the relationship between a spatial process and environmental variables
as a function of spatial scale is a challenging problem. Therefore,
there is a need for a valid and reliable tool to examine and evaluate
scale dependencies in biogeography, macroecology and other earth
Central Europe (latitude 43.99°–54.22° N, longitude 4.79°–15.02° E).
present a method for applying two-dimensional wavelet analysis to a
generalized linear model. This scale-specific regression is combined
with a multimodel inference approach evaluating the relative importance
of several environmental variables across different spatial scales. We
apply this method to data of climate, topographic and land cover
variables to explain variation in annual greening of vegetation (i.e.
phenology) in Central Europe.
use is more important to explain the variation in greening than climate
at smaller resolution while climate is more important at larger
resolution with a shift at c. 1000 km2.
the best of our knowledge, this is the first study analysing the scale
dependency of an ecosystem process, clearly distinguishing between the
different components of scale, namely grain, focus and extent. The
obtained results demonstrate that our newly proposed method is
particularly suitable for studying scale dependencies of various spatial
processes on environmental drivers keeping grain and extent constant
and changing focus (i.e. resolution).