Publications

Coops, NC; Bolton, DK; Hobi, ML; Radeloff, VC (2019). Untangling multiple species richness hypothesis globally using remote sensing habitat indices. ECOLOGICAL INDICATORS, 107, UNSP 105567.

Abstract
Remotely sensed data can estimate terrestrial productivity more consistently and comprehensively across large areas than field observations. However, questions remain how species richness and abundances are related to terrestrial productivity in different biogeographic realms. The Dynamic Habitat Indices (DHIs) are a set of three remote sensing indices each related to a key biodiversity productivity hypothesis (i.e., available energy proxied by the annual cumulative productivity, environmental stress proxied by the minimum productivity throughout the year, and environmental stability proxied by the annual coefficient of variation in productivity). Here, we quantify the relevance of each hypothesis globally and for different biogeographic realms using models of species richness for three taxa (amphibians, birds, and mammals) derived from IUCN species range maps. Using parameterized generalized additive models (GAM's) we found that the available energy hypothesis was the best individual index explain 37-43% of the variation in species richness globally with the best models for amphibians and worst for mammal richness. Examining the residuals of these GAMS indicated that adding the environmental stress hypothesis explained 0-22% additional variance, especially in the Nearctic where large amounts of snow and ice are prevalent and environmental conditions deteriorate during winter. The addition of the environmental stability hypothesis generally explained more variance than the environmental stress hypothesis, especially in the Neartic and Paleartic and for birds however, in certain cases, the environmental stress hypothesis explains more variance at the realm scale.

DOI:
10.1016/j.ecolind.2019.105567

ISSN:
1470-160X