3 53.0 13.3 75.2 220.3 151.9 241.9 185.8
  • 142. Results: Structure after logging Chapter 4 Unlogged Species (n) Density (Trees/ha) Volume (m3/ha) Logged 39 242 186 42 220 152 - Harvested Density 22.4% (3.0 Trees/ha) - Harvested Volume 29.5% (22.2 m3/ha) - Damaged Density 12.6% (18.7 Trees/ha) - Damaged Volume 25.3% (11.7 m3/ha) Similar to other studies in Tropical rain forests by Van Der Hout, (1999); Sist and Brown, (2004) But, Higher than Cambodian guideline (10%)
  • 143. Chapter 4 Discussion and conclusion The harvested trees in ASEAN countries are:  25-40 m3 (KimPhat et al., 2000, 2002) in Cambodia,  24 m3 (Van, 1998) in Vietnam, ,  30 m3 (World Bank, 2002) in Laos, ,  30 m3 (ITTO, 1994) in Thailand ,  30-40 m3 (ITTO, 1994), in Malaysia  30m3/ha (FAO and UNEP, 1981) in Indonesia.  22m3 /ha in this study The damaged on stand are:  40% = 60 trees/ha and 25% after reduced impact logging (Sist et al., 2003) in Indonesia  13%, 25% and 40% for density, volume and basal area in this study site
  • 144. Chapter 4 Recommendation - The harvested and damaged rates are tools to assess the previous harvesting history to find if an area is well managed. - Governments can use the result to revise previous plans or to change their policy.
  • 145. Chapter 5 Stand dynamics of tropical seasonal evergreen forest in central Cambodia -Information on tree and stand dynamics is required to evaluate silvicultural options for sustainable timber yield. - Cutting cycles and minimum diameter cutting limits are often based on diameter increment and/or volume increment of commercial species
  • 146. Chapter 5 Although there are data for some tropical rain forests, especially in Brazilian Amazonia (e.g., Silva et al., 1995;) But very little scientific information is known about stand dynamics of tropical seasonal forests, Objectives: 1) To estimate mortality, recruitment and illegal cut 2) To estimate diameter and volume increment
  • 147. Chapter 5 x Materials and Methods - Permanent Sample Plots: 20 x x x x -Measurements: in 1998 and 2003 x x
  • 148. Chapter 5 Data analysis For; - all species >10 cm - commercial species >MDCL (Minimum Diameter Cutting Limit) On: - Stand structure in 1998 and 2003 - Diameter increment - Mortality, recruitment, illegal cut - Volume increment
  • 149. Chapter 5 Data analysis Rate of mortality, recruitment or illegal cut (Y), Y = 100*{ln N1 – ln (N1 – X)}/t, where - N1 is the number of trees measured in 1998, - X the number of mortality, recruitment or illegal cut, and - t the time between the 1st and 2nd mesurements
  • 150. Chapter 5 Data analysis Volume Increment estimation I = (V2 - V1 +C)/(t2 - t1) where I is the volume increment (m3/ha/year), V2 the volume at measurement 2 (m3/ha), V1 the volume at measurement 1 (m3/ha), C the volume of illegally logged trees (m3/ha) t2-t1 the time (in years)
  • 151. Chapter 5 Results All ≥10 cm Whole Density(Tree/ha) Whole Volume (m3/ha) n of Species Recruitment(%/Year) Mortality (%/Year) Illegal cut (%/Year) DBH Increment(cm/Year) Volume Increment(m3/ha) 545 193 67 2.5 2.4 0.2 3.3 1.06 Commercial ≥ MDCL 23 64 27 1.4 0.5 0.1 3.2 0.86
  • 152. Chapter 5 Discussion and conclusion - Volume increments are similar to some tropical rain forests (e.g. Valle et al., 2006). - Diameter Increment is much smaller than Forestry Administration model in 2004 (FA, 2004) - Mortality is much higher than the Cambodian Guideline (FA, 2004) - Commercial volume increment (0.86 m3/ha/year) of trees with DBH ≥ MDCL was significantly larger than the Cambodian value (0.33 m3/ha/year) (FA, 2001) - While species richness and stocking level in terms of basal area are smaller in tropical seasonal forest than in tropical rain forest, tree density, recruitment, mortality and volume increment are similar.
  • 153. Chapter 5 Recommendation -Further data from longer periods and other locations are required to provide reliable estimates of sustainable yield to forest managers and planners. -Illegal cut inside the forests should be studied on its impact, especially on the change of increment
  • 154. Chapter 7 Evaluating of the Cambodian yield regulation for tropical natural forest management There have been increasing concerns on sustainable forest management in tropical natural forests, being disproportionately important in the - Global carbon budget (e.g. Malhi and Grace, 2000) - Biodiversity conservation (e.g. Myers et al., 2000).
  • 155. Chapter 7 Most of the previous studies on the yield regulations of tropical forests were for seasonal tropical rain forest forests especially in Brazilian Amazonia and in Borneo island. However, there has been a lack of scientific evaluation of sustainable yield regulation Objectives: To evaluate the Cambodian new rule of estimating sustainable yield (annual allowable cut ) under different scenarios
  • 156. Chapter 7 Introduction Cambodian new rule for yield estimations (FA, 2004) - Cutting only commercial trees >MCDL (Minimum Diameter Cutting Limit) - Rotation length is 25 years - Cutting only 50% of commercial trees - Considering Recovery levels after logging for each commercial species
  • 157. Chapter 7 Recovery levels (RL%) of each spices RL(%) = Number of harvestable trees 25 years after logging Number of harvestable trees before logging N<MDCL + N>MDCL (DI)(1-50%)(1-D%)(1-M%)CC × 100, RL(%) = N>MDCL where D% = Damaged rate M% = Mortality rate DI = Diameter Increment (Guideline=10%) (Guideline=1%) (Guideline=5mm) However, the Cambodian Guideline’s assumptions are based on other studies in other countries.
  • 158. Cambodian new rule for yield Estimations (FA, 2004) Chapter 7 Method Calculating Recovery levels (RL) for each species RL>60% for unlogged RL>90% for logged Yes Allow to be cut No Not allowed to be cut Field Inventory However, there have been no studies clarifying which thresholds of RLs should be adopted.
  • 159. Method Chapter 7 - Estimating yield under 2 scenarios x 5 Recovery levels; 60, 70, 80, 90, 100 - Comparing with potential growth = 21.5 m3 = 0.86m3/year (Chapter 5) x 25 years Scenario 1 (Guideline) D% (Damaged rate) M% (Mortality) (%/year ) DBH increment (mm/year) RL%= 10.0 1.0 5.0 Scenario 2 (New Information) 12.6 (Chapter 4) 2.4 (Chapter 5) 3.2 (Chapter 5) N<MDCL + N>MDCL (DI)(1-50%)(1-D%)(1-M%)CC × 100 N>MDCL
  • 160. Chapter 7 Data
  • 161. Chapter 7 Data classification The inventory data were classified by: - Commercial trees >MCDL (Minimum Diameter Cutting Limit) by species and group (Dipterocarp and non-dipterocarp speceis) - All trees with diameter > 10 cm
  • 162. Chapter 7 Volume estimation (FA, 2004) Tree Species Diameter Evergreen forest class Non-dipterocarp <15 cm Volume = 0.022 + 3.4 DBH2 >15 cm Dipterocarp Volume = –0.0971 + 9.503 DBH2 <30 cm Volume = 0.03 + 2.8 DBH2 >30 cm Volume = –0.331 + 6.694 DBH2
  • 163. Chapter 7 Annual allowable cut by species
  • 164. Yield estimation(m3/ha) Chapter 7:Result 70 60 70 Logged Site S1: Guideline Unlogged Site S2: This study 60 40 30 30 20 20 10 10 0 Overcut Growth potential (21.5 m3 50 = 0.86m3/year x 25 years) 40 0 50 None 60 70 80 90 100 None 60 70 Recovery Level (RL, %) 80 90 100 Sustainable - The current guideline results in overcut - This study suggests 10m3 yield, fulfilling 100% of recovery levels for species conservation as well as (to the same as proposed for Amazon Forest by van Gardingen et al., (2004)
  • 165. Chapter 7:Result Discussion and Conclusion AAC is the same to one proposed by van Gardingen et. al (2006) for primary tropical rain forest in the Amazon, based on the modeling approach under the cutting cycle of 30 years Cambodia’s allowable cut level is larger than growth potentials
  • 166. Chapter 7 Recommendation In conclusion, differences in some indicators of productive capacity, such as tree and stand growth, existed between the previous assumed values and ones found newly in this study, calling for revision of the Cambodian management planning guidelines. Future evaluations on long-term dynamics of logged and unlogged sites may be critical for more accurate evaluation of sustainable productive capacity of tropical seasonal forests.
  • 167. General Conclusions Extrapolations of damages to an anticipated acceptable cutting cycle must be interpreted with caution (Chapter 4) Tropical Seasonal Evergreen Forests in Cambodia has similarity of stand structure and dynamics as compared to Tropical Rain Evergreen Forests , such as in Amazon and Sumatra (Chapter 5) Differences are found between my study and the Cambodian guideline's assumption in some indicators of productive capacity: (i) Tree and stand growth, (ii) Mortality, (iii) Damage rates, (iv) Recovery rate, and (v) Sustainable yield. (Chapter 7) The current guideline has a risk, leading to overcut.
  • 168. General Suggestions This study recommends to urgently revise the Cambodian management planning guidelines based on new findings from this thesis as well as additional long-term monitoring and assessments. Reduced impact logging to gain more yield should also need for economic viability.
  • 169. Acknowledgement • Advisors • Committee Advisors • Japanese people who give fund to study and • Colleagues Thank for comments and questions