Impacts of data sources on the predictive performance of species distribution models: a case study for <i>Scomber japonicus</i> in the offshore waters southern Zhejiang, China

Wen Ma; Ling Ding; Xinghua Wu; Chunxia Gao; Jin Ma; Jing Zhao

doi:10.1007/s13131-024-2387-7

Volume 42 Issue 12

Dec. 2024

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Article Navigation > Acta Oceanologica Sinica > 2024 > 43(12): 113-122

Wen Ma, Ling Ding, Xinghua Wu, Chunxia Gao, Jin Ma, Jing Zhao. Impacts of data sources on the predictive performance of species distribution models: a case study for Scomber japonicus in the offshore waters southern Zhejiang, China[J]. Acta Oceanologica Sinica, 2024, 43(12): 113-122. doi: 10.1007/s13131-024-2387-7

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Wen Ma, Ling Ding, Xinghua Wu, Chunxia Gao, Jin Ma, Jing Zhao. Impacts of data sources on the predictive performance of species distribution models: a case study for Scomber japonicus in the offshore waters southern Zhejiang, China[J]. Acta Oceanologica Sinica, 2024, 43(12): 113-122. doi: 10.1007/s13131-024-2387-7

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Impacts of data sources on the predictive performance of species distribution models: a case study for Scomber japonicus in the offshore waters southern Zhejiang, China

doi: 10.1007/s13131-024-2387-7

Wen Ma^{1, 2},
Ling Ding³,
Xinghua Wu⁴,
Chunxia Gao^{1, 5},
Jin Ma^{1
,
,},
Jing Zhao¹

1.
College of Marine Living Resource Sciences and Management, Shanghai 201306, China
2.
College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
3.
Shanghai Investigation, Design & Research Institute Co., Ltd, Shanghai 200335, China
4.
China Three Gorges Corporation, Wuhan 430010, China
5.
The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Shanghai Ocean University, Shanghai 201306, China

Funds: The Research Project of China Yangtze River Three Gorges Group Limited under contract No. 201903173; the Zhejiang Mariculture Research Institute of China under contract No. 325000.

More Information

Corresponding author: jma@shou.edu.cn
Received Date: 2024-04-28
Accepted Date: 2024-09-12

Available Online: 2025-01-11

Publish Date: 2024-12-01

Abstract

Abstract

As our understanding of ecology deepens and modeling techniques advance, species distribution models have grown increasingly sophisticated, enhancing both their fitting and predictive capabilities. However, the dependability of predictive accuracy remains a critical issue, as the precision of these predictions largely hinges on the quality of the base data. We developed models using both field survey and remote sensing data from 2016 to 2020 to evaluate the impact of different data sources on the accuracy of predictions for Scomber japonicus distributions. Our research findings indicate that the variability of water temperature and salinity data from field suvery is significantly greater than that from remote sensing data. Within the same season, we found that the relationship between the abundance of S. japonicus and environmental factors varied significantly depending on the data source. Models using field survey data were able to more accurately reflect the complex relationships between resource distribution and environmental factors. Additionally, in terms of model predictive performance, models based on field survey data demonstrated greater accuracy in predicting the abundance of S. japonicus compared to those based on remote sensing data, allowing for more accurate mastery of their spatial distribution characteristics. This study highlights the significant impact of data sources on the accuracy of species distribution models and offers valuable insights for fisheries resources management.
- species distribution model,
- remote sensing data,
- field survey data,
- predictive performance,
- offshore waters southern Zhejiang,
- Scomber japonicus

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References(46)

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