FishMORPH -An agent-based model to predict salmonid growth and distribution responses under natural and low flows

• Published in: Scientific Reports
• Main Authors: Phang, S.C., Stillman, R.A., Cucherousset, J, Britton, J.R., Roberts, D, Beaumont, W.R.C., Gozlan, R.E.
• Other Authors: Bournemouth University Poole (BU), Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Salmon & Trout Research centre, Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2016
• Subjects: [SDE.BE]Environmental Sciences/Biodiversity and Ecology; Atlantic salmon
• Online Access: https://hal.sorbonne-universite.fr/hal-01360203; https://hal.sorbonne-universite.fr/hal-01360203/document; https://hal.sorbonne-universite.fr/hal-01360203/file/srep29414.pdf; https://doi.org/10.1038/srep29414

International audience Predicting fish responses to modified flow regimes is becoming central to fisheries management. In this study we present an agent-based model (ABM) to predict the growth and distribution of young-of-the-year (YOY) and one-year-old (1+) Atlantic salmon and brown trout in response to flow change during summer. A field study of a real population during both natural and low flow conditions provided the simulation environment and validation patterns. Virtual fish were realistic both in terms of bioenergetics and feeding. We tested alternative movement rules to replicate observed patterns of body mass, growth rates, stretch distribution and patch occupancy patterns. Notably, there was no calibration of the model. Virtual fish prioritising consumption rates before predator avoidance replicated observed growth and distribution patterns better than a purely maximising consumption rule. Stream conditions of low predation and harsh winters provide ecological justification for the selection of this behaviour during summer months. Overall, the model was able to predict distribution and growth patterns well across both natural and low flow regimes. The model can be used to support management of salmonids by predicting population responses to predicted flow impacts and associated habitat change.