Elsevier

Ecological Modelling

Volume 222, Issue 11, 10 June 2011, Pages 1810-1819
Ecological Modelling

The crucial role of the accessible area in ecological niche modeling and species distribution modeling

https://doi.org/10.1016/j.ecolmodel.2011.02.011Get rights and content

Abstract

Using known occurrences of species and correlational modeling approaches has become a common paradigm in broad-scale ecology and biogeography, yet important aspects of the methodology remain little-explored in terms of conceptual basis. Here, we explore the conceptual and empirical reasons behind choice of extent of study area in such analyses, and offer practical, but conceptually justified, reasoning for such decisions. We assert that the area that has been accessible to the species of interest over relevant time periods represents the ideal area for model development, testing, and comparison.

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.

References (86)

  • C.M. Beale et al.

    Opening the climate envelope reveals no macroscale associations with climate in European birds

    Proceedings of the National Academy of Sciences of the United States of America

    (2008)
  • M.S. Boyce

    Scale for resource selection functions

    Diversity and Distributions

    (2006)
  • J.H. Brown et al.

    The geographic range: size, shape, boundaries, and internal structure

    Annual Review of Ecology and Systematics

    (1996)
  • M. Byrne et al.

    Birth of a biome: insights into the assembly and maintenance of the Australian arid zone biota

    Molecular Ecology

    (2008)
  • J.S. Cabral et al.

    Estimating demographic models for the range dynamics of plant species

    Global Ecology and Biogeography

    (2010)
  • P.D. Carey et al.

    The determinants of the distribution and abundance of the winter annual grass Vulpia ciliata ssp. ambigua

    Journal of Ecology

    (1995)
  • B.C. Carstens et al.

    Integrating coalescent and ecological niche modeling in comparative phylogeography

    Evolution

    (2007)
  • W. Dansgaard et al.

    Evidence for general instability of past climate from a 250 kyr ice-core record

    Nature

    (1993)
  • M.B. Davis et al.

    Range shifts and adaptive responses to quaternary climate change

    Science

    (2001)
  • T. Dobzhansky et al.

    Ecological variables affecting the dispersal behavior of Drosophila pseudoobscura and its relatives

    American Naturalist

    (1979)
  • T. Dobzhansky et al.

    Genetics of natural populations. X. Dispersion rates in Drosophila pseudoobscura

    Genetics

    (1943)
  • S.V. Edwards et al.

    Gene divergence, population divergence, and the variance in the coalescence time in phylogeographic studies

    Evolution

    (2000)
  • J. Elith et al.

    The art of modelling range-shifting species

    Methods in Ecology and Evolution

    (2010)
  • R. Engler et al.

    MigClim: predicting plant distribution and dispersal in a changing climate

    Diversity and Distributions

    (2009)
  • J.R. Etterson et al.

    Constraint to adaptive evolution in response to global warming

    Science

    (2001)
  • K.J. Gaston

    The Structure and Dynamics of Geographic Ranges

    (2003)
  • N.J. Gotelli et al.

    Patterns and causes of species richness: a general simulation model for macroecology

    Ecology Letters

    (2009)
  • C.H. Graham et al.

    Integrating phylogenetics and environmental niche models to explore speciation mechanisms in dendrobatid frogs

    Evolution

    (2004)
  • J. Grinnell

    Field tests of theories concerning distributional control

    American Naturalist

    (1917)
  • A. Guisan et al.

    Predicting species distribution: offering more than simple habitat models

    Ecology Letters

    (2005)
  • A.J. Herbertson

    The major natural regions, an essay in systematic geography

    Geographical Journal

    (1905)
  • R.J. Hijmans et al.

    Very high resolution interpolated climate surfaces for global land areas

    International Journal of Climatology

    (2005)
  • R.D. Holt

    On the evolutionary ecology of species’ ranges

    Evolutionary Ecology Research

    (2003)
  • R.D. Holt et al.

    Analysis of adaptation in heterogeneous landscapes: implications for the evolution of fundamental niches

    Evolutionary Ecology

    (1992)
  • G.E. Hutchinson

    Concluding remarks

    Cold Spring Harbor Symposia on Quantitative Biology

    (1957)
  • S.T. Jackson et al.

    Responses of plant populations and communities to environmental changes of the Late Quaternary. Paleobiology

    (2000)
  • S.S. Jakob et al.

    Phylogeographic analyses and paleodistribution modeling indicate Pleistocene in situ survival of Hordeum species (Poaceae) in southern Patagonia without genetic or spatial restriction

    Molecular Biology and Evolution

    (2009)
  • A. Jiménez-Valverde et al.

    Dominant climate influences on North American bird distributions

    Global Ecology and Biogeography

    (2010)
  • A. Jiménez-Valverde et al.

    Not as good as they seem: the importance of concepts in species distribution modelling

    Diversity and Distributions

    (2008)
  • M. Kearney et al.

    Mapping the fundamental niche: physiology, climate, and the distribution of a nocturnal lizard

    Ecology

    (2004)
  • L.L. Knowles

    The burgeoning field of statistical phylogeography

    Journal of Evolutionary Biology

    (2004)
  • M. Kot et al.

    Dispersal data and the spread of invading organisms

    Ecology

    (1996)
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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.

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