Abstract
Most Species Distribution Models include spatial effects to improve
prediction at unsampled locations and reduce Type I errors. Ecologists
tend to try ecologically interpret the spatial patterns displayed by the
spatial effect. However, spatial autocorrelation may be driven by many
different unaccounted drivers, which complicates the ecological
interpretation of fitted spatial effects. This study wants to provide a
practical demonstration that spatial effects are able to smooth the
effect of multiple unaccounted drivers. To do so we use a simulation
study that fit model-based spatial models using both geostatistics and
2D smoothing splines. Results show that fitted spatial effects resemble
the sum of the unaccounted covariate surface(s) in each model.