Author: R.A. Laird 1
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  • 1 Department of Biology, Queen's University Kingston, Ontario, K7L 3N6, Canada
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Several different stochastic models of niche apportionment have been proposed to explain the structure of species' relative abundance patterns within communities. Here I deal with the converse issue, i.e., whether it is possible to infer past niche apportionment processes from current relative abundance patterns. Using Monte Carlo methods, I constructed relative abundance patterns for many .communities. of four to 28 species based on five common niche apportionment models (Dominance Decay, Dominance Preemption, MacArthur Fraction, Random Assortment and Random Fraction). The relative abundance patterns of these individual communities were compared by a best-fit test against those expected to emerge over many replications of the different models. The proportion of instances that the past structuring processes were correctly identified was generally quite low for four-species communities, and was inconsistent across niche apportionment models. For 28-species communities, the probability of correct model identification was greater for all models, but remained inconsistent across models (indicating a persistent identification bias). In a second analysis, I constructed relative abundance distributions for many four-species communities, each composed of seven replicates. In this example (the structure of which was chosen to mirror that of a recently published study), the probability of correct identification was greater than for unreplicated four-species communities, but did not approach 1.0 for any model, and was once again inconsistent across models. These results indicate that in many cases it is not possible to elucidate past ecological structuring processes from current relative abundance patterns alone. Attempts to use such patterns to distinguish among different types of niche apportionment should therefore be confined to situations with very high species richness and/or community replication, the specifics of which must be assessed on a case-by-case basis.

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