FishMORPH - An agent-based model to predict salmonid growth and distribution responses under natural and low flows
Authors: Phang, S.C., Stillman, R.A., Cucherousset, J., Britton, J.R., Roberts, D., Beaumont, W.R.C. and Gozlan, R.E.
Journal: Scientific Reports
Volume: 6
eISSN: 2045-2322
DOI: 10.1038/srep29414
Abstract: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.
https://eprints.bournemouth.ac.uk/24410/
Source: Scopus
FishMORPH - An agent-based model to predict salmonid growth and distribution responses under natural and low flows.
Authors: Phang, S.C., Stillman, R.A., Cucherousset, J., Britton, J.R., Roberts, D., Beaumont, W.R.C. and Gozlan, R.E.
Journal: Sci Rep
Volume: 6
Pages: 29414
eISSN: 2045-2322
DOI: 10.1038/srep29414
Abstract: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.
https://eprints.bournemouth.ac.uk/24410/
Source: PubMed
FishMORPH - An agent-based model to predict salmonid growth and distribution responses under natural and low flows
Authors: Phang, S.C., Stillman, R.A., Cucherousset, J., Britton, J.R., Roberts, D., Beaumont, W.R.C. and Gozlan, R.E.
Journal: SCIENTIFIC REPORTS
Volume: 6
ISSN: 2045-2322
DOI: 10.1038/srep29414
https://eprints.bournemouth.ac.uk/24410/
Source: Web of Science (Lite)
FishMORPH - An agent-based model to predict salmonid growth and distribution responses under natural and low flows.
Authors: Phang, S.C., Stillman, R.A., Cucherousset, J., Britton, J.R., Roberts, D., Beaumont, W.R.C. and Gozlan, R.E.
Journal: Scientific reports
Volume: 6
Pages: 29414
eISSN: 2045-2322
ISSN: 2045-2322
DOI: 10.1038/srep29414
Abstract: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.
https://eprints.bournemouth.ac.uk/24410/
Source: Europe PubMed Central
FishMORPH - An agent-based model to predict salmonid growth and distribution responses under natural and low flows.
Authors: Phang, S.C., Stillman, R.A., Cucherousset, J., Britton, J.R., Roberts, D., Beaumont, W.R.C. and Gozlan, R.E.
Journal: Scientific Reports
Volume: 6
Pages: 29414
ISSN: 2045-2322
Abstract: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.
https://eprints.bournemouth.ac.uk/24410/
http://www.nature.com/scientificreports
Source: BURO EPrints