Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks

A mathematical description of sub-adult cephalopod Instantaneous Growth Rate (1–120 days after hatching) was formulated as a multistage function, combining a Gaussian function during the post-hatching stages and an exponential decay function during the transition to the pre-adult stages. A set of ca...

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Main Authors: Enrico Nicola Armelloni, Giuseppe Scarcella, André E. Punt
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Ecological Informatics
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Online Access:http://www.sciencedirect.com/science/article/pii/S1574954125003541
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author Enrico Nicola Armelloni
Giuseppe Scarcella
André E. Punt
author_facet Enrico Nicola Armelloni
Giuseppe Scarcella
André E. Punt
author_sort Enrico Nicola Armelloni
collection DOAJ
description A mathematical description of sub-adult cephalopod Instantaneous Growth Rate (1–120 days after hatching) was formulated as a multistage function, combining a Gaussian function during the post-hatching stages and an exponential decay function during the transition to the pre-adult stages. A set of candidate mixed effects models was formulated where random parameters derived from a common (hyper)distribution were associated with each experiment and where fixed effects were used to account for dependency on temperature, food type and food amount. The candidate models were fitted to data collected from published aquaculture experiments using a Bayesian hierarchical approach and evaluated using quantitative diagnostics and performance metrics. The results showed that including covariates and random effects improved the ability of the model to fit the data. Growth was found to increase rapidly at low food rations but at a decreasing rate as the food supply becomes abundant. The relationship between temperature and growth transitioned from positive to negative approaching the sub-adult stage. Mixtures of small and medium shrimp were found to lead to higher growth during the first weeks after hatching, while grass shrimp were preferred thereafter. The meta-analytic estimation approach allowed information to be leveraged from multiple studies while accounting for the uncertainty induced by variation in experimental setups. Model posteriors were used to predict growth rate and weight at age, which were compared to out of sample data from aquaculture and wild captured individuals. We discuss how the proposed model can be used to make predictions for the growth of common cuttlefish in aquaculture and fisheries studies.
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spelling doaj-art-9f8c557388b142ffb52763f508fbeb7c2025-08-20T05:05:54ZengElsevierEcological Informatics1574-95412025-12-019010334510.1016/j.ecoinf.2025.103345Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocksEnrico Nicola Armelloni0Giuseppe Scarcella1André E. Punt2Institute for Biological Resources and Marine Biotechnology (IRBIM), National Research Council of Italy (CNR), Ancona, Italy; University of Bologna, Department of Biological, Geological and Environmental Sciences, 40126 Bologna, Italy; Corresponding author at: Institute for Biological Resources and Marine Biotechnology (IRBIM), National Research Council of Italy (CNR), Ancona, Italy.Institute for Biological Resources and Marine Biotechnology (IRBIM), National Research Council of Italy (CNR), Ancona, ItalySchool of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195-5020, USAA mathematical description of sub-adult cephalopod Instantaneous Growth Rate (1–120 days after hatching) was formulated as a multistage function, combining a Gaussian function during the post-hatching stages and an exponential decay function during the transition to the pre-adult stages. A set of candidate mixed effects models was formulated where random parameters derived from a common (hyper)distribution were associated with each experiment and where fixed effects were used to account for dependency on temperature, food type and food amount. The candidate models were fitted to data collected from published aquaculture experiments using a Bayesian hierarchical approach and evaluated using quantitative diagnostics and performance metrics. The results showed that including covariates and random effects improved the ability of the model to fit the data. Growth was found to increase rapidly at low food rations but at a decreasing rate as the food supply becomes abundant. The relationship between temperature and growth transitioned from positive to negative approaching the sub-adult stage. Mixtures of small and medium shrimp were found to lead to higher growth during the first weeks after hatching, while grass shrimp were preferred thereafter. The meta-analytic estimation approach allowed information to be leveraged from multiple studies while accounting for the uncertainty induced by variation in experimental setups. Model posteriors were used to predict growth rate and weight at age, which were compared to out of sample data from aquaculture and wild captured individuals. We discuss how the proposed model can be used to make predictions for the growth of common cuttlefish in aquaculture and fisheries studies.http://www.sciencedirect.com/science/article/pii/S1574954125003541Bayesian hierarchical modelsSepia officinalisAquaculture experimentsGrowth modelInstantaneous growth rateCephalopods
spellingShingle Enrico Nicola Armelloni
Giuseppe Scarcella
André E. Punt
Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
Ecological Informatics
Bayesian hierarchical models
Sepia officinalis
Aquaculture experiments
Growth model
Instantaneous growth rate
Cephalopods
title Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
title_full Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
title_fullStr Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
title_full_unstemmed Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
title_short Integrating published experimental data and hierarchical bayesian modeling: a model for common cuttlefish (Sepia officinalis Linnaeus, 1758) growth to improve predictions for aquaculture and wild stocks
title_sort integrating published experimental data and hierarchical bayesian modeling a model for common cuttlefish sepia officinalis linnaeus 1758 growth to improve predictions for aquaculture and wild stocks
topic Bayesian hierarchical models
Sepia officinalis
Aquaculture experiments
Growth model
Instantaneous growth rate
Cephalopods
url http://www.sciencedirect.com/science/article/pii/S1574954125003541
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AT giuseppescarcella integratingpublishedexperimentaldataandhierarchicalbayesianmodelingamodelforcommoncuttlefishsepiaofficinalislinnaeus1758growthtoimprovepredictionsforaquacultureandwildstocks
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