Inferring True Species Richness and Complete Abundance Distribution in Six Reef-fish Communities from Red-sea, Using the Numerical Extrapolation of Incomplete Samplings

Beguinot, Jean (2019) Inferring True Species Richness and Complete Abundance Distribution in Six Reef-fish Communities from Red-sea, Using the Numerical Extrapolation of Incomplete Samplings. Asian Journal of Environment & Ecology, 11 (3). pp. 1-21. ISSN 2456-690X

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Abstract

Even when ecological communities are incompletely sampled (which is most frequent in practice, at least for species-rich assemblages including many rare species), it remains possible to retrieve much more information than could be expected first, by applying numerical extrapolation to incomplete field data. Indeed, recently developed procedures of numerical extrapolation of partial samplings now allow to estimate, with fair accuracy, not only the number of the still unrecorded species but, moreover, the distribution of abundances of each of these unrecorded species, thereby making available the full range of the Species Abundance Distribution, despite dealing with incomplete data only. In turn, this allows to address a series of descriptive and functional aspects of the internal organization of species assemblages, which otherwise would have required disposing of truly exhaustive samplings.

This approach is applied, here, to the previously reported partial samplings of six neighboring reef-fish communities from Tiran Island, Red Sea, with the goal of better understanding their internal organization in relation to their respective environments.

In practice, the numerical completion contributes to avoid erroneous interpretations that would likely stem from considering only the incomplete field data. This point is especially relevant when studying reef-associated communities because accurate understanding of their organization will help guiding and refining at best the protective measures required by these particularly vulnerable communities.

Item Type: Article
Subjects: Eprint Open STM Press > Geological Science
Depositing User: Unnamed user with email admin@eprint.openstmpress.com
Date Deposited: 17 Apr 2023 07:08
Last Modified: 14 Nov 2023 06:27
URI: http://library.go4manusub.com/id/eprint/19

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