Developing an intermediate-complexity projection model for China’s fisheries: A case study of small yellow croaker (<i>Larimichthys polyactis</i>) in the Haizhou Bay, China

Ming Sun; Yunzhou Li; Yiping Ren; Yong Chen

doi:10.1007/s13131-021-1793-3

Volume 40 Issue 8

Aug. 2021

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Ming Sun, Yunzhou Li, Yiping Ren, Yong Chen. Developing an intermediate-complexity projection model for China’s fisheries: A case study of small yellow croaker (Larimichthys polyactis) in the Haizhou Bay, China[J]. Acta Oceanologica Sinica, 2021, 40(8): 108-118. doi: 10.1007/s13131-021-1793-3

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Ming Sun, Yunzhou Li, Yiping Ren, Yong Chen. Developing an intermediate-complexity projection model for China’s fisheries: A case study of small yellow croaker (Larimichthys polyactis) in the Haizhou Bay, China[J]. Acta Oceanologica Sinica, 2021, 40(8): 108-118. doi: 10.1007/s13131-021-1793-3

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Developing an intermediate-complexity projection model for China’s fisheries: A case study of small yellow croaker (Larimichthys polyactis) in the Haizhou Bay, China

doi: 10.1007/s13131-021-1793-3

Ming Sun^{1, 2, 3},
Yunzhou Li^{1, 2, 3},
Yiping Ren^{1, 3, 4
,
,},
Yong Chen²

1.
Fisheries College, Ocean University of China, Qingdao 266003, China
2.
School of Marine Sciences, University of Maine, Maine 04469, USA
3.
Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, China
4.
Laboratory for Marine Fisheries Science and Food Production Processes, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China

Funds: The Fund of the China Scholarship Council under contract Nos 201806330043 and 201806330042; the Marine Science and Technology Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao) under contract No. 2018SDKJ0501-2; the National Key Research and Development Program of China under contract Nos 2018YFD0900904 and 2018YFD0900906.

More Information

Corresponding author: Email: renyip@ouc.edu.cn
Received Date: 2020-05-13
Accepted Date: 2020-09-29

Available Online: 2021-07-07

Publish Date: 2021-08-31

Abstract

Abstract

Projection models are commonly used to evaluate the impacts of fishing. However, previously developed projection tools were not suitable for China’s fisheries as they are either overly complex and data-demanding or too simple to reflect the realistic management measures. Herein, an intermediate-complexity projection model was developed that could adequately describe fish population dynamics and account for management measures including mesh size limits, summer closure, and spatial closure. A two-patch operating model was outlined for the projection model and applied to the heavily depleted but commercially important small yellow croaker (Larimichthys polyactis) fishery in the Haizhou Bay, China, as a case study. The model was calibrated to realistically capture the fisheries dynamics with hindcasting. Three simulation scenarios featuring different fishing intensities based on status quo and maximum sustainable yield (MSY) were proposed and evaluated with projections. Stochastic projections were additionally performed to investigate the influence of uncertainty associated with recruitment strengths and the implementation of control targets. It was found that fishing at F_MSY level could effectively rebuild the depleted stock biomass, while the stock collapsed rapidly in the status quo scenario. Uncertainty in recruitment and implementation could result in variabilities in management effects; but they did not much alter the management effects of the F_MSY scenario. These results indicate that the lack of science-based control targets in fishing mortality or catch limits has hindered the achievement of sustainable fisheries in China. Overall, the presented work highlights that the developed projection model can promote the understanding of the possible consequences of fishing under uncertainty and is applicable to other fisheries in China.
- two-patch operating model,
- simulation,
- maximum sustainable yield,
- control targets,
- uncertainty

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References(50)

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