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, 1095-9289, Volume 81, 2, Pages 390-401, 10.1093/icesjms/fsad209

Contributors

Mendo, Tania C 0000-0003-4397-2064 (Corresponding author) [1] Mujal-Colilles, Anna 0000-0003-0139-3849 (Corresponding author) [2] Stounberg, Jonathan 0000-0003-2877-9944 [3] Glemarec, Gildas 0000-0003-1801-3179 [3] Egekvist, Josefine 0000-0001-9619-1443 [3] Mugerza, Estanis 0000-0003-4175-8750 [4] Rufino, Marta Mega 0000-0002-0734-7491 [5] [6] Swift, R [1] James, Mark A 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] AZTI
  8. [NORA names: Spain; Europe, EU; OECD];
  9. [5] Portuguese Sea and Atmosphere Institute
  10. [NORA names: Portugal; Europe, EU; OECD];

Abstract

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

Abstract, Fisher, High, Python, Python language, abstract knowledge, activity, analysis, anchor, anchoring sites, applications, code, community, data, devices, distribution, environment, fish, fisheries, fishing activities, fleet, future, geospatial data, highly variable nature, improvement, interval, knowledge, language, large-scale fisheries, marine, marine environment, marine space, method, minutes, nature, nuances, particularities, path, refinement, replicate analyses, sites, space, stakeholder communities, stakeholders, standard methods, temporal distribution, tracking, tracking data, tracking device, trips, users, variable nature, vessel tracking data, vessel trips, workflow

Funders

  • Government of Catalonia
  • European Commission

Data Provider: Digital Science