Abstract

We analyzed forest clearing and regrowth over a 23-year time period for 21 forest concession and management units within the Maya Biosphere Reserve(MBR), Guatemala. The study area as a whole experienced a clearing rate of0.16%/year from 1974 through 1997. The overall clearing rate appears rather low when averaged over the entire study area over 23 years because most of the reserve was inaccessible. However, despite the granting of legal protection to the MBR in 1990, clearing rates continued to rise, with the highest rates occurring in the most recent time period in the analysis, 1995 to1997. Higher rates of clearing relative to regrowth occurred in newly established communities and in the Reserve's buffer zone, where the clearing of high forest was preferred for pasture development. Exploratory models were built and analyzed to examine the effects of various landscape variables on forest clearing. The different units in the analysis showed different relationships of forest clearing with variables such as forest cover type and distance to access(roads and river corridors). Where available, socio-economic household survey data helped to explain patterns and trends observed in the time series Landsat imagery. A strong relationship between forest clearing and distance to access was demonstrated. More clearing occurred further from roads during later time periods as farmers moved deeper into the forest to find land to clear. Communities inside the MBR that were less dependent on farming had forest clearing to regrowth ratios of one:one or less. These communities used fallow fields in greater proportions than communities in the Reserve's buffer zone. General trends in clearing by forest cover type suggest a preference for clearing high forest (bosque alto) types found on the higher elevation, better-drained soils, and fallow fields,and an avoidance of low-lying, seasonally flooded terrain(bajos). Satellite remote sensing observations of forest clearing and regrowth patterns can provide an objective source of information to complement socio-economic studies of the human driving forces in land cover and land use change.

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