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.

http://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.

http://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

http://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.

http://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.

http://eprints.bournemouth.ac.uk/24410/

http://www.nature.com/scientificreports

Source: BURO EPrints