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

Pascal Thoya, Joseph Maina, Christian Möllmann and Kerstin S. Schiele
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Pascal Thoya: Leibniz Institute for Baltic Sea Research Warnemuende (IOW), Seestraße 15, 18119 Rostock, Germany
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

Sustainability, 2021, vol. 13, issue 7, 1-12

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.

Keywords: vessel monitoring system (VMS); automatic identification system (AIS); marine spatial planning; data coverage; fishing effort (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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