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How To Survive A Drought The bioenergetic efficiency of juvenile Chinook salmon feeding strategies during a drought in the San Joaquin River, California Taylor Spaulding Justin Sullivan/Getty Images John Walker Fresno Bee Staff Photo

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Outline 1. Problem a. Mechanism b. Question c. Organism 2. Hypothesis and Predictions 3. Variables a. Main Factors b. Main Effects c. Considerations 4. Experimental Design & Sampling 1. Habitat 2. Prey 3. Salmon 4. Modeling 5. Statistics and Testing 6. Interpretation and Deliverables

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Problem Mechanism Salmonids can employ two different strategies when feeding, Drift (A) and Benthic (B) foraging Drift = ambush Usually more efficient, allowing energy to be conserved and net energy intake optimized Benthic = searching Usually, less efficient, requires actively swimming and searching

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Bioenergetic modeling of salmon only includes drift foraging; assumed to always be more efficient Efficiency of drift foraging is dependent on many factors: Temperature Turbidity Velocity Prey availability and quality Influenced by velocity Predation risk Competitive exclusion Drought conditions in rivers may lessen the efficiency of drift foraging Increased temperatures Decreased prey availability/quality Increased competition and predation risk due to habitat loss Problem Mechanism

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Is the inclusion of benthic foraging a more efficient feeding strategy during drought conditions; optimizing net energy intake? Are observed patterns of growth in salmon reared during a drought consistent with estimates produced with models inclusive of both strategies? Problem Question

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Chinook Salmon (Onchorhyncus tschawytscha Rear in freshwater from approximately January until May/June Small, approximately 30mm to 120mm (~1- ~4.7) Eat invertebrates such as flies (dipterans), caddisflies (trichopterans), mayflies (ephemeropterans), Mites (Hydracarina), and Zooplankton (Daphnidae, Amphipoda, Copepoda) Problem Organism

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Hypotheses and Predictions H 0.1 : Models of drift feeding behavior of juvenile Chinook Salmon will not produce significantly different estimates of growth rates from those observed in nature or from models which also include benthic feeding. H A1 : Models that include benthic and drift feeding strategies will produce growth rate estimates that are significantly greater than growth rates produced in models of only drift feeding. H A2 : Models that include benthic and drift feeding will produce growth rate estimates that are not significantly different from observed growth rates within the natural population

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Variables Main Factors affecting foraging efficiency Water temperature Prey Quality (Metcalfe et. al. 1999) Prey Quantity (Metcalfe et. al. 1999) Water velocity (Shirvell 1994) Turbidity (Gregory & Northcote 1993 & DeYoung 2007) Competition (Nakano 1995) Predation risk (Gregory & Northcote 1993) Habitat characteristics (cover/refugia) Main Effect of foraging efficiency Increased rates of growth Considerations Habitat characteristics (vegetation, substrate, temperature, and water velocity) can affect prey assemblages

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Experimental Design & Sampling Habitat FIGURE 3: MAP OF SAN JOAQUIN RESTORATION AREA FROM SJRRP (2011) SHOWING LOCATIONS OF STUDY SITES FIGURE 4 SCHEMATIC OF SAMPLING DESIGN. SOLID LINES DENOTE TRANSECTS DOTS ON TRANSECT 3 REPRESENT NODES FOR SAMPLING OF WATER VELOCITY AND SUBSTRATE HOLLOW BOXES DENOTE SAMPLING STATIONS FILLED BOXES REPRESENT RANDOMIZED SAMPLE SITE FOR BENTHIC SAMPLES. Four 100m study sites spaced along Restoration reaches 1A and 1B Reaches divided into 10m transects Recorded water velocities, temperatures, substrate classes, turbidity, and dissolved oxygen

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Experimental Design & Sampling Prey Prey collected using a stratified random sampling of each site Drifting prey gathered with depth integrated nets Benthic prey collected using kick-nets. Sorted to Family or lower dependent on Order

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Experimental Design & Sampling Salmon Wild fish only Collected in weirs by the Bureau of Reclamation Trap and Haul effort led by Don Portz Dissected out livers and muscle tissue for stable isotope analysis (SIA) Dissected out otoliths for growth and age calculation

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Experimental Design & Sampling Modeling Stable Isotope Modeling Modeling of diet using ratios of 13 C & 15 N found in salmon liver tissue and invertebrate whole tissue. Liver resolution is ~ 1 week Mixed using MixSIAR a Bayesian model of dietary inputs. Can use priors to inform the model Output is used to determine prey quality (preference for each prey item)

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Experimental Design & Sampling Modeling Bioenergetics/Population Modeling Using inSTREAM, a model of whole populations with a focus on individuals Developed by Steve Railsback and Brett Harvey Components Water velocity, depths, and refugia derived from hydrological models Temperature Turbidity Prey Quality and Quantity (Both benthic and Drifting) Output Daily and average growth rates for each individual within the population

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Testing & Statistics Output from bioenergetic model is growth rate which is directly comparable to growth rates derived from Otolith analyses Growth Rates from models or observations to test Drift Drift + Benthic Observed Mean Testing H 0 testable using ANOVA Dunnets test would be an excellent post-hoc test, setting the observed growth means as the control Other mean testing operations may be available Residual Testing Testing the residuals of the models to determine how well it fits the observed data

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Predicted Results Results should indicate that the growth experienced by the wild population is more similar to one model than the other. Testing the residuals will be used to evaluate model fit If the model fits well, it can be used for future analyses *Not real data *

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Future Directions Best fit model can be used with future San Joaquin River hydrological modeling to better predict salmon growth and survival in the river Results from study may indicate a lack of sophistication in current models when used to describe growth under sub-optimal conditions Results may show that benthic foraging is an effective foraging method under certain conditions.

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Questions?