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AIS and VMS Ensemble Can Address Data Gaps on Fisheries for Marine Spatial Planning

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  • Pascal Thoya

    (Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Seestraße 15, 18119 Rostock, Germany
    Center for Earth System Research and Sustainability (CEN), Institute for Marine Ecosystem and Fisheries Science, University of Hamburg, 22767 Hamburg, Germany
    Department of Earth and Environmental Sciences, Macquarie University, North Ryde, NSW 2109, Australia
    Kenya Marine and Fisheries Research Institute, P.O. Box 81651, Mombasa 80100, Kenya)

  • Joseph Maina

    (Department of Earth and Environmental Sciences, Macquarie University, North Ryde, NSW 2109, Australia)

  • Christian Möllmann

    (Center for Earth System Research and Sustainability (CEN), Institute for Marine Ecosystem and Fisheries Science, University of Hamburg, 22767 Hamburg, Germany)

  • Kerstin S. Schiele

    (Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Seestraße 15, 18119 Rostock, Germany)

Abstract

Spatially explicit records of fishing activities’ distribution are fundamental for effective marine spatial planning (MSP) because they can help to identify principal fishing areas. However, in numerous case studies, MSP has ignored fishing activities due to data scarcity. The vessel monitoring system (VMS) and the automatic identification system (AIS) are two commonly known technologies used to observe fishing activities. However, both technologies generate data that have several limitations, making them ineffective when used in isolation. Here, we evaluate both datasets’ limitations and strengths, measure the drawbacks of using any single dataset and propose a method for combining both technologies for a more precise estimation of the distribution of fishing activities. Using the Baltic Sea and the North Sea–Celtic Sea regions as case studies, we compare the spatial distribution of fishing effort from International Council for the Exploration of the Seas (ICES) VMS data and global fishing watch AIS data. We show that using either dataset in isolation can lead to a significant underestimation of fishing effort. We also demonstrate that integrating both datasets in an ensemble approach can provide more accurate fisheries information for MSP. Given the rapid expansion of MSP activities globally, our approach can be utilised in data-limited regions to improve cross border spatial planning.

Suggested Citation

  • Pascal Thoya & Joseph Maina & Christian Möllmann & Kerstin S. Schiele, 2021. "AIS and VMS Ensemble Can Address Data Gaps on Fisheries for Marine Spatial Planning," Sustainability, MDPI, vol. 13(7), pages 1-12, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:7:p:3769-:d:525915
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    References listed on IDEAS

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    1. Campbell, Maria S. & Stehfest, Kilian M. & Votier, Stephen C. & Hall-Spencer, Jason M., 2014. "Mapping fisheries for marine spatial planning: Gear-specific vessel monitoring system (VMS), marine conservation and offshore renewable energy," Marine Policy, Elsevier, vol. 45(C), pages 293-300.
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    5. Turner, Rachel A. & Polunin, Nicholas V.C. & Stead, Selina M., 2015. "Mapping inshore fisheries: Comparing observed and perceived distributions of pot fishing activity in Northumberland," Marine Policy, Elsevier, vol. 51(C), pages 173-181.
    6. 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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    Cited by:

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    2. Stelzenmüller, V. & Letschert, J. & Gimpel, A. & Kraan, C. & Probst, W.N. & Degraer, S. & Döring, R., 2022. "From plate to plug: The impact of offshore renewables on European fisheries and the role of marine spatial planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).

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