Document généré le 16/04/2026 depuis l'adresse: https://www.documentation.eauetbiodiversite.fr/fr/notice/causal-relationships-in-king-s-littleneck-clam-fisheries-
Titre alternatif
Producteur
Contributeur(s)
Éditeur(s)
EDP Sciences
Identifiant documentaire
10-dkey/10.1051/alr/2025019
Identifiant OAI
oai:edpsciences.org:dkey/10.1051/alr/2025019
Auteur(s):
Hugo Robotham,Eduardo Bustos,Guillermo Rodríguez-Picolli
Mots clés
Causal relationship
convergent cross mapping
clam
sustainability
nonlinear dynamics
time series
Date de publication
09/12/2025
Date de création
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Date d'acceptation du document
Date de dépôt légal
Langue
en
Thème
Type de ressource
Source
https://doi.org/10.1051/alr/2025019
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Description
This study investigates the network of causal relationships in the king’s littleneck clam (Ameghinomya antiqua) fishery in the southern zone of the Los Lagos Region, Chile, using the Convergent Cross Mapping (CCM) method. The dynamics of the system were analysed based on four time series: abundance indices derived from landings per unit effort (LPUE), the percentage of mega-spawners (Mega) in catches, landings and sea surface temperature (SST) anomalies. The study identified a significant unidirectional causal relationship between landings and landings per unit, and between sea surface temperature and catch per unit effort. A marginally significant one-way causal relationship between landing and mega-spawners was found. A unidirectional causal relationship was also observed from temperature to landings; the extended CCM suggested that landings respond with a lag of 2-4 months to changes on SST. Landings and LPUE were driven by the shared environmental force (sea surface temperature). The results suggested that controlling landings rates can influence management decisions aimed at regulating resource conservation, using a precautionary approach and a target reference value for LPUE. The importance of incorporating indicators such as mega-spawners into management strategies is highlighted, as they can be indicators of the stock’s health status. This study improves the comprehension of how environmental and socio-economic factor interact in complex system.
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