FOREST CONVERSION IN SOUTHERN SUMATERA, INDONESIA Christopher Legg

THE STUDY AREAS The EU-funded Forest Inventory and Monitoring Projecct (FIMP) had 7 pilot study areas in the four provinces of Southern Sumatera, Indonesia. Following initial studies, FIMP data- collection and processing techniques were applied to the whole of the Province of Bengkulu Studies of forest conversion were undertaken in Western Jambi and Bengkulu WESTERN JAMBI BENGKULU PROVINCE

Forest Conversion in Bengkulu Province, A vegetation map of Sumatera was prepared between 1986 and 1991 by Laumonnier and others, based mainly on 1985 satellite imagery. Areas of primary forest in 1985 are shown as pale green. FIMP produced a new map based on 1998 satellite imagery. Areas of 1998 primary forest shown as dark green.

Forest conversion by altitude zones, northern and southern districts of Bengkulu province 1985 forest in black, 1998 primary forest medium grey, 1998 primary plus logged- over forest pale grey. Area units square kilometres, altitude zones correspond to major ecological divisions. Northern Bengkulu Southern Bengkulu

Land use in Bengkulu province is dominated by agriculture. Plantation crops such as oil-palm (purple vertical stripes), rubber (orange vertical stripes) and cocoa (brown vertical stripes) are particularly important in north Bengkulu. Cultivation of irrrigated rice (pale blue) is widespread, and coffee (purple shading) is dominant in the highlands.

A more detailed view of north Bengkulu shows how plantation crops are concentrated in the areas converted from forest since 1985 (outlined in red). White areas are logged-over forest, scheduled for re-growth and sustainable logging, but always vulnerable to changes in land classification. Irrigated rice is rarely grown in newly-cleared areas, but rather in older areas of settlement.

The distribution of villages also reflects recent clearing of forest. Old villages (black) are mainly outside or on the fringes of the 1985 forest, while new local settler villages and transmigration settlements (red and blue) are often within recently cleared areas

Degeneration of habitat quality is a serious threat to biodiversity, but fragmentation of forest habitat is also a threat to many plants and animals. The map above shows the total number of bird species recorded from FIMP forest plots. The highest species abundance is in lowland forest, near the present boundary of the forest. The abundance of the gibbon Symphalangus syndactylus is shown on the right. The highest abundance is in an isolated area of hill forest in southern Bengkulu.

Display in three dimensions can assist in visualisation of geographic data. This view drapes a satellite image over a digital elevation model. Vertical columns indicate the locations of villages sampled by FIMP. The height of the column is proportional to the number of households. Black = old villages; Blue = new local settlements; Red = transmigration.

FOREST CONVERSION IN BENGKULU - SOME STATISTICS Loss of lowland forest. In north Bengkulu, forest cover below 150m elevation declined from 39.5% to 1.6% between 1985 and 1998, in south Bengkulu, from 13.5% to 0.5% Rate of Conversion. Mean annual deforestation rate in north Bengkulu has been 0.28 ha/household/year, while in south Bengkulu it has been 0.1 ha/household/year Status of Protected Forest. There has been effectively no clearing of forest designated as protection forest or national park, largely because these occur only at high elevations in Bengkulu. Much of the forest cleared was originally designated as “permanent production forest”, destined for re-growth and sustainable logging. It was later re-classified as “conversion forest” to permit clearing for plantations. Species Diversity. FIMP sample plots in forest below 850 metres elevation indicate that the lowland and hill forests of Bengkulu contain in excess of 400 species of trees at densities of between 400 and 600 trees per hectare. Nearly 50% of the species were recorded only once in four clusters of plots.

THE RANTAU PANDAN AREA, WESTERN JAMBI PROVINCE A detailed study of forest conversion was undertaken in the Rantau Pandan sub-district of western Jambi province. Landsat satellite imagery from 1990 and 1995 was used to map the extent of forest at both dates. Areas cleared of forest between 1990 and forest boundaries in yellow

The change in forest area in 13 villages in the Rantau Pandan area was mapped from satellite imagery. The map above shows areas with loss of forest in blue, and the remaining forest in 1995 in green.

Forest Conversion and Slopes The map shows slopes in the study area, derived from a digital elevation model. White areas are flat, purple 5-10 degrees, blue degrees, and so on. The graph shows that more than 70% of the forest cleared was on slopes of less than 5 degrees.

Forest Conversion and Distance to Streams The map shows distance to streams. Red areas are closest to streams, purple and white furthest away. The graph shows that 60% of the areas cleared lie within 500 metres of a stream.

Forest Conversion and Geology The map shows the geology of the study area. Red is granite, orange metamorphic rocks, blue volcano-sediments and green swamp sediments and alluvium. The graph compares the percentage area of all forest on each rock type with the percentage area converted. Swamp sediments and alluvium are preferred, while metamorphic rocks are avoided.

Forest Conversion and Distance from Settlements Distance buffers from settlements are shown in the map above, white being closest and red furthest away. The graph shows cumulative hectares of forest converted against distance from settlements. More than 50% of the forest cleared is within 3 km of a settlement.

Considered by village areas, there are positive correlations between the rate of forest clearance, in ha/yr, and both the total area of forest on flat land within the village area and the total edge-length of forest in the village area. The first reflects the general preference for flat land for agriculture, while the edge-length is a measure of forest fragmentation.

THE CONCEPT OF SUSCEPTIBILITY TO CONVERSION The studies of forest conversion in the Rantau Pandan area have indicated that the selection of an area of forest for conversion to agriculture is not random, but depends on slope, geology, distance to streams, distance to settlements, and possibly other as yet unknown factors. Maps of factors known to affect the selection of conversion forest can be combined into a single map quantifying the “susceptibility” of the forest to clearing Each of the factors slope, geology, distance to streams and distance from villages must first be quantified and divided into a reasonable number (less than 10 classes) of discrete categories. Weighting factors, accounting for the relative importance of each parameter in decision - making, must be assigned. These would ideally be determined by the use of simultaneous equations, but in this experimental study were determined by trial and error. The map shows the estimated susceptibility of 1990 forest to conversion to agriculture, most susceptible in red, least in purple.

MODELLING FOREST CONVERSION A cellular automaton model was written in the Avenue programming language for ArcView. The model converted cells at the forest edge to non-forest, depending on the susceptibility of the forest to conversion, and on the requirements for new agricultural land in each village. The latter was a function of the village population and total agricultural land holdings. The model ran for each village until five years requirements had been met, or all forest converted. The maps shows the results of initial trials of the model. Blue areas were converted by the model, and observed to be converted in reality. Red areas were actually converted, but not modelled. Purple areas were converted by the model, but not in reality. Reasons for failure of the model must be found by further field work, as well as by refinements to the modelling process.

In late 1997 dramatic land-clearing occurred in the study area as a large oil-palm company started new plantations. Land designated as “Permanent Production Forest” was re-designated as “Conversion Forest” by the provincial governor. This SPOT IV image was acquired in March 1998, and shows newly- cleared land in blue. Logged-over forest is dark brown. Village boundaries are overlain in black.

Forest converted to oil palm plantation is shown in pale blue in the map below, while land cleared for other purposes between 1995 and 1998 is shown in yellow. The area cleared greatly exceeds the annual clearing by all villages in the study area. It may be possible to explicitly model human-forest interactions in closed systems, such as that which prevailed in this study area prior to The influence of external decisions, made without any reference to villagers, is a serious problem in modelling.