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Enregistrement W4409651804 · doi:10.1111/jfb.70064

Advances in telemetry approaches and technologies applied to fish ecology and management

2025· editorial· en· W4409651804 sur OpenAlexaff
Johann Mourier, Taryn S. Murray, Robert J. Lennox, Kim Birnie‐Gauvin

Notice bibliographique

RevueJournal of Fish Biology · 2025
Typeeditorial
Langueen
DomaineEnvironmental Science
ThématiqueMarine animal studies overview
Établissements canadiensOcean Tracking NetworkDalhousie University
Organismes subventionnairesnon disponible
Mots-clésBiologyTelemetryFish <Actinopterygii>EcologyFisheryBiotelemetryEngineeringTelecommunications

Résumé

récupéré en direct d'OpenAlex

Telemetry and biologging have been key tools in fish ecology for several decades (Hussey et al., 2015; Matley et al., 2022; Watanabe & Papastamatiou, 2023) and helped uncover several mysteries within this realm, including migrations, behaviour, activity and space use, intra- and interspecific interactions or human impacts. The technology has remarkably improved since its first application, allowing us to monitor smaller-sized fish for longer periods. Sensors on board tags add additional capacity to measure internal and external properties of the tagged fish, such as their temperature, depth and acceleration. In addition, the analytical tools and approaches to infer fish movement and behaviour derived from telemetry data have considerably advanced to allow complex and high-dimensional spatial and temporal analyses. There is a global community of fish-tracking scientists who use animal tracking tools to address applied and fundamental questions about fish populations in every ocean of the world and scores of inland waters. The Sixth International Conference on Fish Telemetry gathered many of these scientists in Sète, France, from 11 to 16 June 2023, providing the opportunity to share the latest advances in telemetry approaches and technologies for studying movement ecology of fish and for fisheries management. The present collection of papers is representative of the current trends in fish ecology studied through the prism of biologging and telemetry, with 11 (41%) papers focused on marine systems, 7 (26%) on freshwater systems and 9 (33%) addressing both systems (i.e., estuary or transitions between rivers and sea). This special issue offers readers a wide range of approaches and tagging methods applied to dive deeper into a fish's movement ecology. Although the more common tagging methods provided new insights into fish ecology with acoustic telemetry determining the large-scale migrations of rays in a regional network of receivers (Elston et al., 2024) and pop-up archival satellite tags providing the first long-term migration route of sunfish (Mola mola L.) in the Mediterranean Sea (Rouyer et al., 2023), other developing tools were also applied. For example, data-storage tags were used in combination with acoustic telemetry to study connectivity of pollack (Pollachius pollachius) in the French-English Channel (Gonse et al., 2024). In addition, several approaches were proposed to study predation in fish, including acoustic tags with acceleration sensors to map the dynamics of shark activity and its associated predation pressure on prey (Laurioux et al., 2024) or the test and use of predation tags in several case studies: brown trout (Salmo trutta L.; Kennedy et al., 2024), largemouth bass (Micropterus nigricans; Shorgan et al., 2024) and salmon (Salmo salar; Waters et al., 2024). More well-established sensors, such as depth and temperature sensors, integrated into acoustic tags were also used to investigate environmental preferences and niche partitioning of fish (Nickel et al., 2024). Depth sensors integrated into positioning systems allow the incorporation of the vertical dimension of fish activity by building more accurate three-dimensional habitat use models (Richter et al., 2024). Finally, heart-rate sensor tags were implanted in the musculature associated with the cleithrum of Atlantic bluefin tuna (Thunnus thynnus) using an atraumatic trocar to investigate their field physiological rates for the first time (Rouyer et al., 2024). Acoustic telemetry is now an accessible tool for fish ecologists, but there are limitations to what tracking fish can tell us, which was discussed by Jacoby and Piper (2023). One of the most effective ways that acoustic telemetry is used is for improved understanding of behavioural mechanisms in fish, such as homing (Mitamura et al., 2024) or elusive spawning migrations (Abecasis et al., 2024). Acoustic telemetry can also offer the opportunity to investigate research questions at the metacommunity level, for example, studying coexistence, resource partitioning and management of multiple species (Orrell et al., 2024). Applying random forest models to environmental data associated with telemetry-based presence–absence in several species can help improve our ability to infer fish habitat suitability, which can be used for fish management and restoration (Larocque et al., 2024). Acoustic telemetry data can provide critical estimates of fish vital rates, such as survival, when associated with mark-recapture Cormack-Jolly-Seber models, which can be applied for fisheries management (Rodger, Guthrie, et al., 2024) or infer multispecies tagging mortality (Martínez-Ramírez et al., 2024). Acoustic telemetry can also be used in restoration ecology, for example, to monitor how fish use dam passage in fragmented rivers (Dodd et al., 2003; Shry et al., 2024) or by monitoring the behaviour and survival of hatchery-fish reared to stimulate recovery of a population afflicted by low survival of wild fish (Sortland et al., 2024). The development of regional and national scale acoustic telemetry networks also allows one to monitor the migrations of multiple species at larger scales (Livernois et al., 2024) or migrations at the interface of freshwater and marine systems (Pearson et al., 2024; Rodger, Lilly, et al., 2024). Although many acoustic telemetry studies assess connectivity of tagged individuals among and between habitats, the term ‘connectivity’ has never been consistently used. Welch et al. (2024) provide a framework of connectivity definitions to assist future studies on connectivity. Among the limitations of acoustic telemetry is the variability in the detection range, which can be highly reduced in shallow and structurally complex environment. Kanno et al. (2024) challenged the use of acoustic telemetry in mangrove habitats, characterized by very shallow depths and dynamic seascapes, to study shark and ray movement, demonstrating that fish can be successfully tracked in these understudied habitats. Tag attachment innovations are constantly pushing the limits in tag retention and track durations, improving the quality and quantity of data collected from animals (Junge et al., 2024). This research collection provides the reader with a broad overview of the latest developments and application of acoustic telemetry in the field of fish ecology and management. Biologging and telemetry represent a rapidly evolving field, and the biennial International Conference on Fish Telemetry is a key venue for conversations about new developments and novel applications of fish tracking to address the most complex questions confronted by aquatic scientists and managers. This collection of articles provides the readers with inspired new developments in the field and will be useful to support future research for the study of fish movement ecology.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,016
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,010
Score d'incertitude au seuil0,032

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,016
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0060,008
Études des sciences et des technologies0,0010,002
Communication savante0,0030,006
Science ouverte0,0020,003
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0100,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,011
Tête enseignante GPT0,245
Écart entre enseignants0,234 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2025
Routes d'admission1
Résumé présentoui

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