Diversity Analysis using R

Varghese, Eldho (2022) Diversity Analysis using R. In: ICAR-CMFRI -Winter School on Recent Development in Taxonomic Techniques of Marine Fishes for Conservation and Sustainable Fisheries Management. ICAR-Central Marine Fisheries Research Institute, Kochi, pp. 570-582.

[img] Text
Winter School on Recent Development in Taxonomic Techniques of Marine Fishes for Conservation and Sustainable Fisheries Management_2022_Eldho Varghese.pdf

Download (489kB)
Related URLs:

    Abstract

    A diversity index is a numerical measure that quantifies the number of distinct types (such as species) in a dataset (a community) while also accounting for evolutionary relationships among the individuals distributed throughout those types, such as richness, divergence, and evenness. These indicators are numerical representations of biodiversity in a variety of ways (richness, evenness, and dominance). The amount of distinct species present in a community is referred to as species diversity (a dataset). The effective number of species is the number of equally abundant species required to achieve the same mean proportional species abundance as seen in the dataset under consideration (where all species may not be equally abundant). Using diversity analysis, questions like "how many species are in a sample?" and "how similar are these two samples?" are investigated. The number of species recorded within a region is referred to as alpha diversity, while beta diversity is defined as the number of species not common to the two regions being compared is referred to as beta diversity and gamma diversity is defined as the total number of species within all regions. Species richness, taxonomic or phylogenetic diversity, and/or species evenness are all examples of species diversity. The term "species richness" refers to the number of species present. The genetic link between distinct groupings of animals is taxonomic or phylogenetic diversity. Species evenness measures how evenly the species' abundances are distributed.

    Item Type: Book Section
    Subjects: Marine Fisheries > Fisheries Statistics
    Divisions: CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Subject Area > CMFRI > CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Subject Area > CMFRI-Kochi > Marine Capture > Fishery Resources Assessment Division
    Depositing User: Arun Surendran
    Date Deposited: 29 Jan 2022 07:07
    Last Modified: 11 Feb 2022 04:33
    URI: http://eprints.cmfri.org.in/id/eprint/15731

    Actions (login required)

    View Item View Item