PT  - JOURNAL ARTICLE
AU  - John M. Drake
AU  - Robert L. Richards
TI  - Estimating environmental suitability
AID  - 10.1101/109041
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 109041
4099  - http://biorxiv.org/content/early/2017/02/16/109041.short
4100  - http://biorxiv.org/content/early/2017/02/16/109041.full
AB  - Author statement JD proposed the model, JD and RR wrote the code and performed the analysis, JD wrote the first draft of the manuscript, and all authors contributed substantially to revisions.Abstract Methods for modeling species, distributions in nature are typically evaluated empirically with respect to data from observations of species occurrence and, occasionally, absence at surveyed locations. Such models are relatively “theory-free”. In contrast, theories for explaining species, distributions draw on concepts like fitness, niche, and environmental suitability. This paper proposes that environmental suitability be defined as the conditional probability of occurrence of a species given the state of the environment at a location. Any quantity that is proportional to this probability is a measure of relative suitability and the support of this probability is the niche. This formulation suggests new methods for presence-background modeling of species distributions that unify statistical methodology with the conceptual framework of niche theory. One method, the plug-and-play approach, is introduced for the first time. Variations on the plug-and-play approach were studied with respect to their numerical performance on 106 species from an exhaustively sampled presence/absence survey of vegetation in the Canton of Vaud, Switzerland. Additionally, we looked at the robustness of these methods to the presence of irrelevant information and sample size. Although irrelevant variables eroded the predictive performance of all methods, these methods were found to be both numerically and statistically robust.