Xiao Xiao | bioRxiv Science

bioRxiv2015

An extensive comparison of species-abundance distribution models.

A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.

Preprint↗

bioRxiv2014

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

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.

Ecology↗