Progress towards the revised GOODS classification tool
Biogeographical provinces delineated by the Global Open Oceans and Deep Seabed (GOODS; UNESCO, 2009) classification scheme can help safeguard marine biodiversity, support the ecosystem approach and marine spatial management including MPA network design (Rice et al., 2011). Although now adapted for A...
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Format: | Conference Object |
Language: | unknown |
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2017
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Online Access: | https://zenodo.org/record/571070 https://doi.org/10.5281/zenodo.571070 |
Summary: | Biogeographical provinces delineated by the Global Open Oceans and Deep Seabed (GOODS; UNESCO, 2009) classification scheme can help safeguard marine biodiversity, support the ecosystem approach and marine spatial management including MPA network design (Rice et al., 2011). Although now adapted for ABNJ waters >800 m deep (Watling et al., 2013), GOODS lacks ocean-scale biogeographic data from VMEs (Watling et al., 2013). Without improved understanding of biogeography of the fauna that comprise VMEs, it is risky to assume that a protected or managed area is representative of other “similar” VMEs because biogeographically unique areas could be overlooked resulting in a loss of biodiversity. By Month 30 in ATLAS, WP3 aims to deliver a revised GOODS tool for the North Atlantic, focussing specifically on integrating data on VME indicator taxa and deep-sea fish fauna associated with VMEs. Over the last year, appropriately scaled environmental datasets that might resolve biogeographic provinces for the North Atlantic have been compiled from existing sources (see UNESCO, 2009; Watling et al., 2013) but also Esri’s latest geospatial EMU (Ecological Marine Unit) maps of NOAA’s 50-year World Ocean Atlas that clustered the ocean’s physiographic domain at ¼ x ¼ degree resolution resolved over depths. Also being considered is ATLAS’ latest VIKING20 output on MLD (mixed layer depth) and water mass spread. Next steps are to finalise and grid the environmental data in ArcGIS to identify clusters, then validate and refine these with actual VME biodiversity point data compiled in WP3 and species distribution models. Parallel to this revised GOODS activity are statistical modelling activities in WP3 to understand how the interplay between environmental, historic and intrinsic factors determine the biogeography of VME fauna: ATLAS preliminary findings suggest that the life history traits of VME associated fauna can significantly extend or limit biogeographic ranges beyond what was expected purely by environmental factors alone. |
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