Habitat Shifts in the Pacific Saury (Cololabis saira) Population in the High Seas of the North Pacific Under Medium-to-Long-Term Climate Scenarios Based on Vessel Position Data and Ensemble Species Distribution Models

Global climate change poses a significant management challenge for vital transboundary resources like the Pacific saury (<i>Cololabis saira</i>). To address this, we developed an innovative framework that uses high-resolution Automatic Identification System (AIS) data and deep learning to define species distribution, which then informs a robust Ensemble Species Distribution Model (ESDM). The model (TSS > 0.89, AUC > 0.97) identifies sea surface temperature (SST) and chlorophyll-a (CHL) as key habitat drivers. Projections under future climate scenarios reveal two critical threats: (1) a continuous northeastward migration of the habitat's centroid, exceeding 400 km by 2100 under a high-emission SSP5-8.5 scenario, and (2) a drastic contraction of highly suitable habitat (suitability > 0.8), shrinking by up to 94% under the high-emission SSP3-7.0 scenario. By directly linking key oceanographic features to these climate-driven risks, this study delivers an essential scientific decision-support tool for management bodies like the North Pacific Fisheries Commission (NPFC) to develop climate-adaptive strategies.

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Publication Details

Journal
Animals
Published
2025-09-28
DOI
https://doi.org/10.3390/ani15192828
Citations
1
Primary Topic
Marine and fisheries research
Type
article
Field-Weighted Citation Impact
1.11
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article

Habitat Shifts in the Pacific Saury (Cololabis saira) Population in the High Seas of the North Pacific Under Medium-to-Long-Term Climate Scenarios Based on Vessel Position Data and Ensemble Species Distribution Models

Jianhua Wang, Lingzhi Li, Ming Gao, Delong Xiang et al.
1 citations
Animals
Marine and fisheries research
1.11
article

Habitat Shifts in the Pacific Saury (Cololabis saira) Population in the High Seas of the North Pacific Under Medium-to-Long-Term Climate Scenarios Based on Vessel Position Data and Ensemble Species Distribution Models

Jianhua Wang, Lingzhi Li, Ming Gao, Delong Xiang, Yuyan Sun, Yang Li, Sisi Huang, Famou Zhang, Hanji Zhu, Heng Zhang
article en
1 citations

Abstract

Global climate change poses a significant management challenge for vital transboundary resources like the Pacific saury (<i>Cololabis saira</i>). To address this, we developed an innovative framework that uses high-resolution Automatic Identification System (AIS) data and deep learning to define species distribution, which then informs a robust Ensemble Species Distribution Model (ESDM). The model (TSS > 0.89, AUC > 0.97) identifies sea surface temperature (SST) and chlorophyll-a (CHL) as key habitat drivers. Projections under future climate scenarios reveal two critical threats: (1) a continuous northeastward migration of the habitat's centroid, exceeding 400 km by 2100 under a high-emission SSP5-8.5 scenario, and (2) a drastic contraction of highly suitable habitat (suitability > 0.8), shrinking by up to 94% under the high-emission SSP3-7.0 scenario. By directly linking key oceanographic features to these climate-driven risks, this study delivers an essential scientific decision-support tool for management bodies like the North Pacific Fisheries Commission (NPFC) to develop climate-adaptive strategies.

AnimalsVol. 15(19)
Dalian Ocean University (CN), Shanghai Ocean University (CN), Anhui Normal University (CN), Chinese Academy of Fishery Sciences (CN), Nanjing University (CN)
Openalex Percentile: Top 19%
Marine and fisheries research
1.11
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