Quantitative analysis of rudist assemblages: a key for palaeocommunity reconstructions. The Late Barremian record from SE France [An article from: Palaeogeography, Palaeoclimatology, Palaeoecology] Buy on Amazon

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Quantitative analysis of rudist assemblages: a key for palaeocommunity reconstructions. The Late Barremian record from SE France [An article from: Palaeogeography, Palaeoclimatology, Palaeoecology]

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PublisherElsevier
ISBN / ASINB000RQZ9AI
ISBN-13978B000RQZ9A3
AvailabilityAvailable for download now
MarketplaceUnited States  🇺🇸

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This digital document is a journal article from Palaeogeography, Palaeoclimatology, Palaeoecology, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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The present paper addresses the question of rudist assemblages and their interpretation in terms of ecological entities, i.e. communities. Quantitative studies performed on rudist assemblages in the Barremian platform carbonates of the Marseille region (SE France) were based on biological attributes (shell size, shell thickness, packing density, packing index, coverage and shell contribution) and sedimentological attributes from the associated substrate (mud content, grain size and skeletal contribution to the sediment and bed thickness). The studied samples were originally ascribed to four assemblages defined on the basis of semiquantitative data. Contrasting results were obtained from multivariate analysis applied to biological then to biological plus sedimentological data. The latter documents four groups of samples in correspondence with the former assemblages. This grouping refers directly or indirectly to critical attributes of communities: biomass and substrate. Evidence for some taxonomic markers and because the assemblages represent recurrent statistical entities corroborate their interpretation as palaeocommunities. The method proposed here for the reconstruction of rudist palaeocommunities has a potential for unravelling biological assemblages with a low taxonomic resolution.
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