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Spatial analysis of woodfuel supply and demand in Kampong Thom Province, Cambodia
Forest Ecology and Management 194 (2004) 369–378
Spatial analysis of woodfuel supply and demand in Kampong Thom Province, Cambodia Neth Topa,*, Nobuya Mizoueb, Satoshi Itoc, Shigetaka Kaic a
The United Graduate School of Agricultural Sciences, Kagoshima University, c/o Faculty of Agriculture, Miyazaki University, Miyazaki 889-2192, Japan b Department of Forest and Forest Products Sciences, Faculty of Agriculture, Kyushu University, Fukuoka 812-8581, Japan c Department of Biological Production and Environmental Science, Faculty of Agriculture, Miyazaki University, Miyazaki 889-2192, Japan Received 6 May 2003; received in revised form 8 October 2003; accepted 27 February 2004
Abstract This study adopted a GIS-based approach to reveal how the potential supply and demand of woodfuel varies at different spatial scales within Kampong Thom Province, Cambodia. We considered three different scales: the first was the whole area of the province. The second scale calculated village-scale data in zones of 1, 3 and 5 km from each village aggregated for all villages of the province. The third scale also calculated data for the three zones at the village-scale, but data were then aggregated according to three regional groupings based on population density and forest availability. The results indicated large differences in the ratio (ranging between 0.08 and 503.90) of potential supply to demand of woodfuel for the different scales examined. A deficiency of woodfuel resources was identified only in the areas along the main national road, mainly due to high woodfuel demand and predominance of agricultural land and regrowth forest in surrounding areas. This deficiency may have a negative flow-on influence to adjoining areas if they are called upon to fill the supply gap. For more accurate assessments on sustainability of woodfuel resources and use, further research is needed on the available size and species of trees used for fuel. This study indicated that use of GIS could reveal differences in the potential supply and demand of woodfuel at three different scales. Policy makers and energy planners should address such scale dependency in supply and demand relationships when preparing energy development programs. # 2004 Elsevier B.V. All rights reserved. Keywords: Biomass increment; GIS; Population density; Scale dependency; Sustainability; Woodfuel consumption
1. Introduction Wood is the primary source of cooking fuel and plays a vital part in the energy supplies of many developing countries (e.g., Ryan and Openshaw, 1991; Kersten et al., 1998; Mahapatra and Mitchell, 1999; Okello et al., 2001). The ‘‘woodfuel gap theory’’ * Corresponding author. Tel.: þ81-985-587184. E-mail address: [email protected] (N. Top).
was first brought to the world’s attention in the 1970s, implying that woodfuel was being consumed on a nonsustainable basis (Dewees, 1989; Bradley and Campbell, 1998; ESMAP, 2001). The ‘‘gap’’ indicated that woodfuel demand was larger than the sustainable supply, which is defined as the mean annual increment of wood (FAO, 1983; RWEDP, 1997). It was then concluded that deforestation and forest degradation were largely due to firewood harvesting (FAO, 1983; IUCN, 1996). With mounting concerns for the
0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.02.028
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woodfuel sector, national and international agencies commenced many research programs on the relationships between woodfuel supply and demand. The ‘‘gap theory’’ has often been criticized by many later studies (e.g., Dewees, 1989; Bradley and Campbell, 1998; ESMAP, 2001). One reason is that there have been few generally accepted estimates of forest biomass stock and its productivity (Bradley and Campbell, 1998). For example, Amoo-Gottfried and Hall (1999) examined two assessments (ETC, 1990; Millington et al., 1994) of Sierra Leone’s biomass standing stock and MAI (mean annual increment) based on remotely sensed data to assess the sustainability of various biomass use scenarios. They found large differences in the MAI of the two assessments, so they could not reliably predict the sustainability of biomass utilization. Another criticism is that many studies ignore the spatial distribution and variation of woodfuel demand; that is to say, consumption rate (kg/ person per year) tends to decrease with increasing scarcity of wood resources, and there is generally higher consumption in better-wooded areas (Hosier, 1985; Bradley and Campbell, 1998; Kituyi et al., 2001). In addition, Millington et al. (1994) noted that no attempt had been made to relate the distribution of woody biomass supplies to population distribution. They further pointed out that many of the studies have been in areas far from population centers, possibly making them inaccessible as woodfuel resources (e.g., Amoo-Gottfried and Hall, 1999; Schulte-Bisping et al., 1999). This shortcoming can be addressed by adding current population estimates at the provincial or district level to existing biomass data in a geographical information system (GIS) (Millington et al., 1994). In Cambodia, 95% of the population depends on woodfuel for cooking (NIS, 1999); however, few studies have investigated the relationship between supply and demand of woodfuel. To use forests on a sustainable basis, analysis of woodfuel consumption and renewal are crucial, and must address the shortcomings of past studies. Recently Top et al. (2003) investigated the woodfuel consumption rate in Kampong Thom Province and found a dependence between consumption rate and household size and identified localized differences in consumption. In addition, Top et al. (2004) estimated aboveground standing biomass of living trees and biomass increment based on inven-
tory data collected in 1997 and permanent sample plot data obtained in 1998 and 2000. They also assessed the balance between potential supply (annual biomass increment) and demand of woodfuel at the province level. They concluded that there is a need for further assessments at a more detailed scale since provincelevel estimates include remote areas not subject to firewood collection (Millington et al., 1994). Using our previous findings (Top et al., 2003, 2004), we used a GIS to reveal how potential supply and demand of woodfuel vary at different scales within Kampong Thom Province, Cambodia. Our data provide comparisons of woodfuel supply and demand at three different spatial scales: (1) the whole province level, (2) within zones of differing distance from each village aggregated for the whole province, and (3) within zones of differing distance from each village aggregated by three zones of differing population density within the province. For each scale, we determined land use type, forest type, annual potential woodfuel supply and the relationship between potential supply and demand of woodfuel. We hypothesized that spatial analysis of woodfuel supply at three different scales will show areas where forest resources are not sustainable. These assessments can provide a basis to formulate or modify spatially differentiated policies and measures for managing woodfuel consumption to achieve sustainable forest management.
2. Materials and methods 2.1. Study site Kampong Thom Province is situated in central Cambodia, between 128110 2300 –138260 5200 N and 1048120 4900 –1058440 2000 E, and has a total land area of 12,447 km2, about 7% of the country area (DFW, 1999). Ecological and geographical zones are relatively uniform throughout the province. Atmospheric humidity is high throughout the year, ranging between 72 and 87% with an annual mean of 80% (MRD/GTZ, 1985). The climate is tropical with a bi-annual change of monsoonal wind systems; the rainy season extends from May to October and the dry season from November to April. Mean annual rainfall and temperature over the last 5 years (1996–2000) have been 1700 mm and 28 8C, respectively.
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The province has over 0.63 million ha of forests (DFW, 1999), 51% of the provincial area. There are three dominant forest types: deciduous, mixed/semideciduous, and evergreen. The major species in each forest type are Dipterocarpus intricatus, D. obtusifolius, D. tuberculatus, Pentacme siamensis, Shorea obtusa, Terminalia tomentosa for deciduous forest; Anisoptera cochinchinensis, Hopea cochinchinensis, H. pierrei, Irvingia malayana, Lagerstroemia angustifolia, Sindora cochinchinensis for mixed/semideciduous forest; and Dipterocarpus alatus, D. costatus, D. dyeri, Eugenia spp., Hopea odorata, Shorea vulgaris for evergreen forest (FAO, 1998). These forests occur mostly in the northern and northeastern part of the province and represent 3.8, 4.3, and 64.9% of the total forest area, respectively. They are located in the lowland areas ranging in elevation from 9 m above sea level along the shores of Tonlesap Lake to 100 m on the northeastern plain, with a few hills rising to a maximum of 273 m. The remaining 26.9% of forest area consists of inundated and regrowth forests. All forest areas are owned by the government. The province is economically poor with low living standards for the majority of the population (MRD/ GTZ, 1985). The 1998 population was 569,060, of which about 88.5% lived in rural areas (NIS, 1999). The annual population growth in 1998 was 2.49% with an average population density of 46 km2. The total number of households in the province was 106,908, with an average household size of 5.32. 2.2. Data sources The Department of Forestry and Wildlife established a digital land use map (e.g., forested land, shrubland, agricultural land, urban area; scale 1:250,000) of Cambodia derived from Landsat TM images and some ground verifications (DFW, 1999). It is the only reliable land use map available in Cambodia. We used this map to calculate areas for each of the five forest types (evergreen, mixed/semi deciduous, deciduous, regrowth and inundated forests) using ArcView 8.1 (ESRI, Inc.). For population and household data, we used the results of the national population census of Cambodia conducted in 1998 (NIS, 1999), which included spatially referenced data of villages. For forest biomass and annual biomass increment we used the data of Top et al. (2004) (Table 1), and for
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Table 1 Aboveground biomass of living trees and biomass increment by forest type in Kampong Thom Province, Cambodia Forest type
Aboveground biomass (Mg/ha)
Annual increment (Mg/ha per year)
Deciduous Mixed/semi-deciduous Evergreen Inundated Regrowth
189 224 256 160 70
4.59 4.99 5.30 4.19 2.24
Source: Top et al. (2004).
woodfuel consumption rate (kg/person per year) we used data from Top et al. (2003). 2.3. Analysis at different scales Fig. 1 shows land use and village distribution in Kampong Thom Province. Most villages are aligned along the major roads, especially National Road 6, and rivers. In addition, a number of villages surrounded by forest exist in the southern part of Sandan District. A few fishing villages located on the shores of Tonlesap Lake, which account for only about 2% of the provincial population, were not included in the analysis. In this study we estimated the potential supply and demand of woodfuel at three different scales: (1) the whole province scale (12,447 km2), (2) village scale but aggregated for the whole province, termed the provincial village-scale (6086 km2 at 5 km from villages), and (3) the regional village-scale, i.e., the village scale data further subdivided into three regions (2778, 3259 and 692 km2 at 5 km from villages in each group, respectively). To examine the effect of proximity to villages when calculating the village-scale data, we used the buffer function of ArcView 8.1 to calculate variables of interest in zones of 1-, 3- and 5-km distances surrounding villages (Fig. 2). The regional village-scale data were produced to investigate the effects of population density and forest availability on village-scale data. To define the regions we classified the villages into three groups (Table 2). Group A: Villages located within 10 km of National Road 6 (highest population density and lowest forest availability).
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Fig. 1. Distribution of villages in Kampong Thom Province, Cambodia, 1998.
Fig. 2. Zones of 3- and 5-km distances surrounding villages at the provincial village-scale, Kampong Thom Province, Cambodia, 1998.
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Table 2 Basic information for each scale examined in Kampong Thom Province, Cambodia, 1998 Examined scale
Land area (ha)
Population (people)
Whole province scale
1,244,748
558,406
Provincial village-scale 1 km 3 km 5 km
138,924 428,229 608,648
Regional village-scale Group A 1 km 3 km 5 km
78,280 205,536 277,812
Population density (people/km2)
Forest area (ha)
Forest area per person (ha)
Potential supply (Mg per year)
Woodfuel demand (Mg per year) 49,380
45
633,730
1.14
2,943,211
402 130 92
14,286 100,445 189,471
0.03 0.18 0.34
59,392 422,011 823,276
503 191 142
976 6,549 13,855
0.00 0.02 0.04
2,649 20,474 45,037
273 75 49
9,984 65,963 120,712
0.06 0.41 0.76
41,965 271,442 504,202
98 16 8
3,754 30,328 63,421
0.68 5.50 11.49
16,575 139,705 302,456
558,406
49,380
393,545
Group B 1 km 3 km 5 km
58,279 211,587 325,923
Group C 1 km 3 km 5 km
5,638 34,550 69,284
32,993
159,342
15,787
5,519
600
Group B: Villages located outside Group A and not located in the southern parts of Sandan District (intermediate population density and forest availability). Group C: Remote villages located in the southern parts of Sandan District (lowest population density and highest forest availability). To examine the effects of distance from villages at the regional scale, we used ArcView 8.1 to buffer at 1, 3 and 5 km from villages in each of the three groups (Fig. 3). For each group, then, we calculated variables of interest in zones of 1-, 3- and 5-km distances surrounding villages. 2.4. Calculation of potential supply and demand To determine potential woodfuel supply, we first calculated forest area for each of the five forest types at each scale examined. We then used the forest biomass and annual biomass increment data (Table 1) to calculate the total forest biomass and annual biomass increment for each scale. Top et al. (2003) revealed that the household sector represented up to 94.3% of the total woodfuel con-
sumption in Kampong Thom. Thus, this study considered only woodfuel consumption of the household sector (excluding the few villages near Tonlsap Lake). Within the household sector, 68.2% of woodfuel consumed was found to originate from forest sources, and the rest from non-forested sources such as shrubland, agricultural land and homestead. Since there have been no biomass or biomass increment measurements of non-forested areas, only woodfuel extracted from forest areas was considered in the present study. Based on an interview survey of 155 households, Top et al. (2003) also revealed differences in the per capita woodfuel consumption rate among the eight districts in the province. We used the average per capita woodfuel consumption for the 95 households from the interview survey belonging to Group A and the 60 households belonging to Group B. None of the villages belonging to Group C, which were located in Sandan District, were included in the interview survey. Therefore, for Group C we used the results of interviews from 20 households in Group B that were located in the western part of Sandan District. For each village group, the per capita woodfuel consumption rate (kg/person per year) of the sample was
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Fig. 3. Zones of 3- and 5-km distances surrounding villages at the regional village-scale, Kampong Thom Province, Cambodia, 1998.
normalized to the average household size, as obtained from the National Population Census, using the curvilinear relation developed by Top et al. (2003).
3. Results Table 2 illustrates the land area, population, forest area, biomass increment and woodfuel consumption for each scale examined. At the regional village-scale, the population of Group A is the largest (70%), following by Group B (29%) and Group C (1%). Similarly, woodfuel consumption in Group A is also the largest (67%), following by Group B (32%) and Group C (1%). For the regional village-scale analysis, if we considered a 5-km zone around villages, the calculated population density ranged between 8 persons/km2 in Group C and 142 persons/km2 in Group A, as compared to 45 persons/km2 for the whole province. Similarly, at this scale forest area per person approaches zero in Group A (0.04 ha/person) and is highest for Group C (11.49 ha/person), compared to 1.14 ha/person for the whole province. Fig. 4 indicates the share of area by land use type for each scale examined. At the provincial scale, according
to the available data, forest makes up 51% of the total land area, followed by agricultural land (25%), shrubland (16%) and others including wetland, grassland and urban area (8%). At the provincial village-scale and for Groups A and B of the regional village-scale, agricultural land is dominant irrespective of the distance from villages examined. In Group C, forest land is dominant. There is a clear trend in the calculated data at both village scales (provincial and regional) as the distance from villages increases, the proportion of the area occupied by forest increases; conversely, the closer to villages, the greater is the proportion of agricultural land. Fig. 5 illustrates the share of area by forest type within forest land at each scale. Most forests at the scales examined are dominated by evergreen forest, except for Group A which is dominated by regrowth forest. However, the proportion of evergreen forest at the provincial scale, 65%, is higher than at all other scales examined except for the 3 and 5 km zones of Group C at the regional village-scale. Generally, as the distance from villages examined increases, the proportion of the forest made up of evergreen forest increases for both provincial and regional village-scales, except for the 3 and 5 km zones of Group A.
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Fig. 4. Share of area by land use type for each scale examined in Kampong Thom Province, Cambodia.
Fig. 5. Share of area by forest type for each scale examined in Kampong Thom Province, Cambodia.
Fig. 6 indicates the potential woodfuel supply expressed as annual biomass increment divided by total land area (Mg/ha) for each scale examined. At the provincial scale, the potential woodfuel supply of
2.36 Mg/ha was greater than for all other categories examined except for all three zones of Group C. As the distance from villages decreases, the potential woodfuel supply decreases at both the provincial
Fig. 6. Annual potential woodfuel supply per hectare by forest type for each scale examined in Kampong Thom Province, Cambodia.
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Fig. 7. Ratio of annual potential supply to demand of woodfuel for each scale examined in Kampong Thom Province, Cambodia.
village-scale and regional village scale. These trends are similar to those discussed for forest land as a proportion of land area (Fig. 4). Fig. 7 illustrates the ratio of potential supply to demand of woodfuel at each scale examined; a ratio less than one represents a biomass increment lower than woodfuel consumption, and vice versa. The calculated ratios ranged between 0.08 and 503.90. Compared to the 59.60 value for the provincial scale, the ratios for the other scales were lower, except for the 3 and 5 km zones of Group C (ratios of 232.75 and 503.90, respectively). For the 1 and 3 km zones of Group A, the ratios of supply to demand were less than one (0.08 and 0.62, respectively). In the 1 km zone for the provincial village-scale and 5 km zone of Group A, the ratios were slightly higher than one. For all other examined scales, the ratio values were much higher than one. A clear trend was that as the distance from villages decreased, the ratio of potential supply to demand of woodfuel decreased at both the provincial village-scale and the regional village-scale.
4. Discussion GIS revealed differences in land use, forest type, and potential supply and demand of woodfuel at different scales. There were clear trends in potential woodfuel supply at each scale examined; the closer to villages, the less the woodfuel supply at both provincial village-scale and regional village scale. The areas
surrounding the villages of Group A had a much lower supply of woodfuel than in the other groups (Fig. 6). These trends can be explained largely by land use distribution, with agricultural land taking up a much greater proportion of land closer to villages, especially those in Group A (Fig. 4). Distribution of forest type in extant forest was also affected by proximity to villages—the closer to villages the less evergreen forest (which has the largest biomass density of 256 Mg/ha, Table 1) and the more regrowth forest (lowest biomass density of 70 Mg/ha, Table 1). Group A tended to have a much greater proportion of regrowth forest compared to the other groups or levels of data aggregation; this abundance of regrowth forest explains the relatively low potential woodfuel supply for Group A. Regrowth forest is defined as young forest resulting from logging, shifting cultivation, or other major disturbance, and is characteristically poorly stocked (Top et al., 2004). The degree of disturbance to forests, and therefore abundance of regrowth forest, could be expected to be higher in areas closer to villages. Grundy et al. (1993) also indicated that wood harvesting had a highly localized effect on woodland structure in Mutanda Resettlement Area, Zimbabwe, and that the number of live trees and total live biomass were substantially reduced within 300 m of villages. In addition Awasthi et al. (2002) showed that in Garhwal Himalaya of India, the available aboveground woody biomass of preferred firewood species was greatest near temporary huts and least near permanent villages.
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To assess the sustainability of woodfuel resources and use, many studies have examined the supply and demand relationships at relatively large scales, i.e., mainly at the country level (FAO, 1983; RWEDP, 1997; Amoo-Gottfried and Hall, 1999; Schulte-Bisping et al., 1999). At the whole province scale of this study (12,447 km2), the potential supply was 60 times higher than demand, implying that the forest resources and use of woodfuel are sustainable. However, such large scale analysis includes inaccessible areas (Millington et al., 1994). Considering only the areas surrounding villages at the provincial level (provincial village-scale), the ratio of supply to demand sharply decreased with increasing proximity to villages (ratio of 1.20, 8.55 and 16.67 for 1, 3 and 5 km distances from villages, respectively). At a more detailed scale, i.e., within groups A, B, and C, the relations were also different. We identified two zones where demand was higher than potential supply (within 1 and 3 km from villages of Group A). This suggests that forest resources are non-sustainable and will become degraded if woodfuel continues to be consumed within these zones at the current consumption rate. If woodfuel can be obtained from other source areas (such as between 3 and 5 km from villages of Group A and from the areas surrounding Group B), the sustainability of woodfuel production in those areas may be negatively affected. Therefore, it can be suggested that within Kampong Thom Province there is a deficiency in forest resources for woodfuel, at least along National Road 6 (Group A). Schulte-Bisping et al. (1999), studying the global availability of woodfuel supply, indicated that in some 17 countries (e.g., Bangladesh, China, India, Pakistan, Thailand) woodfuel consumption exceeds annual wood increment, and in other countries (e.g., Gambia, Mexico, Morocco, Nigeria, the Philippines) consumption seems to be in balance with or less than wood increment. However, if the analysis is restricted to a specific region close to villages, as in our study, the annual wood increment would be much lower than their estimates and a deficiency in the sustainable woodfuel supply may be evident within certain regions of some of these countries. We considered all tree sizes and species in calculating potential supply of woodfuel as has been the approach in many other studies. However, it is commonly known that local people are not likely to cut
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large trees for fuel. In addition, some species may be selectively targeted (RWEDP, 1998). Therefore, if we exclude large trees and some of the less preferred species from the biomass calculations, the potential woodfuel supply would be much lower and a deficiency in sustainable woodfuel supply may also be seen in areas other than along National Road 6.
5. Conclusion Our study indicates that use of GIS could show differences in potential supply and demand of woodfuel at different scales. This indicates the usefulness of spatially referenced land use and population data. In the case of Kampong Thom Province, we found that a deficiency in woodfuel resources occurs in the areas along National Road 6 due to the high woodfuel demand and dominance of agricultural land and regrowth forest in close proximity to villages. This deficiency may have negative impact on surrounding areas if they have to fill the supply gap. Policy makers and energy planners need to address this scale dependency in supply and demand relationships when preparing energy development programs. For more accurate assessments on the sustainability of woodfuel resources and use, further research is needed on the size and species of trees used for fuel.
Acknowledgements We are grateful to the Director, Mr. Ty Sokun, and the Deputy Director, Mr. Ouk Syphan, of the Department of Forestry and Wildlife of Cambodia for providing the data used in this study and for assistance on a wide range of issues. We also extend our appreciation to Mr. Vong Sarun, and Ms. Lim Sopheap for making valuable documents available. Financial support for this study was partially provided through a Grant-in-Aid for Scientific Research (B) (No. 15405024) from the Japan Society for the Promotion of Science. References Amoo-Gottfried, K., Hall, D.O., 1999. A biomass energy flow chart for Sierra Leone, Biomass. Biomass Bioenergy 16, 361–376.
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Awasthi, A., Uniyal, S.K., Rawat, G.S., Rajvanshi, A., 2002. Forest resource availability and its use by the migratory villages of Uttarkashi, Garhwal Himalaya (India). For. Ecol. Manage. 5887, 1–13. Bradley, P.N., Campbell, B.M., 1998. Who plugged the gap? Reexamining the woodfuel crisis in Zimbabwe. Energy Environ. 9, 235–255. Dewees, P.A., 1989. The woodfuel crisis reconsidered: observations on the dynamics of abundance and scarcity. World Develop. 17, 1159–1172. DFW, 1999. Forest Cover Assessment, Cambodia. Department of Forestry and Wildlife, Phnom Penh, Cambodia. ESMAP, 2001. Sustainable Woodfuel Supplies from the Dry Tropical Woodlands. Energy Sector Management Assistance Programme of The World Bank, ESMAP Technical Paper 013, Washington, DC, USA. ETC (UK), 1990. Biomass Assessment in Africa. The World Bank, Washington, DC. FAO, 1983. Fuelwood Supplies in the Developing Countries. The Food and Agriculture Organization of the United Nation 42, Rome, Italy. FAO, 1998. Technical Guidelines on Forest Inventory for Cambodia. The Food and Agricultural Organization of the United Nation, Project CMB/95/002, Field Document 14, Phnom Penh, Cambodia. Grundy, I.M., Campbell, B.M., Balebereho, S., Cunliffe, R., Tafangenyasha, C., Fergusson, R., Parry, D., 1993. Availability and use of trees in Mutanda Resettlement Area, Zimbabwe. For. Ecol. Manage. 56, 243–266. Hosier, R., 1985. Household energy consumption in Kenya. Ambio 14, 225–227. IUCN, 1996. Forests for Life. The World Conservation Union of the World Wide Fund (Forest Policy Book), Gland, Switzerland. Kersten, I., Baumbach, G., Oluwole, A.F., Obioh, I.B., Ogunsola, O.J., 1998. Urban and rural fuelwood situation in the tropical rain-forest area of South-West Nigeria. Energy 23, 887–898.
Kituyi, E., Marufu, L., Wandiga, S.O., Jumba, I.O., Andreae, M.O., Helas, G., 2001. Biofuel availability and domestic use patterns in Kenya. Biomass Bioenergy 20, 71–82. Mahapatra, A.K., Mitchell, C.P., 1999. Biofuel consumption, deforestation, and farm level tree growing in rural India. Biomass Bioenergy 17, 291–303. Millington, A.C., Critchley, R.W., Douglas, T.D., Ryan, P., 1994. Estimating Woody Biomass in Sub-Saharan Africa. The World Bank, Washington, DC. MRD/GTZ, 1985. Regional Framework Plan Kampong Thom Province. Ministry of Rural Development, Phnom Penh, Cambodia. NIS, 1999. General Population Census of Cambodia, 1998. Final Result. National Institute of Statistics, Ministry of Planning, Phnom Penh, Cambodia. Okello, B.D., O’Connor, T.G., Young, T.P., 2001. Growth, biomass estimates, and charcoal production of Acacia drepanolobium in Laikipia, Kenya. For. Ecol. Manage. 142, 143–153. RWEDP, 1997. Regional Study on Wood Energy Today and Tomorrow in Asia. The Regional Wood Energy Development Programme in Asia 50, Bangkok, Thailand. RWEDP, 1998. Woodfuel Flow Study of Phnom Penh, Cambodia. Regional Wood Energy Development Programme in Asia 54, Bangkok, Thailand. Ryan, P., Openshaw, K., 1991. Assessment of Biomass Energy Resource: A Discussion on Its Need and Methodology. The World Bank Industry and Energy Department, Energy Series Paper No. 48, Washington, DC, USA. Schulte-Bisping, H., Bredemeier, M., Beese, F., 1999. Global availability of wood and energy supply from fuelwood and charcoal. Ambio 28, 592–594. Top, N., Mizoue, N., Kai, S., 2003. Woodfuel consumption rates and flow in Kampong Thom Province, Cambodia. J. For. Plann. 9, 17–24. Top, N., Mizoue, N., Kai, S., 2004. Estimating forest biomass increment based on permanent sample plots in relation to woodfuel consumption, a case study in Kampong Thom Province, Cambodia. J. For. Res., in press.
Spatial analysis of woodfuel supply and demand in Kampong Thom Province, Cambodia Neth Topa,*, Nobuya Mizoueb, Satoshi Itoc, Shigetaka Kaic a
The United Graduate School of Agricultural Sciences, Kagoshima University, c/o Faculty of Agriculture, Miyazaki University, Miyazaki 889-2192, Japan b Department of Forest and Forest Products Sciences, Faculty of Agriculture, Kyushu University, Fukuoka 812-8581, Japan c Department of Biological Production and Environmental Science, Faculty of Agriculture, Miyazaki University, Miyazaki 889-2192, Japan Received 6 May 2003; received in revised form 8 October 2003; accepted 27 February 2004
Abstract This study adopted a GIS-based approach to reveal how the potential supply and demand of woodfuel varies at different spatial scales within Kampong Thom Province, Cambodia. We considered three different scales: the first was the whole area of the province. The second scale calculated village-scale data in zones of 1, 3 and 5 km from each village aggregated for all villages of the province. The third scale also calculated data for the three zones at the village-scale, but data were then aggregated according to three regional groupings based on population density and forest availability. The results indicated large differences in the ratio (ranging between 0.08 and 503.90) of potential supply to demand of woodfuel for the different scales examined. A deficiency of woodfuel resources was identified only in the areas along the main national road, mainly due to high woodfuel demand and predominance of agricultural land and regrowth forest in surrounding areas. This deficiency may have a negative flow-on influence to adjoining areas if they are called upon to fill the supply gap. For more accurate assessments on sustainability of woodfuel resources and use, further research is needed on the available size and species of trees used for fuel. This study indicated that use of GIS could reveal differences in the potential supply and demand of woodfuel at three different scales. Policy makers and energy planners should address such scale dependency in supply and demand relationships when preparing energy development programs. # 2004 Elsevier B.V. All rights reserved. Keywords: Biomass increment; GIS; Population density; Scale dependency; Sustainability; Woodfuel consumption
1. Introduction Wood is the primary source of cooking fuel and plays a vital part in the energy supplies of many developing countries (e.g., Ryan and Openshaw, 1991; Kersten et al., 1998; Mahapatra and Mitchell, 1999; Okello et al., 2001). The ‘‘woodfuel gap theory’’ * Corresponding author. Tel.: þ81-985-587184. E-mail address: [email protected] (N. Top).
was first brought to the world’s attention in the 1970s, implying that woodfuel was being consumed on a nonsustainable basis (Dewees, 1989; Bradley and Campbell, 1998; ESMAP, 2001). The ‘‘gap’’ indicated that woodfuel demand was larger than the sustainable supply, which is defined as the mean annual increment of wood (FAO, 1983; RWEDP, 1997). It was then concluded that deforestation and forest degradation were largely due to firewood harvesting (FAO, 1983; IUCN, 1996). With mounting concerns for the
0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.02.028
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woodfuel sector, national and international agencies commenced many research programs on the relationships between woodfuel supply and demand. The ‘‘gap theory’’ has often been criticized by many later studies (e.g., Dewees, 1989; Bradley and Campbell, 1998; ESMAP, 2001). One reason is that there have been few generally accepted estimates of forest biomass stock and its productivity (Bradley and Campbell, 1998). For example, Amoo-Gottfried and Hall (1999) examined two assessments (ETC, 1990; Millington et al., 1994) of Sierra Leone’s biomass standing stock and MAI (mean annual increment) based on remotely sensed data to assess the sustainability of various biomass use scenarios. They found large differences in the MAI of the two assessments, so they could not reliably predict the sustainability of biomass utilization. Another criticism is that many studies ignore the spatial distribution and variation of woodfuel demand; that is to say, consumption rate (kg/ person per year) tends to decrease with increasing scarcity of wood resources, and there is generally higher consumption in better-wooded areas (Hosier, 1985; Bradley and Campbell, 1998; Kituyi et al., 2001). In addition, Millington et al. (1994) noted that no attempt had been made to relate the distribution of woody biomass supplies to population distribution. They further pointed out that many of the studies have been in areas far from population centers, possibly making them inaccessible as woodfuel resources (e.g., Amoo-Gottfried and Hall, 1999; Schulte-Bisping et al., 1999). This shortcoming can be addressed by adding current population estimates at the provincial or district level to existing biomass data in a geographical information system (GIS) (Millington et al., 1994). In Cambodia, 95% of the population depends on woodfuel for cooking (NIS, 1999); however, few studies have investigated the relationship between supply and demand of woodfuel. To use forests on a sustainable basis, analysis of woodfuel consumption and renewal are crucial, and must address the shortcomings of past studies. Recently Top et al. (2003) investigated the woodfuel consumption rate in Kampong Thom Province and found a dependence between consumption rate and household size and identified localized differences in consumption. In addition, Top et al. (2004) estimated aboveground standing biomass of living trees and biomass increment based on inven-
tory data collected in 1997 and permanent sample plot data obtained in 1998 and 2000. They also assessed the balance between potential supply (annual biomass increment) and demand of woodfuel at the province level. They concluded that there is a need for further assessments at a more detailed scale since provincelevel estimates include remote areas not subject to firewood collection (Millington et al., 1994). Using our previous findings (Top et al., 2003, 2004), we used a GIS to reveal how potential supply and demand of woodfuel vary at different scales within Kampong Thom Province, Cambodia. Our data provide comparisons of woodfuel supply and demand at three different spatial scales: (1) the whole province level, (2) within zones of differing distance from each village aggregated for the whole province, and (3) within zones of differing distance from each village aggregated by three zones of differing population density within the province. For each scale, we determined land use type, forest type, annual potential woodfuel supply and the relationship between potential supply and demand of woodfuel. We hypothesized that spatial analysis of woodfuel supply at three different scales will show areas where forest resources are not sustainable. These assessments can provide a basis to formulate or modify spatially differentiated policies and measures for managing woodfuel consumption to achieve sustainable forest management.
2. Materials and methods 2.1. Study site Kampong Thom Province is situated in central Cambodia, between 128110 2300 –138260 5200 N and 1048120 4900 –1058440 2000 E, and has a total land area of 12,447 km2, about 7% of the country area (DFW, 1999). Ecological and geographical zones are relatively uniform throughout the province. Atmospheric humidity is high throughout the year, ranging between 72 and 87% with an annual mean of 80% (MRD/GTZ, 1985). The climate is tropical with a bi-annual change of monsoonal wind systems; the rainy season extends from May to October and the dry season from November to April. Mean annual rainfall and temperature over the last 5 years (1996–2000) have been 1700 mm and 28 8C, respectively.
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The province has over 0.63 million ha of forests (DFW, 1999), 51% of the provincial area. There are three dominant forest types: deciduous, mixed/semideciduous, and evergreen. The major species in each forest type are Dipterocarpus intricatus, D. obtusifolius, D. tuberculatus, Pentacme siamensis, Shorea obtusa, Terminalia tomentosa for deciduous forest; Anisoptera cochinchinensis, Hopea cochinchinensis, H. pierrei, Irvingia malayana, Lagerstroemia angustifolia, Sindora cochinchinensis for mixed/semideciduous forest; and Dipterocarpus alatus, D. costatus, D. dyeri, Eugenia spp., Hopea odorata, Shorea vulgaris for evergreen forest (FAO, 1998). These forests occur mostly in the northern and northeastern part of the province and represent 3.8, 4.3, and 64.9% of the total forest area, respectively. They are located in the lowland areas ranging in elevation from 9 m above sea level along the shores of Tonlesap Lake to 100 m on the northeastern plain, with a few hills rising to a maximum of 273 m. The remaining 26.9% of forest area consists of inundated and regrowth forests. All forest areas are owned by the government. The province is economically poor with low living standards for the majority of the population (MRD/ GTZ, 1985). The 1998 population was 569,060, of which about 88.5% lived in rural areas (NIS, 1999). The annual population growth in 1998 was 2.49% with an average population density of 46 km2. The total number of households in the province was 106,908, with an average household size of 5.32. 2.2. Data sources The Department of Forestry and Wildlife established a digital land use map (e.g., forested land, shrubland, agricultural land, urban area; scale 1:250,000) of Cambodia derived from Landsat TM images and some ground verifications (DFW, 1999). It is the only reliable land use map available in Cambodia. We used this map to calculate areas for each of the five forest types (evergreen, mixed/semi deciduous, deciduous, regrowth and inundated forests) using ArcView 8.1 (ESRI, Inc.). For population and household data, we used the results of the national population census of Cambodia conducted in 1998 (NIS, 1999), which included spatially referenced data of villages. For forest biomass and annual biomass increment we used the data of Top et al. (2004) (Table 1), and for
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Table 1 Aboveground biomass of living trees and biomass increment by forest type in Kampong Thom Province, Cambodia Forest type
Aboveground biomass (Mg/ha)
Annual increment (Mg/ha per year)
Deciduous Mixed/semi-deciduous Evergreen Inundated Regrowth
189 224 256 160 70
4.59 4.99 5.30 4.19 2.24
Source: Top et al. (2004).
woodfuel consumption rate (kg/person per year) we used data from Top et al. (2003). 2.3. Analysis at different scales Fig. 1 shows land use and village distribution in Kampong Thom Province. Most villages are aligned along the major roads, especially National Road 6, and rivers. In addition, a number of villages surrounded by forest exist in the southern part of Sandan District. A few fishing villages located on the shores of Tonlesap Lake, which account for only about 2% of the provincial population, were not included in the analysis. In this study we estimated the potential supply and demand of woodfuel at three different scales: (1) the whole province scale (12,447 km2), (2) village scale but aggregated for the whole province, termed the provincial village-scale (6086 km2 at 5 km from villages), and (3) the regional village-scale, i.e., the village scale data further subdivided into three regions (2778, 3259 and 692 km2 at 5 km from villages in each group, respectively). To examine the effect of proximity to villages when calculating the village-scale data, we used the buffer function of ArcView 8.1 to calculate variables of interest in zones of 1-, 3- and 5-km distances surrounding villages (Fig. 2). The regional village-scale data were produced to investigate the effects of population density and forest availability on village-scale data. To define the regions we classified the villages into three groups (Table 2). Group A: Villages located within 10 km of National Road 6 (highest population density and lowest forest availability).
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Fig. 1. Distribution of villages in Kampong Thom Province, Cambodia, 1998.
Fig. 2. Zones of 3- and 5-km distances surrounding villages at the provincial village-scale, Kampong Thom Province, Cambodia, 1998.
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Table 2 Basic information for each scale examined in Kampong Thom Province, Cambodia, 1998 Examined scale
Land area (ha)
Population (people)
Whole province scale
1,244,748
558,406
Provincial village-scale 1 km 3 km 5 km
138,924 428,229 608,648
Regional village-scale Group A 1 km 3 km 5 km
78,280 205,536 277,812
Population density (people/km2)
Forest area (ha)
Forest area per person (ha)
Potential supply (Mg per year)
Woodfuel demand (Mg per year) 49,380
45
633,730
1.14
2,943,211
402 130 92
14,286 100,445 189,471
0.03 0.18 0.34
59,392 422,011 823,276
503 191 142
976 6,549 13,855
0.00 0.02 0.04
2,649 20,474 45,037
273 75 49
9,984 65,963 120,712
0.06 0.41 0.76
41,965 271,442 504,202
98 16 8
3,754 30,328 63,421
0.68 5.50 11.49
16,575 139,705 302,456
558,406
49,380
393,545
Group B 1 km 3 km 5 km
58,279 211,587 325,923
Group C 1 km 3 km 5 km
5,638 34,550 69,284
32,993
159,342
15,787
5,519
600
Group B: Villages located outside Group A and not located in the southern parts of Sandan District (intermediate population density and forest availability). Group C: Remote villages located in the southern parts of Sandan District (lowest population density and highest forest availability). To examine the effects of distance from villages at the regional scale, we used ArcView 8.1 to buffer at 1, 3 and 5 km from villages in each of the three groups (Fig. 3). For each group, then, we calculated variables of interest in zones of 1-, 3- and 5-km distances surrounding villages. 2.4. Calculation of potential supply and demand To determine potential woodfuel supply, we first calculated forest area for each of the five forest types at each scale examined. We then used the forest biomass and annual biomass increment data (Table 1) to calculate the total forest biomass and annual biomass increment for each scale. Top et al. (2003) revealed that the household sector represented up to 94.3% of the total woodfuel con-
sumption in Kampong Thom. Thus, this study considered only woodfuel consumption of the household sector (excluding the few villages near Tonlsap Lake). Within the household sector, 68.2% of woodfuel consumed was found to originate from forest sources, and the rest from non-forested sources such as shrubland, agricultural land and homestead. Since there have been no biomass or biomass increment measurements of non-forested areas, only woodfuel extracted from forest areas was considered in the present study. Based on an interview survey of 155 households, Top et al. (2003) also revealed differences in the per capita woodfuel consumption rate among the eight districts in the province. We used the average per capita woodfuel consumption for the 95 households from the interview survey belonging to Group A and the 60 households belonging to Group B. None of the villages belonging to Group C, which were located in Sandan District, were included in the interview survey. Therefore, for Group C we used the results of interviews from 20 households in Group B that were located in the western part of Sandan District. For each village group, the per capita woodfuel consumption rate (kg/person per year) of the sample was
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Fig. 3. Zones of 3- and 5-km distances surrounding villages at the regional village-scale, Kampong Thom Province, Cambodia, 1998.
normalized to the average household size, as obtained from the National Population Census, using the curvilinear relation developed by Top et al. (2003).
3. Results Table 2 illustrates the land area, population, forest area, biomass increment and woodfuel consumption for each scale examined. At the regional village-scale, the population of Group A is the largest (70%), following by Group B (29%) and Group C (1%). Similarly, woodfuel consumption in Group A is also the largest (67%), following by Group B (32%) and Group C (1%). For the regional village-scale analysis, if we considered a 5-km zone around villages, the calculated population density ranged between 8 persons/km2 in Group C and 142 persons/km2 in Group A, as compared to 45 persons/km2 for the whole province. Similarly, at this scale forest area per person approaches zero in Group A (0.04 ha/person) and is highest for Group C (11.49 ha/person), compared to 1.14 ha/person for the whole province. Fig. 4 indicates the share of area by land use type for each scale examined. At the provincial scale, according
to the available data, forest makes up 51% of the total land area, followed by agricultural land (25%), shrubland (16%) and others including wetland, grassland and urban area (8%). At the provincial village-scale and for Groups A and B of the regional village-scale, agricultural land is dominant irrespective of the distance from villages examined. In Group C, forest land is dominant. There is a clear trend in the calculated data at both village scales (provincial and regional) as the distance from villages increases, the proportion of the area occupied by forest increases; conversely, the closer to villages, the greater is the proportion of agricultural land. Fig. 5 illustrates the share of area by forest type within forest land at each scale. Most forests at the scales examined are dominated by evergreen forest, except for Group A which is dominated by regrowth forest. However, the proportion of evergreen forest at the provincial scale, 65%, is higher than at all other scales examined except for the 3 and 5 km zones of Group C at the regional village-scale. Generally, as the distance from villages examined increases, the proportion of the forest made up of evergreen forest increases for both provincial and regional village-scales, except for the 3 and 5 km zones of Group A.
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Fig. 4. Share of area by land use type for each scale examined in Kampong Thom Province, Cambodia.
Fig. 5. Share of area by forest type for each scale examined in Kampong Thom Province, Cambodia.
Fig. 6 indicates the potential woodfuel supply expressed as annual biomass increment divided by total land area (Mg/ha) for each scale examined. At the provincial scale, the potential woodfuel supply of
2.36 Mg/ha was greater than for all other categories examined except for all three zones of Group C. As the distance from villages decreases, the potential woodfuel supply decreases at both the provincial
Fig. 6. Annual potential woodfuel supply per hectare by forest type for each scale examined in Kampong Thom Province, Cambodia.
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Fig. 7. Ratio of annual potential supply to demand of woodfuel for each scale examined in Kampong Thom Province, Cambodia.
village-scale and regional village scale. These trends are similar to those discussed for forest land as a proportion of land area (Fig. 4). Fig. 7 illustrates the ratio of potential supply to demand of woodfuel at each scale examined; a ratio less than one represents a biomass increment lower than woodfuel consumption, and vice versa. The calculated ratios ranged between 0.08 and 503.90. Compared to the 59.60 value for the provincial scale, the ratios for the other scales were lower, except for the 3 and 5 km zones of Group C (ratios of 232.75 and 503.90, respectively). For the 1 and 3 km zones of Group A, the ratios of supply to demand were less than one (0.08 and 0.62, respectively). In the 1 km zone for the provincial village-scale and 5 km zone of Group A, the ratios were slightly higher than one. For all other examined scales, the ratio values were much higher than one. A clear trend was that as the distance from villages decreased, the ratio of potential supply to demand of woodfuel decreased at both the provincial village-scale and the regional village-scale.
4. Discussion GIS revealed differences in land use, forest type, and potential supply and demand of woodfuel at different scales. There were clear trends in potential woodfuel supply at each scale examined; the closer to villages, the less the woodfuel supply at both provincial village-scale and regional village scale. The areas
surrounding the villages of Group A had a much lower supply of woodfuel than in the other groups (Fig. 6). These trends can be explained largely by land use distribution, with agricultural land taking up a much greater proportion of land closer to villages, especially those in Group A (Fig. 4). Distribution of forest type in extant forest was also affected by proximity to villages—the closer to villages the less evergreen forest (which has the largest biomass density of 256 Mg/ha, Table 1) and the more regrowth forest (lowest biomass density of 70 Mg/ha, Table 1). Group A tended to have a much greater proportion of regrowth forest compared to the other groups or levels of data aggregation; this abundance of regrowth forest explains the relatively low potential woodfuel supply for Group A. Regrowth forest is defined as young forest resulting from logging, shifting cultivation, or other major disturbance, and is characteristically poorly stocked (Top et al., 2004). The degree of disturbance to forests, and therefore abundance of regrowth forest, could be expected to be higher in areas closer to villages. Grundy et al. (1993) also indicated that wood harvesting had a highly localized effect on woodland structure in Mutanda Resettlement Area, Zimbabwe, and that the number of live trees and total live biomass were substantially reduced within 300 m of villages. In addition Awasthi et al. (2002) showed that in Garhwal Himalaya of India, the available aboveground woody biomass of preferred firewood species was greatest near temporary huts and least near permanent villages.
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To assess the sustainability of woodfuel resources and use, many studies have examined the supply and demand relationships at relatively large scales, i.e., mainly at the country level (FAO, 1983; RWEDP, 1997; Amoo-Gottfried and Hall, 1999; Schulte-Bisping et al., 1999). At the whole province scale of this study (12,447 km2), the potential supply was 60 times higher than demand, implying that the forest resources and use of woodfuel are sustainable. However, such large scale analysis includes inaccessible areas (Millington et al., 1994). Considering only the areas surrounding villages at the provincial level (provincial village-scale), the ratio of supply to demand sharply decreased with increasing proximity to villages (ratio of 1.20, 8.55 and 16.67 for 1, 3 and 5 km distances from villages, respectively). At a more detailed scale, i.e., within groups A, B, and C, the relations were also different. We identified two zones where demand was higher than potential supply (within 1 and 3 km from villages of Group A). This suggests that forest resources are non-sustainable and will become degraded if woodfuel continues to be consumed within these zones at the current consumption rate. If woodfuel can be obtained from other source areas (such as between 3 and 5 km from villages of Group A and from the areas surrounding Group B), the sustainability of woodfuel production in those areas may be negatively affected. Therefore, it can be suggested that within Kampong Thom Province there is a deficiency in forest resources for woodfuel, at least along National Road 6 (Group A). Schulte-Bisping et al. (1999), studying the global availability of woodfuel supply, indicated that in some 17 countries (e.g., Bangladesh, China, India, Pakistan, Thailand) woodfuel consumption exceeds annual wood increment, and in other countries (e.g., Gambia, Mexico, Morocco, Nigeria, the Philippines) consumption seems to be in balance with or less than wood increment. However, if the analysis is restricted to a specific region close to villages, as in our study, the annual wood increment would be much lower than their estimates and a deficiency in the sustainable woodfuel supply may be evident within certain regions of some of these countries. We considered all tree sizes and species in calculating potential supply of woodfuel as has been the approach in many other studies. However, it is commonly known that local people are not likely to cut
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large trees for fuel. In addition, some species may be selectively targeted (RWEDP, 1998). Therefore, if we exclude large trees and some of the less preferred species from the biomass calculations, the potential woodfuel supply would be much lower and a deficiency in sustainable woodfuel supply may also be seen in areas other than along National Road 6.
5. Conclusion Our study indicates that use of GIS could show differences in potential supply and demand of woodfuel at different scales. This indicates the usefulness of spatially referenced land use and population data. In the case of Kampong Thom Province, we found that a deficiency in woodfuel resources occurs in the areas along National Road 6 due to the high woodfuel demand and dominance of agricultural land and regrowth forest in close proximity to villages. This deficiency may have negative impact on surrounding areas if they have to fill the supply gap. Policy makers and energy planners need to address this scale dependency in supply and demand relationships when preparing energy development programs. For more accurate assessments on the sustainability of woodfuel resources and use, further research is needed on the size and species of trees used for fuel.
Acknowledgements We are grateful to the Director, Mr. Ty Sokun, and the Deputy Director, Mr. Ouk Syphan, of the Department of Forestry and Wildlife of Cambodia for providing the data used in this study and for assistance on a wide range of issues. We also extend our appreciation to Mr. Vong Sarun, and Ms. Lim Sopheap for making valuable documents available. Financial support for this study was partially provided through a Grant-in-Aid for Scientific Research (B) (No. 15405024) from the Japan Society for the Promotion of Science. References Amoo-Gottfried, K., Hall, D.O., 1999. A biomass energy flow chart for Sierra Leone, Biomass. Biomass Bioenergy 16, 361–376.
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