General state-space population dynamics model for Bayesian stock assessment

Samu H.P. Mantyniemi*, Rebecca E. Whitlock, Tommi A. Perala, Paul A. Blomstedt, Jarno P. Vanhatalo, Margarita Maria Rincon, Anna K. Kuparinen, Henni P. Pulkkinen, Sakari Kuikka

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

9 Sitaatiot (Scopus)

Abstrakti

This study presents a state-space modelling framework for the purposes of stock assessment. The stochastic population dynamics build on the notion of correlated survival and capture events among individuals. The correlation is thought to arise as a combination of schooling behaviour, a spatially patchy environment, and common but unobserved environmental factors affecting all the individuals. The population dynamics model isolates the key biological processes, so that they are not condensed into one parameter but are kept separate. This approach is chosen to aid the inclusion of biological knowledge from sources other than the assessment data at hand. The model can be tailored to each case by choosing appropriate models for the biological processes. Uncertainty about the model parameters and about the appropriate model structures is then described using prior distributions. Different combinations of, for example, age, size, phenotype, life stage, species, and spatial location can be used to structure the population. To update the prior knowledge, the model can be fitted to data by defining appropriate observation models. Much like the biological parameters, the observation models must also be tailored to fit each individual case.

AlkuperäiskieliEnglanti
Sivut2209-2222
Sivumäärä14
JulkaisuICES Journal of Marine Science
Vuosikerta72
Numero8
DOI - pysyväislinkit
TilaJulkaistu - 2015
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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