Document Detail

The spatial limitations of current neutral models of biodiversity.
MedLine Citation:
PMID:  21423724     Owner:  NLM     Status:  MEDLINE    
The unified neutral theory of biodiversity and biogeography is increasingly accepted as an informative null model of community composition and dynamics. It has successfully produced macro-ecological patterns such as species-area relationships and species abundance distributions. However, the models employed make many unrealistic auxiliary assumptions. For example, the popular spatially implicit version assumes a local plot exchanging migrants with a large panmictic regional source pool. This simple structure allows rigorous testing of its fit to data. In contrast, spatially explicit models assume that offspring disperse only limited distances from their parents, but one cannot as yet test the significance of their fit to data. Here we compare the spatially explicit and the spatially implicit model, fitting the most-used implicit model (with two levels, local and regional) to data simulated by the most-used spatially explicit model (where offspring are distributed about their parent on a grid according to either a radially symmetric Gaussian or a 'fat-tailed' distribution). Based on these fits, we express spatially implicit parameters in terms of spatially explicit parameters. This suggests how we may obtain estimates of spatially explicit parameters from spatially implicit ones. The relationship between these parameters, however, makes no intuitive sense. Furthermore, the spatially implicit model usually fits observed species-abundance distributions better than those calculated from the spatially explicit model's simulated data. Current spatially explicit neutral models therefore have limited descriptive power. However, our results suggest that a fatter tail of the dispersal kernel seems to improve the fit, suggesting that dispersal kernels with even fatter tails should be studied in future. We conclude that more advanced spatially explicit models and tools to analyze them need to be developed.
Rampal S Etienne; James Rosindell
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-03-14
Journal Detail:
Title:  PloS one     Volume:  6     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2011  
Date Detail:
Created Date:  2011-03-22     Completed Date:  2011-07-05     Revised Date:  2013-06-30    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e14717     Citation Subset:  IM    
Community and Conservation Ecology Group, Centre for Ecological and Evolutionary Studies, University of Groningen, Groningen, The Netherlands.
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MeSH Terms
Computer Simulation
Models, Biological*
Regression Analysis
Species Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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