Modelling the bioenergetics of (marine) salmon migration Doug Booker, Neil Wells, Patrick Ward, Philip Smith, University Marine Biological Station Millport

Project background Aim –To enhance understanding of how annual variations in marine conditions impact salmon migration in the North Atlantic Ocean… Approach –by developing a model to describe the bioenergetics of marine salmon migration. Background –Open competition. –4 year project. –Started in August –SF0237.

Research Need Salmon stocks have been declining Possible causes include: a)overfishing, b)freshwater habitat deterioration, c)impediments to river migration, d)genetic contamination, e)changes in ocean currents and temperature. Source: ICES

Balanced energy model

Physiological relationships Physiological laboratory experiments have been conducted on salmonids, e.g. to investigate relationships between fish size and/or temperature and… –Prey detection –Maximum and minimum prey size –Digestion rates –Stomach size –Efficiency of swimming at various speeds –Maximum sustainable swimming speed –Burst swimming speed –Energy content of prey These relationships provide a physically-based approach for modelling the bioenergetics of salmon migration.

Model boundary conditions 1) Ocean temperature 2) Ocean currents 3) Salmon prey

Input to the bioenergetic model The oceanographic boundary conditions are gained from the OCCAM model ¼ degree resolution 3D ocean circulation model Covers entire globe

Input to the bioenergetic model Salmon prey information could be gained from: 1.Zooplankton ocean surveys e.g. –The National Oceanographic Center: World Ocean Database of Plankton –Alister Hardy Foundation for Ocean Science –British Oceanographic Data Centre 2.Or from ocean ecosystem models –Predictions of biomass can be made from NPDZ models –e.g. HADOCC, OCCAM

Ocean current validation Comparisons of model predictions with real world observations e.g. data from buoys (WOCE-SVP).

Bioenergetic model

March 93 – April 93

March 93 –September 93

Modelling the bioenergetics of salmon migration

Comparison with capture data Source: Holst, J.C., Shelton, R., Hansen, L.P., Holm, M., Hansen, L.P., (2000).. In: Mills, D. The ocean life of Atlantic salmon: environmental and biological factors influencing survival, Fishing News Books, Blackwell Science Ltd, Oxford. Pp

Model sensitivity Model results depend on a combination of factors Physiological algorithms and parameters Migration rules Initial fish weight Ocean current Temperature Food supply Changes in any of these variables can be evaluated through sensitivity analyses.

Conclusions 1.Oceanographic model boundary conditions have been entered to working Bioenergetic modelling 2.This allows a physically and physiologically-based method for investigating survival and growth in the ocean using an individual-based approach.

Future work 1.Continue assessment of oceanographic boundary conditions. 2.Assessment and sensitivity of physiological parameters. (Pacific Vs Atlantic) 3.Assess and improve migration rules. 4.Compare model calculations with observations from tagging and capture experiments. 5.Assess representativeness of ocean conditions with respect to long term climate change. 6.Assess inter-annual variations in salmon growth and survival.