Literature DB >> 26609083

Predicting community structure in snakes on Eastern Nearctic islands using ecological neutral theory and phylogenetic methods.

Frank T Burbrink1, Alexander D McKelvy2, R Alexander Pyron3, Edward A Myers2.   

Abstract

Predicting species presence and richness on islands is important for understanding the origins of communities and how likely it is that species will disperse and resist extinction. The equilibrium theory of island biogeography (ETIB) and, as a simple model of sampling abundances, the unified neutral theory of biodiversity (UNTB), predict that in situations where mainland to island migration is high, species-abundance relationships explain the presence of taxa on islands. Thus, more abundant mainland species should have a higher probability of occurring on adjacent islands. In contrast to UNTB, if certain groups have traits that permit them to disperse to islands better than other taxa, then phylogeny may be more predictive of which taxa will occur on islands. Taking surveys of 54 island snake communities in the Eastern Nearctic along with mainland communities that have abundance data for each species, we use phylogenetic assembly methods and UNTB estimates to predict island communities. Species richness is predicted by island area, whereas turnover from the mainland to island communities is random with respect to phylogeny. Community structure appears to be ecologically neutral and abundance on the mainland is the best predictor of presence on islands. With regard to young and proximate islands, where allopatric or cladogenetic speciation is not a factor, we find that simple neutral models following UNTB and ETIB predict the structure of island communities.
© 2015 The Author(s).

Entities:  

Keywords:  community phylogenetics; dispersal; snakes; unified neutral theory of biodiversity

Mesh:

Year:  2015        PMID: 26609083      PMCID: PMC4685806          DOI: 10.1098/rspb.2015.1700

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


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