Predation07

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Information about Predation07
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Published on December 30, 2007

Author: Miguel

Source: authorstream.com

Slide1:  I. Alternative ways of viewing food webs II. Top down vs. bottom up control? III Magnitude and importance of predation IV. The functional response and implications V. Mechanisms giving rise to strong and weak interactions VI. How to detect and measure interaction strengths Outline Alternative Approaches :  Alternative Approaches Topological Approach:  Topological Approach Linkages are binary (yes / no) No measure of strength of linkage Focus is on the pattern of linkages (structure of the network) Number of linkages Number of cycles Network “hubs” Energetic Approach:  Energetic Approach Quantify the flux of energy / material through food web components Identify strength of material cycling Calculate trophic basis of production (we did this a few weeks ago) Interaction Webs:  Interaction Webs Depict linkages in terms of interaction strengths Interaction strength: the per capita effect of one species on another These can be “top down” or “bottom up” These are often very different from the energetic webs Alternative Approaches :  Alternative Approaches Top – Down vs. Bottom-Up Control:  Top – Down vs. Bottom-Up Control Common terminology, potentially misleading Top-Down control means predators control prey abundance Bottom-Up control means prey control predator abundance False dichotomy? Consumer vs. Resource control is perhaps a better term Slide8:  Trophic Cascades: Top Down Control Gone Wild Producer Grazer “Why is the World Green?” Hairston, Smith, Slobodkin 1960 Carnivore predation limited resource limited resource limited 3-chain food web Slide9:  Producer Grazer “Why is the World Green?” Hairston, Smith, Slobodkin 1960 Carnivore predation limited resource limited resource limited 4-chain food web Apex Predator predation limited Trophic Cascades: Top Down Control Gone Wild Slide10:  Trophic cascade in the North Pacific? Shiomoto, Tadokor, Nagasaw, and Ishida. 1997. Trophic relations in the subarctic North Pacific ecosystem: possible feeding effect from pink salmon. MEPS. 150: 75-85 Slide11:  Magnitude and importance of predation Egg and larvae predation mortality Predation is the major source of egg mortality Information on larval stages not as clear Most larvae die through interactions of starvation and predation Does this affect population dynamics?? Slide12:  Magnitude and importance of predation 2. Juvenile predation mortality Predation mortality is typically large and variable. Tsou and Collie, 2001. Predation mediated recruitment on Georges Bank. ICES J. Mar. Sci. 58: 994-1001 Slide13:  Multi-Species Virtual Population Analysis fisheries catches other mortality Age-0 Age-1 Age-2 Age-3 Explicitly account for interannual variation in predation mortality Slide14:  Magnitude and importance of predation 2. Juvenile predation mortality Predation mortality is typically large and variable. Tsou and Collie, 2001. Predation mediated recruitment on Georges Bank. ICES J. Mar. Sci. 58: 994-1001 Slide15:  Prey Abundance Predator Consumption Rate The Functional Response “The Predator’s Perspective” Type I Type II “Saturating” Type III “Switching” Slide16:  Prey Abundance Prey Mortality Rate The Functional Response “The Prey’s Perspective” Type I Type II “Saturating” Type III “Switching” Slide17:  “There seems to be a widespread opinion that functional responses are an old topic that was thoroughly studied decades ago. However, this is certainly not the case for field measurements.” “...ecologists know pitifully little about the functional response.” Abrams and Ginzburg 2000 Slide18:  Lotka-Volterra Based “The Prey’s Perspective” Alternative Functional Response Models Slide19:  Predator (P) Prey (N) IF P and N are homogenously distributed AND undergo Brownian movement, THEN: Total Prey Consumed = aNP Derivation of Lotka-Volterra Slide20:  Derivation of Lotka-Volterra Slide21:  Actual Consumption Rate = 0 Slide22:  Lotka-Volterra Alternative Functional Response Models Ratio-Dependent “The Prey’s Perspective” Slide23:  Cod Herring Sprat Pelagic Food Web of The Baltic Sea Monoporeia affinis Slide24:  ICES 2000 Population Dynamics in the Baltic Sea Slide25:  q=0.1 q=2 q=1 An Empirical Functional Response Model: Hassell and Varley, 1969 Mp* Mortality Rate = aPq Slide26:  Posterior Distribution of Shape Parameter Sprat Herring * * * Slide27:  Sprat Age 1 Age 2 Age 3 Age 4 Age 5 Age 1 Age 2 Age 3 Age 4 Age 5 Herring Schematic Representation of Predation Mortality % of Total Mortality 100% 50% 10% Slide28:  Sprat Herring Schematic Representation of Predator-Dependence * * * Shape Parameter 1.25 0.7 0.1 Age 1 Age 2 Age 3 Age 4 Age 5 Age 1 Age 2 Age 3 Age 4 Age 5 Issues in Detecting Predator-Control:  Issues in Detecting Predator-Control Best test is via experimentation Potentially suffers from scaling artifacts For many species it is essentially impossible Comparative analyses are hard to do Marine Reserves sometimes used Time series analysis potentially confounded by autocorrelation Potential Solution To Autocorrelation:  Potential Solution To Autocorrelation Combine time series analysis with comparative analysis find separate time series of same predator – prey pair Hopefully these time series are somewhat independent of each other Gives you the statistical power to detect significant inverse correlations between prey and predator abundances Slide31:  Worm and Myers, 2003. Meta-analysis of cod-shrimp interactions reveals top-down control in oceanic food webs. Ecology 84: 162-173 Correlation b/w Cod and Shrimp Abundances:  Correlation b/w Cod and Shrimp Abundances Site-Specific and Combined Correlations:  Site-Specific and Combined Correlations Individual Sites Combined Estimates

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