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Fisheries Stock Assessment

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Fish Population Dynamics, Monitoring, and Management

Part of the book series: Fisheries Science Series ((FISHSS))

Abstract

Fisheries stock assessment methods are categorized into two types: survey-based methods, such as acoustic surveys and swept area and line transect methods, and model-based methods, such as virtual population analysis (VPA), surplus production models, DeLury method, and age-structured production models. The advantages and disadvantages of each are briefly reviewed, followed by a more extensive review and discussion of VPA and several extensions of it. Tuned VPA and statistical catch-at-age analysis have been used globally for many different stocks. An example of tuned VPA and its reliability and validity is presented based on experience in Japanese fisheries stock assessment. Stock assessment methods have been developing in two directions—simple and complex models. The former relates to the recent development of management strategy evaluation. An example of the latter approach is integrated analysis. Complex models are used for data-rich stock assessments and simple assessment models for management purposes and data-poor stock assessments.

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Author information

Authors and Affiliations

  1. Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Chiba, Japan

    Kazuhiko Hiramatsu

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  1. Kazuhiko Hiramatsu
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Correspondence to Kazuhiko Hiramatsu .

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Editors and Affiliations

  1. The University of Tokyo, Tokyo, Japan

    Ichiro Aoki

  2. Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan

    Takashi Yamakawa

  3. Japan Fisheries Research and Education Agency, National Research Institute of Fisheries Science, Yokohama, Kanagawa, Japan

    Akinori Takasuka

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© 2018 Springer Japan KK and the Japanese Society of Fisheries Science

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Hiramatsu, K. (2018). Fisheries Stock Assessment. In: Aoki, I., Yamakawa, T., Takasuka, A. (eds) Fish Population Dynamics, Monitoring, and Management. Fisheries Science Series. Springer, Tokyo. https://doi.org/10.1007/978-4-431-56621-2_9

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