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Ecological Indicators
Article . 2019 . Peer-reviewed
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Article . 2020
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Using species distribution model to predict the impact of climate change on the potential distribution of Japanese whiting Sillago japonica

Authors: Zhixin Zhang; Shengyong Xu; César Capinha; Robbie Weterings; Tianxiang Gao;

Using species distribution model to predict the impact of climate change on the potential distribution of Japanese whiting Sillago japonica

Abstract

Abstract Climate change is one of the most serious global environmental problems and it is of great importance to understand how species respond to climate change. Species distribution models (SDMs) have been regarded as an effective tool to examine the impacts of climate change on species’ potential distribution. In this study, we developed a SDM for a marine fish, the Japanese whiting Sillago japonica by using records of its occurrence and five predictor variables (ocean depth, distance to shore, mean sea surface temperature, salinity, and currents velocity) and predicted its habitat suitability for current conditions and under scenarios of future climates. The SDM suggests that ocean depth, distance to shore, and temperature are the three most important predictor variables determining the distribution of S. japonica. Our SDM accurately predicted the current distribution of the species, with values of true skill statistics and area under the receiver operating characteristic curve above 0.95. Under future climate scenarios, the suitable habitat of S. japonica is predicted to become smaller in size and to shift northward. Differences between climate change scenarios for 2040–2050 and 2090–2100 showed that this species will lose more suitable habitat as climate change progresses over time. Future fisheries management strategies should take this range contraction and associated northward shift into account.

Country
Portugal
Keywords

Range shift, Poleward movement, Species distribution modelling, Climate change, Sillago japonica

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    91
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
91
Top 1%
Top 10%
Top 1%
gold