Literature DB >> 16001221

Niche overlap estimates based on quantitative functional traits: a new family of non-parametric indices.

David Mouillot1, Wendy Stubbs, Matthieu Faure, Olivier Dumay, J Antoine Tomasini, J Bastow Wilson, Thang Do Chi.   

Abstract

The concept of niche overlap appears in studies of the mechanisms of the maintenance of species diversity, in searches for assembly rules, and in estimation of within-community species redundancy. For plant traits measured on a continuous scale, existing indices are inadequate because they split the scale into a number of categories thus losing information. An index is easy to construct if we assume a normal distribution for each trait within a species, but this assumption is rarely true. We extend and apply an index, NO(K), which is based on kernel density functions, and can therefore work with distributions of any shape without prior assumptions. For cases where the ecologist wishes to downweight traits that are inter-correlated, we offer a variant that does this: NO(Kw). From either of these indices, an index of the mean niche overlap in a community can be calculated: NO(K,community) and NO(Kw,community). For all these indices, the variance can be calculated and formulae for this are given. To give examples of the new indices in use, we apply them to a coastal fish dataset and a sand-dune plant dataset. The former exhibits considerable non-normality, emphasising the need for kernel-based indices. Accordingly, there was a considerable difference in index values, with those for an index based on a normal distribution being significantly higher than those from an index which, being based on kernel fitting, is not biased by an assumption for the distribution. The NO(K) values were ecologically consistent for the fish species concerned, varying from 0.02 to 0.53. The sand-dune plant data also showed a wide range of overlap values. Interestingly, the least overlap was between two graminoids, which would have been placed in the same functional group in the coarse classification often used in functional-type/ecosystem-function work.

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Year:  2005        PMID: 16001221     DOI: 10.1007/s00442-005-0151-z

Source DB:  PubMed          Journal:  Oecologia        ISSN: 0029-8549            Impact factor:   3.225


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