Please use this identifier to cite or link to this item: http://repositorio.udec.cl/jspui/handle/11594/9340
Title: Biological basis for the stock assessment in Guyana using an adaptive evaluation and management approach for data-limited fisheries.
Authors: Cubillos Santander, Luis, supervisor de grado
Alika Bacchus, Olanna
Keywords: Industria Pesquera;Captura Marítima;Población de Peces
Issue Date: 2021
Publisher: Universidad de Concepción, Facultad de Ciencias Naturales y Oceanográfica, Departamento de Oceanografía.
Abstract: Many data-limited fisheries remain without formal stock assessment and management worldwide, and it is the case of Guyana's fisheries. Before assessing the status of data-limited fisheries, it is essential to start with a biological framework that can provide life-history parameters and biological reference points. We utilized estimates of life history parameters for six species sustaining the small-scale and semi-industrial fisheries from the four administrative regions of Guyana. The life history parameters were estimated using the FishLife R package, a multivariate evolutionary model, which allows determining biological reference points. Catch data covered only from 2015 to 2018, and the time series were not enough to apply a formal data-limited stock assessment model. We utilized yield and biomass per recruit models to estimate the age and length at first capture. Target reference points for fishing mortality based on spawning per recruit and a reduction in absolute spawning biomass (B/B0) were close to 50%. The target fishing mortality was F55% for the target species of the small-scale and semi-industrial fisheries in Guyana. Further study is essential to implement, monitor, and conduct stock assessment of the fisheries, and the framework utilized here is a starting point.
Description: Tesis para optar al grado de Magíster en Ciencias con mención en Pesquerías.
URI: http://repositorio.udec.cl/jspui/handle/11594/9340
Appears in Collections:Departamento de Oceanografía - Tesis Magíster



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