Ecology, Evolution & Natural Selection

• Ecology studies living organisms, their interactions, environment, abundance, and distribution.
• Evolution changes inherited traits in a population from one generation to the next, involving genotypic and phenotypic diversity.
• Natural selection makes helpful traits more common for survival and reproduction, while harmful traits become rarer.

Tinbergen's Four Questions

• Ultimate questions focus on function (adaptation) and evolutionary history (phylogeny).
• Proximate questions investigate causation (mechanisms) and individual development (ontogeny).

Darwin's Theory

• Intraspecific competition (struggle for existence) always exists.
• Fitness differences determine survival and reproduction capacity.
• Fitness differences are heritable.
• Population composition shifts towards improved adaptation, increasing fitness.

Optimality Paradigm

• Explains adaptations in terms of fitness maximization (Sewall Wright).
• Uses a 'proxy' for fitness in practical applications.
• An approach that involves:
• Specifying available option set (strategies) through information and constraints.
• Deriving fitness consequences using currency (proxy for fitness), trade-offs and cost-benefit analysis.
• Finding the optimal solution using optimality criterion (fitness maximum, ESS).
• Comparing observed behavior with optimal behavior.
• Improving the optimality model.

Marginal Value Theorem

• Determines which value of t maximizes 'yield per time,' where yield per time corresponds to the slope.
• To find the value of t maximizing yield, locate the line with maximal slope.
• Optimal time can be found graphically when 'yield per time' is maximized.

Sinistral Fish Example

• Sinistral fish have a sinistral beak, enabling easier eating on the right side.
• Frequency-dependent selection causes generation oscillations around an 'evolutionary stable' ratio of 1:1.
• Lorenz' rule states: organisms with dangerous weapons avoid using them in intraspecific fights.
• Population fitness explanation: reduction in population fitness occurs, but behavioral evolution cannot maximize population fitness.

Maynard Smith's Hawk-Dove Game

• Hawk strategy: aggressive.

• Dove strategy: peaceful.

• The variables:

• V: value of resource.

• D: cost of getting injured.

• pH: proportion of hawks.

• Fitness of hawks calculation: pH × (-1) + (1-рн) х 6.

• Population with only doves has the highest fitness, but hawks can invade it, search for uninvadable strategies.

• An evolutionarily stable strategy (ESS) is a strategy S* that cannot be invaded by any mutant strategy, meaning F(s*,s*) > F(s,s*) for all S is not s*.

• Unique ESS in hawk-dove game: pH = V/D =6/8 = 75%, this explains Lorenz' rule.

• Fitness equality at ESS: FH(PH) = FD(PD). p stands for proportion represented by p hat.

Simple Games

• An evasion game, scale-eating cichlids with PĀ = 0.5 (first square)

• A coordination game, PA = 0.5 is fitness equilibrium, but not an ESS.

• The game has two ESS's, either no one does A or everyone does A.

• Example: driving on the right or on the left side of the road with PA = 0 or PA = 1.

• Pairwise interactions can be described by payoff matrix.

• Frequency dependence (playing the field) often occurs in more diffuse forms.

• Inevitable trade-off exists between foraging and vigilance (looking out for predators).

• S* represents the strategy (e.g., vigilance time) of the resident population.

• S stands for the strategy of a mutant.

• F(s,s*): represents fitness of mutant in resident population.

• Evolutionarily stable strategy has F(s*,s*) > F(s,s*). In an s*-population, resident individuals (playing s*) have higher fitness avoiding mutant strategies invading.

• Pairwise Invisibility Plots (PIP) is used.

• In case of 2 or 3 strategies (e.g., Hawk-dove) fitness graphs with intersection points of fitness functions are analyzed.

• In case of continuum strategies (e.g., vigilance game) pairwise invisibility plot (PIP) is analyzed.

Frequency Dependent Selection (23/2 Lecture)

• Potential reasons why the model fails:
• Behavior is not yet optimal due to environmental changes, evolution can't keep up.
• Evolutionary problem is not adequately represented (predation, social dominance, mate choice are not taken into account).
• Currency chosen is no adequate representation of fitness (energy uptake, energy gain, efficiency).
• Constraints not adequately represented (information, storage capacity).

Plausible Proxies for Fitness

• Energy uptake per time unit (gross gain)

• Energy gain per time unit: g(t) = net energy gain

• Energetic efficiency: s(t) = energy spent

• The approach to optimally allows testable predictions to be derived, focusing on the benefits and costs of phenotypic trait values

• It provides information on the currency being optimized by selection and the available options and the constraints

• Reverse engineering

• To maximize F(s), the fitness of an individual using strategy s

• when fitness is contingent only on one's own behavior

• Often however , the fitness is also determined behavior of others where Frequency dependent selection is used

• Fitness is calculated as F(s,s*), where s* is the strategy of others

• Ideal competition is when competitors are ideally (e.g. perfectly informed about the environment) and free (i.e. able to move instantaneously without costs)

• Competitors divide themselves so that the intake rate is equivalent to all habitats to maximize fitness is reached using a habitat matching rule for their behaviour

• In an ideal distribution the densities d is that various habitats matches the profitability's P of these habitats

• Selection always does not lead to a fitness peak

24/2 Sexual Selection

• Male and female individuals can look different until classified as distinct species Many traits that have diverged between the sexes sometimes hinder survival
• Evolution proves an individual's competition for access to economical opportunity also improves an individuals access to mating opportunities
• Biologists use the term sexual selection like kin selection or group selection it is a component of natural selection
• Broader perspective (Roughgarden): other kinds of intraspecific interactions, besides those between males and females, can be important as well, social selection.

Historical Perspectives

• Darwin's first ideas focused on the male perspective.

• Fisher created the first verbal model of female choice evolution.

• 1940-1975 was considered a 'dark age' of sexual selection research.

• 1985-1995 brought theoretical consolidation and the first empirical tests.

• Factors that control competitive success on the mating market often differ for males and females.

• Reproductive division-of-labor states that one sex (typically females) is limited by the energy investment into offspring, so mate quality is more important than quantity.

• The other sex (typically males) can potentially produce many offspring, so mate availability limits its reproductive success.

• Sex role asymmetries can be more or less pronounced, based on the mating system, but most species follow the typical pattern:

• Intrasexual selection (male-male competition)

• Inter-sexual selection (female choice)

• Some species have exhibit sex-role-reversal which are excellent for testing sexual selection theory.

• Distinguishing intra and intersexual selection is useful conceptually, but reality can blur the lines.

• Female elephant seals provoke fights between males through cryptic female choice.

• Many sexual signals serve a dual function: communicating with rivals and potential mating partners.

• Male-male contests choose for improved sensory capacities and locomotor action, in order to succeed in scramble competition

• And for weaponry, increased body size and fighting strength, for those who may succeed in competitions

• The morphological, physiological and behavioral adaptations that make a male successful in male-male competition sometimes need a high degree of specialization, creating opportunities for males to employ alternative reproductive tactics.

• Female choice selects for elaborate morphological ornamentation and behavioral displays in males and strong mating preferences in females. -Studies suggest that female preferences are labile: losses of elaborate male traits are frequent and widespread and female preferences for these male traits can be reduced, lost or even reversed.

• Males and females share a evolutionary interest in the production of offspring, but their options for maximizing reproductive success may be incompatible.

• It Creates a potential for evolutionary conflict between sexes, sexual conflict. being choosy can provide benefits that directly promote female survival or fecundity.

• choosiness should be referred to as a a reluctance to Mate and is a counteradaptation to harassment by males

• weak preferences which have direct benefits or resulting from sensory biases can become greatly exaggerated.

• accereleararing runaway occurs when trade and preference genes are strongly generally Associated

• rapid depletion in genetic and male variation and no maintain of costly makeup preference

• quality has a complex genetic basis and is subject to frequent deleterious mutations so some variation a long males will always be maintained result is a persistanr benefit of a choice ti compensate ti for for costly mating Preference

• Good genes can only work if Ornaments are either condition dependent or revealing handicaps Other wise males can cheat by signaling dishonestly

• In addition the process varies on a continual influx of variation in quality

• sexual selection differs to the advantage which certain individuals have over other individuals of the same species sole in respect of reproduction

25/2 Lecture: Sex Allocation

• Easy to quantify effect on fitness.
• Relatively simple to model.
• Sex ratios are easy to measure.

Aristotle's Contributions

• Aristotle (322 BC) noted that pigeons lay a male egg and a female egg with a day's interval.

Early Perspectives on Sex Allocation

• John Arbuthnot (1667-1735) argued polygamy is against natural law and justice.
• Charles Darwin (1871) mentioned natural selection could shape offspring sex ratios in "The Descent of Man, and Selection in Relation to Sex."

Fisher's Genetical Theory

• Ronald Fisher (1930) stated total reproductive value of all males equals all females because everyone has one father and one mother.
• Individuals of the rare sex have higher reproductive value.
• Parents producing the rare sex gain advantage and higher fitness.
• Sex ratio becomes a stable equilibrium with equal allocation.

-Where the variables are; -Vf = reproductive value of daughter -Vm = reproductive value of son -S = sex ratio (proportion sons) -Then calculate equal total RV: (1-s) Vf = SVm or: vm = (1-s)/S X Vf equilibrium: vf = Vm

Cost Analysis

• Ef = cost of making a daughter
• Em = cost of making a son
• Determine ratios
• Then derive principles where S* em = (1-s*) ef is equal allocation principle and unequal costs

Hamilton's Observations

• Hamilton (1967) noted female-biased sex ratios in inbreeding species.
• Fisher's assumption of population-wide random mating occurs.
• Local competition between sons drives selection for female-biased sex ratios.

Hamilton's LMC Model

• Several notes; -N unrelated females oviposit in same patch -Offspring mate randomly -Mated daughters disperse

-An extra son (and a daughter less) improves related males to compete for fewer mating opportunities.

Trivers and Willard's Idea (1973)

• Parents vary in state (condition, size etc.), and parental state affects fitness of sons and daughters differently.
• Parents should overproduce the sex that benefits most from the current state.

Charnov and Bull's Model (1977)

• Created a mathematical model.
• The green line represents the bang-bang theory that goes from one side to the other.
• Queen-worker sex ratio conflict is seen as usually haploid/diploid.
• The ratio Queen's optimal is (daughters : sons) should be 1:1. Workers' sisters is more important with the sister and brothers ration being Workers' optimal : (sisters : brothers) 3:1.

Critique

• Includes queen control and local mate competition better explanation
• Workers close to brother under polyandry
• When queen singly mates, there are way more daughters, with their daughters are closely related to queens.

Lectures from 26/2 on Foraging

• The diet choice problem involves what to accept and not to accept as food like (large vs small caterpillar)

• The patch choice problem involves flying further for a larger prey or flying close for smaller choice

• Choosing between high or low variability; giving which the awards is the varience sensitivity

• Where the variables are -Energy gain : esmall < elarge -Handling time: hs = hL -Profitability: e/h -Search time: ST

• Accept all small prey when (es / h) > eL / (h+STL) which the profitability of small prey is largerthan including the search time for small prey

• Never accept small prey when (es / h) < eL / (h+STL)the STS affects prey but not STLs

Then The Patch Choice Problems are analysed

• When to Leave. Where the variables have.

• Maximum Gain / Time analysis

• How more they have to travel prey to how longer they stay at the preys

• Choose close or close or far/ or far and is for large prey

• Steeper prefer is the more preferred where they prefer they small prey, it the Prey but Close

• What should a foraging animal aim

• Then we should ask how to maximize collection and time and what it wants to maximize and minimize.

• Currency’s in foraging is Gain/Time •Minimizations on Time of Total Collection Maximization (gain - cost) / time what is total collection

• Which that means that we also have The Cost

• How do we get Efficient The Efficiency on (gain - cost) / cost is time that we need and matters.

• Walking costs less energy than flying (is the cost in foraging currency).

Important point

The thing to find out is when the fitness proxy is the same in different currencies

And R (reward) for Currency’s when its is the same or in Everything that happens.

Variables

CF -Flying CW -Walking

-When you look at Gain (total), its not just how much food per Time matters and the E values in the Equations the want to just Maximize’s there Gross Gain

• When they are wanting their maximums, they always want Cost(time and the Vertical Purple)

• How does the slope compare where to the 2 types, and there Net Gains. Is the process a time to leave, or to stay with a long time in waiting.

Walking and flying are currencies. How is this predicted in there Net Gain?

Titration Procedures

The number of flight requirements per request R

The numbers of runs with that request R

• Forced cycle; Binds do both options once in a cages that are set

• For a Choice Cycled Are bind that can choose twice on a time