Scale-dependent relationships between population and environment in northeastern Thailand

Social and biophysical data were collected, integrated and analyzed to exam ine scale-dependent relationships between selected population and environme ntal variables for a study site in northeast Thailand. Data sets were gener ated through the use of remote sensing to characterize land-use/land-cover and plant biomass variation across the Nang Rong district; GIS to derive el evation, slope angle, and soil moisture potential; social survey data at th e village level to categorize demographic variables; and a population distr ibution model to transform demographic data collected at discrete village l ocations to spatially continuous surfaces stratified by agricultural land u ses. Statistical analysis employed multiple regression to estimate populati on density in relation to social and biophysical variables, and canonical a nalysis to relate population variables to environmental variables across a range of spatial scales extending from 30 to 1050 m. Findings indicate the importance of spatial scale in the study of population and the environment. Regression models reflect the scale dependence of the selected variables t hrough plots of slope coefficients and R-2 values across nine scale steps. The variation in relationships among environment and population variables, evidenced through factor loadings associated with canonical correlation, su ggest that relationships are not generalizeable across the sampled spatial scales.