Habitat for Coilia nasus in southern Zhejiang Province, China, based on a maximum entropy model

As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used fishery survey data from southern Zhejiang coastal waters from 2016 to 2020, employing a maximum entropy model (MaxEnt) to map the habitat distribution of C. nasus. Model performance was evaluated using two metrics: the area under the curve (AUC) of the receiver operating characteristic curve for the training and test sets and true skill statistics (TSS). This study aimed to predict the habitat distribution of C. nasus and explore how environmental variables influence habitat suitability. The results indicated that the models for each season had strong predictive performance, with AUC values above 0.8 and TSS values exceeding 0.6, indicating that they could accurately predict the presence of C. nasus. In the study area, C. nasus was primarily found in brackish or marine waters near bays and coastal islands. Among all environmental factors, salinity (S) and bottom temperature (BOT) had the highest correlations with habitat distribution, although these correlations varied across seasons. The findings of this study provide empirical evidence and a reference for the conservation and management of C. nasus and for the designation of its protected areas.

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Publication Details

Journal
Scientific Reports
Published
2024-08-20
DOI
https://doi.org/10.1038/s41598-024-70044-y
Citations
3
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
2.76

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article

Habitat for Coilia nasus in southern Zhejiang Province, China, based on a maximum entropy model

Song Qin, Jiu Tang, Huawei Zhang, Junfeng Liu et al.
3 citations
Scientific Reports
Species Distribution and Climate Change
2.76
article

Habitat for Coilia nasus in southern Zhejiang Province, China, based on a maximum entropy model

Song Qin, Jiu Tang, Huawei Zhang, Junfeng Liu, Qingsong Fan, Zhixing Huang, Weicheng Liu, Shen Ye, Wei Tang
article en
3 citations

Abstract

As an important fishery resource and endangered species, studying the habitat of Coilia nasus (C. nasus) is highly significant. This study used fishery survey data from southern Zhejiang coastal waters from 2016 to 2020, employing a maximum entropy model (MaxEnt) to map the habitat distribution of C. nasus. Model performance was evaluated using two metrics: the area under the curve (AUC) of the receiver operating characteristic curve for the training and test sets and true skill statistics (TSS). This study aimed to predict the habitat distribution of C. nasus and explore how environmental variables influence habitat suitability. The results indicated that the models for each season had strong predictive performance, with AUC values above 0.8 and TSS values exceeding 0.6, indicating that they could accurately predict the presence of C. nasus. In the study area, C. nasus was primarily found in brackish or marine waters near bays and coastal islands. Among all environmental factors, salinity (S) and bottom temperature (BOT) had the highest correlations with habitat distribution, although these correlations varied across seasons. The findings of this study provide empirical evidence and a reference for the conservation and management of C. nasus and for the designation of its protected areas.

Scientific ReportsVol. 14(1)
Zhejiang Mariculture Research Institute (CN)
National Key Research and Development Program of China
Life below water
Openalex Percentile: Top 9%
Species Distribution and Climate Change
2.76
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