Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico

Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico

 The yield of the Pacific sardine Sardinops sagax caeruleus from Bahía Magdalena, B.C.S., was analyzed using a stockrecruitment model. The model was stochastic, and it used the hypotheses of process error (H1) in the model, and observation error (H2) in the data. The results showed a positi...

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Yazar: Morales-Bojórquez, E
Materyal Türü: Online
Dil:eng
Baskı/Yayın Bilgisi: Iniversidad Autónoma de Baja California 2002
Online Erişim:https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/216
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spelling oai:cienciasmarinas.com.mx:article-2162019-05-01T00:01:02Z Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico Teorema de Bayes aplicado a la estimación del rendimiento de la sardina Monterrey (Sardinops sagax caeruleus Girard) de Bahía Magdalena, Baja California Sur, México Morales-Bojórquez, E risk analysis uncertainty Monte Carlo simulation decision table management análisis de riesgo incertidumbre simulación Monte Carlo tabla de decisión manejo  The yield of the Pacific sardine Sardinops sagax caeruleus from Bahía Magdalena, B.C.S., was analyzed using a stockrecruitment model. The model was stochastic, and it used the hypotheses of process error (H1) in the model, and observation error (H2) in the data. The results showed a positive bias in the management quantities and the parameters of the model. Confronting both hypotheses with a Monte Carlo simulation resulted in evidences of the effect of the observation error in the measurement of the adult stock of the sardine population. Statistical analysis supported in the Bayes theorem showed that the probabilities estimated from a maximum likelihood model for hypothesis H1 are informative enough as prior probability. In this way, the maximun sustainable yield (MSY) of the fishery was 14,400 t with uMSY = 0.35. The decision table showed that parameters of the model have a probability > 0.80 for α (density-independent parameter) between 0.040 and 0.058, while β (density-dependent parameter) varies between 1.6 and 2.2 with a probability > 0.85. The joint distribution of both parameters allowed a yield 10,100 t < MSY < 20,200 t per fishing season. Se analizó el rendimiento de la sardina monterrey Sardinops sagax caeruleus de Bahía Magdalena, B.C.S., utilizando un modelo de stock-reclutamiento. En este caso, el modelo fue estocástico y utilizó las hipótesis de error de proceso (H1) en el modelo, y error de observación (H2) en los datos, confrontando ambas hipótesis con una simulación Monte Carlo. Los resultados mostraron un sesgo positivo en las cantidades de manejo y en los parámetros del modelo, con este resultado se muestran evidencias del efecto del error de observación en la medición del "stock" adulto de la población de sardina. Un análisis estadístico apoyado en el teorema de Bayes mostró que las probabilidades estimadas de un modelo de máxima verosimilitud para la hipótesis H1 fueron bastante informativas como probabilidades previas. De esta forma, el rendimiento máximo sostenible (MRS) de la pesquería fue de 14,400 t con uMRS = 0.35. La tabla de decisión mostró que los parámetros del modelo tienen una probabilidad > 0.80 para α (parámetro de denso independencia) entre 0.040 y 0.058, mientras que β (parámetro de densodependencia) varía entre 1.6 y 2.2 con probabilidad > 0.85. La distribución conjunta de ambos parámetros permitió un rendimiento 10,100 t < MRS < 20,200 t por temporada de pesca. Iniversidad Autónoma de Baja California 2002-03-06 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article Artículo Arbitrado application/pdf https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/216 10.7773/cm.v28i2.216 Ciencias Marinas; Vol. 28 No. 2 (2002); 167-179 Ciencias Marinas; Vol. 28 Núm. 2 (2002); 167-179 2395-9053 0185-3880 eng https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/216/183
institution Ciencias Marinas
collection OJS
language eng
format Online
author Morales-Bojórquez, E
spellingShingle Morales-Bojórquez, E
Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
author_facet Morales-Bojórquez, E
author_sort Morales-Bojórquez, E
title Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
title_short Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
title_full Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
title_fullStr Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
title_full_unstemmed Bayes theorem applied to the yield estimate of the Pacific sardine (Sardinops sagax coeruleus Girard) from Bahia Magdalena, Baja California Sur, Mexico
title_sort bayes theorem applied to the yield estimate of the pacific sardine (sardinops sagax coeruleus girard) from bahia magdalena, baja california sur, mexico
description  The yield of the Pacific sardine Sardinops sagax caeruleus from Bahía Magdalena, B.C.S., was analyzed using a stockrecruitment model. The model was stochastic, and it used the hypotheses of process error (H1) in the model, and observation error (H2) in the data. The results showed a positive bias in the management quantities and the parameters of the model. Confronting both hypotheses with a Monte Carlo simulation resulted in evidences of the effect of the observation error in the measurement of the adult stock of the sardine population. Statistical analysis supported in the Bayes theorem showed that the probabilities estimated from a maximum likelihood model for hypothesis H1 are informative enough as prior probability. In this way, the maximun sustainable yield (MSY) of the fishery was 14,400 t with uMSY = 0.35. The decision table showed that parameters of the model have a probability > 0.80 for α (density-independent parameter) between 0.040 and 0.058, while β (density-dependent parameter) varies between 1.6 and 2.2 with a probability > 0.85. The joint distribution of both parameters allowed a yield 10,100 t < MSY < 20,200 t per fishing season.
publisher Iniversidad Autónoma de Baja California
publishDate 2002
url https://www.cienciasmarinas.com.mx/index.php/cmarinas/article/view/216
_version_ 1715723943403323392

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