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Scientific methods to understand fish population dynamics and support sustainable fisheries management

(2021) Water. 13(4).
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Abstract
Fisheries play a significant role in the livelihoods of the world population, while the dependence on fisheries is acute in developing countries. Fisheries are consequently a critical element for meeting the sustainable development (SDG) and FAO goals to reduce poverty, hunger and improve health and well-being. However, 90% of global marine fish stocks are fully or over-exploited. The amount of biologically unsustainable stocks increased from 10% in 1975 to 33% in 2015. Freshwater ecosystems are the most endangered ecosystems and freshwater fish stocks are worldwide in a state of crisis. The continuous fish stock decline indicates that the world is still far from achieving SDG 14 (Life Below Water), FAO’s Blue Growth Initiative goal and SDG 15 (Life on Land, including freshwater systems). Failure to effectively manage world fish stocks can have disastrous effects on biodiversity and the livelihoods and socio-economic conditions of millions of people. Therefore, management strategies that successfully conserve the stocks and provide optimal sustainable yields are urgently needed. However, successful management is only possible when the necessary data are obtained and decision-makers are well informed. The main problem for the management of fisheries, particularly in developing countries, is the lack of information on the past and current status of the fish stocks. Sound data collection and validation methods are, therefore, important. Stock assessment models, which support sustainable fisheries, require life history traits as input parameters. In order to provide accurate estimates of these life history traits, standardized methods for otolith preparation and validation of the rate of growth zone deposition are essential. This review aims to assist researchers and fisheries managers, working on marine and freshwater fish species, in understanding concepts and processes related to stock assessment and population dynamics. Although most examples and case studies originate from developing countries in the African continent, the review remains of great value to many other countries.
Keywords
Geography, Planning and Development, Aquatic Science, Biochemistry, Water Science and Technology, life history traits, methods comparison, population imbalance, stock assessment, SHARK, AGE

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Citation

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MLA
Kidane, Shewit Gebremedhin, et al. “Scientific Methods to Understand Fish Population Dynamics and Support Sustainable Fisheries Management.” Water, vol. 13, no. 4, 2021, doi:10.3390/w13040574.
APA
Kidane, S. G., Bruneel, S., Getahun, A., Anteneh, W., & Goethals, P. (2021). Scientific methods to understand fish population dynamics and support sustainable fisheries management. Water, 13(4). https://doi.org/10.3390/w13040574
Chicago author-date
Kidane, Shewit Gebremedhin, Stijn Bruneel, Abebe Getahun, Wassie Anteneh, and Peter Goethals. 2021. “Scientific Methods to Understand Fish Population Dynamics and Support Sustainable Fisheries Management.” Water 13 (4). https://doi.org/10.3390/w13040574.
Chicago author-date (all authors)
Kidane, Shewit Gebremedhin, Stijn Bruneel, Abebe Getahun, Wassie Anteneh, and Peter Goethals. 2021. “Scientific Methods to Understand Fish Population Dynamics and Support Sustainable Fisheries Management.” Water 13 (4). doi:10.3390/w13040574.
Vancouver
1.
Kidane SG, Bruneel S, Getahun A, Anteneh W, Goethals P. Scientific methods to understand fish population dynamics and support sustainable fisheries management. Water. 2021;13(4).
IEEE
[1]
S. G. Kidane, S. Bruneel, A. Getahun, W. Anteneh, and P. Goethals, “Scientific methods to understand fish population dynamics and support sustainable fisheries management,” Water, vol. 13, no. 4, 2021.
@article{8695413,
  abstract     = {{Fisheries play a significant role in the livelihoods of the world population, while the dependence on fisheries is acute in developing countries. Fisheries are consequently a critical element for meeting the sustainable development (SDG) and FAO goals to reduce poverty, hunger and improve health and well-being. However, 90% of global marine fish stocks are fully or over-exploited. The amount of biologically unsustainable stocks increased from 10% in 1975 to 33% in 2015. Freshwater ecosystems are the most endangered ecosystems and freshwater fish stocks are worldwide in a state of crisis. The continuous fish stock decline indicates that the world is still far from achieving SDG 14 (Life Below Water), FAO’s Blue Growth Initiative goal and SDG 15 (Life on Land, including freshwater systems). Failure to effectively manage world fish stocks can have disastrous effects on biodiversity and the livelihoods and socio-economic conditions of millions of people. Therefore, management strategies that successfully conserve the stocks and provide optimal sustainable yields are urgently needed. However, successful management is only possible when the necessary data are obtained and decision-makers are well informed. The main problem for the management of fisheries, particularly in developing countries, is the lack of information on the past and current status of the fish stocks. Sound data collection and validation methods are, therefore, important. Stock assessment models, which support sustainable fisheries, require life history traits as input parameters. In order to provide accurate estimates of these life history traits, standardized methods for otolith preparation and validation of the rate of growth zone deposition are essential. This review aims to assist researchers and fisheries managers, working on marine and freshwater fish species, in understanding concepts and processes related to stock assessment and population dynamics. Although most examples and case studies originate from developing countries in the African continent, the review remains of great value to many other countries.}},
  articleno    = {{574}},
  author       = {{Kidane, Shewit Gebremedhin and Bruneel, Stijn and Getahun, Abebe and Anteneh, Wassie and Goethals, Peter}},
  issn         = {{2073-4441}},
  journal      = {{Water}},
  keywords     = {{Geography,Planning and Development,Aquatic Science,Biochemistry,Water Science and Technology,life history traits,methods comparison,population imbalance,stock assessment,SHARK,AGE}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{20}},
  title        = {{Scientific methods to understand fish population dynamics and support sustainable fisheries management}},
  url          = {{http://doi.org/10.3390/w13040574}},
  volume       = {{13}},
  year         = {{2021}},
}

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