Species distribution models: Spatial autocorrelation and non-stationarity

The main goal of species distribution modeling is to identify important underlying factors related to broad-scale ecological patterns in order to make meaningful explanations or accurate predictions. When standard statistical methods such as regression are used to formulate these models, assumptions about the spatial structure of the data and the model parameters are often violated. Autocorrelation and non-stationarity are characteristics of spatial data and models, respectively, and if present and unaccounted for in model development, they can result in poorly specified models as well as inappropriate spatial inference and prediction. While these spatial issues are addressed here in an ecological context using species distribution models, they are broadly relevant to any statistical modeling applications using spatial data.