open access publication

Article, 2024

A workflow for standardizing the analysis of highly resolved vessel tracking data

ICES Journal of Marine Science, ISSN 1054-3139, Volume 81, 2, Pages 390-401, 10.1093/icesjms/fsad209

Contributors

Mendo T. 0000-0003-4397-2064 (Corresponding author) [1] Mujal-Colilles A. 0000-0003-0139-3849 (Corresponding author) [2] Stounberg J. [3] Glemarec G. 0000-0003-1801-3179 [3] Egekvist J. 0000-0001-9619-1443 [3] Mugerza E. 0000-0003-4175-8750 [4] Rufino M. 0000-0002-0734-7491 [5] Swift R. [1] James M. 0000-0002-7182-1725 [1]

Affiliations

  1. [1] University of St Andrews
  2. [NORA names: United Kingdom; Europe, Non-EU; OECD];
  3. [2] Universitat Politècnica de Catalunya
  4. [NORA names: Spain; Europe, EU; OECD];
  5. [3] Technical University of Denmark
  6. [NORA names: DTU Technical University of Denmark; University; Denmark; Europe, EU; Nordic; OECD];
  7. [4] Basque Research and Technology Alliance (BRTA)
  8. [NORA names: Spain; Europe, EU; OECD];
  9. [5] Universidade de Lisboa
  10. [NORA names: Portugal; Europe, EU; OECD]

Abstract

Knowledge on the spatial and temporal distribution of the activities carried out in the marine environment is key to manage available space optimally. However, frequently, little or no information is available on the distribution of the largest users of the marine space, namely fishers. Tracking devices are being increasingly used to obtain highly resolved geospatial data of fishing activities, at intervals from seconds to minutes. However, to date no standardized method is used to process and analyse these data, making it difficult to replicate analysis. We develop a workflow to identify individual vessel trips and infer fishing activities from highly resolved geospatial data, which can be applied for large-scale fisheries, but also considers nuances encountered when working with small-scale fisheries. Recognizing the highly variable nature of activities conducted by different fleets, this workflow allows the user to choose a path that best aligns with the particularities in the fishery being analysed. A new method to identify anchoring sites for small-scale fisheries is also presented. The paper provides detailed code used in each step of the workflow both in R and Python language to widen the application of the workflow in the scientific and stakeholder communities and to encourage its improvement and refinement in the future.

Keywords

fisheries management, geospatial data, marine spatial planning, small-scale fisheries

Funders

  • International Council for the Exploration of the Sea
  • European Regional Development Fund
  • Ministerio de Ciencia e Innovación
  • Interreg Atlantic Area Programme
  • Generalitat de Catalunya

Data Provider: Elsevier