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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Main Author: Lea-Anne Henry
Format: Lecture
Language:unknown
Published: Zenodo 2017
Subjects:
Online Access:https://doi.org/10.5281/zenodo.571070
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spelling ftzenodo:oai:zenodo.org:571070 2024-09-15T18:23:05+00:00 Progress towards the revised GOODS classification tool Lea-Anne Henry 2017-04-25 https://doi.org/10.5281/zenodo.571070 unknown Zenodo https://zenodo.org/communities/atlas https://zenodo.org/communities/eu https://doi.org/ https://doi.org/10.5281/zenodo.571070 oai:zenodo.org:571070 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode ATLAS 2nd General Assembly, Mallorca, Spain, 24 - 28 April, 2017 info:eu-repo/semantics/lecture 2017 ftzenodo https://doi.org/10.5281/zenodo.571070 2024-07-26T11:43:33Z 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. Lecture North Atlantic Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description 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.
format Lecture
author Lea-Anne Henry
spellingShingle Lea-Anne Henry
Progress towards the revised GOODS classification tool
author_facet Lea-Anne Henry
author_sort Lea-Anne Henry
title Progress towards the revised GOODS classification tool
title_short Progress towards the revised GOODS classification tool
title_full Progress towards the revised GOODS classification tool
title_fullStr Progress towards the revised GOODS classification tool
title_full_unstemmed Progress towards the revised GOODS classification tool
title_sort progress towards the revised goods classification tool
publisher Zenodo
publishDate 2017
url https://doi.org/10.5281/zenodo.571070
genre North Atlantic
genre_facet North Atlantic
op_source ATLAS 2nd General Assembly, Mallorca, Spain, 24 - 28 April, 2017
op_relation https://zenodo.org/communities/atlas
https://zenodo.org/communities/eu
https://doi.org/
https://doi.org/10.5281/zenodo.571070
oai:zenodo.org:571070
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.571070
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