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Quantifying Antarctic marine biodiversity and richness using SCAR-MarBIN

Explore the methodology and findings of the SCAR-MarBIN study on Antarctic marine biodiversity, including taxonomic coverage, geographic distribution, and depth distributions. Help is needed for further analysis and modeling.

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Quantifying Antarctic marine biodiversity and richness using SCAR-MarBIN

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  1. Quantifying Antarctic marine biodiversity and richness using SCAR-MarBIN Huw Griffiths Bruno Danis and Andrew Clarke

  2. Overview • Methodology • Taxonomic coverage • Area of interest • Geographic distribution • Phylum level species and sampling distributions • Major groups level species and sampling distributions • Depth distributions • Conclusions • Polar Synthesis Macroscope Update • Plea for help!

  3. Methodology • Cleaning of whole ANTOBIS database • Depth data added to all benthic records using ETOPO2 data • Species counts vs number of stations maps for each major phylum (nematoda, mollusca, cnidaria, echinodermata, chordata, arthropoda & annelida) • Species counts vs number of stations maps for major groups: (fish, birds and mammals, pelagic & benthic) • Depth analysis. Numbers of benthic stations & species by depth

  4. SCAR-MarBIN & RAMS

  5. Areas of interest

  6. SCAR-MarBIN data distribution

  7. All Species

  8. Nematoda

  9. Annelida

  10. Cnidaria

  11. Echinodermata

  12. Mollusca

  13. Chordata

  14. Arthropoda

  15. Summary • Spatial & taxonomic coverage varies greatly between groups • Major taxa “missing”: Sponges, Isopods, Pycnogonids, Bryozoans, Decapoda, Crinoidea & Brachiopoda • Under-sampled & un-sampled areas: W. Weddell Sea, Amundsen Sea, deep sea

  16. Benthic Species

  17. Planktonic Species

  18. Birds & Mammals

  19. Fish

  20. Summary • Bias towards shallow, presence of bases and ship routes • Overall dataset: bird & mammal observations and tags dominate the station analysis • Benthic data drives overall pattern of species richness • Concurrence between benthic data hotspots and station presence • Fish and CPR observation data drive pelagic data patterns

  21. Depth Analysis

  22. Conclusions • Sampling bias's drive many of the patterns • Depth bias, massive under sampling in deep water for benthos • Well sampled areas and groups are suitable for further analysis and predictions………..

  23. Macroscope update • 251 “Bi-polar” species- increased Arctic species list • Physical classification of Ice-Oceans (benthic and pelagic) • First comprehensive Arctic species list • Diversity modelling

  24. Benthic classification Distance From Shallows Temperature Depth & Rugosity

  25. Pelagic classification

  26. Plea for help…….. • New “bi-polar” species coordinator! • New sponge dataset! • More datasets needed for modelling and phylogenetic analysis

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