Ecology Week 6
Ecology Week 6 LIFE 320-001
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This 9 page Class Notes was uploaded by Rheanna Gimple on Thursday October 13, 2016. The Class Notes belongs to LIFE 320-001 at Colorado State University taught by Ed K Hall in Fall 2016. Since its upload, it has received 6 views. For similar materials see Ecology in Biology at Colorado State University.
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Date Created: 10/13/16
Ecology Week 6: Social Systems Ecology: study of the relationships between organisms and their environment Interaction with “environment” includes: o Abiotic (light, heat, nutrients) o Biotic: interactions with other organisms Other species Organisms within their own species Positive Altruism Cooperation (+) Fitness incremen Negativ Spitefulness Selfishness t of e (-) recipient Negative (-) Positive (+) Fitness increment of donor Fundamental equation of behavior Net payoff= Benefits – Costs o Benefits: Fitness: number of children, fraction of children surviving, surviving another year o Costs: Something negatively affecting fitness: Calories Increased probability of dying Reduced fecundity Themes of social and behavioral ecology o Group living has both costs and benefits Animals form groups to: Increase their chances to: o Find mates o Avoid predation o find food individual vigilance for predators tends to decrease as group size increases food handling time decreases at group size increases Costs: Competition for resources Increased parasite and disease transmission Cheaters taking advantage of others in the population Mate competition o Relatedness determines likelihood of altruistic behavior Relatedness alters behavior Some animals (i.e. worker bees) do not reproduce, but behave to benefit close relatives Costs and benefits of behaviors maximize inclusive fitness o Total fitness of a gene responsible for a particular behavior Costs and benefits are from the gene’s perspective Calculating relatedness, r R = (1/2 x ½) + (1/2 x ½) = ½ Half-siblings: r= ¼ Full-siblings: r= ½ Cousins: r= 1/8 Calculating Inclusive Fitness o Every behavior has a: Cost to donor (C) Benefit to recipient (B) o There’s probability (r) of any two organisms sharing the same genes Parents and offspring: r = .5 Siblings: r = .5 Half-siblings: r = .25 Nieces/nephews and grandparents: r = . 25 Cousins: r = .125 o Can calculate that a behavior has a positive inclusive fitness when C<B*r Example: Male turkeys form “leks” (pairs of males) to do courtship displays, but only dominant male reproduces Males can try to attract female on their own o game theory: predicts behavior based on costs and benefits of actions prisoner’s dilemma: game theory example where two gang members are arrested and separately told that they will be released if they give up the other member. If neither talks they get a short sentence, if they both betray each other they each get a medium length sentence, and if only one talks the other goes away for the maximum sentence. There is a Nash equilibrium: Betray Medium length Betrayed gets sentence for both maximum sentence, other goes free Silence Betrayed gets Minimum sentence maximum for both sentence, other goes free Betray Silence Both players should stay quiet o Even though the best option is for both to be cooperative o Key is that solution is based only on rational self-interest In real world o Choices faced by countries dealing with climate change are a kind of prisoner’s dilemma Everyone benefits if everyone works to reduce Carbon emissions Strong incentive to defect and gain an economic advantage by not investing in reducing carbon emissions Will still benefit from other countries efforts Philosophical answer that there is no moral justification to defect Cooperation among unrelated individuals is rare but not impossible Key Point: sometimes costs and benefits of behavior depend on what everyone else is doing Conflict can reduce the fitness of selfish individuals below fitness of cooperative individuals o When most of society is cooperative, selfish individuals can gain advantage Hawks and Doves Example: when two individuals seek same resource Hawks: fight for resources o Win average of ½ the time, so benefit is ½*B o Fights are costly (time, injuries) so they lose C o Net benefits = ½*B-C Doves: share instead of fight o Net benefit = ½*B Examples: o Hawk meets hawk: ½*B-C for each Hawk o Dove meets Dove: ½*B for each Dove o Hawk meets dove: hawk gets B, Dove gets nothing Payoff for each strategy o Payoff depends on frequency of encountering each type P = proportion of hawks (1-p) = proportion of doves o hawks receive: p*(1/2*B-C) + (1-p)B always exceeds payoff of doves o Doves receive: ½*(1-p)*B o strategy with the biggest payoff will have the most reproductive success Evolutionarily stable strategy (ESS) o Hawk strategy is better when ½*B > C Society of all doves can be taken over by hawks, but society of hawks can’t be taken over by doves This strategy is an ESS o Conditions for stable mixed strategy When fighting has big cost so that ½*B < C, there’s a point where hawk strategy is not ESS Greater payoff to be a dove when there is a high hawk density There is a payoff equilibrium (peq in this strategy o History of ESS Nash equilibrium holds foundational mathematics of ESS John Maynard Smith applied the concept to evolutionary biology creating the ESS o Eusociality Eusocial organisms display most extreme form of altruism Traditionally defined by 3 characteristics: overlap of generations cooperative specialized castes of no-reproductive individuals o some individuals are sterile Examples: Mole-rates o Only two mammals are known to be eusocial Damaraland and naked mole rats Hymenoptera (bees, ants and wasps) o Haplodiploidy: Males originate from unfertilized eggs (Haploid) Females come from fertilized eggs (diploid) o Hamilton thought haplodiploid sex determination may give predisposition to Eusociality due to high relatedness Most hymenoptera are not eusocial High relatedness doesn’t necessarily lead to Eusociality Eusociality evolves in hymenoptera groups with complex nests and larval care Ecological conditions changing costs and benefits are likely drivers Spatial population structures Distribution in space o Organisms experience a place on the spatial scale of their movement o Places differ in “quality” Food, shelter, water, temperature, etc. o fundamental niche: range of physical conditions over which a species can persist o realized niche: predators, pathogens, competitors sub-set of conditions where a species is actually found smaller than fundamental niche o Niche modeling: Spatial distribution of a species can be predicted: 1. Map locations where species has been recorded 2. Graph “ecological envelope” or physical conditions where species is found 3. Use ecological envelope to predict other present and future locations where species may be Critical for conservation biology for reserve design and genetic preservation techniques o Why everything’s not everywhere Not every habitat is suitable Dispersal limitation: population is absent from a suitable area because of a barrier to seed/offspring movement Migration: regular or episodic movement of individuals to a different part of their home range Population structures o Dispersion of individuals Evenly spaced distribution: competition for water Antagonism between individuals Local depletion of a common resource Clumped distribution: vegetative reproduction of aspen Attraction between individuals Attraction to common resource Random distribution: neutral interactions between individuals and local environment o Meta-populations Population size influenced by Births, Deaths, Immigration, Emigration View of population structure vary in sophistication Metapopulation models: habitable patches (full or empty) separated by inhabitable barrier, occasional migration o Levins, 1969, 1970 Populations connected by dispersal are ephemeral with patch extinctions and colonizations occurring over time Levins/classic Mainland-island Stepping stone Source-sink o Basic metapopulation model is given at right with m the colonization rate, P the number of occupied patches and e, the extinction rate of patches dP/dt = mP(10P) –eP at equilibrium: dP/dt = ) -> P* = 1- e/m o assumptions of metapopulations: patches are in one of two states habitat is discrete time is continuous colonization and extinction can occur at any moment Source-sink models: looking at high-quality v. low quality landscape models o more complex -> can make species predictions from this o Ideal free distributions: where organism are free to move between patches with distribution proportional to availability of resources Behavior leads to ideal free distributions (IFD) Habitat quality is reduced by presence of competitors Switching among patches should occur when good patches become overfilled Each individual exploits a patch of apparent quality Assumptions: perfect knowledge of the habitat each individual can move to food sources at any time every individual can compete equally for the resource o Estimating population size Total population size = density * area Mark-recapture methods Capture a subset of individuals, mark them, and capture again N = total population size M = number of marked individuals .n = number caught in re-capture effort x = number of recapture that were marked Mark-recapture equations o Predict that the number of recaptures, x, is described by: x= nM/N o rearrange equation to calculate N, population size N= nM/x Assumptions of mark-recapture: o All individuals have equal probability of being captured o Population is not increased by births or immigration between marking and recapture o Marked and unmarked individuals die and emigrate at the same rate o No marks are lost Factors affecting estimate o Individuals that like being captured o Double marked individuals o Sampling near/far from reproductive event o A change in behavior o Dispersal Metapopulations to dispersal ecology Metapopulations have discrete structure o Extinctions and colonizations are distinct events o True Levins’ metapopulations not strongly supported in natural systems Dispersal ecology o Study of the effects of dispersal on populations o Reaction-diffusion equations: PDEs Turing’s chemical basis of morphogenesis Gives rise to complex patterns in time and space Continuous time and space model Traveling waves in continuous time and space have limited velocities o Discrete time, continuous space models Integrodifference equations Size of tail of kernel determines the rate of spread Leptokurtic dispersal causes accelerating invasions Size of tail not important for persistence, mean dispersal distance is Tail becomes important for dispersal in a flow regime, analogous to invasions at this point Good model for invasive species o Mechanisms of dispersal Environmental factors Food limitations Mating limitations Low Reynolds number flow Density dependent factors Threshold effects Locusts o Morphological changes o Behavioral changes Density dependent movement If population increases beyond threshold density dependent dispersal occurs Can continue to cause movement (cascade like effects)
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