z-logo
open-access-imgOpen Access
Estimating environmental suitability
Author(s) -
Drake John M.,
Richards Robert L.
Publication year - 2018
Publication title -
ecosphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.255
H-Index - 57
ISSN - 2150-8925
DOI - 10.1002/ecs2.2373
Subject(s) - niche , contrast (vision) , robustness (evolution) , ecology , probability distribution , environmental niche modelling , computer science , ecological niche , species distribution , statistics , econometrics , mathematics , artificial intelligence , habitat , biology , biochemistry , gene
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here