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A demo-genetic individual-based model for Atlantic salmon populations: Model structure, parameterization and sensitivity

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  • Piou, Cyril
  • Prévost, Etienne

Abstract

Predicting the persistence and adaptability of natural populations to climate change is a challenging task. Mechanistic models that integrate biological and evolutionary processes are helpful toward this aim. Atlantic salmon, Salmo salar (L.), is a good candidate to assess the effect of environmental change on a species with a complex life history through an integrative modelling approach due to (i) a large amount of knowledge concerning its biology and (ii) extensive historical data sets that can be used for model validation. This paper presents an individual-based demo-genetic model developed to simulate S. salar population dynamics in southern European populations: IBASAM (Individual-Based Atlantic SAlmon Model). The model structure is described thoroughly. A parameterization exercise was conducted to adjust the model to an extensive set of demographic data collected over 15 years on the Scorff River, Brittany, France. A sensitivity analysis showed that two parameters determining mean and variability of juvenile growth rates were crucial in structuring the simulated populations. Additionally, realistic microevolutionary patterns of different aspects of life history were predicted by the model, reproducing general knowledge on S. salar population biology. The integration into IBASAM of a demo-genetic structure coupled with the explicit representation of individual variability and complex life histories makes it a cohesive and novel tool to assess the effect of potential stressors on evolutionary demography of Atlantic salmon in further studies.

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  • Piou, Cyril & Prévost, Etienne, 2012. "A demo-genetic individual-based model for Atlantic salmon populations: Model structure, parameterization and sensitivity," Ecological Modelling, Elsevier, vol. 231(C), pages 37-52.
    • Handle: RePEc:eee:ecomod:v:231:y:2012:i:c:p:37-52
    DOI: 10.1016/j.ecolmodel.2012.01.025
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    8. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    9. Rougier, Thibaud & Drouineau, Hilaire & Dumoulin, Nicolas & Faure, Thierry & Deffuant, Guillaume & Rochard, Eric & Lambert, Patrick, 2014. "The GR3D model, a tool to explore the Global Repositioning Dynamics of Diadromous fish Distribution," Ecological Modelling, Elsevier, vol. 283(C), pages 31-44.
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    11. Jager, Henriette I. & DeAngelis, Donald L., 2018. "The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes," Ecological Modelling, Elsevier, vol. 384(C), pages 341-352.

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