Can mechanism inform species' distribution models?

  • Buckley L
  • Urban M
  • Angilletta M
 et al. 
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Two major approaches address the need to predict species distributions in response to environmental changes. Correlative models estimate parameters phenomenologically by relating current distributions to environmental conditions. By contrast, mechanistic models incorporate explicit relationships between environmental conditions and organismal performance, estimated independently of current distributions. Mechanistic approaches include models that translate environmental conditions into biologically relevant metrics (e.g. potential duration of activity), models that capture environmental sensitivities of survivorship and fecundity, and models that use energetics to link environmental conditions and demography. We compared how two correlative and three mechanistic models predicted the ranges of two species: a skipper butterfly (Atalopedes campestris) and a fence lizard (Sceloporus undulatus). Correlative and mechanistic models performed similarly in predicting current distributions, but mechanistic models predicted larger range shifts in response to climate change. Although mechanistic models theoretically should provide more accurate distribution predictions, there is much potential for improving their flexibility and performance. Rapid anthropogenic changes in climatic conditions and land use necessitate accurate predictions of how species will respond to environmental changes. Despite this need, fundamental questions persist about how to predict distri-butions most accurately (Pearson & Dawson 2003; Araujo & Guisan 2006). One primary question is whether a statistical relationship between species localities and environmental conditions is sufficient to predict future distributions (and over what temporal and spatial scales) or whether accurate predictions require a more mechanistic understanding of the processes underlying distributions (Kearney 2006). We address this question by comparing two major approaches for modeling the geographic distributions of species: correlative and mechanistic approaches. Correlative models implicitly incorporate biological processes by statistically estimating environment-range associations from occur-rences. Mechanistic models explicitly capture hypothetical biological processes and derive their parameters from the phenotypes of organisms, which are then used to construct distributional models. The models differ in their ability to characterize the abiotic, biotic, and historical niches of a species (Soberon 2007), although existing models focus primarily on abiotic constraints. Correlative models generally require only data on the localities of specimens and their associated environmental conditions. These models have been applied in a wide variety of contexts (Elith et al. 2006), such as understanding species invasions (Peterson & Vieglais 2001; Thuiller et al. 2005), predicting glacial refugia (Hugall et al. 2002; Strasburg et al. 2007), delimiting species (Raxworthy et al. 2007; Rissler & Apodaca 2007; Stockman & Bond 2007), defining modes of speciation (Graham et al. 2004), and identifying conservation hotspots (Rissler et al. 2006). A correlative model can accurately predict range dynamics if (1)

Author-supplied keywords

  • Biophysical model
  • Climate change
  • Climate envelope model
  • Demography
  • Fundamental niche
  • Physiology
  • Realized niche
  • Species' range model

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  • Michael SearsClemson University

  • Lauren B. Buckley

  • Mark C. Urban

  • Michael J. Angilletta

  • Lisa G. Crozier

  • Leslie J. Rissler

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