logging in or signing up Predation07 Miguel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: Embed: Flash iPad Copy Does not support media & animations WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 87 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: December 30, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... By: vinimalik (24 month(s) ago) its good Saving..... Post Reply Close Saving..... Edit Comment Close Premium member Presentation Transcript 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 OutlineAlternative 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 websAlternative 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 termSlide8: 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 webSlide9: 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 WildSlide10: 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: 75-85Slide11: 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: 994-1001Slide13: Multi-Species Virtual Population Analysis fisheries catches other mortality Age-0 Age-1 Age-2 Age-3 Explicitly account for interannual variation in predation mortalitySlide14: 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: 994-1001Slide15: 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 2000Slide18: Lotka-Volterra Based “The Prey’s Perspective” Alternative Functional Response ModelsSlide19: Predator (P) Prey (N) IF P and N are homogenously distributed AND undergo Brownian movement, THEN: Total Prey Consumed = aNP Derivation of Lotka-VolterraSlide20: Derivation of Lotka-VolterraSlide21: Actual Consumption Rate = 0Slide22: Lotka-Volterra Alternative Functional Response Models Ratio-Dependent “The Prey’s Perspective”Slide23: Cod Herring Sprat Pelagic Food Web of The Baltic Sea Monoporeia affinisSlide24: ICES 2000 Population Dynamics in the Baltic SeaSlide25: q=0.1 q=2 q=1 An Empirical Functional Response Model: Hassell and Varley, 1969 Mp* Mortality Rate = aPqSlide26: 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 5Issues 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 autocorrelationPotential 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 abundancesSlide31: Worm and Myers, 2003. Meta-analysis of cod-shrimp interactions reveals top-down control in oceanic food webs. Ecology 84: 162-173Correlation b/w Cod and Shrimp Abundances: Correlation b/w Cod and Shrimp AbundancesSite-Specific and Combined Correlations: Site-Specific and Combined Correlations Individual Sites Combined Estimates You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
Predation07 Miguel Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: Embed: Flash iPad Copy Does not support media & animations WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 87 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: December 30, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... By: vinimalik (24 month(s) ago) its good Saving..... Post Reply Close Saving..... Edit Comment Close Premium member Presentation Transcript 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 OutlineAlternative 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 websAlternative 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 termSlide8: 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 webSlide9: 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 WildSlide10: 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: 75-85Slide11: 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: 994-1001Slide13: Multi-Species Virtual Population Analysis fisheries catches other mortality Age-0 Age-1 Age-2 Age-3 Explicitly account for interannual variation in predation mortalitySlide14: 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: 994-1001Slide15: 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 2000Slide18: Lotka-Volterra Based “The Prey’s Perspective” Alternative Functional Response ModelsSlide19: Predator (P) Prey (N) IF P and N are homogenously distributed AND undergo Brownian movement, THEN: Total Prey Consumed = aNP Derivation of Lotka-VolterraSlide20: Derivation of Lotka-VolterraSlide21: Actual Consumption Rate = 0Slide22: Lotka-Volterra Alternative Functional Response Models Ratio-Dependent “The Prey’s Perspective”Slide23: Cod Herring Sprat Pelagic Food Web of The Baltic Sea Monoporeia affinisSlide24: ICES 2000 Population Dynamics in the Baltic SeaSlide25: q=0.1 q=2 q=1 An Empirical Functional Response Model: Hassell and Varley, 1969 Mp* Mortality Rate = aPqSlide26: 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 5Issues 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 autocorrelationPotential 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 abundancesSlide31: Worm and Myers, 2003. Meta-analysis of cod-shrimp interactions reveals top-down control in oceanic food webs. Ecology 84: 162-173Correlation b/w Cod and Shrimp Abundances: Correlation b/w Cod and Shrimp AbundancesSite-Specific and Combined Correlations: Site-Specific and Combined Correlations Individual Sites Combined Estimates