Remote sensing and GIS techniques for spatial and biophysical analyses of alpine treeline through process and empirical models

Two modelling approaches are used to assess the sensitivity of alpine treeline to climate change. Each of the models is limited to a range of spatial scales. First, empirical models of vegetation pattern provide a regional- to landscape-scale perspective on the biophysical controls of the pattern. Generalized linear and additive models are presented as techniques for diagnostic and predictive modelling of spatial patterns. Second, plant physiological process models characterize resource use and partitioning, particularly net carbon gain, at the plant and stand scales. Regression residuals from empirical spatial models were analysed to define regional factors - including geomorphology and geology, drainage basin configurations, summer seasonal solar radiation, snow potential and soil moisture potential - affecting model performance. The two modelling approaches offer different perspectives on vegetation pattern that can be integrated for complementary, multiscale analyses linking pattern and process at the alpine treeline ecotone. A rule-based hierarchical model is suggested for integrating the approaches. -Authors

Remote sensing and GIS techniques for spatial and biophysical analyses of alpine treeline through process and empirical models Academic Article