7 - Spatial Regression and Multiscale Analysis

Summary

Quantifying the relationships between variables is affected by the spatial structure in which they occur and the scales of the processes that affect them. First, this chapter covers the topics of spatial regression, spatial causal inference and the Mantel and partial Mantel statistics. These are all methods designed to assess the relationships between variables of interest within a spatial structure. Then, multiscale analysis is presented because it is key to understanding how ecological processes and patterns change with the scale of observation. Indeed, multiscale analysis has become increasingly important as ecologists address studies at larger and larger scales with increasing probability of significant spatial heterogeneity. We describe several approaches, including multiscale ordination (MSO), Morán’s eigenvector maps (MEMs) and wavelet decomposition.