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A practical overview of transferability in species distribution modeling

Authors :
Ministerio de Economía y Competitividad (España)
Universidad de Castilla La Mancha
Ministerio de Ciencia e Innovación (España)
Ministerio de Agricultura, Alimentación y Medio Ambiente (España)
Werkowska, Wioletta
Márquez, Ana Luz
Real, Raimundo
Acevedo, Pelayo
Ministerio de Economía y Competitividad (España)
Universidad de Castilla La Mancha
Ministerio de Ciencia e Innovación (España)
Ministerio de Agricultura, Alimentación y Medio Ambiente (España)
Werkowska, Wioletta
Márquez, Ana Luz
Real, Raimundo
Acevedo, Pelayo
Publication Year :
2017

Abstract

Species distribution models (SDMs) are basic tools in ecology, biogeography, and biodiversity. The usefulness of SDMs has expanded beyond the realm of ecological sciences, and their application in other research areas is currently frequent, e.g., spatial epidemiology. In any research area, the principal interest in these models resides in their capacity to predict species response in new scenarios, i.e., the models' transferability. Although the transferability of SDMs has been the subject of interest for many years, only in the 2000s did this topic gain particular attention. This article reviews the concept of the transferability of SDMs to new spatial scenarios, temporal periods, and (or) spatial resolutions, along with the potential constraints of the model's transferability, and more specifically: (i) the type of predictors and multicollinearity, (ii) the model complexity, and (iii) the species' intrinsic traits. Finally, we describe a practicable analytical protocol to be assessed before transferring a model to a new scenario. This protocol is based on three fundamental pillars: the environmental equilibrium of the species with the environment, the environmental similarity between the new scenario, and the areas used to model parametrisation and the correlation structure among predictors.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1247924953
Document Type :
Electronic Resource