Spatially varying coefficients can improve parsimony and descriptive power for species distribution models

Species distribution models (SDMs) are widely used to relate species occurrence and density local environmental conditions, often include a spatially correlated variable account for spatial patterns in residuals. Ecologists have extended SDMs varying coefficients (SVCs), where the response given covariate varies smoothly over space time. However, SVCs see relatively little use perhaps because they remain less known relative other SDM techniques. We therefore review ecological contexts can improve interpretability descriptive power from SDMs, including responses regional indices that represent teleconnections; density-dependent habitat selection; detectability; context-dependent interactions with unmeasured covariates. then illustrate three additional examples detail using vector autoregressive spatio-temporal (VAST) model. First, decadal trends model identifies arrowtooth flounder Atheresthes stomias Bering Sea 1982 2019. Second, trait-based joint highlights role of body size temperature community assembly Gulf Alaska. Third, an age-structured walleye pollock Gadus chalcogrammus contrasts cohorts broad distributions (1996 2009) those more constrained (2002 2015). conclude extend address wide variety be better understand range processes, e.g. dependence, population dynamics.