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author:

Tong, R. (Tong, R..) [1] | Davies, A.J. (Davies, A.J..) [2] | Yesson, C. (Yesson, C..) [3] | Yu, J. (Yu, J..) [4] | Luo, Y. (Luo, Y..) [5] | Zhang, L. (Zhang, L..) [6] | Burgos, J.M. (Burgos, J.M..) [7]

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Scopus

Abstract:

Species distribution models (SDMs) are useful tools for describing and predicting the distribution of marine species in data-limited environments. Outputs from SDMs have been used to identify areas for spatial management, analyzing trawl closures, quantitatively measuring the risk of bottom trawling, and evaluating protected areas for improving conservation and management. Cold-water corals are globally distributed habitat-forming organisms that are vulnerable to anthropogenic impacts and climate change, but data deficiency remains an ongoing issue for the effective spatial management of these important ecosystem engineers. In this study, we constructed 11 environmental seabed variables at 500 m resolution based on the latest multi-depth global datasets and high-resolution bathymetry. An ensemble species distribution modeling method was used to predict the global habitat suitability for 10 widespread cold-water coral species, namely, 6 Scleractinian framework-forming species and 4 large gorgonian species. Temperature, depth, salinity, terrain ruggedness index, carbonate saturation state, and chlorophyll were the most important factors in determining the global distributions of these species. The Scleractinian Madrepora oculata showed the widest niche breadth, while most other species demonstrated somewhat limited niche breadth. The shallowest study species, Oculina varicosa, had the most distinctive niche of the group. The model outputs from this study represent the highest-resolution global predictions for these species to date and are valuable in aiding the management, conservation, and continued research into cold-water coral species. Copyright © 2023 Tong, Davies, Yesson, Yu, Luo, Zhang and Burgos.

Keyword:

benthic habitats biogeography cold-water corals deep sea ecological niche ensemble modeling habitat suitability model

Community:

  • [ 1 ] [Tong R.]Department of Transportation, Fujian University of Technology, Fuzhou, China
  • [ 2 ] [Tong R.]Institute of Smart Marine and Engineering, Fujian University of Technology, Fuzhou, China
  • [ 3 ] [Davies A.J.]Department of Biological Sciences, University of Rhode Island, Kingston, RI, United States
  • [ 4 ] [Davies A.J.]Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, United States
  • [ 5 ] [Yesson C.]Institute of Zoology, Zoological Society of London, London, United Kingdom
  • [ 6 ] [Yu J.]The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China
  • [ 7 ] [Luo Y.]The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China
  • [ 8 ] [Zhang L.]The Academy of Digital China (Fujian), Fuzhou University, Fuzhou, China
  • [ 9 ] [Burgos J.M.]Demersal Division, Marine and Freshwater Research Institute, Hafnarfjörður, Iceland

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Source :

Frontiers in Marine Science

ISSN: 2296-7745

Year: 2023

Volume: 10

2 . 8

JCR@2023

2 . 8 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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