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Spatio-Temporal Variations in the Potential Habitat Distribution of Pacific Sardine (Sardinops sagax) in the Northwest Pacific Ocean
Pacific sardine (Sardinops sagax) is a commercially important species and supports important fisheries in the Northwest Pacific Ocean (NPO). Understanding the habitat distribution patterns of Pacific sardine is of great significance for fishing ground prediction and stock management. In this study,...
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Published in: | Fishes 2023-01, Vol.8 (2), p.86 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Pacific sardine (Sardinops sagax) is a commercially important species and supports important fisheries in the Northwest Pacific Ocean (NPO). Understanding the habitat distribution patterns of Pacific sardine is of great significance for fishing ground prediction and stock management. In this study, both single-algorithm and ensemble distribution models were established through the Biomod2 package for Pacific sardine by combining the species occurrence data, sea surface temperature (SST), sea surface height (SSH), sea surface salinity (SSS) and chlorophyll-a concentration (Chla) in the NPO during the main fishing season (June–November) from 2015 to 2020. The results indicated that the key environmental variables affecting the habitat distribution of Pacific sardine were the SSH and SST. The suitable habitat area for Pacific sardine showed significant monthly changes: the suitable habitat range in June was larger than that in July and August, while the suitable habitat range gradually increased from September to November. Furthermore, the monthly geometric centers of habitat suitability index (HSI) for Pacific sardine presented a counterclockwise pattern, gradually moving to the northeast from June, and then turning back to the southwest from August. Compared with single-algorithm models, the ensemble model had higher evaluation metric values and better spatial correspondence between habitat prediction and occurrence records data, which indicated that the ensemble model can provide more accurate prediction and is a promising tool for potential habitat forecasting and resource management. |
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ISSN: | 2410-3888 2410-3888 |
DOI: | 10.3390/fishes8020086 |