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Dynamic programming part II - Life history evolution in cod - From individual states to populations
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Physical forcing Individual state Trade-offs emerge A population is a collection of individuals and their actions Patterns emerge Evolution emerges Bioenergetics
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Northeast Arctic cod Marshall CT, Yaragina NA, Ådlandsvik B, and Dolgov AV. 2000. Reconstructing the stock- recruit relationship for Northeast Arctic cod using a bioenergetic index of reproductive potential. Can. J. Fish. Aquat. Sci., 57: 2433- 2442.
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Why is state dependence important? An example: Recruitment in fish. Something Recruitment ?
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What is ’something’ that we can measure? Biomass? Recruitment Mature biomass? Spawning stock biomass? But, what about juvenile and immature stages? But, what about mature fish that do not spawn?
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Recruitment in Icelandic cod Marteinsdottir G and Thorarinsson K. 1998. Improving the stock-recruitment relationship in Icelandic cod (Gadus morhua) by including age diversity of spawners. Can. J. Fish. Aquat. Sci., 55: 1372-1377.
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What is ’something’ that we can measure? Recruitment Spawning stock biomass? SSB and age?
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Condition and recruitment Recruitment to age 3 Marshall CT, Yaragina NA, Ådlandsvik B, and Dolgov AV. 2000. Reconstructing the stock-recruit relationship for Northeast Arctic cod using a bioenergetic index of reproductive potential. Can. J. Fish. Aquat. Sci., 57: 2433-2442.
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What is ’something’ that we can measure? Recruitment SSB and condition? SSB and age?
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Population structure Describing a population by more than abundance or biomass: Describing a population by more than abundance or biomass: –Length. –Age and length. –Age and length and condition. A state-dependent dynamic programming model. Patterns in a structured population.
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Food intake Stored energy OffspringOffspring Growth A model for energy allocation Bioenergetic description of energy allocation. State-dependent life history optimized using reproductive value. External factors Mortality Food intake Migration costs States Age Body length Stored energy Model presented in: Jørgensen C and Fiksen Ø. In press. State-dependent energy allocation in cod (Gadus morhua). Can J Fish Aquat Sci.
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Energy utilization in the model Food ingested monthly (variable) –Routine metabolism = Energy for allocation [Spawning season]: Total stored energy – Energy required for migration (both ways) =Energy available for egg production Store Growth
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State dynamics Energy in food E EGEG ESES G · S · Growth: Energy stores: At spawning: FecSa+1,LVPS a,L V tttSt 111,max),( (1- ) Stochasticity
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Allocation Model presented in: Jørgensen C and Fiksen Ø. In press. State-dependent energy allocation in cod (Gadus morhua). Can J Fish Aquat Sci.
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Predicted growth in the model
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Life history evolution: Effects of fisheries
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Spawner fishery Northeast Arctic cod Feeder fishery More than 1000 years Since ~1920
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Mortality in feeder fishery (year -1 ) Mortality in spawner fishery (year -1 ) Mean age at maturation (year) Historic fishing Present trawling
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Skipped spawning
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Allocation Model presented in: Jørgensen C and Fiksen Ø. In press. State-dependent energy allocation in cod (Gadus morhua). Can J Fish Aquat Sci.
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Effects of mortality In general: In general: –Increasing mortality decreases the value of future reproductions. –Current reproduction becomes more important. –Skipped spawning becomes less frequent.
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Skipped spawning: Ecological relationships
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The effect of condition
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Spawning Not spawning Interaction: condition and length Richard Nash, Institute of Marine Research, unpublished data.
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Relationship with food availability
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Natural mortality (year -1 ) Relative food intake Skipped spawning (% of repeat spawners)
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Skipped spawning: Relationships with age
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Skipped spawning and age Present growth Continued fishing Historic growth Harvest: Skipped spawning more common Evolution: Skipped spawning less common
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Histology in Barents Sea cod Oganesyan, S. A. (1993). Periodicity of the Barents Sea cod reproduction. ICES CM 1993/G:64. Barents Sea Bear Island bank
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Young mature cod skip more Present growth Continued fishing Historic growth
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HAVFORSKINGSINSTITUTTET INSTITUTE OF MARINE RESEARCH Evidence of skipping 2 nd -time spawners strongly underrepresented 1 st -time spawners 2 nd -time spawners ‘5 th -time spawners’ Spawning area Slide and data courtesy of Georg Engelhard and Mikko Heino.
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How to predict recrutiment? Something Recruitment
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Individual state and fecundity Fecundity (million eggs)
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Population measures and fecundity Total egg production
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Population measures and fecundity Including Energy Stores RemovingSkippedSpawners
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Liver energy and fecundity Total egg production Fecundity (million eggs) Individual Population
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Physical forcing Individual state Trade-offs emerge A population is a collection of individuals and their actions Patterns emerge Evolution emerges Bioenergetics
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Acknowledgements Collaborators and co-authors: Øyvind Fiksen (supervisor) Bruno Ernande Ulf Dieckmann Mikko Heino Richard Nash Collaborators and co-authors: Øyvind Fiksen (supervisor) Bruno Ernande Ulf Dieckmann Mikko Heino Richard Nash Thanks to the Research Council of Norway for financial support. Thanks to the Research Council of Norway for financial support.
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