How to Extrapolate Species Abundance Distributions with Minimum Bias When Dealing with Incomplete Species Inventories
Advances in Research · pp. 1–24 · Published 7 Feb 2018
10.9734/AIR/2018/39002Abstract
The total number of co-occurring species (“true species richness”) and the way their respective abundances are distributed (“species abundance distribution”) are two major descriptive traits of species assemblages, in numerical terms. Moreover, beyond mere description, the species abundance distribution may help to infer how ecological factors/constraints are currently shaping the hierarchical structure of species assemblages and thereby, may contribute to shed light upon general traits regarding the functional organisation within communities of species. Unfortunately, both total species richness and exhaustive abundance distributions are not available when dealing with more or less incomplete species inventories, a situation which becomes increasingly frequent with the generalisation of the so-called “quick surveys” and “rapid biodiversity assessments”, which are almost unavoidable when addressing very species-rich assemblages, such as, for example, invertebrate communities. Hence, the necessity of extrapolating with minimum bias (i) the species accumulation curve, thereby deriving reliable estimates of the total species richness of sampled assemblage and (ii) the species abundance distribution to get an exhaustive pattern including the full set of co-occurring species. Previous reports from the same author already dealt with the least-biased extrapolation of species accumulation and the associated derivation of total species richness. Now, an appropriate method is proposed, hereafter, to extrapolate with minimum bias the Species Abundance Distribution itself, when having to deal with only partial species inventories. The method shares in part some theoretical results that had already served to support the extrapolation of species accumulation process. The procedure leading to the extrapolation of the Species Abundance Distribution is first detailed in principle and then put into practice utilising a few examples. Improvements as compared to an earlier attempt at the same goal are discussed.
Cited by 3
Jean Béguinot · Asian Journal of Environment & Ecology · 2018
Roberto Cazzolla Gatti, Nicola Amoroso, Alfonso Monaco · Ecological Modelling · 2020
Jean Béguinot · International Journal of Environment and Climate Change · 2018
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