Process-based models of species distributions and the mid-domain effect
Connolly, Sean R. (2005) Process-based models of species distributions and the mid-domain effect. American Naturalist, 166 (1). pp. 1-11.
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Null models that place species ranges at random within a bounded geographical domain produce hump-shaped species richness gradients (the “Mid-Domain Effect”, or MDE). However, there is debate about the extent to which these models are a suitable null expectation for effects of environmental gradients on species richness. Here, I present a process-based framework for modeling species distributions within a bounded geographical domain. Analysis of null models consistent with the mid-domain hypothesis shows that MDEs are indeed likely to be ubiquitous consequences of geographical domain boundaries. Comparing the probability distributions of range locations for the process-based and randomization-based models reveals that randomization models probably overestimate the contribution of MDEs to empirical patterns of species richness, but it also indicates that other, testable predictions from randomization models are likely to be robust. I also show how this process-based framework can be extended beyond null models, to incorporate effects of environmental gradients within the domain. This study provides a first step towards an ecological theory of species distributions in geographical space that can incorporate both “geometric constraints” and effects of environmental gradients, and shows how such a theory can inform our understanding of species richness gradients in nature.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||macroecology; mid-domain effect; geographic range; species richness; latitudinal gradient|
Copyright 2005. The University of Chicago Press. Reproduced in accordance with publisher policy.
|Date Deposited:||24 May 2007|
|FoR Codes:||06 BIOLOGICAL SCIENCES > 0699 Other Biological Sciences > 069999 Biological Sciences not elsewhere classified @ 100%|
|SEO Codes:||97 EXPANDING KNOWLEDGE > 970106 Expanding Knowledge in the Biological Sciences @ 100%|
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