Resilience and Critical Stock Size in a Stochastic Recruitment Model

J. Grasman, M.J. Huiskes

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

A stochastic model for fish recruitment is fitted to data after performing an age-structured stock assessment. The main aim is to investigate the relation between safe levels of spawning stock size and fish stock resilience. Resilience indicators, such as stock recovery time and the frequency that a stock is below a critical size, are computed by means of simulation using the fitted stochastic model. The stochastic element of the model describes the early life stage survival of the fish using a nonlinear stochastic Leslie type of matrix. From catch data and fishing mortality rates, the free parameters in the model are estimated by means of a maximum likelihood method. The performance of the maximum likelihood estimation method is tested by means of simulation. The method is applied to data of a halibut population (Hippoglossus stenolepis) in the Southeastern Bering Sea. It turns out that given the fluctuation in recruitment, data of at least 25 consecutive years are required
Original languageEnglish
Pages (from-to)1-12
JournalJournal of Biological Systems
Volume9
DOIs
Publication statusPublished - 2001

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Resilience
Stochastic models
Fish
Fishes
Flounder
Maximum likelihood estimation
fish
Stochastic Model
halibut
catch statistics
Maximum likelihood
fishing mortality
stock assessment
estimation method
Model
Mortality Rate
simulation
Maximum Likelihood Method
Recovery
spawning

Cite this

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title = "Resilience and Critical Stock Size in a Stochastic Recruitment Model",
abstract = "A stochastic model for fish recruitment is fitted to data after performing an age-structured stock assessment. The main aim is to investigate the relation between safe levels of spawning stock size and fish stock resilience. Resilience indicators, such as stock recovery time and the frequency that a stock is below a critical size, are computed by means of simulation using the fitted stochastic model. The stochastic element of the model describes the early life stage survival of the fish using a nonlinear stochastic Leslie type of matrix. From catch data and fishing mortality rates, the free parameters in the model are estimated by means of a maximum likelihood method. The performance of the maximum likelihood estimation method is tested by means of simulation. The method is applied to data of a halibut population (Hippoglossus stenolepis) in the Southeastern Bering Sea. It turns out that given the fluctuation in recruitment, data of at least 25 consecutive years are required",
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Resilience and Critical Stock Size in a Stochastic Recruitment Model. / Grasman, J.; Huiskes, M.J.

In: Journal of Biological Systems, Vol. 9, 2001, p. 1-12.

Research output: Contribution to journalArticleAcademicpeer-review

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