The crucial role of the accessible area in ecological niche modeling and species distribution modeling
Highlights
► Use of ecological niche modeling approaches should be grounded in a clear conceptual framework for species’ environmental and geographic distributions. ► The set of areas accessible to the species over relevant periods of its history is termed “M”. ► M is a critical determinant to the outcome of model calibration, model evaluation, and model comparison. ► Estimating M is a complex challenge, and requires further research.
Section snippets
Importance of estimating the region M
The extent used during the niche modeling process has pervasive influences on the outcome of the model. Specifically, if the extent under consideration is too limited to represent M entirely, the importance of coarse-resolution factors such as climate in delimiting species’ distributions may be underestimated. A rather dramatic example of this limitation was the recent conclusion that climate has negligible influences on species’ distributions (Beale et al., 2008), a conclusion that turned out
Worked example: a virtual species
A virtual ecological niche was generated by means of visualizing climatic variation across North America with respect to the conditions presented at Lawrence, Kansas (7 of the so-called “bioclimatic variables” at a resolution of 0.17° from Hijmans et al., 2005: annual mean temperature, mean diurnal temperature range, maximum temperature of warmest month, minimum temperature of coldest month, annual precipitation, and precipitation of the wettest and driest months). We transformed this
Approaches to estimating M
Although effects of spatial scale (i.e., extent) on resource selection and ENM studies are well-known (Boyce, 2006, Meyer and Thuiller, 2006), selection of appropriate regions within which to develop analyses is not straightforward. Most frequently, researchers take this decision without any biologically meaningful basis (Meyer and Thuiller, 2006). For instance, in most studies, a geopolitical unit is used to delimit the area of analysis without justification – in the best and most fortunate
The geographic setting
We used a simple 12 × 12 cell grid to denote the geographic domain of interest in this simulation, G. For geographic reality, we used environmental conditions corresponding to the region 103–109°W, 34.5–40.5°N. The occupied area (i.e., the actual area of distribution/area of occupancy) of a species at time t can be represented by the symbol GO(t), a vector of ones and zeros corresponding to cells where the species is present (1) or absent (0). The coordinates of each cell are maintained in
General scenarios
The arguments and examples presented in the first section of this paper should – we believe – suffice to convince the reader that M is an important consideration in studies of distributional ecology. Basically, it is the realm within which the species has sampled the landscape in question, and so it is the appropriate arena for training, validating, and comparing ecological niche models. Because our simulation was little more than a caricature of the processes involved in producing a complex
Acknowledgements
Microsoft Research provided funding for much of this effort. ALN (fellowship #189216) and FV were supported by graduate fellowships from Consejo Nacional de Ciencia y Tecnología, Mexico, and FV by the Posgrado en Ciencias Biológicas, UNAM. AJV was supported by a postdoctoral fellowship from the Ministerio de Educación y Ciencia, Spain (Ref.: EX-2007-0381) and the Juan de la Cierva Program.
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- 1
Present address: Departamento de Biologia Animal, Facultad de Ciencias, Universidad de Malaga, 29071 Malaga, Spain.
- 2
Present address: Odum School of Ecology, University of Georgia, 140 E. Green St., Athens, GA 30602.