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bioRxiv · 10.1101/003657

Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology

Daniel McGlinn·Xiao Xiao·Justin Kitzes·Ethan P White
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Abstract

AimThe Maximum Entropy Theory of Ecology (METE) is a unified theory of biodiversity that attempts to simultaneously predict patterns of species abundance, size, and spatial structure. The spatial predictions of this theory have repeatedly performed well at predicting diversity patterns across scales. However, the theoretical development and evaluation of METE has focused on predicting patterns that ignore inter-site spatial correlations. As a result the theory has not been evaluated using one of the core components of spatial structure. We develop and test a semi-recursive version of METEs spatially explicit predictions for the distance decay relationship of community similarity and compare METEs performance to the classic random placement model of completely random species distributions. This provides a better understanding and stronger test of METEs spatial community predictions.\n\nLocationNew world tropical and temperate plant communities.\n\nMethodsWe analytically derived and simulated METEs spatially explicit expectations for the Sorensen index of community similarity. We then compared the distance decay of community similarity of 16 mapped plant communities to METE and the random placement model.\n\nResultsThe version of METE we examined was successful at capturing the general functional form of empirical distance decay relationships, a negative power function relationship between community similarity and distance. However, the semi-recursive approach consistently over-predicted the degree and rate of species turnover and yielded worse predictions than the random placement model.\n\nMain conclusionsOur results suggest that while METEs current spatial models accurately predict the spatial scaling of species occupancy, and therefore core ecological patterns like the species-area relationship, its semi-recursive form does not accurately characterize spatially-explicit patterns of correlation. More generally, this suggests that tests of spatial theories based only on the species-area relationship may appear to support the underlying theory despite significant deviations in important aspects of spatial structure.

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Daniel McGlinn, Xiao Xiao, Justin Kitzes, Ethan P White. 2014-03-30. Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology. https://doi.org/10.1101/003657

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