Animal tracking with particle algorithms informs protected area design

Animal movements affect their exposure to threats and the efficacy of conservation measures, such as marine protected areas (MPAs). However, many species' movements are difficult to reconstruct from available datasets, hampering conservation efforts. This is especially the case for aquatic species that rarely surface, for which data are often limited to observations from acoustic telemetry (detections) and ancillary sensors. Here, we pioneer the use of state-of-the-art particle algorithms to model movements, integrate datasets, and assess MPA design, leveraging a case study of a Critically Endangered elasmobranch. Our algorithms led to 5-fold improvements in space-use maps and 30-fold improvements in residency estimates compared to prevailing methods. By integrating tracking datasets, we were uniquely able to examine movements beyond acoustic receivers, MPA-scale residency, and specific habitats beyond protected areas that warrant protection. This work reveals a modeling framework that enhances the conservation value of acoustic telemetry, supporting analyses of MPA efficacy worldwide.

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Publication Details

Journal
Science Advances
Published
2025-11-26
DOI
https://doi.org/10.1126/sciadv.adx0255
Citations
2
Primary Topic
Ichthyology and Marine Biology
Type
article
Field-Weighted Citation Impact
4.63
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article

Animal tracking with particle algorithms informs protected area design

Jane Dodd, Carlo Albert, James Thorburn, Helen Moor et al.
2 citations
Science Advances
Ichthyology and Marine Biology
4.63
article

Animal tracking with particle algorithms informs protected area design

Jane Dodd, Carlo Albert, James Thorburn, Helen Moor, Janine Illian, Dmitry Aleynik, Peter J. Wright, Stanisław W. Biber, Edward Lavender, Andreas Scheidegger, Jakob Brodersen, Georgina Cole, Mark James, Sophie Smout
article en
2 citations

Abstract

Animal movements affect their exposure to threats and the efficacy of conservation measures, such as marine protected areas (MPAs). However, many species' movements are difficult to reconstruct from available datasets, hampering conservation efforts. This is especially the case for aquatic species that rarely surface, for which data are often limited to observations from acoustic telemetry (detections) and ancillary sensors. Here, we pioneer the use of state-of-the-art particle algorithms to model movements, integrate datasets, and assess MPA design, leveraging a case study of a Critically Endangered elasmobranch. Our algorithms led to 5-fold improvements in space-use maps and 30-fold improvements in residency estimates compared to prevailing methods. By integrating tracking datasets, we were uniquely able to examine movements beyond acoustic receivers, MPA-scale residency, and specific habitats beyond protected areas that warrant protection. This work reveals a modeling framework that enhances the conservation value of acoustic telemetry, supporting analyses of MPA efficacy worldwide.

Science AdvancesVol. 11(48)
Royal Zoological Society of Scotland (GB), Marine Scotland (GB), University of St Andrews (GB), Edinburgh Napier University (GB), NHS Lanarkshire (GB), University of Surrey (GB), Argyll and Bute Hospital (GB), Aberdeenshire Council (GB), Swiss Federal Institute of Aquatic Science and Technology (CH), University of Glasgow (GB), Scottish Association For Marine Science (GB)
Openalex Percentile: Top 5%
Ichthyology and Marine Biology
4.63
DOIOpen Access PDFOpenAlex
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