Unit 3 Ecology PPT - Community Dynamics

Community Dynamics Dr. Basile 1 Succession and Disturbance 2 Community Structure Community includes the populations of all species in a specific geographic area. Patternsof species abundance and the relationships between members within a...

Community Dynamics Dr. Basile 1 Succession and Disturbance 2 Community Structure Community includes the populations of all species in a specific geographic area. Patternsof species abundance and the relationships between members within a community Community structure is dynamic. 3  Disturbance and Succession Disturbance-"any relatively discrete event in time that disrupts ecosystem, community, or population structure and changes resources, substrate availability, or the physical environment.”  covers nearly anything that creates open space Succession- “the repeatable change in community composition through time following a disturbance." 4 Stages of Succession K-selected r-selected (Early) (Mid) (Late) Life history traits and strategies determine what species exist during each successional stage. 5 Conceptual Models of Succession What causes early successional species to give way to later species? Possible mechanisms responsible for succession  Facilitation, inhibition, tolerance Assumptions 1. Autogenic succession 2. Species are stationary 3. Initial colonists are good dispersers with life history traits that help then reach new habitats quickly. 4. Initial colonists change conditions where they live. 6  Facilitation Model (Primary Succession) Model has three assumptions 1. Barren ground is uninhabitable by all but the most stress tolerant of colonists 2. Early colonists make the environment more suitable for successive species. 3. This sequence continues until the most competitively dominant species no longer facilitate the invasion and growth of any other species. 7 Secondary Succession Succession after non-catastrophic event. Secondary succession not always governed by facilitation. 8  Inhibition Model Only applicable to secondary succession Assumptions 1. Initial community composition is simply a function of who gets there first. 2. Once a colonist becomes established, it inhibits growth of subsequent arrivals 3. Only when space and/or resources are released through the death or decay of dominant residents can new colonists invade and grow. Because short lived early species die more frequently, succession slowly progresses from short lived to long lived species. 9 Tolerance Model Only applicable to secondary succession Assumptions: 1. The initial community composition is simply a function of who gets there first. 2. Species that appear later simply arrived later or arrived early but grew more slowly. 3. Late arriving species tolerate the presence of early species.  They are good competitors  Over time, late successional species exclude other species. 4. Early successional species have no effect on late successional species. 10 Model Summary 11 Late Succession Community Climax community- in absence of additional disturbance succession progresses to a stable endpoints. Allogenic succession- when principle forces driving succession are from outside the system.  Immigration of new species  Seasonal changes in weather and sunlight  Disturbance Communities are almost never in equilibrium 12  Disturbance Regime Typically defined in terms of:  Timing  Magnitude  Frequency  Predictability. Disturbance creates diversity:  Habitat diversity = Species diversity 13 Intermediate Disturbance Hypothesis 14 Aquatic Succession- Ponds 15 Marine Succession 16 Food Chain and Indirect Effects 17 Trophic Levels 18 Indirect Interactions 1. Trophic cascades 2. Behavioral cascade 3. Ecosystem engineers 19 Trophic Cascade “top down control” 20 Behavioral Cascade Predator alters foraging behavior of its prey which stimulates primary production or alters population size lower trophic levels Ecology of fear (predation risk) 21  Ecosystem Engineers Physicallymodify habitat and alter availability of environmental resources for other species. Allogenic Autogenic 22 Community Dynamics Part 2 Dr. Basile 23 Top-Down / Bottom-Up Control 24 Top-Down / Bottom-Up Control “Trophic Cascade” 25  What Determines Structure of Ecological Communities? Theory #1 Top-down control  Trophic cascades  Control of primary production is biotic (consumers) Theory #2  Bottom-up control  Control of primary production is abiotic (resource availability) 26  Role of Trophic Levels Tropic level 1 = primary producers  Limited by environmental resources  Competition is important until second trophic level is added Trophic level 2 = primary consumers  Limits the primary producers  Can also be limited by primary production Trophic level 3 and 4 = secondary/tertiary consumers  Limited by food availability (resource limited) Lower levels will alternate between resource limitation and consumer limitation (competition).  PP limited by competition for resources when odd # links  PP limited by consumers when even # of links 27 Bottom-Up Control 10% energy transfer 28 Bottom-Up Control in Streams Headwater streams  Shown with 3 links  Allochthonous materials supply energy at base of food chain. 29 Bottom-Up Control in Lakes Lakes are good places to investigate how bottom-up forces affect community structure. 1. First, food chain length in lakes is variable and fish are the top predator. 2. Second, the most important primary producers in lakes are photosynthetic algae (phosphorus concentration). 3. Third, lake ecosystems have relatively discrete boundaries. 30 What Determines Food Chain Length? 31 Testing the Hypotheses Mean chain length estimated by stable isotope technique. Stable isotope looks at the 14N / 15N ratio in prey and predator species. There is a shift to more 15N and less 14N the further down the chain. Strong empirical support for the importance of ecosystem size in the structure of food webs! 32 What Determines Community Structure? Exploitation ecosystem hypothesis- food chain length is controlled by bottom-up forces, with top-down control becoming increasingly important as more trophic levels are added. Otherresearchers have hypothesized that disturbance regimes can affect the relative importance of top-down versus bottom-up forces. 33 Community Stability 34 Components of Stability- 3R’s Resistance- Describes how much the community changes due to a particular disturbance.  How big a change did the disturbance cause? Return time- The time it takes a community to return to an equilibrium state.  How quickly did the community recover from disturbance? Resilience-How close does the post disturbance resemble the pre-disturbance community.  How closely did the post-recovery community resemble the pre-disturbance community? 35  Resilience The overall degree to which a community stays the same over time, especially after disturbances, is called the community’s persistence. Alternative states occur when more than one type of community can exist in a particular environment. An alternative state is considered stable if it is unlikely to transition back to the previous state (or some other state). 36 Return Time Recovery time correlates to spatial scale of disturbance 37 Change Without Disturbance Constancy- when a community is less variable in its oscillations of population size. 38 Why are some communities more stable than others? Increasedcommunity diversity (habitat and species!) leads to more stability after disturbances.. Fundamental vs. realized niche! 39 Why are some communities more stable than others? Food web theory- communities with higher connectance (with many species interactions) should be more stable 40  Why are some communities more stable than others? More species can be removed from communities with high connectance without causing additional species to go extinct compared to those with lower connectance. Species loss lowers a community's resilience, reducing its ability to withstand further species loss. If species loss lowered the community's resilience enough, any subsequent disturbances were likely to push the community across a threshold, producing drastic changes. 42 Keystone Species Some species play an important role in communities simply because they are the most abundant or have the greatest biomass, these are dominant species. Keystone species have much bigger effects than would be predicted from their proportional biomass alone. 43 Invasive Species Another way that communities change over time is when they are colonized by new species. Exotic species- non-native species that do no disturb community structure. Usually fail to thrive. Invasive species- an exotic species that can pose serious risk of harm to the environment (including community structure), economy or human health. 44 Competition Dr. Basile 45 What is Competition? When resources are low, competition occurs. If resources are limited populations grow logistically and competition occurs. Intraspecific Interspecific 46 Niche Concept Complete set or range of conditions under which the species can survive and reproduce, known to ecologists as its fundamental niche Realizedniche is generally smaller. Set of conditions where species is actually found.  Restricted by competition, predation, parasitism 47 Competitive Exclusion Principle Niches cannot overlap! Bettercompetitor wins while other species becomes extinct. 48 Paradox of the Plankton Rea lized Nich e!!!! Why does one sample of ocean water have hundreds of species of phytoplankton when the principle of competitive exclusion predicts only one or a few??? 49 Indirect vs. Direct Competition Resource (exploitation) competition- indirectly competing due to shared resource.  Interaction where both competitors suffer. This indirect interaction may cause the population density to decline over time  Self-thinning (intraspecific) Scramble Competition 50 Indirect vs. Direct Competition Interference competition- when direct interactions result in restricted access to a resource Allelopathy-plants releasing poisons Territoriality- exclusions of individual from resources Preemption- arriving first Contest Competition 51 Competition Intraspecific  Effects between individuals equal Interspecific  Effects between individuals of different species may not equal How do you determine the more effi cient competitor?  Size of populations?  Growth rate of populations? Logistic population growth models can predict the results competition 52 Competition Coeffi cients Competition coeffi cients represent the per capita effect on the growth of one species (1), due to interactions with the second species (2). If  12 and  21 are positive the species are competitive. 53 Competition Coeffi cients  If 12 is zero that means there is no effect on species 1 because of species 2.  No competition (dynamics of species 1 follows logistic growth)  If 12 is one then individuals of species 2 compete for the resources of species 1 just as strongly as do members of species 1 (intraspecifi c competition).  If 12 is negative then the presence of species 2 increases the resources available to species 1. 54 Competition Coeffi cient   If 12 and 21 are negative the species are mutualistic.   If 12 or 21 is negative and the other is zero the species have a commensal relationship. If one of the two is positive and one is negative, the species are said to have a parasitic relationship. 55 Lotka-Volterra  12 =0  12 =1  12 is + 56 Lotka-Volterra Predictwhich species should win a competitive interaction. 57 Lotka-Volterra Models Equilibrium population size when populations stop growing. Steady state is when no changes occur in population sizes over time Phaseplane plots population of species 1 vs species 2. Each data point represents a passage of time.  Allow for a global view of all possible outcomes from different initial conditions in one plot 58 Using Time Phase Plots Globally stable when the steady state does not depend on initial population size. Time phase shows population size for both species is at equilibrium after a time and remains so over time (steady state) and it occurs regardless of the initial population sizes. 59 Using Phase Portraits Phase portrait shows trajectories of change (based on a specific  and K) for each combination of initial population size for the two competing species. 60  Using Zero Growth Isoclines dN1/dt = 0 Populations will coexist at this  and K dN2/dt = 0 no matter the initial population size Theorange line is the zero growth isocline for species 1. Ifcombinations of population sizes (N 1 , N 2 ) start on this line, in the next timestep, species 1 population size will not change. 61  Using Zero Growth Isoclines and Trajectories to Determine Model Outcomes K1 / α12 K2 Isocline for Species 1 Isocline for Species 2 dN1/dt = 0 dN2/dt = 0 N2 N2 K1 K2 / α21 N1 N1  Outcomes of Lotka-Volterra Plot the isoclines for 2 species together to Competition Equation examine population trajectories Coexistence at a stable equilibrium K1/12 > K2 K1α12 K2/21 > K1 For species 1: K1 > K2α12 (intrasp. > intersp.) N2 K2 For species 2: K2 > K1α21 (intrasp. > intersp.) = stable equilibrium K1 K2α21 N1  Outcomes of Lotka-Volterra Plot the isoclines for 2 species together to Competition Equation examine population Competitive exclusion with an trajectories unstable equilibrium Outcome depends on starting population sizes K2 > K1/α12 K2 K1 > K2/21 For species 1: K2α12 > K1 K1/ α12 (intersp. > intrasp.) N2 For species 2: K1α21 > K2 (intersp. > intrasp.) = stable equilibrium = unstable equilibrium K2 / α21 K1 N1  Outcomes of Lotka-Volterra Plot the isoclines for 2 species together to Competition Equation examine population trajectories Competitive exclusion of Species 1 by Species 2 K2 > K1/ 12 K2/21 > K1 K2 For species 1: K212 > K1 (intersp. > intrasp.) K1/ 12 For species 2: N2 K2 > K121 (intrasp. > intersp.) = stable equilibrium K1 K2 / 21 N1  Outcomes of Lotka-Volterra Plot the isoclines for 2 species together to Competition Equation examine population trajectories Competitive exclusion of Species 2 by Species 1 K1/12 > K2 K1 > K2/21 K1 / 12 For species 1: K1 > K212 (intrasp. > intersp.) K2 N2 For species 2: K121 > K2 (intersp. > intrasp.) = stable equilibrium K2 / 21 K1 N1 How do you change the outcome of the model? Change r Change  Change K Change N … 67 Changing the competitive ability…  If 0 < 12 < 1 (but greater than zero) then intraspecific competition is more important.  Adding more of species 1 will reduce the growth of species 1 more than the same number of additional species 2.  If 12 > 1 than interspecific competition is more important.  Adding additional species 2 will have a greater effect than the addition of more species 1 68 Changing the competitive ability…  Species coexist   Species 2 Wins  69 Changing N… When both species are strong interspecific competitors (12 and 21) are both greater than 1 the winner is relative to initial population size.  Either species can win  Or they can coexist Unstablevs. Stable Equilibrium 70  Condition Condition Condition 1 2 3 K1/12 K1 225 K1/12 450 12 0.5 K2 75 K2 K2/21 150 K2 /21 K1 21 0.5 Outcome? Species 1 wins! 71  Condition Condition Condition 1 2 3 K1/12 K1 225 225 K1/12 450 450 12 0.5 0.5 K2 75 75 K2 K2/21 150 300 K2 /21 21 0.5 0.25 K1 What changed? Outcome? Stable Equilibrium! Competition Coef. 72  Condition Condition Condition 1 2 3 K2 K1 225 225 400 K1/12 450 450 200 K1/12 12 0.5 0.5 2 K2 75 75 400 K2/21 150 300 200 K2 /21 21 0.5 0.25 2 K1 What changed? Outcome? Carrying Capacity Unstable Equilibrium! and Comp coef. 73 Other Factors Affecting Competition Modelsdo not account for other confounding variables.  Mechanism of competition  Stochasticity  Abiotic factors  Disease  Parasitism in one of the competitive species  Cannibalism 74 Competition Studied in the Field Removeor exclude a species and observe the response of the other. (Common garden experiments.) 75 Competitive Coexistence 1. Our interpretation of species' niches is often wrong. 2. Environmental factors can shift the competitive interaction so it favors one species under certain conditions and another species under different conditions. 3. If competing species adapt to alternate sides of the tradeoff, they can coexist.  Character displacement 76  Character Displacement Assumptions:  There is genetic variance in the population for resource acquisition.  Competition depends on one common resource. 77 Competitive Coexistence 4. Neutral theory of biodiversity – species distributions change randomly over time. 5. Competition is weak due to predation or other ecological interactions in the community. 78 Predation Herbivory Parasitism Dr. Basile 79 Species Interactions Competition (-/-) Exploitation (+/-) (predation/herbivory/p arasitism) Mutualism (+/+) Commensalism ( 0 / + ) Amensalism (0/-) 80  Parasitism Need their host to complete life cycles Adapted to specific hosts Canbe more than one host needed to complete life cycle. Passive vs. Active transmission Direct host to host transmission Vector to host transmission 81 Endoparasites Stable environment Many classified as pathogens Host immune system Parasitesdevelop strategies to evade attack  Modulate host immune response  Camouflage or hide 82 Ectoparasites Active transmission Do not need to evade host immune system Exposed to predation Hosts have mutualistic relationships with ectoparasite predators. 83 Parasitoids Use hosts for reproduction Kills host Cannot be too effective at finding hosts! 84 Impacts of Parasitism Ecological  Directly affecting host population.  Directly affecting evolution of host species  Indirectly, reduction of host survival and or reproduction can affect another species the host interacts with. Individual  Reduction in survival and or reproduction  Change behavior 85 Herbivory Not often true predator  Grazer, browser, granivore, frugivore Herbivoresoften share mutualistic relationships with symbiotic microorganisms. 86 Strategies Against Herbivory Resistance- little to no reduction in fitness due to herbivore attack  Mechanical  Chemical  Nutritional Greatertolerance = smaller reduction in fitness. 87 Impacts of Herbivory Reduce individuals in a population Change community composition Herbivoresare especially likely to affect communities when they feed on a plant that is a strong competitor. Evolution of plant species 88 Predation Strategies  Stalk, ambush, pursuit, random encounter Stages 1. Encounter 2. Detection 3. Identification 4. Approach (capture) 5. Subjugation (gaining control or killing) 6. Consumption 89  Defenses Against Predation Prey species have evolved ways to avoid predators 1. Crypsis 2. Aposematism 3. Chemical warfare 4. Physical barriers 5. Mimicry- Mullerian and Batesian 6. Behavioral strategies 90 Predator Prey cycling (LV Equations) dX/dt= rx X – aXY dY/dt= abXY- mY X= population size of prey Y= population size of the predator r= intrinsic growth rate of the prey a= effi ciency of predator b= conversion factor (one prey eaten does not mean one predator born) m= mortality of predator Lotka-Volterra Predator-Prey Equations a is the searching Encounter rate effi ciency or attack rate of predator b is the conversion factor that accounts for the idea that one prey Consumption rate eaten does not equal one predator born. m is the mortality rate of the predator 92 Predator-Prey Population Cycling Decreases the increase in population  Creates longer cycles  93 Predator-Prey Population Cycling 94 Cycling and Extinction High predation effi ciency (a) mixed with high prey production (r) most likely to produce extinction  Boom and bust Why not high (a) and low (rprey)? Predators do not wipe out prey populations because large predators cannot be supported by small prey populations 95 Lotka-Volterra Model Limitations Deterministic model (LV model) No randomness Always produces the same outcome from given initial conditions. Stochastic model Estimates probability distributions of potential outcomes by allowing for random variation in one or more inputs over time. 96 Assumptions of the Lotka- Volterra Model No density Predator and Prey is only dependent prey are equally food for growth likely to meet predator Predator is No handling No immigration cause of death time of emigration for prey 97 Density Dependence As the prey population grows, its rate of growth decreases. At higher prey densities, fewer predators are required to restrict further prey population growth If prey reaches K, no growth is possible even if there are no predators. Density dependent limitations can increase stability in predator-prey populations. 98  Prey Refuges Effi cient predator  Relatively large and stable population of predators supported by relatively small population of prey when prey have refuges and predators are very efficient. Less effi cient predator  Predator population will be smaller and less stable while prey are generally more numerous when prey have refuges and predators are less efficient 99 Metapopulations Patchiness in populations can promote stability in predator-prey systems and help avoid extinctions. Some patches may that are colonized as a refuge may not have predators that follow right away When predators come to patch some of the prey may have already moved to another patch and so on… Individual populations may not survive long but the metapopulation is stable. 100 Functional Response I. If the density of prey doubles, each predator (and thus the population of predators as a whole) eats twice as many Maximum Rates of prey. Predation II. As prey increases predator increases (not in direct proportion) and predation rate slows. III.Predator ignores prey until a certain density is reached. 101 Optimal Foraging Theory It is a behavioral ecology model that helps predict how an animal behaves when searching for food. A predator may also be prey. Predators seek to minimize foraging time to reduce exposure to other predators and hazards. 102 Optimal Foraging Theory Foragers may optimize energy gain per unit time, or minimize time spent foraging. There are two components to time spent in finding and consuming prey:  Waiting time- average time between encounters with prey  Handling time- average time to consume prey 103 Optimal Foraging Theory Wagtail Bird- eats insects. Largerinsects require more handling time but have a greater energy return. They prefer 7mm even though 8mm is more common. Birdsare modifying selection of prey towards greatest energy return per unit of time. 104 Coevolution Predator and prey  Herbivore and plants Parasite and host Pathogens 105  Coevolution Theease of disease transmission depends on vector and virulence. Evolution moves towards viruses with intermediate levels of virulence are most successful. Hosts are also evolving. Strong selection for resistance to virus/pathogen. 106 Coevolution Diffuse (guild evolution)- number of species coevolving with response to each other Specifi c- two species coevolving 107 Coevolution Some alleles that allow Traits under selective individuals to exploit pressure from or avoid exploitation coevolution often may reduce growth, involve trade-offs. survival or reproduction. 108  (Hypothesis) Organisms are constantly struggling to keep up with one another in an evolutionary race between predator and prey species. Species that evolve fast enough to keep up with or outpace evolution in their enemies will generally persist longer than those that evolve more slowly Evolve “to keep in the same place” 109 Explanation for Sexual Reproduction? Recombination speeds up the rate of evolution! Gives offspring a higher chance of possessing a new combination of alleles that will provide increased fitness in a changing environment. 110 Sexual Selection Individualsof one sex (usually females) are choosy in selecting their mates. One hypothesis is that females prefer male traits that are correlated with “good genes.” 111