Models in Ecology

“All models are false Evolutionary Fundamentals for Ecology but some models are useful” Principles of Ecology Sorts of Models (not exhaustive and not necessarily exclusive): Biology 472 – Verbal – Descriptive 6/22/99 – Quantitative – Predictive Objective Something All Models Share: Simplifying Assumptions Review the basic notions of phenotype, genotype, selection, and evolution. Give an example – Robustness: how many assumptions can you violate before the model becomes of the evolution of a simple trait controlled by a single locus (melanism in moths). Then seriously inaccurate? consider quantitative characters inuenced by many loci and by environmental factors. – Depending on the application of the model, the violations of the assumptions might This brings us to quantitative genetics. We will try to get through enough of that eld to actually be what you are interested in. understand what narrow-sense heritability is and we will review heritabilities for the sorts We will concern ourselves primarily with quantitative/predictive models in this course. of traits we will be investigating for the rst half of the quarter. You should always be asking yourself, “What are the assumptions of this model?”

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Some Review A Classic Example of Evolution

environment Genotype Phenotype → → → The pepper-moth, Biston betularia, and the Industrial Revolution Genotypes: the genetic “architecture” that the individual carries and which has a Two morphs—dark (melanized) and light chance to be transmitted to ospring Melanization controlled by a single autosomal locus (dark = dominant trait) Phenotype: this is essentially “what you see.” The outcome of a melting pot of genetic Before the Industrial Revolution tree trunks were lighter in color and environmental factors – Light-colored morph was better camoauged Evolution as change of gene frequencies Dark morphs hide better on soot-covered trees Natural selection operates through tness dierences between dierent phenotypes Over 40 generations the freq. of the dark morph increased from about 2% to about – Ultimately these are dierences in reproductive success 94% in some polluted forests. Dierential reproductive success and natural selection “become interesting” when there Kettlewell’s mark-recapture experiments is a correspondence between phenotype and genotype Two situations in which evolution on a trait has a hard time occurring: But this is all very simple!! – canalization: many genoytpes = single phenotype ⇒ The “one-trait, one-locus” paradigm doesn’t apply to more complex traits – environmental plasticity: when many dierent phenotypes have the same underlying genotype 2 3 Two Morphs of the Pepper-Moth Variation, Fitness, and Heritability in More Complex Traits

Many traits of interest are controlled by multiple genes Traits might be continuous Quantitative genetics is the eld that seeks to understand variation, heritability, and tness of such traits – A spectacular achievement of the 20th century – But very complex (a) Light on Unpolluted (b) Light on Polluted – Eagerly accepted since its inception by animal and plant breeders, but ecologists have been slower to appreciate its utility – Recently, however, that trend is changing For today we want to take home an understanding of: – Breeding Values – Heritability – Additive Genetic Variance

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(c) Dark on Unpolluted (d) Dark on Polluted

Consider a Quantitative Trait Hypothetical Population Distribution of Tarsus Length

How about tarsus length in red-legged grasshoppers

2 3 4 5 6mm

There is variation from Genetic and Environmental sources 6 7 Total Phenotypic Variance = VG + VE ( + 2CovG,E) The “Breeding Value of an Individual” Additive Genetic Variance

This is the amount of variation in a trait that can be explained by applying to it a very The Breeding Value of an individual may be obtained by a thought experiment: simple model of genetic variation. Namely: – Produce many ospring by mating the individual at random with the rest of the population There are many loci of small eect – Compute the mean tarsus length of that individual’s ospring The contribution of each locus to the trait only depends additively on the number of – Multiply by two the dierence between that gure and the population’s mean tarsus length alleles (0, 1, or 2) of a particular type at that locus – That gives you the individual’s breeding value Hence this model does not include dominance or epistasis Consider doing that with every individual in the population and looking at the distribution of breeding values over all the individuals in the population The additive genetic variance is, however, that which is most available to alteration by The variance of that distribution of breeding values equals the additive genetic variance. natural selection This is the most important part of the variance of phenotypes that can be attributed Thus one denes “heritability in the narrow sense,” or h2 as the proportion of the total to genetic dierences. phenotypic variance accounted for by the additive genetic variance VG = VA + VD + VI

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Estimates of Heritability in Wild Populations Using Quantitative Genetics to Study Evolutionary Ecology

From Mousseau and Ro (1987) as presented in Stearns (1992): Heritability estimates In addition to allowing people to estimate heritabilities and selection pressures on for dierent types of traits in populations of wild animals. traits, a quantitative genetics perspective is available for learning more about the genetic constraints on evolution (genetic correlations between traits that could impede evolutionary progress). Life History Physiology Behavior Morphology n 341 104 105 570 Given this it seems as though it would provide a worthy paradigm for analyzing the Mean Heritability 0.262 0.330 0.302 0.461 evolution of ecological strategies. However, in behavioral ecology the quantitative genetics S.E. 0.012 0.027 0.023 0.004 perspective has been rarely adopted. Rather, people have traditionally used optimality models and game theoretic models. We’ll see those starting on Thursday, returning to In studying evolutionary ecology, we will focus on Behavorial traits and Life-History a more quantitative genetic perspective when we look at the evolution of life-history traits strategies later in the quarter.

10 11 Historical Backdrop for Optimality Models Optimality Models and Game Theory

Principles of Ecology Late 1950’s and early 1960’s amongst geneticists Biology 472 – Well after the appreciation of the Neo-Darwinian synthesis – Neutral Theory of Evolution gaining more acceptance 6/24/99

Mid 1960’s amongst ecologists – Rapidly increasing interest in role of ecological strategies – Sought ways to analyze strategies – Developed an adaptation-oriented perspective

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Strategies for Successful Reproduction in Salmon Evolutionary Ecologists are Interested in the Evolution of Strategies Females establish spawning territory. Males compete with one another for access to females. Study the fate of dierent strategies in populations Two distinct strategies for males: Why are some strategies present and some not? 1. Get big and compete heartily The classical, genetics-based approach would be to: 2. Mature young and very small and hope larger males won’t harass you 1. Establish strategy heritability 2. Observe variability in strategies in population Strategy 1 is adopted by most individuals: much allocation to somatic 3. Document tness dierences and hence selection for particular growth and development of secondary sexual xters (erce jaws) strategies Straregy 2 is adopted by “jacks”—males at least one year younger than Ecologists seldom do this. Instead use Optimality Models or Game most. They allocated much less to somatic growth, and much more Theory energy to the growth and early maturation of their gonads.

– Sneaking 2 3 Strategy: a behavior or trait that accounts for energy input into different aspects of Assumptions for Optimality Models life

The Big Assumptions (that are seldom tested)

Growth 1. Strategies are heritable

2. The optimal strategy was available for selection long ago in the population Reproduction 3. The strategy has been subject to a fairly constant selective regime over Foraging some time, so the optimal strategy has had a chance to be selected in the population

Survival/Defense 4 5

Steps for Developing an Optimality Model Constraints and Trade-os

1. Choose a currency—Should be a limiting resource Constraint: a restriction not subject to change by evolution food, protein, access to mates, (ENERGY or ENERGY/TIME) Trade-o: a relationship between two things which is modiable by evolution 2. Quantify the costs and benets of dierent strategies in terms of the chosen currency

3. Find the optimal strategy subject to assumed constraints and trade-os There may be many genetic constraints, but these are typically assumed not to exist 4. Test to see if individuals in a population are using the optimal strategy

6 7 Criticisms of Optimality Models Optimal Foraging in Fine Grained Environments—Macarthur and Pianka (1966) Optimal The strategy investigated may not actually be under selection Number of Prey Items It presents a hypothesis that isn’t really falsiable. Consider the The goal was to predict the optimal diet breadth—i.e. how many prey interpretive options if optimal behavior is not observed: items should an individual exploit – We chose the wrong currency – We chose the wrong cost-benet function for the strategies This was a cost-benet analysis—nding a balance between: – We did our experiment incorrectly – Time Spent Searching for Food – These critters truly fail to behave optimally – Time Spent Handling Food

Want to maximize long-term food intake per unit time The dierent strategies are ”Dierent Number of Prey Types in Diet” 8 9

Assumptions The Optimal Strategy Minimizes Time Spent per Unit of Benet From Food

The standard optimality assumptions about evolution Let: Environmental structure is repeatable (not patchy) T (n)=total time spent searching and handling for a set a given amount “Jack of All Trades Assumption” of food when the diet includes n prey types – The animal can’t be good at handling all food types TS(n)=amount of time spent searching in order to obtain a given amount of food when the diet includes n prey types However, assume that the animal can linearly rank prey items in terms of their Energy/Time (i.e. Benet/Time) TH(n)=amount of time spent in handling prey in order to obtain a given amount of food when the diet includes n prey types In addition to Handling Time for items, some time must be spent searching for items as well. The “Jack of All Trades Assumption” does T (n)=TS(n)+TH(n) not apply to searching

10 11 Evidence from the field: • 3 size classes in rank order of energy gain per Crabs behave somewhat as one would expect: Shore Crabs and Mussels unit of handling time. 1, 2, and 3. Comparing to “coin-foraging” Elner and Hughes 1978 • The Manipulation: Fix the proportion of dif- ferent sized mussels but vary the overall • Our foraging experiment with pennies, abundance (# of each class in a given area). nickels, dimes, and quarters was similar: • The Observation: Proportion of each size • The handling times for each coin type class eaten under different abundances. Size Class---> 1 2 3 were equal, but the “energy-gains” followed • Shore Crabs forage for mussels which come Low 24 8 the value of the coins. in different lengths. Abundance • Different gain/time values for different (Available) coins • Different length mussels provide different Low 30% 65% 5% amounts of energy per second of handling Abundance • Under high abundance, participants could time. (Eaten) be more selective for high-value coins, even High 10 20 40 • Elner and Hughes collected mussels of 3 Abundance when there were many more pennies to be different sizes and measured crab energy gain. (Available) found. High 60% 35% 5% • 1 Abundance • This phenomenon can be predicted by the 2 (Eaten) graphical analysis we did relating to Mac- • • The Conclusion: The crabs are foraging in a Arthur and Pianka’s diet breadth model. 3 size-selective manner AND they get more se- • lective at higher abundances. Joules/Sec of Handling Joules/Sec of 4 cm • Note though, they still sample unprofitable Mussel Length size classes.

A tidy graphical result: The Effect of ∆-ing Abundance A further experiment: MacArthur and Pianka revisited • The goal of the Brown Trout Prey Selection optimal foager is to Ringler (1979) • Thinking in terms of crabs and mussels: Prey Classes: minimize time per • Searching and handling are mutually exclusive • Brine Shrimp (15 Joules) energy yield which is • Call different mussel lengths the “prey • Small Crickets and Mealworms (104 J) the dotted line to the types” • Large Crickets and M-worms (230-240 J) • Energy per handling time greatest by special- right: izing on size class 1. And decreased when # of prey items in diet • Aquatic “Conveyor Belt” for food more size classes are added. • Increasing the abundance shifts the search time • Expmter can manipulate “search times” • This is equivalent to noting that handling time curve down and to the left--decreasing optimal • Fish can’t handle two prey items simultaneously per unit energy increases when more size diet breadth. Red = Low Abund. Green = Hi Abund. • Manipulation: Different arrival rates and diet qual. classes are added to the diet. A xx x Time Spent Searching x for An Item x Time Spent per Joule from x

an average item KJoules per day x B Time Time Low------>Diet Quality------>High A = Optimum predicted on highest quality diet B = Optimum predicted on low quality diet (only # of prey items in diet brine shrimp) • Brown trout never achieved their optimal energy Seabirds and shell-breaking: Example 1: intake at the high quality diet, because they kept Revision of Optimality Northwest Crows and Whelks sampling the lower quality brine shrimp (and Zach 1979 hence missed some high quality food oppotunities. Hypotheses---Examples • Why? Look back at assumptions: • Three Examples: • Crows drop whelks on rocks to break them open • Maybe trout can’t rank prey quality • NW Crows and Whelks • Perhaps more learning of rank quality is needed • Several Observations: • “Ambient Background Sampling” may be • NW Crows and Mussels • 5 Meter Drop Height advantageous if novel prey types appear or if handling • Oystercatchers and Mussels • Re-Drop Until they break times can be decreased through learning: • Encapsulate the Adaptationist reply to criticism • Choose to drop only large whelks •Morgan 1972 with Dog Whelks eating a novel from non-Adaptationists mussel variety. Over 60 days handling time per • Demonstrate what is deemed relevant to the mussel decreased threefold. • Currency assumptions may be wrong---maybe energy optimal foraging modeler: isn’t the limiting factor. • Finding plausible explanations for behavior • There are quite a number of models that try to account for • Not trying to prove that evolution has made such factors--->complicated mathematics. everything the best that it can be. • Maybe there are too many constraints/ • Optimality is the tool---not the hypothesis complexities for evolution to produce optimally that is being tested! feeding trout. • The hypotheses to be tested are the assumptions made about currencies and cost/ benefit functions relating currencies to fitness. • Start with simple assumptions and only make your model more elaborate if necessary Optimality Assumption: Crows maximize energy gain per energy spent handling whelks.

Example 2: Example 3: Hypothesis to be tested: •Crows behave as they do because their NW Crows and Littleneck Clams Oystercatchers and Mussels energy gain is highly dependent on getting the Richardson and Verbeek 1986 Meire and Ervynck 1986 whelk to break. • Crows must find clams in the sand and dig up •Oystercatchers eat mussels, but break them • Tests: • Once they dig them out, they drop them on with their beaks. •Drop whelks from different heights rocks to break them •Drop different sized whelks • Mussels of 29 mm are abandoned without even trying to open them 50% of the time. •Results: • Mussels >32 mm are always dropped on rocks •Large whelks break more easily •(Small whelks almost never break) • The obvious Hypothesis, extrapolating from •Probability of breakage the same for each Zach: drop Hyp #1: Large clams break more easily •Increased breakage minimal above 5 m •The Test: Not true!!

•The Revision: •First M & E only looked at the energy content of Hyp #2 Little clams are left behind because mussels that birds successfully opened. larger clams yield more energy • Large ones took longer but were still more profitable • Measurement of mussel energy content is Hyp. 1: Oystercatchers should utilize consistent with Hyp #2 the largest mussels they can find Moving to a related, but new topic: Foraging in Patches A The Patchy Env. Problem •Environments are not always “repeatable” as assumed in MacArthur and Pianka’s model Example: Great Blue Herons and backyard fish ponds Profitability B •Food is typically clumped. Examples: • Grubs in logs •The Habitat consists of all the fish ponds the GBH Mussel Length • Flowers of particular plant types can visit •The Patches are the fish ponds themselves Hypothesis 1 is based on Model A • In Seattle--Lawns for geese and robins •How a Theoretical Ecologist Might View •GBH seriously reduces fish abundance--- •OOPS! Reconsidering the data, some large diminishing returns over time in each patch mussels are impossible to open. Patches: •Leads to Model B which yields • Decision that must be Hyp 2 An intermediate size made: at which point will be optimal does the GBH decide that patch profitability The Model Predictions didn’t quite fit the data: has been reduced Finally it was discovered that enough that it is time to length was confounded with move on to a new patch. barnacles. Barnacles interfere with opening, and are more likely to be found on some (but not all) big mussels. Forager must now search for patches and then Key Point = Constant decide how long to stay in each patch. Revision of Hypoth.

Another classical graphical result Long Travel Time Optimum: The Marginal Value Theorem Basic Results of MVT Charnov 1976 • Forager should leave patch when its Assume: instantaneous rate of energy (food) gain is •Many copies of one type of patch dispersed through equal to the average rate of food gain the habitat Average Rate of Energy Gain in Long Travel Time Habitat (averaged over the whole habitat)

•All patches have the same “depletion curve” •Longer average travel time between patches •Fixed travel time/costs between patches travelling-----> spent time 0 time in patch-----> should lead to longer patch residence times •Desire to maximize long-term average energy gain •Could extend to variable patch quality; •Bizarre Axis System: foragers should stay longer in better patches

Depletion Curve Short Travel Time Optimum: • Empirical work on seeing if animals respond to MVT-based cues is very difficult • Hard to discriminate which cues the forager is really using to make decisions about staying in patches

•Consider observations on the aardwolf, time spent travelling-----> spent time 0

time in patch-----> Ave Rate of E Gain in Short Habitat Proteles cristatus, foraging on patches of its time spent travelling-----> spent time 0 time in patch-----> favorite termite species, Trinervitermes bettonianus, in the Serengeti. One arena where MVT ideas/results figure nicely: Answer: Soldier Termites filled with terpenoids. Aardwolf seeking termites Central Place Foraging Forages by cruising over the grasslands slowly, So, do you say that they are leaving the patch Basic Notion: Animals forage outward from a Starting 3 hours before because they have depleted the edible termites, or central “home-base” to which they return dark and continuing until are they leaving because they can’t stand the dawn. taste? Especially germane when animals bring food back: Don’t seem to use olfactory • Rodents/Squirrels storing food SO WHAT? The point is that there are many • Bird foragers bringing food back for offspring cues to locate termites cues that animals may respond to. Other issues: Two Classic Experiments: Use their ears instead! •Is it reasonable that animals can monitor •Squirrels feeding on manipulated sunflower-seed patches • Manipulated distance of different sunflower patches (They cancel all foraging for rainstorms---can’t “instantaneous rate of food intake” when prey • Squirrels spent longer feeding at the more distant hear the termites!) arrive as discrete chunks? seed patches, and filled their cheek pouches fuller •Not a great fit with MVT predictions though (Kramer When they find a colony of termites they root Simpler explanations for patch-staying behavior? 1982) Could be a simple “turning rule” based on how through the dirt with their noses, and lick up the •Starlings trained to get food from a “decreasing termites much food has been obtained in the last few profitability mealworm dispenser (Kacelnik) minutes. Search theory: a well developed field of inquiry Maximizing After they’ve left though, you can run over there energy gain to and still find plenty of termites milling around, just into these questions self? or energy Computer lab this week asks you to optimize delivered to there for the taking? Why did they leave the chicks? patch? intake of a silicon gopher given simple search/ foraging rules. 2 different things!

A new topic: Further Manipulations by Real: Multiple Foragers at Once Risk-Sensitive Foraging •Swap Flower colors. So that the blue flowers are the Charnov and Stephens constant ones Simple notion that is often invoked: •Result: bees prefer blue then! Up until now, the optimal in optimal foraging • Try a different nectar distribution in “risky” The Ideal Free Distribution: has meant “maximizing the long-term average flowers: 2/3 get 0.5 µl 1/3 get 5 µl rate of food intake” but consider experiments Same result--->Bumble bees don’t like to gamble. Foragers will disperse themselves amongst patches by Les Real with bumble bees (Bombus): or across habitats so that their individual gains are Notice: in all of these trials, the mean rate of food intake maximized Two Colors of Imitation flower: is the same between flower colors, but the variance of what the bee gets from any one flower is zero for one of In terms of aggregate behavior this means the the flower colors (constant 2µl) and positive for the other animals distribute themselves with respect to both flower color. the quality of resources and the number of competitors In the jargon of the field we say that these bumble bees are Risk-Averse: Example: Milinski and more stickleback • They will go for the food that gives them the experiments. all yellows filled 1/3 of blues have 6 µl constant reward rate with 2 µl of IFD assumes that animals are free to move where 2/3 have 0 µl artificial nectar • The opposite of Risk Averse is called Risk Prone they want to. So long term average rate of food intake would be • Question? Why would any critter in its right mind be Akin to the ideal gas law the same while visiting either flower color. risk prone? We’ll see this again as an assumption in the Cartar However, the bees overwhelmingly prefer the paper yellow flowers. Risk Sensitivity Z-score model In its simplest form: •Discrete choice nature of the model---either Provides a way of explaining risky versus non- predicts risk-averse yes! or risk-prone yes! •Two different meanings for “Risky risky food choices when the sum of all the food Foraging”: items must exceed some threshold (i.e. survival is •Hunger-level sensitive risk-sensitivity •Risk of Predation a step function of energy obtained) •e.g. energy stores accumulated over the day in order to •When energy-reserves are depleted animal •Example: Another Milinski stickleback survive the night should be more risk-prone. epxeriment •Assumption that food is obtained in small parcels •Forms the basis for the hypothesis in Cartar’s •Risk of variable food payoff* throughout the “day” and food quality of items is independent from one to the next bumble bee paper. Bees facing energy shortfall •Les Real’s bumble bees and paper flowers •(This requirement satisfies the Central Limit Theorem should forage on assumptions. CLT yields normal distribution) •Definitions: the more variable Low Risk (low variability) •Risk-sensitive 0.4 food Dotted lines are (but equal mean) hypothetical payoff flower type •Risk-averse 0.3 High Risk (low thresholds variability) •Risk-prone food 0.2 •Why be risk-prone?

•Threshold requirement condition Probability Density 0.1

95 100 105 110

Total Food Accumulated in the day

Going over Cartar 1991: Natural History Features Brood Clump Estimating profitabilities of flower types: Life on the island: Three summers on Mitlenatch and 1. Measure nectar levels at the end of the day •Bee Colonies Transplanted from S-F U. campus HoneyPot ---the 2. Measure time required for bees to forage on •Cycle of Bumble bee colony communal feed- the different flower types ing trough •Hive temp (Quite a lot of work!) •Energy reserves 3. Combine those estimates into profitabilities

Main result: Same Expected Profitabilities Two types of plants provide nectar for the BUT dwarf huckleberry was more variable. colonies: • Seablush AHA! Two different food types: •Dwarf huckleberry High Variance = Risky Figure legend: The development of a free foraging B. terricola colony. Cumulative totals of the bees are given by the shaded symbols. The open circles signify the actual number of workers in the colony at that date. source: http://indecol.mtroyal.ab.ca/bumble/ The big assumption about nectar levels in flowers and A Dwarf huckleberry congener is: A Laboratory- raised colony Low Variance = Not so risky The “Null-Hypothesis” is an Ideal Free Distribution type of prediction •Two flavors of the IFD argument •Both qualitatively predict that risk-aversion should decrease when energy stores decrease Applications of Foraging Theory Honey Pot Manipulations One final flavor of optimal Artificially creating the spectre of energy shortfall in Conservation and Solving •Between 1430 and 1600 in the afternoon he foraging “Ecological Problems” drained some honey pots and added sugar Up to now we have considered two different solution to others “currencies” that foragers might be optimizing. •Scientific Method things to Note: OK...How can we use this stuff? •Randomization 1. Long term average intake •Minimization of carryover effects There’s not an over-abundance of examples •Balancing the number of foraging bees 2. Probability of meeting minimal requirements Three though: •Results: Counting Color-coded bumble bees •Schmitz (1990): Evaluating Treatment A final currency you should know about is time supplemental feeding programs for Reserves Reserves Enhanced Depleted required to satisfy nutrient requirements white-tailed deer •Monaghan (1996): Using seabirds to Dwarf H. 24 (47%) 61 (68%) (optimization now means “minimization”) Seablush 27 (53%) 29 (32%) •Different than long term average intake monitor fish populations •Overall intake may affect fitness less than, say, •Luck (long-term programme) biocontrol avoiding being preyed upon or succumbing to of citrus pests *Only late in the afternoon. climatic extremes while foraging: •Example: desert ant colonies *Statistically significant differences in the above table. Bottom line: the proper currency should be •Indicates a preference for the “higher risk” flower intimately linked to fitness! when stores are depleted (wow...even with other avenues available to them---more foragers, nectar/pollen switch, etc.)

Extensive OFT modelling in White-tailed deer Schmitz’s OFT Model Data and Inputs Assume that deer will forage optimally, then Brrrrrrrr...a long, cold winter watching deer. Schmitz 1990 develop a model to predict what they ought to be Majestic beasts and also val- eating. •Rumen volume and turnover times uable for sport hunting econ- •Bulkiness of different forage types omy. Optimization of diet types subject to three factors •Time deer can spend foraging vs. temp which he calls his three constraints: •Cropping rates (how quickly can they browse) •Truly charismatic megafauna •Measured many twigs •Northern latitudes/harsher winters 1. Processing Constraint •Energy requirement model •Supplemental feeding programs “ad libitum” 2. Time Constraint (How long can a deer forage Observed Behavior: per day? •Non-supplemented deer foraged as predicted Important question: How effective and efficient by the energy-intake maximizing criterion are these supplemental feeding programs. 3. Energy constraint (how much is required?) Schmitz claims it is not sufficient to just survey •Energy typically limiting in northern environments in •Optimal Behavior for supplemented deer the winter....good! food use by deer in supplemented and non- would be to “eat nothin’ but the good stuff” supplemented areas: Investigated the optimal diet composition subject •Implication: Supplemented deer not being as “The efficiency of feeding programs can only be judged to these constraints using two different efficient as they could be. by predicting diets deer should select in different optimality criteria we’ve seen before. They environments and comparing how well their diets match were: •Interpretation and management implications the predictions.” --- Oswald Schmitz Feeding stations and such... Surface Feeders: Fisheries and Seabirds Bird-Related Indicators for Fish Abundance Monaghan and colleagues’ long term study investi- gating: •Inextricably intertwined: Arctic Tern --> •Historical sideshow-->Seabirds Preservation Act •Colony breeding numbers of 1869 in Britain •Reproductive parameters •Body condition •Fluctuations in fish popns due to fishing has a •Diet Composition great impact on seabird populations •Foraging Behavior*

•Some background on fisheries stock assessment <-- Kittiwake •First three not very reliable because changes in and the “development” of fisheries foraging behavior could compensate for some effects •Monaghan works on Shetland seabird colonies. •Foraging behaviors of diving birds changed •Main fishery = lesser sandeels. Yearly harvests noticeably---birds worked harder! in the North Sea around 10 BILLION kg! •Surface feeders also changed their behavior: •Small fishery opened for sandeels in 1974, Diving Birds: •Longer foraging journeys when abundance was low peaked in 1982, then guess what happened? (recall central place foraging) •Could reliably monitor by recording time that both •Populations of surface feeding birds had greatly Guillemots and shags parents remained at the nest reduced reproductive output •Diet Composition is potentially useful (clearly) •Diving birds not so badly hit but would require much more work (empirical and theoretical) to make it a reliable indicator

On to a new topic: Territoriality

•How I would like to traverse this topic: •Definitions •Varieties of Territorities •Phyletic perspective on territoriality

•Costs and benefits of territories •More optimization ideas

•Mechanisms of territory maintenance •Some game theoretic ideas

•Effects of territoriality on larger ecological issues Definitions of Territoriality Not a Home Range! Varieties of Territory There are many. Huntingford and Turner’s defns are specifically One end of the spectrum---Odum: geared toward distinguishing territory from h.r. A bit ad hoc: •“An actively defended home range” 1. Based on Resource that the owner gets •“At the risk of offending semantic purists we are Home range is basically just the area in which access to: including under the heading of territoriality any active mechanism that spaces individuals or groups apart from an individual tends to restrict itself food one another, which means that we can talk about territoriality in plants and microorganisms as well as in Example of coatis: mates shelter animals.” Exclusive home ranges but not territories. •Huntingford and Turner---A Behaviorally defined notion. Territorial behavior has 4 components: 1. Site attachment also nest sites 2. Exclusive use of the area 3. Agonistic behavior 4. Attack changes to retreat at the territory 2. Length of Time defended. boundary Ranges from hours to year-round

Typically refers to an area in space rather than a 3. Defended by whom and how many? mobile resource (for example red deer stag and Single individuals versus mating pairs, etc. his harem of does)

Yarrow’s Spiny Lizards on Mt. Graham Phyletic Perspective on Territories Population-level consequences Studying the phyletic a. Biol. Of or pertaining to the development of a A fatal blow for the Ideal Free Distribution species or other taxonomic group. effects of test- concept. osterone implants Winn 1954. Territoriality in Darters (fish) in male lizards. Thus, Natl Seln may act to increase (Marler and proportion of territorial animals in a Moore) population. A continuum of territorial behavior across closely related species from “more primitive” to more recent/more specialized: •Percina caprodes---lake dweller, non- Costs and Benefits of Territoriality territorial Benefits: •Hadropterus maculatus---drive other males •Food: lasts longer, lower depletion rates, less away from females variability in supply •Mates •Etheostoma (2 spp.) defend females and •Offpspring rearing (female salmon) remain near landmarks •Lowered predation (due to nest dispersion) •E. blennoides---high aggression and fixed Costs: territories. •Acquisition •Displays and patrolling •Possibility of injury (though not very common!) •“Single-Use” Territory •TTP (Displays and Patrolling really are costly!) How Large a Territory? African Bee-eaters: Conditional Territoriality Another simple graphical framework: Live in mud- Some animals are bank colonies, territorial at times and but forage in downright gregarious at separate other times. foraging terri- tories that Bellbirds in New they defend Zealand. against intru- ders Fitness Currency Extra 25 kJ/day from switching to terr. behav. under low food density Communal feeding area close to home: XY 100 mg insect/hour average Territory Size Rypstra (1989) studying a social spider: Defended, distant territories •Low Food Density---solitary and highly territorial 250 mg insect/hour average! The optimum occurs where the slopes of the •Hi FD---social. aggregations spin webs and individuals are free to go where they will. Fewer cost and the benefit curves are equal (That is insects escape from the group webs. Yet, some birds abandoned their territory to feed where the marginal benefits of a larger territory start to •The bee-eater mystery close to home. Why?!?! decrease faster than the costs are increasing. ) •One would expect that individuals that voluntarily Curve shapes will depend on environmental quality and choose to be non-territorial will do so because there is Once again (as in the starling, central place population size relative to limiting factors not an energetic advantage to holding the territory. foraging example---bringing food back to chicks

Explanations for Territory The Resource-holding Power The Payoff Asymmetry Maintenance Asymmetry Hypothesis Hypothesis

Two interesting observations: Territory owners are bigger and stronger by 1. Most territory owners don’t forfeit their nature. There are certain costs to establishing a new territories in conflicts with intruders territory, initially 2. Things don’t often escalate to full-blown This generates predictions: fighting but then the payoffs increase over time because you have an “agreement” with your familiar Why could this be? We’ll look at three neighbors explanations. Two testable predictions: 1. If you remove an individual, and let somebody take 1. The “Arbitrary Rule” ESS over his territory, he is less likely to regain his territory if hypothesis: Beewolf wasps (O’Neill 1983) you keep him captive longer Pseudoscorpions (Zeh et al. 1997) 2. The duration of contest to re- Damselflies, endurance flying, and fat gain the territory should increase reserves (Marden and Waage 1990) with increasing time of being away from its original territory

Speckled wood butterfly and sunspot Krebs 1982: found these trends territories. (Davies 1978) But note red-winged blackbirds (Shutler and BUT---not a properly controlled Wetherhead 1991) experiment Testosterone enhancement in lizards Taken from Alcock 1998

Energetic costs of territoriality. Males of Yarrow’s spiny lizards became unusually territorial during the summer when they received an experimental testosterone implant. (A) The experimental males spent much more time moving about than did control males. (B) Testosterone-implanted males that did not receive a food supplement disappeared (and presumably died) at a faster rate than did control males. Testosterone- implanted males that received a food supplement survived as well or better than controls; thus the high mortality experienced by the unfed group probably stemmed from the high energetic costs of their induced territorial behavior. (Source: Marler and Moore 1989, 1991) The arbitrary-rule hypothesis. Experimental evidence. (Taken from Alcock 1998)

The resident always wins? An experimental test of the hypothesis that territorial resident males of the speckled wood butterfly always win conflicts with intruders. When one male (“White”) is the resident, he always defeats intruders (1,2). But when the resident is temporarily removed (3), permitting a new male (“Black”) to settle on his sunspot territory (4) then “Black” will defeat “White” upon his return after release from captivity. (Source: Davies 1978). But note that this was in a condition when sunspots were plentiful, and unoccupied ones were frequently available nearby. The Payoff Asymmetry hypothesis test by Krebs on great tits. (Taken from Alcock 1998) In great tits, the more time a new resident has been on a territory, the longer the fights between that individual and the oringinal resident (which was temporarily removed from his territory by the experimenter). (Source: Krebs 1982) Examples related to the resource-holding power asymmetry hypothesis: taken from Alcock (1998)

Body size, territoriality and reproductive success in a tropical pseudoscorpion. During the genertions when the pseudoscorpions are living on trees, where males are not territorial, being large carries no reproductive advantage. But when the tiny pseudoscorpions disperse on the backs of beetles, males fight for space, favoring large individuals. As a result, the mean size of males shifts upward during the dispersal generation by an amount shown here

as S1. (Source: Zeh 1997)

Resource-holding power and the resident advantage in a beewolf wasp. The graph plots the size of the original resident (as measured by head width) agtainst the size of the replacement male that occupied his territory upon his removal. Points that fall above the ascending line represent cases in which the oringinal resident was larger than the replacement. (Source: O’Neill 1983) 2. Sexual ritual or calling behavior between males Purposes of Signals and females Tungara Frogs Fireflies Animal Signalling and 1. recognition of species, individuals, neighbors, castes (social insects), kin, or demes 3. Establishing territories and/or social status Communication •Bird-song differences between species: are they Red deer, red-winged blackbirds adaptive? •Allopatric Speciation 4. Alarm calling •Hybridization zones Ground squirrels •If hybridization decreases fitness, we’d expect Outline: Great tits and other birds subject to raptor predation greater song differentiation in areas of closely- 1. Purposes and variety of Convergent evolution in “seet” calls related species overlap. signals •Gill and Murray (1972): Compared bird songs of 2. Signals in evolutionary context golden-winged and blue-winged warbler in areas of species 5. Information in groups of foragers Tactical components overlap and non-overlap Honey-bee example. The Sensory exploitation “Waggle Dance” Unintended receivers •Songs were less 3. Evolutionary thought on signalling varied in areas of Number of waggles gives •Strategic components overlap, perhaps info re: distance to food •Honest and deceptive signals because it was •Zahavi’s handicap principle adaptive to be more Direction of the straight- 4. Specific examples in territorial behavior specific. run gives info regarding •But this is a lone the direction toward a study amongst Golden-winged warbler food source. many that suggest bird song is not so important for species recognition.

Tactical Components 6. Parental care: offspring/parent recognition Signal Components “Getting the message across” Studholme (1994): Example from Johnstone (1997): Anoline lizards Fiordland penguins Tactical Components: and the “assertion display” versus the “challenge Offspring orient to and Features of a signal which are concerned display” respond to their parent’s with how easy it is for the signaller to calls more than other calls. (But parents seem transmit it, for the receiver to receive it and less responsive to their discriminate it from other signals. particular offspring’s call.) Strategic Components: The assertion display is not Properties of a signal that are concerned sent out to anyone in parti- with what good they do to the signaller, i.e. cular. But it “ought” to be how does the signaller benefit from emitting noticed by some other lizard. the signal. Conveying Hunger levels: •Common features of signals ensuring their appropriate reception: Adult birds bringing food back Both have been viewed from an adaptationist 1. Conspicuousness for nestlings. The hungrier nestlings perspective. 2. Stereotypy analogy to electronic signal transmission could scream louder. 3. Redundancy } 4. Alerting components Tactical Components and the Back to the Methodology Zone for a moment: The Nasty Statistical Issue: It is important to know if the observed relationship Environment The Comparative Method between the two variables in statistically significant. Signals’ conspicuousness seems to have evolved with However a simple linear regression (put a least- respect to the environmental background. •Definition: squares-fit line through the data and then test to see •Marchetti (1993): Plumage patterns of congeneric Quite often, the relationship between two traits, if the slope of the line is significantly different from warblers. Those living in low light environments had OR the relationship between an environmental zero) is invalid because it assumes that all the brighter plumage. characteristic and an organismal trait will be observations are independent. •Wiley (1991): Comparison of song-birds in North explored by comparison of the traits and American habitats. environments across species (or other taxa). But in the comparative method, the different points •Rated sonograms of birdsongs for The goal is to demonstrate a significant are not independent. They are related by their •period of repeat of elements correlation between the two traits in question, or common phylogenetic history. Consider: •buzzes between the environmental conditions and the trait. This, then, might be taken as evidence of •side-bands oo o adaptation. This process is called the o o •Categories for habitat type (i.e. grassland versus o forest, etc) Comparative Method. x xx x •Songs from birds in open habitat had more •Example: Length of Rep. El. reveberation-degradable features than songs from Studying, for example, the length of a repeated Env. Reverb forest habitats. element in bird songs versus the amount of x reverberation from the environment x x x xx each x represents a x x x different species o x o x xx x o

Some Sonograms of different birdsongs Length of Rep. El. o Env. Reverb o

If the X’s and O’s are more closely related to one another, Tactical Components and the Tactical Components and evolutionarily, then the observations in the cluster of X’s and the cluster of O’s are not independent of one another. “Audience” Unintended Audiences “Color blind organisms should not have colorful A simple linear regression will treat each point (species) as displays or signals.” Any time an animal is signalling, the message if it were an independent observation. may get picked up by an unintended receiver The Result: too much statistical significance inferred. Sensory Exploitation: (for example a predator). When signalling behavior evolves to take advantage of In reality, bird species of the “x” cluster may have all pre-existing sensory biases. Two types of alarm calls in great tits: inherited a mutation that shortens the length of song Proctor (1991): male water mites Mobbing alarm call: loud indiscreet signal to elements, and they may live in less reverberative “tremble” at a similar frequency to others to mob and molest a perched hawk. environments, but the two may not be related. prey. The females are acutely sens- itive to this (being part of their for- “Seet” alarm call: short, high-pitched, discrete There are methods to try to correct for the non- aging behavior repertoire). alarm call given to warn others of a flying hawk. independence between closely related species (for example Felsenstein (1985)). The female grabs at the The frequency of the seet call is high enough that These are what Johnstone is referring to when he uses male who somehow con- hawks cannot hear it very well, but it is well within phrases like “incorporating various measures to control tends with the female’s the range that great tits can hear well. fro the effects of phylogeny.” mouth parts, and is able to effectively mate with (Studies with hawk orientation to recorded seet her. calls.)

Was this sensory exploita- tion? (Proctor 1992) and phylogenies. The Evolution of Strategic Signalling and Conflict of Honest Signals Interest Components of Signals An honest signal is one which reflects the true state of Signaller and Receiver don’t always stand to benefit in the sender by virtue of physical necessity Traditional Ethological View (Pre-1970’s) the same way •Signals were there to “facilitate and coordinate Examples: social interactions by making information available Examples: Hill and Montgemorie (1994): Correlation between to be shared.” Displays of territory owners coloration and nutritional condition of male house •Reasonable for cooperative signaling--- finches •When both the signaller and the receiver In some species males seek matings with as many benefit females as possible while females seek to mate with •Deceit was not commonly considered, even the “most fit” males though it was well-known on an inter-specific level, i.e. Batesian mimicry: Early 1970’s. Maynard Smith and game theory for signalling---without appropriate controls deceit should abound and signals should evolve to become meaningless.

Since signals are not all meaningless, something has Clutton-Brock and red deer roaring contests maintained their honesty or utility. What? Two main (and related) types of explanation: Also, frog-croaking tone. Small frogs •“Honest Signals” are unable to croak at the lowest freqs. •Handicap Principle Main point = direct link between the ability to generate the Viceroy Butterfly Monarch Butterfly These reflect other evolutionary pressures that may be signal and the physical condition or foraging ability (taken Basilarchia archipus Danaus plexipus acting on signalling behavior to be a surrogate for fitness) of the signaller

Another way (in theory) to curtail deceit Handicap Principle At the heart of the Handicap Principle are (Zahavi 1975 and later) Condition-Dependent Cost or •Similar to the Honest Signal notion, but here the link Benefits between condition and the ability to generate the signal is The signal/handicap must cost more for the “low-quality” not so clear. individual than the “high-quality” individual •Rather, deceit is discouraged because one must have high fitness in order to overcome the handicap of the signal. Conceptually/Graphically: •Example: Andersson (1982): Male Widowbirds in central Costs to africa. The “signal” is the long tail. Low Qual. Benefit of •Females have a preference for males with long tails Indiv. the signal •The tails don’t confer a fitness advantage to the males- --if anything they are a handicap. Male Widowbird Costs to Hi Qual. Indiv. Costs and Benefits Notion of the handicap principle Signal Intensity echoes Veblen (1899): The Theory of the Leisure Class, and his idea of This has made actual testing of the Handicap “conspicuous Principle very difficult. Almost no studies consumption” have managed to quantify condition-dependent costs. First we must entertain a few ideas about Sex & Sexual Selection The Evolution of Sex The Origin of Sex: Sexual Selection : when individuals differ in Long ago, given the reproductive success either because: The spectrum of reproductive possibilities: Near ubiquity in eukaryotes •Asexual: The Maintenance of Sexual Distinction 1. of competition within one sex for access •Parthenogenetic (eggs developing without to mates and their gametes (intrasexual fertilization. Oftern females giving rise to Both of the above present difficult evolutionary females) selection ), or problems with several hypotheses for each. 2. one sex prefers the gametes received from •Clonal (quaking aspens) •Sexual certain members of the opposite sex Why is this so? •Self-fertilization (some dioecious plants) though (intersexual selection or epigamic often there are mechanisms for self- Asexual Reproduction selection). incompatibility or partial self-incompatibility advantages: •In genera Petunia and Oenethera: •Single locus with two alleles disadvantages: •pollen and stigma must differ for the seed to develop Sexual Reproduction •Sex-switching: protandrous or protogynous advantages: species/individuals •Order often related to which sex has a disadvantages: greater advantage if they are larger •Reef fishes, plants Thus, how did the “longer term” benefits of sex evolve and how are they maintained in the face of short-term benefits to individuals of asexuality?

Many mechanisms of: Males, Females, and Sexual Determination Fisher’s Sex Ratio Theory Anisogamy Haplo-Diploid (Hymenoptera) Males haploid, females diploid R.A. Fisher pointed out that in a sexually- What typically distinguishes males from females? Chromosomal/Genetic (i.e. XX or XY) reproducing population, every individual has whether females are heterogametic or homogametic varies across taxa exactly one mother and one father. Yeast, protozoa, some green algae: Environmental Sex Determination With Further assumptions: Gametes are identical (isogamy) Nutrition •Random mating Different mating types (but not sexes) Presence of conspecifics of different sexes •Equal cost to producing sons and daughters Sex-switching reef fishes •Heritability of propensity to produce sons or Most multicellular organisms: Temperature-dependent (crocodilians) daughters Female gametes: Sex-ratio should evolve toward 50-50. Large and few Also cominations of above. A difficult mess to untangle Energetically expensive evolutionarily. However, non-random mating is standard: Male gametes: •Positive assortative mating: like mates with like More bizarre: in parasitoid Nasonia Small and many •Negative assortative mating (or disassortative wasps: mating) Energetically cheap •“Paternarnal Sex Ratio Factor” •Drosophila and pheromones, the more Differentiation of gametes is known as anisogamy. a non-chromosomal element that wipes out the paternal dissimilar ones were more likely to mate chromosomes in a zygote •“Rare male mating” in Drosophila House Wren: making it male (recall haplo- A different idea: •Egg is >15% of body diploidy) Operational Sex Ratio: the ratio of sexually receptive weight •Wolbachia: a maternally males to receptive females in a population at any given •Males may have up to transmitted, bacterial factor A Nasonia egg that was stained time. which kills male zygotes, so with lacmoid to visualize the 8 billion sperm at any •Typically quite high for reasons of investment in most of the female’s offspring Wolbachia. The darkly stained one time are females. dots are the bacteria. gametes. Trivers’ Predictions in the Selection for 2° Sexual Differences in Parental Field Some examples Characteristics Investment Rick Howard (1983) while a grad student in Michigan. Robert L. Trivers coined the phrase “parental Spent almost every night at a investment” and made “Triver’s Prediction” pond on campus watching marked bullfrogs Mate choice should depend on parental •Recorded who mated with whom then watched which investment, i.e. eggs hatched •Female investment higher 1. Size and costs of gametes •Male variance in reproductive success is 2 to 3 times 2. Costs of mating greater than for females 3. Costs of parental care With High Male Investment: Gwynne (1981) and Epigamic selection appears to be responsible for the maintenance of some very outrageous traits. For the higher investment sex, choice katydids. (intersexual selection) should be more important. Male passes a spermatophore (up to 27% of body weight of male )to the female Darwin noted this The female also eats the spermatophore Peacock is a classic example For the lower-investment sex getting more In high density populations matings should be important •Males have access to many mates •Females readily accept the chance to mount Darwin mused that perhaps this was due to the aesthetic whims of females. The sex that invests less should be able to Males preferentially mate with larger (and more fecund) females tolerate more variation in reproductive success A similar example with an Australian katydid species--- Since then theorists have searched for more under low food conditions females fight for access to males plausible/rigorous hypotheses.

Three Broad Hypotheses for Typically the runaway process “imagines” that Discriminating Between the Intersexual Selection there was some utilitarian purpose (giving rise to Three Hypotheses (when nuptial gifts are not involved) the female preference) for the trait in the first place. Very, very, very difficult: Example: Healthy Mate Hypothesis: females choose males that •Not mutually exclusive appear to be healthy and so will not transmit disease or Perhaps primordial peacocks with slightly longer tails •Runaway process could start as “good genes” parasites to the female’s offspring (a non-genetic were better foragers •Healthy males that don’t infect their offspring explanation) with parasites may also have “good genes” However, more explicit theoretical models of the •Advanced runaway process leading to The Good Genes Theory: females informed by the courtship Runaway Process by Lande and Kirkpatrick handicap principle = “good genes” once again process choose healthy, well-conditioned mates because they suggest •Example from peacocks studied by Petrie will produce offspring that are more fit. (a genetic •Current evidence suggests “good genes” maintains explanation) •Needn’t have a utilitarian genesis male feather trains: •The handicap principle is a subset of this •Offspring of highly ornamented (HO) males •Even arbitrary traits that decrease survival grow faster, and their sons have higher The Runaway Process (Fisher): Starts with some females may spread through the population by a reproductive fitness having genes that make them selective for a particular trait in runaway process •Peacocks taken by foxes typically have shorter a male. They will pass these genes on to daughters who will tails and got fewer matings than other males also prefer males with that trait. At the same time, if the trait the year before. is heritable, then the existence of females in the population •But, can’t rule out that the feather train traits with a preference for that trait will lead to higer reproductive originated out of “healthy males” or a runaway success of the offspring of males with that trait, and things process (or both). ratchet ahead like that. It’s difficult just demonstrating female choice in peacocks. Petrie et al. (1991) Petrie et al. 1991 Lekking •Black Grouse •Yearly variation in lek sites 120 years after Darwin suggested female From Scandinavian word ‘lek’ for “play” choice could maintain elaborate plumage: Evidence in support of Hot Spot: Males defend small territories of no resource value •Multiple species lekking near river confluences First demonstration of female preference •Typically clumped in a small display area for elaborate plumage in males. Females arrive there solely for finding mates Evidence against female preference hypothesis: •Uganda kob (an antelope that leks) Underlying Theory: Why do this? Bradbury’s hypothesis •Operational Sex Ratio across leks is fairly •Intersexual Selection •Should be favored in species with wide-ranging constant Specific Hypotheses foraging ecology 1. Female mate choice depends on male plumage •Unpredictable, temporally variable food However, as with all things ecological: train characteristics (intersexual sel’n hyp.) versus sources (tropical fruits ripening at different Depends heavily on the species. 2. Certain plumage train characteristics confer a times on different trees) •Ruffs (type of sandpiper) exhibit competitive advantage to males (intrasexual sel’n behavior supporting all three hypothesis) Big Question: Why do males congregate in small areas? hypotheses Not mutually exclusive hypotheses •Three Hypotheses: •Located near small ponds on elevated ground •“Hot Spot” hypothesis •Females prefer groups with at least 5 displayers Previous Studies (Two) •“Hot Shot” hypothesis •Low-ranking males choose to display near •Experimental manipulations •Female preference hypothesis dominant males •Demo’d increased mating success but didn’t clearly document the mechanism Evidence for “Hot Shot” •Great snipes (European sandpipers) Observational Study •Removal of dominant males caused desertion •One lek at Whipsnade Zoological Park (England) by nearby subordinates •Removal of subordinates created rapidly-filled vacancies Back to Peacocks...

Lekking is one example of various Petrie et al. Observations Monogamy Mating Systems •Morphological measurements on males Inquiry into evolution of patterns of mating Why would males ever be monogamous? •Train features systems started fairly recently. •Other body features 1. Mate Guarding Hypothesis •Females may remain receptive after mating Definitions: •Behavior at one lek •Females may be hard to locate -gyny --> females •Female visits •Clown Shrimp •Male courtship attempts (hoot-dash) -andry --> males -gamy --> both sexes •Male interference and intrusion 2. Mate-Assistance Hypothesis Monogamy, Polygyny, Polyandry, etc. •Improvement in offspring survival with paternal Polybrachygyny --> male “serial monogamy” •Results care may be dramatic •High variance in male mating success •Seahorses Defined in different ways: •Displaying males •Male brood pouches •Peripheral displaying males Pair bonds versus ability to monopolize access to •Floating males mates 3. Female-Enforced Monogamy •Males did attempt to interfere with copulation •American Burying Beetle attempts of other males •But interference did not seem to alter mating Mammals and others: Polygamy far more common--- success interesting cases are monogamy •Successful matings correlated with train morphology •Train size and eye-spot number Birds: Monogamy quite common---interesting cases are •Not correlated with other body measurements or polygyny and polyandry lekking position •Data on 11 female visit sequences Mechanisms of Paternity Infidelity in Monogamous Matings Polygyny and Polyandry Rationale for extra-pair matings Assurance/Remating Prevention Monogamy is the norm in birds Male perspective Examples: •Potential for male reproductive care (mate-assistance •Costs: cuckoldry while he’s gallivanting about hypothesis) seems dominant reason •Risks of searching for extra-pair copulations and Dragonfly hitchhikers: •Most theory about polygyny and polyandry contending with other mates •Fly around on top of developed in the context of bird studies •Clear benefits the female he’s fertilized until eggs are Resource-Defense Polygyny Female Perspective laid •Polygyny Threshhold (Gordon Orians) •Possible Genetic benefits •At some point it benefits females to become a •Sufficient sperm quantity Calopteryx spp. Plugs and cementious semen second mate of a male with a large territory •Sperm competition (fitter sons if heritable) •Lenington with red-winged blackbirds •Genetic variety Chemically noxious odorizing •Males arrive first and establish territories •Sibs less likely to compete ecologically? •Females appear later and choose males •Material benefits Infanticide •Initial choice of unmated males •Resources on extra male territories •“Recently promoted” dominant primate males •Eventually polygyny was chosen over •Parental care •Female fetus resorption mating with males on poorer territories •Two territory variables Male Response on Evolutionary Time Scale: The job of paternity assurance is more difficult in species • Cattail density Paternity Assurance where the female stores semen from previous males • Food density* •Solution in Calopteryx maculata---the hoooked penis

Female defense polygyny: •Pre-existing female clusters •Some bat species females forage together and roost together at night a single site in their cave •Single male defends these clumps •DNA studies: 60 to 90% of matings •Up to 50 pups per male!

•Some males form their own female clusters •Marine amphipod---constructs “mobile apartment buildings” with up to three females

Male dominance polygyny •See lekking Two examples of costly sociality from Alcock 1998 Sociality and Altruism Sociality and Social Behavior Ovicidal female Broadly-defined: any non-solitary behavior acorn woodpeckers Overview: The Spectrum of social behavior, broadly defined: •Some costs of social behavior •From “simple” conspecific interactions such as •Imply importance of demonstrating benefits encounters between territory owners and intruders •To highly organized eusocial systems (honeybees) •Assumption of genetic basis •Direct selection, Indirect selection Human bias in thinking about social systems: •Types of social interaction in terms of costs/benefits •Highly organized social behavior and social living are “more evolved” in some way •Mutual versus Selfish versus Altruistic behaviors •This is a bias because it is what we do •Explaining altruistic behavior •Nothing says evolution should proceed toward greater social organization •Quick dispatch of Group Sel’n and Recip. Altru. •Kin Selection •Social Organization may incur high costs: Parasite-harboring cliff-swallows •Inclusive fitness •Hamilton’s Rule •Bottom Line: To explain social living and social behavior you must be very clear about the fitness benefits of sociality to individuals

Recalling the Genetic Cost/Benefit classification of Explaining Altruistic Behavior Perspective social behaviors THE BIG QUESTION: How could a behavior Big assumption underlying the evolutionary Social behaviors can be characterized as which reduces the fitness of an individual ever ecology perspective on social behavior: interactions between “Self” and “Neighbor” •Behaviors in question have a genetic basis •Four main types based on cost or benefit to self evolve in a population? •For behaviors to increase in frequency in populations or neighbor: the genes controlling them must make it to future THREE PROPOSED EXPLANATIONS: generations at a higher than average rate Effect On Neighbor 1. Group Selection (a largely discredited •How do these behaviors “help those genes along” to the hypothesis) next generation? Imagine an individual named Fred: +– (a) Direct Selection: Fred’s genes make him behave in such a way as to increase the chances of passing on his Mutually 2. Reciprocal Altruism (a game theoretic genes (i.e. of having more offspring) OR in such a + Beneficial Selfish notion with little empirical support) way as to increase the chances of Fred’s offspring surviving to pass on their genes. 3. Kin selection (a fairly widely-accepted This promotes the direct fitness of the genes Mutually influencing Fred’s behavior Altruistic Disadvantageous hypothesis based on genetic arguments and

Effect On Self – (b) Indirect Selection: Fred’s behavior promotes the indirect selection) fitness of individuals who are not his offspring, BUT those individuals happen to carry copies of Fred’s genes (because they may share a common ancestor) • MB and S are easily explained via natural selection This leads to indirect fitness benefits. • MD ought not be very frequent • Altruistic behavior is the tough one to explain

Note: Altruistic behavior doesn’t mean “consciously altruistic” as in “Oh! You’re such an altruist!” A Brief History of Group Critical Reassessment of Before getting to kin-selection, however, we investigate Reciprocal Altruism Selection Group Selection (Trivers) Reciprocity: a mechanism by which altruistic behavior Basic Premise of Group Selection: the Wynne-Edwards (early 1960’s) stimulated a great deal of might be maintained by increasing the direct fitness of the “evolutionary battleground” is the space of all separate criticism of group selection individual behaving altruistically populations (groups) of organisms. The “winners” and “losers” in this evolution match are the populations Oddly, Wynne-Edwards was a great proponent of GS Direct Fitness is increased because the recipient of the (groups) themselves. •Natural Regulation of Population size altruistic behavior “returns the favor later” •“Saw its (GS’s) magnificent consequences so “You rub my back and I’ll rub yours” Contrast to Individual Selection within a population universally that evolutionary ecologists were forced to consider the argument more carefully.” --Ricklefs Requires that the cost for the giver is less than the benefit The first Group-Selection Argument was formed by for the recipient Darwin in his On the Origin of Species to explain features Huge Backlash!! of sterile worker bees: Problem: Single or Few Interactions: Game theory shows How could features of “good” sterile workers be Criticisms of Group Selection: cheaters can easily invade a population of reciprocators: acted upon by natural selection if they don’t leave any 1. Most organisms don’t organize themselves into “You rub my back and I’ll say I’ll rub yours, but I’ll really offspring? groups the way that they would have to for Group leave town before I do” Selection to be effective Darwin: “By the survival of communities with females 2. The time scale for group selection is slow---much Possible Solution: Repeated interaction makes it harder to which produced most neuters having the advantageous slower than for individual selection within cheat successfully. modification, all the neuters come to be thus populations. Group selection should be overwhelmed characterized.” by selfish behavior. Does reciprocity occur? Very few examples This was a widely accepted idea, adopted for many Hamilton (1964) and Maynard Smith (1964) proposed kin- Wilkinson (1984) and vampire bats explanations in evolutionary ecology for many years...until selection which has essentially replaced group selection the early 1960’s. thinking.

And now: Imagine you are a contestant on the The Theory of Kin Selection Kin Selection Game Show The Rules: Kin Selection: A process whereby altruism may be •You are the contestant selected for in a population because it increases the •You are a diploid organism inclusive fitness of the individual doing the altruistic •two copies of the “locus in question” behavior •You score points by “putting individuals into a population” •You get one point for each gene in those individuals that is a copy of one of your genes at the “locus in question” •Your plays are choices between 2 alternatives

Wilkinson’s data Example: Choose between from vampire bats (a) putting 50 offspring (from matings with individuals unrelated to you) into the population suggests reciprocal (b) putting 100 individuals that aren’t related to altruism in giving you into the population food (blood meals) reciprocally Belding’s Ground Squirrel between individuals A tougher one: Choose between (a) 10 offspring (from matings with individuals in a group. unrelated to you) (b) 10 full-brothers (i.e. ten more offspring of There are few other both of your parents) examples, though Back to the Game Show: Choose between Surprise: In the second case, the expected gain in points How about r between two full siblings (a) 10 offspring (from matings with individuals Ma Pa is the same for choice (a) and (b). unrelated to you) 12 3 4 (b) 10 full-brothers (i.e. ten more offspring of both of Why? To understand why we need a few more concepts. your parents)

Identity by Descent: two genes are said to be identical by descent if they are copies of the same ancestral gene Either choice a or b will give you 5 points. 1 3 14 23 24 Coefficient of relatedness (r): the coefficient of How about: relatedness between two individuals is the expected (a) 4 full brothers proportion of their genes which are identical by descent (b) 4 uncles and 16 first cousins? 4 Possible Genotypes in the Siblings Example: r between a parent and an offspring Probability 1/4 for each.

Parent A Parent B Now Consider the Expected Proportion of IBD Coefficients of Relatedness o o between say o o 13 Relationship of Self to: Coeff. of Rel. (r) Self 1.0 One gene from and a randomly chosen One gene from Offspring or Parent 0.5 Parent A Parent B sibling. Full Sibling 0.5 o o = (.25)(1) + (.25)(.5) + (.25)(.5) + .25(0) = .5 Half Sibling 0.25 Uncle/Aunt or 0.25 Nephew/Niece So, r between two full siblings is 0.5 Grandparent or 0.25 Half of the offsprings genes are from either Grandchild parent. Hence r = 1/2. First Cousin 0.125

Back to Biology: The points in the gameshow are Hamilton’s Rule measured in the units of inclusive fitness of your genes Hamilton’s Rule: an altruistic behavior may be Inclusive Fitness = Direct Fitness + Indirect Fitness adaptive if it results in positive inclusive fitness. = (Survival of offspring) x (r for parent-offspring) + (Survival of non-descendant kin) x (the proper r for each Numerical Example: You save the lives of 5 nephews, type of relationship) but in doing so you lose the opportunity to produce two sons. Example calculation of inclusive fitness: Imagine you have 29 offspring. Through your diligent parental care 15 Inclusive fitness = -2(.5) + 5(.25) = .25 survive to reproduce. 5 survive even though you neglected Conclusion via Hamilton’s rule: this could be adaptive them. You give your life in an heroic deed that saves the lives of 8 cousins, 4 nephews and 2 half-sibs who would have died if you hadn’t saved them. Reyer (1984) Your inclusive fitness is: Pied Kingfisher (5 + 15)(.5) + 8(.125) + 4(.25) + 2(.25) = 10 + 2.5 = 12.5 Study Altruism and Inclusive Fitness: altruistic behaviors have costs which are reductions in direct fitness but if they benfit See the reading relatives, the indirect fitness benefits to the altruist may from Alcock for offset the direct fitness costs. details. Alarm Calls in Ground Squirrels Hypotheses for Evolution of Observations Made Sherman 1977 Alarm Calls Audaciously large observation programme since 1969 Natural History of Belding’s Ground Squirrels 1. Predator attention diversion •Tagging and Kinship studies---pedigrees available Female sedentism •Pandemonium! or ventriloquism •Females remain near their natal nest throughout Summers of 1974–1976: 3082 hours of observation life 2. Predator discouragement •Males disperse after birth. •The “I see you!” hypothesis 9 ground squirrels observed to be killed in that time •Brothers do not congregate elsewhere 6 adults and 3 juveniles •Females are thus surrounded by kin! 3. Alerting relatives •This is the kin-selection hypothesis 102 alarm calls heard when a predator was also observed Foraging and daily behavior habits •Females give alarm calls more often than “expected” 4. The Group-selection hypothesis •Especially females with kin nearby Natural predators •Males give alarm calls less often than “expected” 5. Reduction of probability of later attack •“Expected” means “expected at random” Alarm calling •Depriving predators of experience Alarm callers were stalked by predators significantly more 6. The reciprocal altruism hypothesis often than non-alarm callers

3 of the 6 adults killed were alarm callers (NS)

The method of competing, alternative, hypotheses...

Confronting the Hypotheses The Reality of Diversity Bednekoff’s Model The question: Can a simple model (i.e. direct fitness 1 and 2 not supported: Kin-selection is not necessarily the explanation for all considerations alone) account for the rota. •No pandemonium and predators stalk alarm callers instances of alarm-calling. •Alarm caller not always the closest one to predator A discrete time, stochastic model with many individuals Generalizing from one species or study to another is a Would not be possible to reject 3 (kin-selection) in favor risky business in ecology Consider a single individual of 4 (group selection), also •Choice made at each time step: •Anecdotally, no between group differences Sentinel Behavior: •Forage or Somewhat different than ground squirrel alarm- •Be a sentinel 5 does not hold water calling •Predators don’t preferentially return to particular •Sentinels are self-appointed •If you forage, you have a certain probability of areas “lookouts” who take the job finding a certain amount of food in that time step •Older females call more often of watching out for “the •If you are a sentinel, you have zero probability of group” while the others finding food in that time step 6 Reciprocity not supported forage. •Females don’t call as often when they have no living •However, the probability of being killed by a kin. If reciprocity existed beyond kin relationships, •The “rota” may seem like a predator is lower if you are a sentinel or a forager this should not be the case highly organized, complex, AND those probabilities depend on how many others •Presence of non-callers does not deter callers social behavior. in the group are already sentinels

Left with Hypothesis 3 (kin-selection) being far more •An extra tradeoff: sentinels •An individual may die by intact than the others. can’t forage simultaneously •Starvation •But, sentinels may be better •Predation at avoiding predators Optimization Clutton-Brock et al. 1999 Clutton-Brock et al. cont’d Checking Bednekoff’s predictions in meerkats Assume: evolution has given animals optimal decision rules Key Observations: •Group Structure of Meerkats •No sentinels were killed by predators in 2000 hours •i.e. Given hunger level and number of other sentinels •One dominant female (75% of litters are hers) in the current time step, an animal may choose to of observation (did they see any meerkats get killed?) •One dominant male (fathers most of the litters) • (0.68/year mortality rate amongst adults) forage with probability p or become a sentinel with •Note that the close kinship is there probability 1-p. • More adults killed in small groups than large •Foraging: can’t watch out for predators while digging groups •There is some p that maximizes the individual’s •Sentinels watch for predators and give alarm calls probability of long-term survival •Recent babysitters spend less time as sentinels •Seldom will an individual take two successive guarding •(They ate less the day before) Finding that p, (mathematically) bouts, but there is not a clearly •Meerkats were more likely to go on sentinel duty if defined rotation pattern there was currently no sentinel on duty Simulating groups of animls behaving optimally •This yields very organized-looking rota behavior! Nonetheless, because there is Manipulation of hunger status: some alternation in sentinel •Fed some individuals 25g of hard-boiled egg THE VALUE OF MODELLING: behavior; it appears “organized” •They subsequently spent more time on sentinel •Demonstrated that direct fitness arguments could duty explain sentinel behavior •Generated testable predictions: All this may be explained by Bednekoff’s model •Sentinels have reduced predation risk •Better-fed individuals are more likely to become Not necessary to invoke kin-selection. sentinels An application of Occam’s Razor: “one should not increase, beyond what is necessary, the number of entities required to explain anything” Life History Traits Relation to the “Life Table” Life History Variation in

Brief review of strategies we’ve seen so far: Imagine following a cohort of individuals in a population Pacific Salmon •Foraging strategies Fecundity and Age at Maturation, etc. •Territorial behaviors •Sockeye •Signalling behaviors •Pink •Reproductive behaviors •Chum •Mating systems Time •Chinook (years) New Offspring Non-reproductive Reproductive AdultsDead Juveniles •Coho We investigated these different behaviors and traits in •Steelhead terms of how they affect fitness of the individual 0

Another class of traits have a clear and direct bearing on Intraspecific Variation in Fecundity in Chum Salmon fitness. These are the life-history traits. The major life 1 Chum salmon from the Amur River Siberia: history traits are: •Age at first reproduction Summer run: 39.8 eggs/cm fork length •Number and size of offspring 2 •Reproductive lifespan and ageing Autumn run: 53.5 eggs/cm fork length 3

All of these affect the so-called “Life Table” of an organism 4

Note, there are more formal representations using matrix algebra

3. Correlation of traits between relatives Goals of life history theory Evidence for Trade-offs •Quantitative genetics approach •Maybe useful for demonstrating short-term Four main ways people have tried to demonstrate To Answer, “Why all this variation?” constraints and trade-offs that these trade-off exist: •Long term selection may not be constrained by genetic correlations detected in such studies and 1. Phenotypic Correlations within or among populations •Example: egg size and egg number between salmon Ultimately wish to construct models which populations of the same species 4. Correlated responses to selection predict what sorts of traits will be favored in •Doesn’t really demonstrate direct trade-offs •Artificially select for a trait and see what else what sorts of environments. changes along the way. 2. Experimental Manipulations •Famous experiments by Rose and Charlesworth •Trade-offs between clutch size and offspring survival. •Squashed fruit flies at an unnaturally young age Without constraints, the answer is easy, for •Inspired greatly by the “Lack Clutch” hypothesis of 30

highest fitness one would. . . . the 1940’s 25 •Hypothesis regarding latitudinal clutch-size 20 trends 15 The CORNERSTONE (as in other optimality models): 10 •Hogsted (1980) Magpie clutch augmentation/ 5 Assumption of limited time and resources reduction experiments. 0 0 5 10 15 20 25 and the need to allocate these to particular -5 -10 4 -15 traits Difference in Eggs per Day 3 -20 2 -25 Adult Life Span (days) Trade-offs 1

Chicks Fledged 0 56789 Selection for both shorter life and higher fecundity Number of Eggs Another Model Simple Mathematical Models Relationship between reproductive life-span and Phenotypic Plasticity reproductive investment. Perennial vs. Annual Life Histories: Noted in many other types of traits as well, S0 = Probability of survival in the first year So = Probability of surviving the first year (to but has received much attention in the study of life SP= Probability of survival in later years reproductive age) history traits. B = number of offspring produced in a season Ba = Seed production rate of annual plant Back to our first day: Bp = Seed production rate of perennial Sp = probability of surviving adult years Environment Partitioned into: Genotype ------> Phenotype Sr = factor of survival probability that is L = rate of increase affected by your reproductive investment S = factor of survival probability unaffected by Reaction Norms. L (annual) = (Ba)(S ) reproductive investment 0 Selection for phenotypic plasticity itself L (perennial) = (Bp)(S ) + S 0 P L = (S)(Sr) + (So)(B)

What values of B and S lead to the annuals Now, imagine changing B (and hence Sr). Our common increasing faster than the perennials? trade-off assumption would say that Sr would become smaller as B became larger. Annuals will be favored when S is high relative to S 0 P ∆L = S(∆Sr) + So(∆B) If not, annual seed production must be high to compete High adult survival favors lower yearly investment in with perennials reproduction.

Reaction norms

Genetically determined---may be an item under selective pressure. Annual vs. Perennial Broad Patterns of Plant Life Histories Reproductive Life-span vs Annual Life History reproductive investment Time 0 Time 1 Time 2 So Time 0 Time 1 Time 2 Time 3 Time 4 So S(Sr) S(Sr) S(Sr)

So

So Ba B So { Desert floras dominated by annual plants---> Few adults can survive the dry seasons, but seelings are seldom space limited Assume a negative relationship between Sr and B Perennial Life History and may grow well (low Sp/So ratio) Tropical rain forest zones: seedling survival Time 0 Time 1 Time 2 is low due to So Sp competition for Sr space and light from other So plants. Mostly peren- Bp So nials. { (High Sp/So ratio.) B

Semelparity versus Iteroparity in Scarlet gilia Scarlet gilia Semelparity vs. Iteroparity Paige and Whitman 1987 Salmon survival schedule: Ipomopsis aggregata in Arizona typically exhibits a semel- •egg to fry: abysmal! parous pattern, but is facultatively iteroparous, depending •fry to smolt: lousy! on the environmental conditions!

•smolt to adult: poor environment •pre-reproductive adult: genotype------>phenotype much better So, why not have a more “perennial life history?” •Hypothesis: massive expenditure on reproduction. Three Manipulations: 1. Pollinator exclosures

Agave: 2. Flower chopping Semelparous reproduction Hypothesis: environmental cond- 3. Herbivory simulation itions seldom suitable for seedling survival. Results: 1 and 2 increased incidence

of rosette production 5 to Rosette formed by iteroparous plant 7-fold Many broad predictions, but with greater detail things become 3 did not increase the freq- much more complicated... uency of iteroparity. Phenotypic Plasticity Predator Induced Phenotypic Plasticity Prey-induced plasticity Some terms and defns Daphnia grow thicker and Cichlid fishes fed Canalization: one genotype produces a single phenotype, spinier helmets in the presence different diets regardless of environment of compounds associated with developed different jaw their predators morphologies. These Phenotypic plasticity: a general term covering all types of changes were environmentally induced phenotypic variation Helmet reversible. (Meyer 1987) Polyphenism: a type of phenotypic plasticity in which the change is between two or more discrete phenotypes: •environmental sex determination •castes of social insects Also: Grasshopper mandible •locust behavior (isolated/sedentary vs. gregarious) Thais lamellosa, morphology changes •semelaparity or iteroparity in Gilia the fringed dog- whelk. An aquatic in response to diet. Reaction norm: the continuous relationship between a snail that drifts as •Soft leaves versus trait changing due to phenotypic plasticity, and some a planktonic larval hard leaves feature of the environment. veliger. If it Chaoborus, a Daphnia predator •Having the right man- “A mirror that reflects environmental effects into “lands” in an area dibles makes a with Cancer phenotypes” difference in energy productus (a crab accumulation. predator) it (Thompson 1988) With all this phenotypic plasticity, how can natural selection develops a thicker “grab onto” different genotypes? shell.

Comparative Study of Reaction Norms in Lizards Evolutionary Theories of Reaction Norms 2 lizard species Sinervo & Adolph 1994 1 2 3 Sceloporus occidentalis Aging and Senescence Curves representing Sceloporus graciosus •Taken from three different elevations (low, med, high) in CA different genotypes and one population from OR. Some observations: •High elevation/latitude populations have fewer active hours Raised under good conditions with no predation risk: •Activity = body temp high enough for growth to occur •Birds typically live longer than mammals 3 •Hatchlings raised in 4 expmtal condns: 6, 9, 12, and 15 hours •Bats typically live longer than terrestrial rodents of potential activity time. (Incandescent light bulb) •Flightless birds live shorter than flying birds Phenotype 1 •Results: 1) Short-day specialists (high altitude/latitude lizards) •Thick-shelled bivalves live longer than other molluscs growth rate did not increase with >9 hr of potential activity •Tortoises live longer than other reptiles 2 2) Lower elevation lizards could capitalize on longer potential activity days in the laboratory Interesting Features: 3) Among family variation in reaction norms •Death occurs, eventually with certainty 4) Family x treatment interaction-->G x E interaction Environment •Ideal-condition lifetimes vary greatly across taxa

An Early Explanation for “Programmed Death” (by G x E interaction: when reaction norms for different Wallace) genotypes cross “...when one or more individuals have provided a sufficient •Expected to be pervasive (Stearns 1989) number of successors they themsleves, as consumers of •Are commonly observed nourishment in a constantly increasing degree, are an injury to those successors. Natural selection therefore weeds •Due to trade-offs? them out, and in many cases favours such reaces as die The reaction norm itself is under genetic control! almost immediately after they have left successors” This is how natural selection can “grab” the genotype, (quoted in Rose 1991). even in the presence of phenotypic plasticity Senescence Antagonistic Pleiotropy Mutation Accumulation Basic Premise: “Senescence later in life is the price of •If you survive to a ripe old age: youthful vigor.” Basic Premise: new, deleterious mutations build up in the •Shouldn’t your extra experience increase your genome. Such early-acting mutations are weeded out by probability of survival into the future? pleiotropy = when one gene affects two or more traits selection, but late-acting ones basically fill a “genomic •Maybe so, but it doesn’t work that way. garbage can” that never really gets emptied. •Senescence = greater susceptibility to injuries, disease, Williams (1957) “Selection of a gene that confers an and death as one grows older advantage at one age and a disadvantage at another will Experimental Evidence: Difficult to come by. Some •Neural degeneration depend not only on the magnitudes of the effects Drosophila selection studies show accumulation of •Reduction in kidney filtration themselves, but also on the times of the effecgts. An deleterious alleles without a cocnomitant change in early •Decreased respiratory capacity, etc advantage during the period of maximum reproductive life reproductive fitness. probability would increase the total reproductive Environmental (proximate) causes probability more than a proportionately similar Overall, it is very difficult to distinguish between •Sure, but senescence is still inevitable, it seems disadvantage later on would decrease it.” antagonistic pleiotropy and accumulation of late-acting, deleterious mutations. An evolutionary/genetic explanation: Medawar (1946) Experimental Evidence: “What is important from our point of view is that the •Quantitative genetic correlations between early Much research directed in the area of evolution of contribution which each age-class makes to the fecundity and longevity (sib analysis, line crosses) senescence, however, due in part to the medical interest in ancestry of the future decreases with age” •Mendelian inherited, pleiotropically acting the subject. mutations: The key is reduced selection on older age classes. This •C. elegans age-1 mutant (Friedman and Phylogenetic relations between adult mortality rate and could lead to senescence by two mechanisms: Johnson 1988) life-span under “ideal conditions” 1) antagonistic pleiotropy •D. subobscura grandchildless mutation--- 2) accumulation of late-acting mutations female offspring have much longer lifespan, but no ovaries!

A 5-Minute Review Regarding the Exam Regarding the lecture notes: •Covers everything from the first day of class. •A good resource for studying Evolutionary Ecology covers themes from many different •It will be closed book, closed notes, closed handouts, etc. •Note: some of the titles and the bottoms of the slides disciplines (which overlap themselves). Notably: •Readings versus lectures: might get chopped off by some printers. You may Evolution: •You are expected to have done the readings, but won’t be asked want to add those back in pen (everything appears •Quantitative genetics, natural selection, sexual questions of exasperating detail from them. The readings have been of two types: correctly on screen in Acrobat Reader) selection, phenotypic plasticity, kin-selection, 1) "textbook" type readings---sections of texts or edited volumes that •The lectures often contain material that won’t be life-history theory describe general themes or methodologies. Typically in my lectures I found in the required readings Behavioral Ecology: have covered the aspects of those readings that I find most important •Foraging theory, signalling, and reproductive and relevant. The lectures are a good indication of which parts of those readings to focus on. These readings serve to supplement lectures. Also, •One study strategy: be able to tell the story behind behavior if it was a reading that you discussed in section, you should be quite each of the pictures in the lecture notes. The Sociobiology comfortable with its general content. examples make the theory come alive a bit more. •Kin-selection, mating systems, territoriality 2) research articles---we've read quite a few of these. It's good to read Have fun while studying---tell your friends about the these to get a sense of how research in evolutionary ecology is done and natural history items you’ve learned; tell your We’ve encountered four main methods for interpreting how its results are transmitted. Some of the articles were not discussed significant other about the American burying beetle, variation in strategies in an evolutionary context: in lecture. Nonetheless for each article you should be able to tell me: etc. 1. Optimality modeling (optimization ideas are ubiquitious in the field) (a) which of the general topics we have covered it is relevant to (b) the hypotheses that the authors were trying to test •Most notable in Optimal Foraging Theory, but (c) the general methods---for example whether it was an observational elements of it appear everywhere study or a manipulation, what animals were studied, and what variables 2. Game theoretic perspective (ESS’s) were observed 3. Comparative method (d) the general results; especially how the results relate to the general theory that the study is relevant to 4. Population/Quantitative genetic perspectives You should pay particular attention to those articles about which I talked at length in lecture.