Using Spatial Information to Understand Forest Change and Community Dynamics: A Case from Nepal

Abstract

"The forest composition we witness today is a product of temporal anthropogenic and nonanthropogenic disturbances. Any investigation dedicated to understanding the impact of human activities on forest resources requires longitudinal information related to forest condition. Or does it? Scholars from geography, anthropology and other disciplines have long been aware of the informing nature of spatial relationships: human actions in a previous time often leave their imprints in today's landscape. Traditional empirical studies of forest condition typically ignore this type of information and rely of aggregated forest-level indicators developed from aspatial plot-level analyses. This paper conducts a spatial analysis of one forest product species in forests in a foraging setting in the Siwalik hills of Nepal. The forest species of particular importance to the surrounding communities for timber, fodder and fuelwood. Forest plot locations were accurately located using Differential Global Positioning Systems (DGPS) technology and were processed using an Arc-Info Geographic Information System (GIS). After accounting for the natural distribution of the species and other physiographic influences using maximum likelihood regression analysis, a pattern over the landscape is revealed. This pattern is not surprising for it accurately reflects what we would expect given the incentive structures, forest governance arrangements, village geography and community norms and dynamics in the area. This provides an example of how a spatial analysis of cross-sectional forest condition data can be used to extract information about forest change when longitudinal data are nonexistant."