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Jin P, Zhang Y, Du Y, Chen X, Kindong R, Xue H, Chai F, Yu W. Eddy impacts on abundance and habitat distribution of a large predatory squid off Peru. Mar Environ Res 2024; 195:106368. [PMID: 38286075 DOI: 10.1016/j.marenvres.2024.106368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/14/2024] [Accepted: 01/15/2024] [Indexed: 01/31/2024]
Abstract
The pelagic cephalopod species jumbo flying squid Dosidicus gigas is ecologically and economically important in the Humboldt ecosystem off Peru. This squid species is sensitive to oceanic environmental changes, and regional oceanographical variability is one of the important factors driving its redistribution. Off Peruvian waters, mesoscale eddies are ubiquitous and dominate the biogeochemical processes in this region. This study first explored the role of mesoscale eddies in regulating the environments and their effects on the abundance and habitat distribution of D. gigas off Peru by analyzing squid distribution in eddy-centric coordinates and building a habitat suitability index (HSI) model. Results indicated that the abundance and habitat distribution of D. gigas in mesoscale eddies varied across months, with significant differences observed between anticyclonic eddies (AE) and cyclonic eddies (CE). In AE, a higher abundance and proportion of suitable habitat occurred. While in CE, the abundance was relatively low and the suitable habitat was relatively less, concentrating at the periphery of CE. Based on the HSI model results, sea surface temperature (SST) and 50 m water temperature (T50m) in AE were more favorable for D. gigas, which was 0.3-0.5 °C lower than that in CE, yielding high-quality habitats and higher abundance of D. gigas. Our findings emphasized that mesoscale eddies have a significant impact on water temperature conditions and nutrient concentrations off Peruvian waters.
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Affiliation(s)
- Pengchao Jin
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
| | - Yang Zhang
- State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, Zhejiang, China
| | - Yanlin Du
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
| | - Xinjun Chen
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China
| | - Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China
| | - Huijie Xue
- State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiamen, China
| | - Fei Chai
- State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiamen, China
| | - Wei Yu
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai 201306, China.
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Kindong R, Wu F, Sarr O, Zhu J. A simulation-based option to assess data-limited fisheries off West African waters. Sci Rep 2023; 13:15290. [PMID: 37714923 PMCID: PMC10504299 DOI: 10.1038/s41598-023-42521-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023] Open
Abstract
Most sophisticated stock assessment models often need a large amount of data to assess fish stocks, yet this data is often lacking for most fisheries worldwide, resulting in the increasing demand for data-limited stock assessment methods. To estimate fish stock status, one class of these data-limited methods uses simply catch time series data and, in other instances, life history information or fishery characteristics. These catch-only methods (COMs) built differently are known to make assumptions about changes in fishing effort and may perform differently under various fishing scenarios. As a case study, this paper used European anchovy (Engraulis encrasicolus) caught in the northwest African waters, though very economically and ecologically important, but still unassessed. Our study investigated the performance of five COMs under different fishing scenarios using as a reference the life-history information of the European anchovy captured in this region of the Atlantic. Hence, the present study developed a simulation approach to evaluate the performance of the five COMs in inferring the stock biomass status (B/BMSY) with consideration of different fishing scenarios under prior information true to anchovy. All five COMs mostly underestimated B/BMSY throughout the simulation period, especially under constant fishing mortality, and in the last five years of the simulation during all fishing scenarios. Overall, these COMs were generally poor classifiers of stock status, however, the state-space COM (SSCOM) generally performed better than the other COMs as it showed possibilities of recovering an overfished stock. When these methods were explored using actual anchovy catch data collected in the northwest African waters, SSCOM yielded results that were deferred from the other COMs. This study being the first to assess this species' stock in this area using a suite of COMs, presents more insights into the species stock status, and what needs to be considered before scientifically putting in place management measures of the stock in the area.
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Affiliation(s)
- Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China.
- Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai, 201306, China.
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, 201306, China.
- National Engineering Research Centre for Oceanic Fisheries, Shanghai Ocean University, Shanghai, China.
| | - Feng Wu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China
- Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai, 201306, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, 201306, China
- National Engineering Research Centre for Oceanic Fisheries, Shanghai Ocean University, Shanghai, China
| | - Ousmane Sarr
- College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China
| | - Jiangfeng Zhu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, 201306, China.
- Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai, 201306, China.
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, 201306, China.
- National Engineering Research Centre for Oceanic Fisheries, Shanghai Ocean University, Shanghai, China.
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Kindong R, Sarr O, Wang J, Xia M, Wu F, Dai L, Tian S, Dai X. Size distribution patterns of silky shark Carcharhinus falciformis shaped by environmental factors in the Pacific Ocean. Sci Total Environ 2022; 850:157927. [PMID: 35963405 DOI: 10.1016/j.scitotenv.2022.157927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 08/05/2022] [Accepted: 08/05/2022] [Indexed: 06/15/2023]
Abstract
Commercial fisheries, especially pelagic longline fisheries targeting tuna and/or swordfish, often land silky sharks (Carcharhinus falciformis), which are currently listed as vulnerable by the International Union for Conservation of Nature (IUCN). Due to increasing fishing effort and the fact that they overlap in habitat with target species, the population trend of silky sharks is declining worldwide. Understanding their relationships with environmental variables that lead to their capture by fisheries is critical for their management and conservation. Nevertheless, little is known about their size distribution in relation to environmental variables in the Pacific Ocean. Using data from the Chinese Observer Tuna Longline fishery from 2010 to 2020, this study developed a species distribution model (SDM) to analyze the relationships between silky shark size distribution patterns and environmental variables and spatio-temporal variability at fishing locations. Observed sizes ranged from 36 to 269 cm fork length (FL). The final model suggests that sea surface temperature (SST), primary production (photosynthetically available radiation, PAR), and ocean surface winds were the key environmental variables shaping size distribution patterns of silky sharks in the Pacific. A high proportion of larger silky sharks has been predicted in areas associated with productive upwelling systems. In addition, the model predicted that larger specimens (>140 cm FL) occur near the equator, and smaller specimens farther from the equator but still in tropical regions. Two regions in the eastern Pacific (the coastal upwelling area off northern Peru and the waters around the Galapagos Islands) seem to be important locations for larger specimens. The size distribution patterns of silky sharks in relation to environmental variables presented in this study illustrate how this species segregates spatially and temporally and presents potential habitat preference areas. The information obtained in the present study is critical in the quest for management and conservation of menaced species such as the silky shark.
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Affiliation(s)
- Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China.
| | - Ousmane Sarr
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
| | - Jiaqi Wang
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China
| | - Meng Xia
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China
| | - Feng Wu
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China
| | - Libin Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
| | - Siquan Tian
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China.
| | - Xiaojie Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China; Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China; Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China; Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China
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Kindong R, Xia M, Pandong NA, Sarr O, Wu F, Tian S, Dai X. All we know about the crocodile shark (Pseudocarcharias kamoharai): Providing information to improve knowledge of this species. J Nat Conserv 2021. [DOI: 10.1016/j.jnc.2021.126039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Wu F, Kindong R, Dai X, Sarr O, Zhu J, Tian S, Li Y, Nsangue BTN. Aspects of the reproductive biology of two pelagic sharks in the eastern Atlantic Ocean. J Fish Biol 2020; 97:1651-1661. [PMID: 32892380 DOI: 10.1111/jfb.14526] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 09/02/2020] [Accepted: 09/03/2020] [Indexed: 06/11/2023]
Abstract
This study used data provided by the Chinese Longline Fishery Scientific Observer Programme from the tropical eastern Atlantic Ocean to estimate the reproductive parameters of the blue shark (Prionace glauca) and crocodile shark (Pseudocarcharias kamoharai). Sizes ranged from 80 to 298 cm fork length (FL) for blue sharks and from 48 to 99 cm FL for crocodile sharks. Sexual segregation was observed during different months for both sharks. The sex ratio for blue sharks was 1.38 F:1 M, and 1 F:2.79 M for crocodile sharks. The size of adult blue sharks ranged from 144 to 280 cm for males and from 174 to 298 cm for females; and that of crocodile sharks from 63 to 97 cm for males and 78-99 cm for females. The size at 50% of maturity for blue sharks was estimated at 191.7 cm FL for females and 197.5 cm FL for males, and that of crocodile sharks was assessed at 84.9 cm FL for females and 78.5 cm FL for males. Most sexually matured females were pregnant; their means were 207.2 ± 16.4 cm FL for blue sharks and 89.4 ± 4.3 cm FL for crocodile sharks. Mature sizes for both species were significantly different among months. Embryonic sizes also varied widely among months for crocodile sharks, but a slight change was recorded for those of blue sharks. The observed mean size at birth and litter size were 34.5 cm FL and 37 ± 12 for the blue sharks, and that of the crocodile sharks, 39.5 cm FL and a dominant four embryos in the uterus. Due to the observed increasing catch trend of blue sharks and the slow reproductive cycle of crocodile sharks, this study presents the need of implementing conservation measures to ensure the sustainability of both species in their habitat.
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Affiliation(s)
- Feng Wu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Xiaojie Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Ousmane Sarr
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Jiangfeng Zhu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Siquan Tian
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Yunkai Li
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observing and Experimental Station of Oceanic Fisheries Resources and Environment, Ministry of Agriculture and Rural Affairs, Shanghai, China
- Key Laboratory of Oceanic Fisheries Exploration, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Bruno T N Nsangue
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
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Kindong R, Wu J, Gao C, Dai L, Tian S, Dai X, Chen J. Seasonal changes in fish diversity, density, biomass, and assemblage alongside environmental variables in the Yangtze River Estuary. Environ Sci Pollut Res Int 2020; 27:25461-25474. [PMID: 32350839 DOI: 10.1007/s11356-020-08674-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 03/30/2020] [Indexed: 06/11/2023]
Abstract
The present study used multivariate techniques, to analyze the fish species diversity and distribution patterns in order to determine the possible role of environmental parameters as drivers of fish community structure and composition in the Yangtze River Estuary (YRE). This analysis was conducted using data obtained in the YRE from February 2012 to December 2014. Analysis of the catch data showed that species composition, total density, and total biomass varied significantly between stations and seasons. Thirty-eight species belonging to 18 families were collected. Sciaenidae was the most dominant family accounting for 40.8% of total captured specimens. In descending order, Collichthys lucidus, Cynoglossus gracilis, Chaeturichthys stigmatias, and Lophiogobius ocellicauda dominated catches in the YRE. These four species constituted 64.2% of the total catches and showed average dissimilarities of 74.19% between stations and 81.3% between months. The highest number of fish specimens captured was recorded in August 2012 while the highest species richness was observed in December 2013. The mean fish density and biomass for the YRE was 0.35 individuals/m2 and 2.5 g/m2, respectively. The mean density and biomass for the most important and dominant species changed significantly between stations and seasons. Canonical correspondence analysis indicated that salinity and chlorophyll-a were the key variables that structured the fish assemblage in the YRE. High total species density and biomass were recorded in high saline stations (North Branch) of the YRE. This study confirms that most species captured in the YRE needs estuarine conditions to complete their growth and development. Hence, the findings in this study are important to understanding and developing suitable conservation plans for the management of fish resources in the YRE.
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Affiliation(s)
- Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observation and Experimental Station, Oceanic Fisheries Resources and Environment, Ministry of Agriculture, Shanghai, China
- Collaborative Innovation Center for Distant Water Fisheries, Shanghai Ocean University, Shanghai, China
| | - Jianhui Wu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- Shanghai Aquatic Wildlife Conservation Research Center, Shanghai, 200003, China
| | - Chunxia Gao
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observation and Experimental Station, Oceanic Fisheries Resources and Environment, Ministry of Agriculture, Shanghai, China
- Collaborative Innovation Center for Distant Water Fisheries, Shanghai Ocean University, Shanghai, China
| | - Libin Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Siquan Tian
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China.
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China.
- Scientific Observation and Experimental Station, Oceanic Fisheries Resources and Environment, Ministry of Agriculture, Shanghai, China.
- Collaborative Innovation Center for Distant Water Fisheries, Shanghai Ocean University, Shanghai, China.
| | - Xiaojie Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
- National Engineering Research Center for Oceanic Fisheries, Shanghai, China
- Scientific Observation and Experimental Station, Oceanic Fisheries Resources and Environment, Ministry of Agriculture, Shanghai, China
- Collaborative Innovation Center for Distant Water Fisheries, Shanghai Ocean University, Shanghai, China
| | - Jinhui Chen
- Shanghai Aquatic Wildlife Conservation Research Center, Shanghai, 200003, China
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Kindong R, Zhu J, Wu F, Dai L, Dai X, Tian S, Chen Y, Xia M. Evaluation of management procedures for a length-frequency data-limited fishery. Environ Sci Pollut Res Int 2019; 26:15894-15904. [PMID: 30963434 DOI: 10.1007/s11356-019-04521-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 02/06/2019] [Indexed: 06/09/2023]
Abstract
Management procedures (MPs) based on data-limited methods (DLMs) recently developed to give management advices for data-limited stocks worldwide are scarce or yet to be implemented on freshwater species. In this study, case studies (CSs) were developed using length-frequency data (LFD) of common carp species harvested from Dianshan Lake to estimate life-history parameters from existing methods. These CSs were later used to examine their influences when tested with various MPs under scenarios when operating models (OMs) were subjected to observation and estimation uncertainties. The results after management strategy evaluation (MSE) was run for various defined OMs showed that three MPs emerged best for providing managing advice. For high yield to be maintained during short-term periods, MinlenLopt1 suggested the smallest length at full retention (sLFR) to be 42.11 cm; while Slotlim and matlenlim2 suggested that to maintain biomass and stable spawning biomass (SBMSY) and also avoid overfishing from occurring in this fishery, sLFR should be 56.1 cm. Values given by these MPs allowed the removal of species that spawned at least once. Also, life-history parameters derived from CS4 presented the best results, being more reliable in presenting better inputs for effective management of the said fishery.
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Affiliation(s)
- Richard Kindong
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Jiangfeng Zhu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Feng Wu
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Libing Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Xiaojie Dai
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China.
| | - Siquan Tian
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
| | - Yong Chen
- School of Marine Sciences, University of Maine, Orono, ME, 04469, USA
| | - Meng Xia
- College of Marine Sciences, Shanghai Ocean University, Shanghai, China
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