Agritrop
Accueil

Modeling bycatch abundance in tropical tuna purse seine fisheries on floating objects using the Δ method

Dumont Agathe, Duparc Antoine, Sabarros Philippe S., Kaplan David Michael. 2024. Modeling bycatch abundance in tropical tuna purse seine fisheries on floating objects using the Δ method. ICES Journal of Marine Science, 81 (5) : 887-908.

Article de revue ; Article de revue à facteur d'impact
[img]
Prévisualisation
Version publiée - Anglais
Sous licence Licence Creative Commons.
611959.pdf

Télécharger (3MB) | Prévisualisation

Type d'url non précisé : https://github.com/Agathedumont/modeling-bycatch-abundance-delta-method

Résumé : Bycatch rates are essential to estimating fishery impacts and making management decisions, but data on bycatch are often limited. Tropical tuna purse seine (PS) fisheries catch numerous bycatch species, including vulnerable silky sharks. Even if bycatch proportion is relatively low, impacts on pelagic ecosystems may be important due to the large size of these fisheries. Partial observer coverage of bycatch is a major impediment to assessing impacts. Here we develop a generic Δ modeling approach for predicting catch of four major bycatch species, including silky sharks, in floating object-associated fishing sets of the French Indian Ocean PS fleet from 2011 to 2018 based on logbook and observer data. Cross-validation and variable selection are used to identify optimal models consisting of a random forest model for presence–absence and a negative binomial general-additive model for abundance when present. Though models explain small to moderate amounts of variance (5–15%), they outperform a simpler approach commonly used for reporting, and they allow us to estimate total annual bycatch for the four species with robust estimates of uncertainty. Interestingly, uncertainty relative to mean catch is lower for top predators than forage species, consistent with these species having similar behavior and ecological niches to tunas.

Mots-clés Agrovoc : gestion des pêches, pêcherie de thon, pêche à la senne coulissante, capture accessoire, filet tournant avec coulisse, requin, flottille de pêche, Baliste, dorade tropicale, panneau composite, modèle mathématique, données sur les pêches, modèle de simulation

Mots-clés géographiques Agrovoc : France, océan Indien

Mots-clés libres : Prediction intervals, Random Forest, General additive model (GAM), Silky shark (Carcharhinus falciformis), Dolphinfish (Coryphaena hippurus), Rainbow runner (Elagatis bipinnulata), Rough triggerfish (Canthidermis maculata)

Agences de financement européennes : European Commission

Agences de financement hors UE : Institut de Recherche pour le Développement, Direction des Pêches Maritimes et de l'Aquaculture

Programme de financement européen : H2020

Projets sur financement : (EU) REDUCING BYCATCH OF THREATENED MEGAFAUNA IN THE EAST CENTRAL ATLANTIC

Auteurs et affiliations

  • Dumont Agathe, CIRAD-BIOS-UMR PHIM (FRA)
  • Duparc Antoine, Université de Montpellier (FRA)
  • Sabarros Philippe S., Université de Montpellier (FRA)
  • Kaplan David Michael, Université de Montpellier (FRA) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/611959/)

Voir la notice (accès réservé à Agritrop) Voir la notice (accès réservé à Agritrop)

[ Page générée et mise en cache le 2025-03-08 ]