This lecture introduces students to use of behavioral ecology to study social behavior (and thereby opens the door to the field of sociobiology, the topic of a follow-on course). The lecture starts with a discussion of conspicuous social behaviors seen in collective motion, as in starling murmurations, and discusses how the "selfish herd" hypothesis provides an explanation for these patterns based entirely on benefits to individuals (and not benefits to the group). This discussion motivates a description of the grid of social behaviors that mix costs and benefits to actors with costs and benefits to recipients, including altruism, spite, by-product mutualism, and selfishness. The bottom half of the lecture focuses on introducing inclusive fitness theory (kin selection) as an explanatory framework for understanding some forms of (apparent) altruism, where an individual pays an appreciable cost to perform an action that provides an appreciable benefit to a relative. This allows for introducing the Prisoner's Dilemma from game theory and using it to derive Hamilton's rule, which is a theoretical framework for predicting when benefits to relatives are strong enough to outweigh the costs to the individuals doing them. We then close by applying Hamilton's rule to a parental–investment problem considered by Trivers (first discussed in a prior lecture on parental care) that ends up predicting that offspring may evolve behaviors that lead to over-investment by parents relative to the investment strategy that is best for the reproductive success of the parents.
Topic highlights:
explanations for collective motion behavior in herds
taxonomy of social behaviors based on costs and benefits to actors and recipients
inclusive fitness theory as a gene-centric framework for explaining helping behavior (apparent altruism between individuals)
introduction to Hamilton's rule
application of Hamilton's rule to an analysis of parent–offspring conflict in parental investment
Important terms: murmuration, selfish herd, domain of danger (or “Voronoi cell”), social exploitation, positive externalities, public good, by-product mutualism, negative externalities, common-pool resources (or open-access goods), Tragedy of the Commons, selfishness, altruism (or cooperation), spite (or altruistic punishment), Prisoner’s Dilemma, inclusive fitness theory (or kin selection), relatedness, direct fitness, indirect fitness, inclusive fitness, Hamilton’s rule, Generalized Hamilton’s rule
In this lecture, we return to the notion that different amounts of physiological reproductive investment can lead to different behaviors. However, whereas we focused on mating behaviors and sexual selection in the previous lecture, we pivot to parental care behaviors here. Parental behavior involves interactions with a wider range of individuals – from multiple offspring (both current and future) as well as other individuals that share in parenting or the fitness consequences of parenting – as well as many more degrees of freedom of behavior. Life history theory, which we introduce in this lecture, provides a framework for understanding consistent behavioral patterns that tend to emerge from different environments. After discussing life history theory, highlight different forms parental behavior and the kinds of opportunities and conflicts that can emerge from them. After discussing topics surrounding infanticide in biparental care, we close with an introduction to classical theories in parent–offspring conflict.
Topic highlights:
parental care and investment
life history traits, life history strategies, and life history theory
sibling conflict, sibling rivalry, and the insurance egg hypothesis
uniparental, biparental, and alloparental care and relationship to internal and external fertilization
sexual conflict and infanticide
parent–offspring conflict
Important terms: anisogamous species, spermatophore, nuptial gifts, Syngnathidae, brood pouch, breeding sail, parental care, parental investment, life history traits, life history strategy, life history theory, 𝑟-selected, 𝐾-selected, sibling conflict, sibling rivalry, insurance egg hypothesis, parent–offspring recognition, external fertilization, egg guarding, mouth brooding, fry, alloparental care, uniparental care, biparental care, maternal care, paternal care, altricial young, joey, precocial young, sexual conflict, infanticide, concealed ovulation, The Bruce effect, parent–offspring conflict, begging, weaning
In this lecture, we discuss sexual reproduction and how asymmetries in investment can lead to asymmetries in mating behavior among the sexes. We open the lecture with preliminaries and definitions related to the biological description of sexual behavior. We then introduce Bateman's principle and the various downstream predictions of it related to animal behavior. We then pivot to cases which may appear to contradict Bateman's principle. We then close with a discussion of the likely reason why sex evolved and the different functions that mate choice has to provide.
Topic highlights:
definitions and theories of the adaptive value of sex
Bateman's principle and evidence both for and against
examples for the evolution of polygyny, monogamy, and polyandry
Red Queen Hypothesis and the evolution of sex
sperm competition
mate choice, sexual selection, and genetic compatibility
Important terms: sex, meiosis, mating/sexual reproduction, physiological and anatomical differences correlated with the production of different types of gamete, including, primary sexual characteristics, secondary sexual characteristics, somatic cells, gametic cells (or gametes), diploid, haploid (or sometimes monoploid), sperm (or spermatozoa), eggs, “cost of meiosis”, haplodiploid sex-determination system, Bateman’s principle, polygyny, monogamy, polyandry, sperm competition, spermatophore, nuptial gifts, Syngnathidae, brood pouch, breeding sail, Red Queen Hypothesis, anisogamous species, hermaphrodite, protandrous hermaphrodites, protogynous hermaphrodites, isogamous species
In this lecture, we discuss fundamentals of self defense from predators. We start with an introduction to mimicry, which allows prey with significant defenses to converge on signals that are easier for larger predators. We also describe prey that do not have significant defenses but can deceptively mimic those organisms that do in order to make themselves appear to be less palatable than they are. This gives us an opportunity to discuss the how mimicry can lead to mimicry complexes embedded in ecological communities. We also discuss other forms of crypsis, including camouflage and hiding, and strategies for providing more time to evade a predator, such as startle behavior and vigilance. We close with an exploration of agonism more broadly and how individuals in agonistic interactions may sometimes choose to fight and other times choose to flee. We use the Hawk–Dove game from game theory to illustrate the balance in such choices and explore a special case of predator–prey oscillations related to a similar negative frequency-dependent selection phenomenon.
In this lecture, we pivot from thinking about optimal group size when animals have positive externalities to using the same logic to better understand how animals distribute themselves within a habitat. We introduce interference and scramble competition as mechanisms that couple animal decision making, and then we introduce the Ideal Free Distribution (IFD) as a concept that can predict the likely location of animals under these competitive pressures. The IFD is a natural extension of the matching law from psychology. There can be variations of the IFD due to differences in competitive ability (which are modeled by the ideal despotic distribution, IDD) as well as due to non-foraging-related conspecific attraction (which can lead to colony life). The IFD does give us an opportunity to introduce the Nash equilibrium, which we then use to discuss another important model in social foraging, the stag hunt game. Closing with the stag hunt game lets us introduce concepts such as social efficiency, payoff and risk dominance, and coordination and assurance games.
Topic highlights:
habitat selection
interference and scramble competition
the ideal free distribution (IFD) and the matching law
conspecific attraction and colony life
game theory and the Nash equilibrium
the stag hunt game as an assurance/coordination game
Important terms: habitat choice/selection, interference competition, scramble competition, ideal free distribution (IFD), matching law (from psychology), ideal despotic distribution (IDD), conspecific attraction, colony, Nash equilibrium, stag hunt game, socially efficient, payoff dominant, risk dominant, coordination game, assurance game
In this lecture, we introduce social foraging as an opportunity for exploitation by conspecifics to either: (a) exploit positive externalities from the foraging behaviors of others, or (b) make foraging choices that reduce the benefit to others around them (imposing negative externalities). We discuss how these pressures complicate understanding the foraging group sizes observed in nature – such as densities of socially foraging bats and sizes of wolf packs. In particular, we introduce the tragedy of the commons (and open-access/common-pool resources) as a conceptual framework for understanding group sizes. We then pivot to focusing on within a group, how do individuals decide whether they should search for food or pay attention to others who are searching for food (and then parasitize the discovered food locations). This gives us an opportunity to use basic game theory to make predictions about behaviorally stable strategies (i.e., strategies that can change dynamically but will have consistent outputs in consistent contexts).
Topic highlights:
positive and negative externalities in social foraging
open-access/common-pool resources and the tragedy of the commons
optimal group size and equilibrium group size
producer–scrounger game
Stable Equilibrium Frequency (SEF) and Behaviorally Stable Strategy (BSS)
Important terms: positive externality, negative externality, open-access resource/common-pool resource, tragedy of the commons, “G star” (intake-maximizing group size), “G hat” (open-access equilibrium group size), finder’s advantage, Stable Equilibrium Frequency (SEF), Behaviorally Stable Strategy (BSS)