Estimating biomass of benthic kelp forest invertebrates from body size and percent cover data
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  • 作者:D. C. Reed ; J. C. Nelson ; S. L. Harrer ; R. J. Miller
  • 刊名:Marine Biology
  • 出版年:2016
  • 出版时间:May 2016
  • 年:2016
  • 卷:163
  • 期:5
  • 全文大小:476 KB
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  • 作者单位:D. C. Reed (1)
    J. C. Nelson (1)
    S. L. Harrer (1)
    R. J. Miller (1)

    1. Marine Science Institute, University of California, Santa Barbara, CA, 93106, USA
  • 刊物类别:Biomedical and Life Sciences
  • 刊物主题:Life Sciences
    Ecology
    Biomedicine
    Oceanography
    Microbiology
    Zoology
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1432-1793
文摘
The inability to compare different measures of species abundance (such as density and percent cover) or different metrics of species biomass (such as wet mass and ash-free dry mass) hampers quantitative studies of community dynamics, trophic interactions, energy flow and biodiversity. This has been especially problematic for the dynamic and highly productive communities inhabiting shallow reefs in temperate seas where varied metrics are commonly used to characterize the abundance and biomass of different suites of species. To facilitate the conversion of abundance data into common metrics of biomass, we developed quantitative relationships between wet mass and length and wet mass and percent cover, and conversion factors for transforming wet mass into dry mass, shell-free and decalcified dry mass, and ash-free dry mass for 84 species of benthic macroinvertebrates common to giant kelp forests in southern California. Regressions for all 84 species were highly significant, and regression fits were very good for most species. Interspecific differences between regression slopes and in the ratios used to convert one metric of mass into another varied by as much as an order of magnitude among species within the same taxonomic group indicating that caution should be used when attempting to estimate biomass using generic relationships or ratios that were developed for other species, even if those species are closely related.

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