Integrated assessment of the spatial distribution and structural dynamics of deep benthic marine communities
Type | Article | ||||||||||||
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Date | 2020-04 | ||||||||||||
Language | English | ||||||||||||
Author(s) | Jansen Jan1, 2, Dunstan Piers K.3, Hill Nicole A.1, Koubbi Philippe4, 5, Melbourne‐thomas Jessica2, 6, Causse Romain7, Johnson Craig R.1 | ||||||||||||
Affiliation(s) | 1 : Institute for Marine and Antarctic Studies (IMAS) University of Tasmania Hobart, Australia 2 : Australian Antarctic Division Kingston, Australia 3 : CSIRO Oceans and Atmosphere Hobart, Australia 4 : UFR 918 Terre Environnement Biodiversité. Sorbonne Université. Paris, France 5 : IFREMER, Channel and North Sea Fisheries Research Unit Boulogne‐sur‐Mer, France 6 : Antarctic Climate & Ecosystem Cooperative Research Centre (ACE CRC) University of Tasmania Hobart ,Australia 7 : Unité Biologie des Organismes et Ecosystèmes Aquatiques (BOREA) Muséum National d’Histoire Naturelle Sorbonne Université Université de Caen Normandie Université des Antilles CNRS IRD Paris ,France |
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Source | Ecological Applications (1051-0761) (Wiley), 2020-04 , Vol. 30 , N. 3 , P. e02065 (16p.) | ||||||||||||
DOI | 10.1002/eap.2065 | ||||||||||||
WOS© Times Cited | 2 | ||||||||||||
Keyword(s) | Antarctica, continental shelf, deep sea, ecosystem dynamic, ecosystem structure, qualitative network model, Southern Ocean, spatial model, species archetype model, upper slope | ||||||||||||
Abstract | Characterising the spatial distribution and variation of species communities and validating these characteristics with data from the field are key elements for an ecosystem‐based approach to management. However, models of species distributions that yield community structure are usually not linked to models of community dynamics, constraining understanding and management of the ecosystem, particularly in data‐poor regions. Here we use a qualitative network model to predict changes in Antarctic benthic community structure between major marine habitats characterised largely by seafloor depth and slope, and use multivariate mixture models of species distributions to validate the community dynamics. Further, we then assess how future increases in primary production associated with anticipated loss of sea‐ice may affect the ecosystem. Our study shows how both spatial and structural features of ecosystems in data‐poor regions can be analysed and possible futures assessed, with direct relevance for ecosystem‐based management. |
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