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• W4310712114 startingPage "109759" @default.
• W4310712114 abstract "Climate change is an important driving force affecting species distribution, so quantifying the influences of climate change on species distributions is necessary for effective fishery management. To identify the geographical distribution pattern and future potential suitable habitat area of fishes in the Yellow and Bohai Seas (YBS), we built ensemble models of spatial distribution for 22 important fish species using 3185 valid distributional records and 9 environmental variables extracted from multiple databases. The constructed ensemble models showed high accuracy with mean AUC, Kappa and TSS values of 0.97, 0.82 and 0.84. Salinity and temperature proximal to the seabed were the main environmental factors affecting the distribution of fishes. Presently, the number of important fish species (NIFS) tends to be low in the Bohai Sea and high in the Yellow Sea. Future projections indicated that there would be obvious interspecific differences in the geographical distribution of fishes, and the number of species with range contractions is predicted to be greater than that of range expansions. Coastal fishes and cold temperate fishes are predicted to narrow their occupied areas. In the future, the NIFS in the YBS is expected to increase overall. Spatially, sporadic areas in the central and southern Yellow Sea will have a reduced NIFS, while the Bohai Sea, coastal waters near the southern Shandong Peninsula and the northern East China Sea may experience increased NIFS. Our results provide a theoretical basis for predicting the climate-driven range shifts of fishes in one of the world’s most heavily impacted marine ecosystems, that can be extended to develop climate-adaptive management strategies." @default.
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• W4310712114 date "2023-02-01" @default.
• W4310712114 modified "2023-10-05" @default.
• W4310712114 title "Ensemble projections of fish distribution in response to climate changes in the Yellow and Bohai Seas, China" @default.
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• W4310712114 doi "https://doi.org/10.1016/j.ecolind.2022.109759" @default.
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