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  4. An ensemble analysis to predict future habitats of striped marlin (Kajikia audax) in the North Pacific Ocean
 
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An ensemble analysis to predict future habitats of striped marlin (Kajikia audax) in the North Pacific Ocean

Journal
ICES Journal of Marine Science
Journal Volume
70
Journal Issue
5
Pages
1013-1022
Date Issued
2013
Author(s)
Su, N.-J.
Sun, C.-L.
Punt, A.E.
Yeh, S.-Z.
Dinardo, G.
YI-JAY CHANG  
DOI
10.1093/icesjms/fss191
URI
http://www.scopus.com/inward/record.url?eid=2-s2.0-84883307763&partnerID=MN8TOARS
http://scholars.lib.ntu.edu.tw/handle/123456789/380288
Abstract
Su, N.-J., Sun, C.-L., Punt, A. E., Yeh, S.-Z., DiNardo, G., and Chang, Y.-J. 2013. An ensemble analysis to predict future habitats of striped marlin (Kajikia audax) in the North Pacific Ocean. - ICES Journal of Marine Science, 70: 1013-1022.Striped marlin is a highly migratory species distributed throughout the North Pacific Ocean, which shows considerable variation in spatial distribution as a consequence of habitat preference. This species may therefore shift its range in response to future changes in the marine environment driven by climate change. It is important to understand the factors determining the distribution of striped marlin and the influence of climate change on these factors, to develop effective fisheries management policies given the economic importance of the species and the impact of fishing. We examined the spatial patterns and habitat preferences of striped marlin using generalized additive models fitted to data from longline fisheries. Future distributions were predicted using an ensemble analysis, which represents the uncertainty due to several global climate models and greenhouse gas emission scenarios. The increase in water temperature driven by climate change is predicted to lead to a northward displacement of striped marlin in the North Pacific Ocean. Use of a simple predictor of water temperature to describe future distribution, as in several previous studies, may not be robust, which emphasizes that variables other than sea surface temperatures from bioclimatic models are needed to understand future changes in the distribution of large pelagic species. © 2013 © 2013 International Council for the Exploration of the Sea. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Subjects
global climate models; sea surface temperature; spatial distribution; thermal preferences
SDGs

[SDGs]SDG13

[SDGs]SDG14

Other Subjects
climate modeling; ensemble forecasting; fishery management; fishery modeling; fishery policy; habitat selection; habitat type; migratory behavior; pelagic fish; perciform; population distribution; prediction; spatial distribution; temperature effect; water temperature; Pacific Ocean; Pacific Ocean (North)
Type
journal article

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