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Constructing logbook-like statistics for coastal fisheries using coastal surveillance radar and fish market data

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  • Chang, Shui-Kai

Abstract

As catch and effort statistics including fishing time and location are essential for producing abundance indices for utilized fish stocks, fishing states are encouraged under the FAO Code of Conduct for Responsible Fisheries to collect and maintain such statistics. However, for coastal fisheries (including artisanal fisheries) that are mainly composed of small-sized vessels which are usually too numerous to monitor, fisheries statistics collection systems are often either lacking or of insufficient quality (e.g. incomplete or inaccurate). Vessel monitoring system (VMS) data are commonly used to construct or improve estimation of fishing effort and fishing location in large-scale fisheries. Most coastal fisheries lack VMS but their countries do have coastal surveillance radar systems (CSRS) for security and enforcement purposes. This study illustrates and recommends opportunistic use of CSRS data to provide similar scientific benefits to VMS data for coastal fisheries. CSRS in combination with market landings data can construct logbook-like catch and effort statistics. This study introduces a method and demonstrates its usefulness for scientific research and management purposes, including the potential to obtain a higher accuracy and precision, particularly for fishing location and catch amount. Limitations of the CSRS data and challenges to managers involved in its application are also discussed.

Suggested Citation

  • Chang, Shui-Kai, 2014. "Constructing logbook-like statistics for coastal fisheries using coastal surveillance radar and fish market data," Marine Policy, Elsevier, vol. 43(C), pages 338-346.
    • Handle: RePEc:eee:marpol:v:43:y:2014:i:c:p:338-346
    DOI: 10.1016/j.marpol.2013.07.003
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    References listed on IDEAS

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    Cited by:

    1. Tommaso Russo & Lorenzo D'Andrea & Antonio Parisi & Stefano Cataudella, 2014. "VMSbase: An R-Package for VMS and Logbook Data Management and Analysis in Fisheries Ecology," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-18, June.

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