The Geometry of Spatial Analyses: Implications for Conservation Biologists

Most conservation biology is about the management of space and therefore requires spatial analyses. However, recent debates in the literature have focused on a limited range of issues related to spatial analyses that are not always of primary interest to conservation biologists, especially autocorrelation and spatial confounding. Explanations of how these analyses work, and what they do, are permeated with mathematical formulas and statistical concepts that are outside the experience of most working conservationists. Here, we describe the concepts behind these analyses using simple simulations to exemplify their main goals, functions and assumptions, and graphically illustrate how processes combine to generate common spatial patterns. Understanding these concepts will allow conservation biologists to make better decisions about the analyses most appropriate for their problems.