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1000 Titel
  • AIS and VMS Ensemble Can Address Data Gaps on Fisheries for Marine Spatial Planning
1000 Autor/in
  1. Thoya, Pascal |
  2. Maina, Joseph |
  3. Möllmann, Christian |
  4. Schiele, Kerstin S. |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-03-29
1000 Erschienen in
1000 Quellenangabe
  • 13(7):3769
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.3390/su13073769 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • 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.
1000 Sacherschließung
lokal marine spatial planning
lokal fishing effort
lokal data coverage
lokal vessel monitoring system (VMS)
lokal automatic identification system (AIS)
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0001-6725-0301|https://frl.publisso.de/adhoc/uri/TWFpbmEsIEpvc2VwaA==|https://frl.publisso.de/adhoc/uri/TcO2bGxtYW5uLCBDaHJpc3RpYW4=|https://frl.publisso.de/adhoc/uri/U2NoaWVsZSwgS2Vyc3RpbiBTLg==
1000 (Academic) Editor
1000 Label
1000 Förderer
  1. Leibniz-Gemeinschaft |
1000 Fördernummer
  1. -
1000 Förderprogramm
  1. Open Access fund
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Leibniz-Gemeinschaft |
    1000 Förderprogramm Open Access fund
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6432814.rdf
1000 Erstellt am 2022-04-05T12:30:22.130+0200
1000 Erstellt von 317
1000 beschreibt frl:6432814
1000 Bearbeitet von 317
1000 Zuletzt bearbeitet Tue Apr 05 12:31:40 CEST 2022
1000 Objekt bearb. Tue Apr 05 12:31:17 CEST 2022
1000 Vgl. frl:6432814
1000 Oai Id
  1. oai:frl.publisso.de:frl:6432814 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

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