COS 260-5 - Can scale-dependent geodiversity improve species distribution models in a montane biodiversity hotspot?

Thursday, August 10, 2023

11:00 AM – 11:15 AM PDT

Location: D140

Presenting Author(s)

BG

Beth E. Gerstner

PhD Candidate
Department of Fisheries & Wildlife; Ecology, Evolution, and Behavior Program, Michigan State University
East Lansing, Michigan, United States

Coauthor(s)

PZ

Phoebe L. Zarnetske

Associate Professor
Department of Integrative Biology; Ecology, Evolution, and Behavior Program; Institute for Biodiversity, Ecology, Evolution, and Macrosystems, Michigan State University, United States

Abstract: Knowledge about species’ distributions is essential for conservation, especially in light of global change. Species distribution models (SDMs) are commonly used to identify species’ ranges as part of designating their conservation status. These models often rely solely on environmental variable means as predictors at single resolutions, yet species distributions are also a function of environmental heterogeneity and filtering acting at different spatial scales. To capture spatial heterogeneity in the environment, scale-dependent measures of geodiversity can be applied to environmental variables and incorporated into SDMs. These variables offer an opportunity to improve biodiversity and conservation assessments, but their utility for SDMs has not been tested. We test a range of geodiversity variables computed at varying scales of remotely sensed climate and elevation. We compare the performance of Maxent SDMs generated using CHELSA bioclim variables only, to those including geodiversity measures for mammals in the Northern Andes. Certain scales of geodiversity, such as standard deviation of elevation (SDelev), improve the ability of SDMs to explain species distributions. Permutation importance, a measure of variable contribution in Maxent, also increased with increased spatial resolution of SDelev, signaling that certain measures of geodiversity are more relevant at some scales than others, but not that SDelev was ubiquitously more important locally. For example, for the ornate tití monkey, a lowland species, importance of SDelev increased with spatial scale, likely because a broadening of the calculation radius increasingly included montane areas, a strong limiting factor to the species’ dispersal and therefore their distribution. This indicates that some topographic geodiversity variables are more important at broader scales when the radius of calculation incorporates known limiting factors to the species’ distribution. By identifying a vetted set of variables that perform well for species, we can help conservation groups generate SDMs that can be used for conservation planning. This study’s open workflow for identifying scales of geodiversity predictors and their SDM performance will help practitioners generate more robust models of species ranges, and improve conservation assessments for species in a topographically complex biodiversity hotspot.