Bulletin of Marine and Coastal Research

Vol. 54 No. 1 (2025)
Research Articles

Relative abundance index of yellownose skate between Chile’s Isla Choros (29° 16’ S) and Punta Refugio (42° 10’ S) as a contribution to its stock management

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  • Javier Legua,
  • Cristian Canales Ramírez,
  • Luis La Cruz Aparco
Javier Legua
Instituto de fomento Pesquero
Cristian Canales Ramírez
Pontificia Universidad Católica de Valparaíso, Laboratorio de Dinámica de Poblaciones Marinas y Modelamiento Estadístico (Dimare), Valparaíso, Chile.
Luis La Cruz Aparco
Instituto de Fomento Pesquero, Departamento de Evaluaciones Directas, Blanco 839, Valparaíso, Chile.
DOI: https://doi.org/10.25268/bimc.invemar.2025.54.1.1305

Published 2025-01-01

Keywords

  • Zearaja chilensis,
  • GLM,
  • Lognormal delta approximation,
  • Abundance index,
  • Spatial pattern

How to Cite

1.
Legua J, Canales Ramírez C, La Cruz Aparco L. Relative abundance index of yellownose skate between Chile’s Isla Choros (29° 16’ S) and Punta Refugio (42° 10’ S) as a contribution to its stock management. Bol. Investig. Mar. Costeras [Internet]. 2025 Jan. 1 [cited 2025 Jan. 8];54(1):71-92. Available from: https://boletin.invemar.org.co/ojs/index.php/boletin/article/view/1305

Copyright (c) 2024 Javier Legua

Creative Commons License

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Abstract

In many fisheries, particularly those with limited data, CPUE is not a good indicator of abundance due to multiple operational factors that influence variability in catchability. In order to estimate an annual CPUE abundance signal of a data-limited fishery resource, in this paper we analyze the yellownose skate (Zearaja chilensis) accompanying fauna data collected in the common hake (Merluccius gayi) hydroacoustic surveys (1993-2019) off south-central Chile
(29° 10’ S - 42° 10’ S). Operational information is analyzed by means of Generalized Additive Models (GAM) and Generalized Linear Models (GLM). The results indicate that Z. chilensis presents notable density zones and a higher frequency of presence of this species between 300 m and 425 m depth. The CPUE model showed that depth is the most important fixed effect in its variability, while the year effect proved to be determinant in a binomial model of
the proportion of positive hauls. The study suggests that this type of indices be considered in the management of this fishery, either in stock assessment models, or as empirical indices for the annual adjustment of catches or fishing effort. effort.

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