The study of human behavior has been at the core of scientific research since its inception, and theories to describe its emergence, transformation, and diversity continue to engage scholars across the natural and social sciences. For many social scientists, evolutionary theory has been a useful framework for understanding what motivates and constrains human behavior and also why it varies both among individuals in the same society and across cultures. Within the diversity of perspectives studying the nexus of evolution and human behavior, the field of human behavioral ecology (HBE) emerged as the study of the adaptive nature of behavior as a function of socioecological context. In this volume, we explore the history and diversification of HBE, a field which has grown considerably in the decades since its emergence in the 1970s. At its core, the principles of HBE have remained a clear and cogent way to derive predictions about the adaptive function of behavior, even as the questions and methods of the discipline have evolved to be more interdisciplinary and more synergistic with other fields in the evolutionary social sciences.
Any study of human behavior is helped by first highlighting the myriad ways in which we are unique as a species. As primates, we share many important traits with our closest relatives, the great apes, including a slow life history, a large brain-to-body size ratio, group living with kin-based alliances, and complex patterns of social behavior. However, among apes, humans are also distinct. For instance, humans exhibit less sexual dimorphism than other great apes, not only in overall body size but also in the size of canine teeth that can serve as weaponry among primate males. The slow life history of apes is even more extended in humans, with a long period of childhood and a delayed age at first birth. Yet, compared to other primates, humans have a relatively high fertility rate, resulting from shorter interbirth intervals. In addition, humans routinely live for an extended time beyond the birth of their last children, and this long postreproductive life span is common even in settings without modern health care technologies. The intersecting features of delayed maturity, short interbirth intervals, and long life span contribute to our designation as a species of cooperative breeders, as it is common for multiple individuals to contribute to the care and provisioning of human children, including care from grandparents and elder siblings.
Other facets of human behavior also distinguish us from our primate relatives. In general, collaborative subsistence strategies and food sharing are ubiquitous features of human societies, as opposed to the more solitary foraging habits of other primates. Our social organization is relatively flexible, and kinship systems, rules of descent, and postmarital residence rules exhibit remarkable cross-cultural diversity. This variation partly relates to local ecological constraints, paralleling the heterogeneous social organization of nonhuman primates. However, the diversity of social structures among humans displays variety and combinations not seen within other species. These structures are further elaborated by cultural practices, which add additional complexity. For example, marriage is a cultural universal with deep evolutionary roots, and it involves social connections and obligations that go far beyond mating. Kinship likewise extends beyond biological bonds through cultural processes such as fictive kinship, affinal relationships, and adoption.
Our system of communication, including symbolic language, is also unrivaled in the animal world. In particular, humans exhibit a pronounced reliance on language for cultural transmission and social learning. Cumulative cultural transmission facilitates the use of tools and other technological adaptations to local environments. Language and other adaptations also allow humans to cooperate on unparalleled scales, not only with kin and other local group members but also with out-group members – an unusual trait for any primate. Together, the capacity for human culture has allowed us to inhabit and thrive on the most remote parts of the planet, create complex institutions, and develop cumulative technologies that transform both our own ways of life and the ecosystems we inhabit.
Human behavioral ecologists maintain a long-standing interest in both the evolution of these distinctive traits and the ways in which they vary within our species. To pursue research questions along these lines, projects typically occur at the level of individuals. This methodological individualism (Udehn Reference Udehn2002) reflects several key assumptions of the HBE approach. First, long-term evolutionary processes are the result of variation in fitness-related outcomes among individuals throughout their lives (Williams Reference Williams1966b). Accordingly, studies of behavioral variation in human populations can elucidate key trade-offs that underlie the long-term evolution of adaptive traits. Relatedly, humans are assumed to respond flexibly to socio-environmental variation in ways that promote fitness-enhancing outcomes.
This assumption of behavioral flexibility is central and implicit in theoretical models, meaning that behavior is expected to vary across individuals based on their respective socioecological circumstances. The resulting view of behavioral flexibility departs from alternative views of behavior as instinctive, rote, or culturally determined. That is not to claim, however, that all human behaviors are unambiguously adaptive. Humans also exhibit maladaptive behaviors, and these behaviors potentially reflect important constraints on human evolution, therefore meriting attention from researchers, too. In general, though, the HBE approach posits that humans evolved to respond effectively to diverse evolutionary challenges, and the resulting natural history of our species is what motivates human behavioral ecologists to pursue their research.
1.1 The Intellectual History of Human Behavioral Ecology
Human behavioral ecology has its roots in two fields, both of which emerged in the middle of the twentieth century. The first, cultural ecology, sought to understand the role of the natural environment in effecting culture change. Cultural ecology was a response to two opposing worldviews of the time, each of which propagated an iteration of the nature versus culture dichotomy. First, emphasizing nature as primary, environmental determinists proposed that human behavior was dictated by local environmental conditions, relegating culture to a response rather than a primary force. On the other hand, the possibilists, led by Franz Boas and Alfred Kroeber, posited that human response to environmental conditions was extremely mutable and that culture could take a variety of possible forms in the same environment, with cultural history and the diffusion of ideas and technologies playing key roles. The cultural ecology movement, led by Julian Steward, proposed that the environment influenced the ways that people adapted to their environment but did not determine it, offering a middle ground between determinism and possibilism. This middle ground was a critical contribution of cultural ecology. However, it did not offer an explanation for why such patterns of adaptation would occur. To fill this gap, early human behavioral ecologists turned to evolutionary theory.
Like cultural ecology, the field of ethology focused on human-environment interactions, but it grew out of biology and comparative psychology. It can be traced back to Darwin, but the works of scholars such as Konrad Lorenz and Niko Tinbergen focused evolutionary theory on the study of behavior in natural settings, which would become a hallmark of behavioral ecology. The 1960s and 1970s saw the emergence of many of the models and theories that would form the backbone of behavioral ecology, including kin selection theory (Hamilton Reference Hamilton1964), optimal foraging theory (MacArthur and Pianka Reference MacArthur and Pianka1966), parental investment theory (Trivers Reference Trivers and Campbell1972), and life history theory (Stearns Reference Stearns1976). These models continue to be at the core of behavioral ecology and are the foundation of much of the work in this volume.
In the mid-1970s, a number of anthropologists and archaeologists began to apply evolutionary theory and the aforementioned models within particular human populations through ethnographic fieldwork. These early studies tackled basic questions about the roles of kin selection, sexual selection, and fitness optimization in humans (Chagnon Reference Chagnon, Chagnon and Irons1979; Hames Reference Hames, Chagnon and Irons1979; Strassmann Reference Strassmann1981; Turke and Betzig Reference Turke and Betzig1985). Around the same time, the first applications of optimal foraging theory were applied to hunter-gatherers (Winterhalder and Smith Reference Winterhalder and Smith1981; O’Connell and Hawkes Reference O’Connell, Hawkes, Winterhalder and Smith1981; Smith Reference Smith1985). In general, the results of these studies frequently upheld the predictions of HBE models, which helped to launch additional theorizing and applications to increasingly diverse research questions.
1.2 Basic Principles of HBE
The evolutionary study of behavior is traditionally organized around four complementary approaches: causation, development, function, and phylogeny (Tinbergen Reference Tinbergen1963). The first two focus on proximate (i.e., more temporally direct or immediate) explanations: understanding the mechanism of the behavior (causation) and its ontogeny (development). The second two questions address ultimate (i.e., more distal or evolutionary) explanations: studies of phylogeny and studies of adaptation or function. Of these, behavioral ecologists have almost exclusively focused on function, aiming to understand how natural selection has produced organisms that respond to environmental conditions in ways that increase their chances of surviving and passing on genes to the next generation. This focus on adaptation means that HBE uses, as a starting point, the hypothesis that behavior will be close to optimal in terms of maximizing fitness.
Human behavioral ecology’s conventional agnosticism about development and mechanism has been exemplified through its acceptance of the “phenotypic gambit,” an assumption that systems of inheritance do not meaningfully constrain adaptive responses to local variation. In practice, this approach allows a researcher to study the fit between ecology and behavior without needing to uncover or specify the exact proximate mechanisms (developmental, physiological, or behavioral) through which this fit is achieved.
While HBE research continues to focus on function, the field has become more integrative of other approaches to the study of behavior. In so doing, the methodological agnosticism that initially characterized HBE is being replaced by the notion that “mechanisms matter” (Borgerhoff Mulder Reference Borgerhoff Mulder2013). For example, researchers in genomics have made important discoveries about feedbacks between genes and behavior that highlight the need for a deeper consideration of genetic mechanisms (Adkins et al. Reference Adkins, Rasmussen and Docherty2018; Kuzawa and Thayer Reference Kuzawa and Thayer2011). In addition, the role of transmitted culture is increasingly being recognized by human behavioral ecologists as important not only to understanding why maladaptive outcomes occur but also in illuminating how behavioral strategies arise and thrive (Mesoudi Reference Mesoudi2021; Newson et al. Reference Newson, Richerson, Boyd, Kitayama and Cohen2007), which again highlights a need for greater integration of proximate and ultimate approaches in research. Throughout this volume, readers will see evidence of this integration of the four basic approaches, though generally still with an overarching emphasis on adaptation and function.
Another central tenet of behavioral ecology involves conceptualizing behavior in terms of conditional strategies to understand variation in phenotypes, often organized around a strategy set that represents possible variations of a behavior in a particular context. In simple form, conditional strategies involve logic such as: “When conditions are X, use strategy i, but when conditions are Y, switch to strategy j.” For example, males in a population who want to find a mate could either fight to control a territory and the females on it or try to sneak matings from within other males’ territories. Which strategy any individual male chooses is predicted to be contingent on factors such as his physical condition, his relative status, and the density of females in the area.
More complex decisions require much larger strategy sets. When a forager decides what resources to pursue, for example, she has a variety of possible combinations to choose from. Strategies can also cross domains, including decisions about how to meet both childcare and food production goals (Scelza and Bliege Bird Reference Scelza and Bliege Bird2008; Starkweather et al. Reference Starkweather, Reynolds, Zohora and Alam2023), or assessing both the social and productive aspects of foraging alone versus in a group (Smith Reference Smith1985; Alvard and Nolin Reference Alvard and Nolin2002). Behavioral responses are expected to vary according to local conditions; thus, what is optimal in one context is likely to differ from what is optimal in another circumstance or for another person. Early HBE studies focused on how ecological variation in the physical environment helps to explain the diverse behavioral repertoire that characterizes modern humans despite a lack of noteworthy genetic differences across populations. As the field has grown, ecology has begun to be construed more broadly to include social and institutional contexts such as socially enforced norms and government policies.
The goal of HBE continues to be understanding variation in phenotypes and predicting what characteristics of the local environment lead to the uptake of one strategy over another. At their core, these decisions are believed to be about optimizing fitness. This approach might include predictions that foragers will pursue only resources that increase their return rate, that optimal family size will reflect local mortality risks, or that the likelihood of cooperation between individuals depends on their biological relatedness and level of need.
Human behavioral ecology’s reliance on the logic of optimization does not presuppose that humans are perfectly adapted to their environments (though this is a common misconception).Footnote 1 Instead, optimization models follow from the principles of natural selection, which is expected to favor locally advantageous adaptations over time, leading to an increasingly better fit of behavior with local environments. Yet, behavioral ecologists are also keenly aware of the potential for mismatch between fitness and local behavioral adaptations when environments change very quickly, as they have been in many regions of the world in the era of globalization (Gurven et al. Reference Gurven, Stieglitz, Trumble and Kaplan2017). In these contexts, behavioral ecologists aim to understand how traditional behavior may have been adaptive given the past environment and also how changing patterns of behavior may be understood from an evolutionary perspective.
In order to assess the costs and benefits of alternative strategies, behavioral ecologists need a standardized “currency“ for comparison. The ideal currency for evolutionary models is fitness, but fitness is a probabilistic rather than an absolute measure, representing the likelihood that an individual will survive and pass on genes to the next generation. This makes it very difficult to measure directly. Instead, behavioral ecologists use fitness proxies, traits that are widely accepted to be positively correlated with survival and reproduction. Within human behavioral ecology, commonly used proxies include calories, body composition, mating frequency, number of children born, and number of children who survive early childhood.
The final factors that behavioral ecologists must consider are the constraints to the system, namely the aspects of the environment that are not under the control of the actors whose decisions are being modeled. Most systems have both extrinsic and intrinsic constraints. Extrinsic constraints include ecological characteristics, such as the distribution of prey in the landscape, the number of competing hunters in the group, or the level of risk from infectious disease. Intrinsic constraints can include diverse perceptual and sensory factors, cognitive constraints, and physiological limitations and other morphological considerations.
1.3 What We Work On
Human behavioral ecology focuses on behavioral responses to variation in the environment, which opens up a wide variety of topics for its practitioners. However, the majority of HBE studies have focused on production, cooperation, distribution of resources, and reproduction. Here we provide a brief history of work on these topics, and then we shift to describe what we perceive as the major trends that are guiding current and future research in HBE.
Human behavioral ecology largely originated with applications of optimal foraging models, borrowed from behavioral ecology and applied to contemporary foraging societies. These models address trade-offs and strategies of subsistence-based production, including whether to pursue a prey type when it is encountered, how long to stay in a particular location or “patch,” and how to account for stochasticity in the resource base to avoid shortfalls. Over time, this part of the field expanded further to consider the motivations behind foraging activities (e.g., do men hunt to provision families or to attract mates?), how foraging strategies vary across the life span, and the sexual division of labor. Market integration has also resulted in changing modes of production and increased the likelihood of mixed modes of production within communities, meaning researchers need to pay careful attention to complicated aspects of the household economy, including the practice of traditional livelihood strategies (e.g., agriculture, fishing, herding) alongside new ones (running a local shop, migrating to cities for work) – several of which may be simultaneously evident among members of the same family, household, compound, or village (Tucker et al. Reference Tucker, Tsimitamby, Humber, Benbow and Iida2010; Ready and Power Reference Ready and Power2018; Starkweather Reference Starkweather2017). The first part of this volume addresses these topics with chapters on foraging strategies (Chapter 3), modes of subsistence (Chapter 4), and the division of labor (Chapter 6).
Another recurrent theme within HBE research has been a focus on the unprecedented scale of cooperation that humans exhibit. At first, much of this work examined the question of altruism and the conundrum of how natural selection could favor behaviors that benefit others at a cost to the actor. Kin selection and reciprocal altruism, both also widely discussed in other species, were early models that HBE practitioners considered in depth. Much of the empirical work on this front focused on food sharing and cooperative production, providing interesting addenda to tests of optimal foraging models. These extensions include the ways in which biological markets have affected cooperation and food sharing (Jaeggi et al. Reference Jaeggi, Hooper, Beheim, Kaplan and Gurven2016b). Beyond food production and distribution, HBE has devoted attention to myriad other aspects of cooperation, including political alliances, warfare, and childcare. This volume addresses these topics in chapters on cooperation (Chapter 5), status and hierarchy (Chapter 7), and political organization (Chapter 8).
Studies of reproduction represent the broadest and fastest-growing area of research within HBE (Nettle et al. Reference Nettle, Gibson, Lawson and Sear2013). This literature encompasses studies of mating and marriage, the role of parents and alloparents, and broader demographic patterns of fertility and mortality. Much of this work relies on principles from life history theory, which outlines how natural selection can shape patterns of growth, survival, and reproduction in a given species. Classic research in this area focused on variation in mating and marriage strategies, often extrapolating from models like the polygyny threshold model (Borgerhoff Mulder Reference Borgerhoff Mulder1990), as well as tackling variation in marriage payments across societies (Dickemann Reference Dickemann1991; Gaulin and Boster Reference Gaulin and Boster1990). Early work on fertility and parental investment investigated the optimality of birth spacing (Blurton Jones Reference Blurton Jones1987) and differential investment (Mace Reference Mace1996; Daly and Wilson Reference Daly and Wilson1983; Borgerhoff Mulder Reference Borgerhoff Mulder1998a), and researchers also took on the challenge of explaining the demographic transition (Borgerhoff Mulder Reference Borgerhoff Mulder1998b; Mace Reference Mace1998).
As with studies of production, changes brought about by urbanization, market integration, and globalization have also spurred strong interest in shifting patterns of mating, marriage, and parental and alloparental investment. Recent studies of mating and marriage have considered how an HBE perspective can be useful for understanding issues such as dowry inflation (Shenk Reference Shenk2007), the relationship between wealth inequality and polygyny (Ross et al. Reference Ross, Borgerhoff Mulder and Oh2018), and how labor migration affects mating market dynamics (Schacht and Smith Reference Schacht and Smith2017). Industrialization is also often implicated in the shift toward more intensive investment in a smaller number of children who can compete for opportunities in the emerging wage labor economy (Kaplan Reference Kaplan1996). This shift has prompted novel forms of parental investment, notably including formal education, which was traditionally nonexistent but is often the primary form of investment in children in market-integrated societies. These changes have motivated researchers to consider how investment in children changes with subsistence patterns (Hassan et al. Reference Hassan, Lawson, Schaffnit, Urassa and Sear2021) and also how to conceptualize such new forms of investment from a theoretical perspective. Moreover, education leads to novel forms of social learning and cultural transmission (Kline et al. Reference Kline, Boyd and Henrich2013), which may accelerate the effects of cultural change in market-integrated societies (Richerson and Boyd Reference Richerson and Boyd2005); it is thus unsurprising that the study of social learning has become a very active field of study in the past few years. Finally, new iterations of sexual selection theory have triggered reevaluations of some classic evolutionary models, as seen in studies of the adult sex ratio and mating market dynamics (Schacht and Borgerhoff Mulder Reference Kasper and Borgerhoff Mulder2015) and the role of multiple mating for women (Scelza Reference Scelza2013). Often drawing upon life history theory (Chapter 2), the second half of this volume addresses these topics, including chapters on mating (Chapter 9), marriage (Chapter 10), parental investment (Chapter 11), cooperative breeding (Chapter 12), and evolutionary demography (Chapter 13).
As HBE has developed, not only have the questions changed, but so have the ways in which researchers have addressed them. With an increasing number of researchers working alongside NGOs and in areas of the world where economic development policies are being implemented, the field has also taken a turn toward applied approaches, leading to the emergence of a subfield of applied evolutionary anthropology (Gibson and Lawson Reference Gibson and Lawson2015; Pisor and Jones Reference Pisor and Jones2021; Tucker and Rende Taylor Reference Tucker and Rende Taylor2007). The goals of this approach are to apply the logic and models of HBE to address practical challenges faced by communities and to engage with the international development community to understand the consequences of development projects, ideally steering programs in a more locally appropriate direction. Human behavioral ecologists taking this approach have studied numerous topics, including health (Lawson and Uggla Reference Lawson, Uggla, Gibson and Lawson2014; Pepper and Nettle Reference Pepper and Nettle2017), the green revolution (Tucker Reference Tucker, Gibson and Lawson2014), microfinance (Lamba Reference Lamba2014), family planning decisions (Leonetti et al. Reference Leonetti, Nath and Hemam2007), the nutrition transition (Neill Reference Neill2007), sex ratio bias (Shenk et al. Reference Shenk, Towner, Starkweather, Atkisson and Alam2014), and climate change (Bliege Bird and Bird Reference Bliege Bird and Bird2021). As in other subfields of anthropology, these approaches sometimes constitute a critique of policies promoted by development agencies that ignore important ethnographic context or take unrealistic or ethnocentric approaches to problems where evolutionary theory provides key insights, such as work on “child” marriage (Schaffnit and Lawson Reference Schaffnit and Lawson2021), dowry (Shenk Reference Shenk2007), and domestic violence (Stieglitz et al. Reference Stieglitz, Trumble, Kaplan and Gurven2018).
To address these issues and generally add depth to the study of HBE, causal mechanisms have become an area of greater interest. There has also been a shift from studies focused largely on individual-level decision-making to ones that encompass institutions and cultural processes. Whereas HBE has historically been set in tension with other disciplines studying evolution and human behavior, increasingly researchers are finding fruitful areas of overlap. Accordingly, this volume includes chapters on human biology (Chapter 14), cultural evolution (Chapter 15), and evolutionary psychology (Chapter 16), which showcase the ways in which HBE fits within the larger field of evolutionary social science.
1.4 How We Work
Like most basic science research, HBE relies on a hypothetico-deductive research strategy, which involves the use of models to derive specific, testable predictions. HBE strategically relies on simple models that capture the basic elements of a situation, sacrificing detail and nuance for clarity and generalizability. Simple models are useful because they can be applied across many contexts. This means that general theoretical concepts can be applied across diverse settings to identify the kinds of conditional strategies that are at the core of the field. But the fact that HBE models are generalizable rather than context-specific has sparked intermittent criticism from cultural anthropologists, who assert that such reductionism is unrealistic. In one sense, this criticism is justified; simple models cannot provide a holistic replication of real-world dynamics. Yet, rather than trying to replicate reality, HBE models aim to highlight the central role of particular variables and trade-offs that underlie behavioral strategies in multiple contexts. This approach requires simplifying assumptions, including assumptions that are unlikely to capture all relevant variation.
For example, when human behavioral ecologists first adapted the polygyny threshold model from biology (Orians Reference Orians1969), it was assumed that co-wives did not offer benefits to one another, such as increased production efficiency or help with childcare (Figure 1.1). The models focused only on the relative benefits that women could gain from partnering with either an unmarried or an already married man. This allowed for the derivation of clear predictions (e.g., women should choose to marry a married man only when the share of resources that she would receive are greater than those she would have upon marrying an unmarried man). The goal was to identify the effect of male resources on women’s decisions about whom to marry.
Figure 1.1 A graphical depiction of the polygyny threshold model (Orians Reference Orians1969). The two sigmoidal curves show the respective fitness functions of a woman who either partners monogamously (solid line) or as a second mate (dashed line). The curves vary as a function of the male partner’s resources, and assuming an unconstrained choice, women are expected to choose the option that maximizes their fitness. The optimal choice depends on the potential partners’ respective resources. Consider the choice between the monogamous option in which the partner’s resources are represented by point A and the polygynous option with a partner’s resources at point B. The horizontal dotted line represents the threshold at which the choices are equivalent. If point B were to shift downward, then monogamy would be favored. Conversely, if point B were to shift upward, the polygynous option would be advantageous. Note that the fitness functions depicted here are hypothetical and could vary substantially in different contexts, particularly when integrating additional considerations such as those described in the text (e.g., potentially beneficial cooperation among co-wives).
Empirically, however, researchers found mixed support for the basic polygyny threshold model. Among Kipsigis of Kenya, female choice based on relative resource access appeared to be a key factor in the decision to marry polygynously, supporting the conceptual model (Borgerhoff Mulder Reference Borgerhoff Mulder1990). In other settings, however, polygynous women fared worse than their monogamous counterparts, indicating that the female choice model advanced by Orians does not necessarily fit well in human populations and that men may be coercing women into polygynous marriages that benefit their own fitness interests (Chisholm and Burbank Reference Chisholm and Burbank1991). This led researchers to follow up with studies that focused on the importance of co-wife cooperation and conflict as motivators or detractors for choosing polygyny (Jankowiak et al. Reference Jankowiak, Sudakov and Wilreker2005; Scelza Reference Scelza2015), the interaction of polygyny with other socioecological factors (Lawson et al. Reference Lawson, James, Ngadaya, Ngowi, Mfinanga and Borgerhoff Mulder2015), and the role of parental marriage arrangements in curtailing female choice (Apostolou Reference Apostolou2007). Other work incorporated richer demographic data to assess the links between polygyny and fertility and to assess whether a choice or coercion model is a better fit (Winking et al. Reference Winking, Stieglitz, Kurten, Kaplan and Gurven2013). That is, researchers started with a simple model, and then, as they accrued data, they were able to use previous results to develop refined models that better predicted men’s and women’s decisions.
To test their models, human behavioral ecologists employ diverse methods from biology, anthropology, economics, and psychology, often integrating quantitative and qualitative data. Typically, quantitative data are used in direct tests of predictions, while qualitative data help researchers to design methodological tools and contextualize their results. Quantitative methods frequently include surveys or questionnaires for demographic data, direct observation for behavioral data, weighing and measuring of items (e.g., gathered foods or household goods) to understand return rates or wealth, and health measurements (e.g., height, weight, blood pressure). Traditional qualitative methods from cultural anthropology are also widely used, including open-ended interviews, focus groups, and participant observation. These are central to gaining local ethnographic knowledge, developing nuanced questions for more structured data collection, and interpreting the results of those data during analysis (Box 1.1).
To illustrate how human behavioral ecologists approach research problems, it is useful to consider an example. In this case, consider the example of polyandry, marital unions with one woman and multiple men. Ethnographically, polyandrous marriages are significantly rarer than polygynous marriages, but a survey of the literature reveals a few societies, mostly in the Himalayas, where polyandry is common (Figure B1.1.1). If natural selection favors behaviors and decisions that tend to increase an individual’s long-term evolutionary fitness, then initially it may seem irrational for a man to consider a polyandrous union that limits his fertility relative to a monogamously or polygynously married man. However, this seemingly suboptimal behavior recurs intermittently in diverse contexts, which invites attention and scrutiny from human behavioral ecologists.
Figure B1.1.1 Fraternal polyandry has been documented primarily in the Himalayas, including the state of Himachal Pradesh in northern India.
To consider why polyandry occurs, a human behavioral ecologist might begin by considering similar behaviors among nonhuman primates and other animals. The comparative approach is valuable because behavioral strategies among animals may be homologous traits that are similar because of shared ancestry (Wrangham Reference Wrangham and Kinzey1987). For example, many primates exhibit predispositions to develop fears of snakes, and consequently the presence of this homologous trait in humans does not require an explanation of its origin in the hominin lineage (Öhman and Mineka Reference Öhman and Mineka2003). In the case of polyandry, however, the behavior is not found generally among extant catarrhine primates, including apes, which suggests that polyandry in humans is not an ancestral trait.
Independent of homology, though, humans often face decisions that resemble those by nonhuman animals. Among some nonhuman primates, males similarly decide either to stay in a social group with a dominant breeding male – with limited reproductive opportunities – or to disperse in search of other females (e.g., Snyder-Mackler et al. Reference Snyder-Mackler, Alberts and Bergman2012). The decision to stay and share reproduction with another male often results from a lack of better alternatives, and these theoretical models can be adapted to human contexts. Analogously, most explanations of polyandry in humans maintain that polyandry is more likely when socioecological constraints limit men’s ability to support their families through monogamous marriage, and thus wife-sharing may be a better alternative than remaining single (Levine and Silk Reference Levine and Silk1997).
Human behavioral ecologists attempt to consider the full range of costs and benefits that underlie behavioral choices. For example, following kin selection theory (see Chapter 5), the costs of polyandry can be mitigated if co-husbands are related because the offspring are genetic relatives of all husbands. Known as fraternal polyandry, marriages involving brothers are the most common type of polyandrous union across human societies (Starkweather and Hames Reference Starkweather and Hames2012). In human contexts, meanwhile, institutions and cultural norms can also shape the trade-offs of different strategies. In Himalayan settings, for example, oldest sons often inherit their parents’ estate, which provides them with advantages in the marriage market.
With these considerations in mind, Smith (Reference Smith1998) examined the trade-offs of fraternal polyandry by adapting the member-joiner model, which had been developed previously to study the aggregation of foraging groups in animal populations, including humans (see Chapter 3). Applying the model to a polyandrous Tibetan population, Smith found that for “members” (i.e., the already married eldest brother), polyandry seemingly results in a loss of inclusive fitness compared to monogamy, but for “joiners” (i.e., younger brothers), polyandry increases their inclusive fitness relative to their alternative options. Notably, this result was based on the tenuous assumption that all husbands have an equal probability of fathering the wife’s offspring. Greater reproductive opportunities for the older husband within the marriage would alter the trade-offs accordingly. The potentially asymmetric benefits to the co-husbands, however, illustrate a general point that family relationships are often unstable as individuals constantly reevaluate the costs and benefits of their possible choices.
In principle, if all of the contributing factors can be identified and measured precisely for a given individual at a certain moment in time, then the individual’s adaptive decision is knowable scientifically. Although such comprehensive precision may be impossible, the theoretical models nonetheless facilitate hypotheses that can be tested empirically. Whether those hypotheses relate to polyandrous marriages or other decisions, the enterprise of human behavioral ecologists is to theorize about the primary determinants of adaptive decision-making and to marshal the evidence needed to test the predictions of those theories.
One set of methods, borrowed from behavioral ecology studies of other species and advantageous for providing both reliable observations of behavior and deeply contextualized data, is the systematic recording of time allocation (Hames Reference Hames1992). Common sampling designs include focal follows, which allow for longer periods of observation focused on a single individual, or instantaneous scans, which are designed to gather information on many individuals over a short period of time. In humans, time allocation data have been used to test optimal foraging models (Hill et al. Reference Hill, Kaplan, Hawkes and Hurtado1987; Koster Reference Koster2008), to assess the role of parents and alloparents in studies of investment (Ivey Reference Ivey2000; Scelza Reference Scelza2009), and to examine behavioral specialization and trade-offs in subsistence strategies (Koster and McElreath Reference Koster and McElreath2017). The methods have also been used to address questions about human life histories, including how time allocation changes across the life span (Gurven and Kaplan Reference Gurven and Kaplan2006) and how children’s labor can help to offset their costs, allowing for larger family sizes (Kramer Reference Kramer and Alvard2004).
Time allocation observations are the methods most closely associated with HBE, and the approach has several benefits. First, it allows researchers to learn about actual behavior, rather than normative rules or hypotheticals that ask participants to speculate on how they would behave in a certain situation. Quantitative observational studies can reduce reporting biases from interviews and ethnographic observations that tend to overrepresent cultural rules while underestimating behavioral variability (Johnson and Behrens Reference Johnson and Behrens1989). Second, because the methods are clearly defined, the studies are replicable and amenable to cross-cultural comparisons. For example, a cross-cultural study leveraged time allocation data from twelve different study sites to investigate how the local socioecology, including the risk of encountering dangerous animals and the sexual division of labor, affected children’s activity budgets (Lew-Levy et al. Reference Lew-Levy, Reckin, Kissler and Koster2022). However, there are some important limitations to using time allocation data, including the time required to get participants accustomed to being observed and the inability to observe certain types of behavior that are either private or otherwise inaccessible to the researcher.
Structured and semi-structured interviews are another key method of HBE research that aims to collect systematic data for hypothesis testing. These interviews can be used to elicit demographic data (e.g., reproductive and marital histories), life history trajectories, measures of household wealth, or patterns of mobility. Many researchers develop questions and measures to fit local situations, but increasingly cross-culturally validated measures are also used, including food and water security scales (Young et al. Reference Young, Boateng, Jamaluddine and Stoler2019), the Big Five personality inventory (Gurven et al. Reference Gurven, von Rueden, Massenkoff, Kaplan and Lero Vie2013), and measures of sexual conflict (Stieglitz et al. Reference Stieglitz, Trumble, Kaplan and Gurven2018) and mental health (Hadley and Patil Reference Hadley and Patil2006; Lawson et al. Reference Lawson, Schaffnit, Hassan and Urassa2021).
Human behavioral ecologists also borrow methods from other disciplines in the social sciences. For example, economic games have been widely used to assess norms about cooperation (Henrich et al. Reference Henrich, Boyd, Bowles and Ensminger2005). However, the mixed-method approach favored by human behavioral ecologists has led to integration of these games with other behavioral measures. For example, Gerkey (Reference Gerkey2013) used locally relevant derivations of the public goods game to understand how cultural norms and institutions frame cooperative decision-making. In another novel experiment, Gervais (Reference Gervais2017) had Fijian participants allocate money within their social networks to assess how factors like relative need, altruism, and spite affect behavior.
While human behavioral ecologists have long studied cooperation, conflict, kin residence patterns, and other forms of social interactions, quantitative data on social networks allow social relationships to be described and analyzed in a more sophisticated way. Social network data can be used to illuminate the latent structure of the underlying network, examine the relationships of different networks to each other, and compare how networks change across time. Such studies have allowed testing of hypotheses about food sharing (Nolin Reference Nolin2010) and religious practices (Power Reference Power2017b), as well as the dynamics of multiplex networks in studying cooperation and reciprocity across multiple domains (Atkisson et al. Reference Atkisson, Górski, Jackson, Hołyst and D’Souza2020).
Increasing interest in physiological proxies of fitness such as cardiovascular health, malnutrition, and stress have also led human behavioral ecologists to integrate health measurements into their work. These range from conventional anthropometrics (e.g., height, weight, triceps skinfolds) to biomarkers of conditions such as anemia, diabetes, and inflammation that are evident in blood and saliva samples. Health trackers have also been used to analyze heart rate, sleep, and blood pressure. These studies also allow for further integration of proximate and ultimate explanations of behavior, as mechanisms are studied alongside functional outcomes. When used alongside demographic and behavioral data, these measures can be used to test adaptive predictions. For example, Wander and Mattison (Reference Wander and Mattison2013) used anthropometric and breastfeeding data to test the Trivers-Willard hypothesis of sex-biased investment, Scelza and Silk (Reference Scelza and Silk2014) used anthropometrics to test predictions about whether fosterage is adaptive among Himba pastoralists, and Trumble et al. (Reference Trumble, Smith, O’Connor, Kaplan and Gurven2014) looked at testosterone and cortisol to test between signaling and provisioning predictions for explaining men’s work.
As with other fields of anthropology, there has also been a recent shift toward greater collaboration in the research process. This includes increased community engagement in the development of research projects (Broesch et al. Reference Broesch, Crittenden, Beheim and Borgerhoff Mulder2020; Mangola et al. Reference Mangola, Lund, Schnorr and Crittenden2022; Scelza et al. Reference Scelza, Atkinson, Prall, McElreath, Sheehama and Henn2020a), integrating positive outcomes for communities into research plans (Gurven et al. Reference Gurven, Stieglitz, Trumble and Kaplan2017), co-publication with local scholars and/or members of study communities (Urassa et al. Reference Urassa, Lawson, Wamoyi and Placek2021) and a commitment to better engagement with policy, development, and the general public (Jones et al. Reference Jones, Ready and Pisor2021a). These shifts are motivated by goals of both increased equity and improved science.
1.5 Where We Work
At the field’s inception, human behavioral ecologists worked mainly in small-scale societies, particularly among foraging and pastoralist groups. This focus reflected both theoretical and practical constraints. Theoretically, foraging populations were often chosen because they had features that were believed to have been common throughout our evolutionary history, such as a strong reliance on kin, low population density, substantial familiarity with one’s social group, fertility and mortality patterns that were minimally affected by contraception and biomedical care, and a reliance on intermittently acquired food resources (Box 1.2). Practically, the initial emphasis of HBE on foraging strategies led to the frequent choice of field sites where groups were still hunting and gathering for a substantial portion of their calories. These sites represent some of the best long-term anthropological field sites in the field of HBE, including researchers of several generations (Marlowe Reference Marlowe2010; Gurven et al. Reference Gurven, Stieglitz, Trumble and Kaplan2017).
Box 1.2 The Human Behavioral Ecology of Academic Research: An Ideal Free Distribution
A premise of HBE is that humans flexibly adapt to the costs and benefits of behavioral choices in a given setting. This adaptive flexibility is evident not only among the people being studied but also among the researchers themselves. When selecting research questions and study sites, human behavioral ecologists respond to incentives that reward certain kinds of studies.
Among human behavioral ecologists, the perceived value of a study typically is commensurate with its purported relevance for understanding key aspects of human evolution. This emphasis is shared by cognate subdisciplines. Among primatologists, for instance, that relevance is assumed to vary as a function of phylogenetic distance to humans, lending extra cachet to research on the great apes. Among paleoanthropologists, there is similar prestige associated with studying hominin species that are assumed to be directly on the human lineage, more than offshoot clades such as paranthropines. Accordingly, particularly since the Harvard Kalahari Project among the !Kung of Botswana in the 1960s, human behavioral ecologists were motivated to seek out contemporary study populations living in environments or engaging in subsistence practices that presumedly resemble those of human populations in the Pleistocene (Yellen Reference Yellen1990; see Chapter 16).
The societies that are studied by human behavioral ecologists often exhibit noteworthy variation in food production directed to meeting subsistence needs, social organization based around kinship, and sociopolitical arrangements in which state-level involvement may be minimal (Figure B1.2.1). In many cases, these societies are Indigenous or ethnic minorities who maintain distinct languages and cultures that differ from the majority in the nation-states where they reside. In general, these settings often provide worthwhile opportunities for human behavioral ecologists to examine specific predictions from theoretical models. For example, when research questions focus on cooperative food production by groups of kin, it is sensible to focus on study sites where these behaviors occur regularly.
Figure B.1.2.1 This figure shows a comparison of selected demographic and economic variables for a diverse set of societies. Calculated as averages, the variables include (1) years of maturity, starting at age 15, before individuals have their first child, (2) rates of child mortality under the age of 5 years old, (3) the total fertility rate, and (4) wealth per adult. Values within each category are standardized as the proportion of the maximum value. So-called WEIRD populations are represented with darkened symbols, whereas the six other societies are unfilled, with the latter sample drawn from studies by human behavioral ecologists. Among other implications, the comparisons suggest that HBE research often expands the range of behavioral variation observed in human populations. (WEIRD is an acronym to describe societies that are Western, Educated, Industrialized, Rich, and Developed.)
To explain the preponderance of HBE studies among subsistence-oriented ethnic minorities, it is helpful to refocus the field’s theoretical models onto its practitioners. Chapter 3, for instance, presents the Ideal Free Distribution model. Similar to the polygyny threshold model, the Ideal Free Distribution model assumes that individuals select habitats that offer the greatest value, adjusting for the extent to which the benefits are shared with others. By analogy, the high value that is placed on studies with perceived evolutionary relevance helps to explain why human behavioral ecologists have chosen their study sites and research questions in accordance with an Ideal Free Distribution.
The approach has pros and cons. On the one hand, the effort to document and understand human diversity has merit. It remains an effort that anthropologists have taken more seriously than any other academic community. On the other hand, the emphasis on similarities to ancestral populations can lead researchers to exaggerate or misrepresent aspects of their study sites in order to fit preconceptions about the ideal analogues for studying human evolution. In contrast to exotified narratives, ubiquitous features of nearly all study populations include monetized economies, modern contraceptive methods, medicines and vaccines, reliance on domesticated crops and animals, involvement of state-level governments, exposure to tourists and missionaries, and other factors that preclude the use of contemporary societies as straightforward analogues of Pleistocene populations. Clear acknowledgments of these factors benefit the interpretations of findings from HBE studies.
It is also important to acknowledge that the economic, social, and demographic orientation of many study communities relates in part to a legacy of political and racial marginalization. In some cases, the societies studied by human behavioral ecologists have retreated to remote locations to escape genocides and other violations of human rights, to maintain cultural independence, and to seek sustainable livelihoods. Those histories are considered carefully by human behavioral ecologists, who typically have substantial respect and affinity for their study communities and who hope to preempt the misuse of their published findings as a basis for further discrimination.
In principle, valuable research can be done in any human community. As human behavioral ecologists reconsider past biases, including the emphasis on contemporary societies as proxies for ancestral populations, there is likely to be a shift in the Ideal Free Distribution as greater consideration is given to the diversification of samples and the alignment between research questions and study populations.
Between the small-scale societies, where early HBE research was primarily conducted, and the postindustrial societies, in which researchers primarily live, lies most of the world – and our work is increasingly shifting to fill this gap both geographically and topically (Barrett Reference Barrett2020a). Owing to the recent rise of globalization and market integration, few societies rely solely on their own subsistence, and some have argued that the process has created an ecological shift as great as the widespread adoption of intensive agriculture. Upon encountering changing lifeways in their own field sites, many researchers have explored the causes and consequences of change – while for some the process of market integration itself has become a central organizational concept. Integration into regional and global market economies creates a shift in subsistence patterns (Gurven et al. Reference Gurven, Jaeggi, von Rueden, Hooper and Kaplan2015) with the potential to create downstream changes in numerous aspects of life, including parental investment (Colleran Reference Colleran2020), fertility and mortality rates (Shenk et al. Reference He, Zhang, Zhang and Tao2013), and health (Mattison et al. Reference Mattison, Hare, MacLaren and Wander2022b). These shifts also alter local cultural patterns of cooperation, kinship, family, residence, marriage (Shenk et al. Reference Shenk, Towner, Voss and Alam2016b; Scelza et al. 2019). These changes have steered attention toward novel research questions while motivating new methodological approaches.
The use of national-level data and large demographic surveys has also allowed for tests of adaptive hypotheses with large sample sizes typically unavailable in small-scale ethnographic fieldwork (Mattison and Sear Reference Mattison and Sear2016). These studies test the assumption within HBE that phenotypic plasticity leads to relatively fast adaptation to novel conditions. At the same time, they also highlight areas of potential adaptive lag, namely the possibility that humans exhibit suboptimal behavioral responses to novel environmental conditions that differ considerably from the settings to which human behavioral tendencies are adapted (Irons 1998).
Finally, because human behavioral ecologists have long been interested in the sources of behavioral variation, cross-cultural comparisons have played an important role in HBE research. Often, these studies rely on comparative analyses of similar demographic measures across cultures, such as variance in reproductive success (Brown et al. Reference Brown, Laland and Borgerhoff Mulder2009), the effects of alloparents on child mortality (Sear and Mace Reference Lawson and Mace2008), and kinship dynamics as a function of age (Koster et al. Reference Koster, Lukas, Nolin and Massengill2019). As with time allocation data, demographic data are comparatively straightforward to categorize and operationalize in cross-cultural studies. By contrast, studies that require consistent definitions of constructs such as “household” or “marriage” or “status” or other analogous variables have conventionally been challenging to standardize and analyze cross-culturally. Studies of psychology and cognition are likewise challenging, particularly those that require translations of complex concepts into diverse languages and cultural contexts.
Successfully navigating those challenges requires a thoughtful research design, and human behavioral ecologists have responded with careful attention to key methodological details and translations. Instead of replicating protocols that were developed in other disciplines, for instance, researchers have found success by beginning with considerations of local contexts and by pioneering methods that are appropriate to the study population (e.g., Hruschka et al. Reference Hruschka, Munira, Jesmin, Hackman and Tiokhin2018). Other collaborative studies have brought human behavioral ecologists together with those studying evolutionary psychology and cultural evolution to look at variation and universals in behavior and psychology (Barrett et al. Reference Barrett, Bolyanatz, Crittenden and Pisor2016; Scelza and Prall Reference Scelza and Prall2018). As the methods of HBE become increasingly refined and standardized, cross-cultural comparisons should continue to flourish.
1.6 The Future of the Field
When HBE arose as a field, it was one of several theoretical perspectives aiming to use evolutionary theory to better understand human behavior, the others being evolutionary psychology, which focuses on evolved psychological mechanisms, and dual inheritance theory, which focuses on culture-gene coevolution. At the time, as is common with nascent fields of research, the three perspectives were often pitted against each other, and differences between the three perspectives were highlighted (Smith Reference Smith, Cronk, Chagnon and Irons2000). In many ways, these differences have fallen increasingly into the background with a freer exchange of methods (Scelza et al. Reference Scelza, Prall, Blumenfield and McElreath2020c), increasing engagement with culture and social learning in the development of predictions (McElreath et al. Reference McElreath, Lubell, Richerson and Paciotti2005; Colleran Reference Colleran2016), and more nuanced understandings of the relationship between psychological mechanisms and behavior (Barrett Reference Barrett2015).
Why then produce a volume entitled Human Behavioral Ecology now? While HBE has become more methodologically diverse and more integrative of both proximate mechanisms and broader processes of cultural evolution, its approach remains distinct within the evolutionary social sciences. Unlike its sister fields, HBE has strong grounding in both qualitative and quantitative methods. Ethnography is at the core of most projects, not only to provide context for quantitative data but also to drive the formation of locally specific predictions, which can then be used to understand variation in behavior across time and place. Moreover, at its core, HBE is a field that embraces human behavioral and cultural diversity. Understanding variation in behavior is a central tenet of the field, an emphasis that enables a theoretically informed position on processes such as market integration, globalization, and climate change.
Amid the rapid social and environmental changes, that is, viewpoints from behavioral ecology can help to discern shifting trade-offs and novel strategic responses. For example, Colleran (Reference Colleran2020) has shown that increasing market integration reduces the density of kin networks among women in rural Poland, and given that kin tend to have more pro-natal influences on women’s reproductive decisions, this could facilitate the transition to smaller family sizes. Meanwhile, Schaffnit et al. (Reference Schaffnit, Page, Lynch, Spake, Sear, Sosis, Shaver, Alam, Towner and Shenk2023) show that market integration alters the dynamics of parent-offspring conflict over marriage arrangements, with daughters increasingly able to control their own partnership decisions. Behavioral ecologists have also highlighted the ways that an adaptationist perspective can usefully inform climate change policy by emphasizing relationships between risk and innovation, examining ways that people maintain access to resources in the face of changing ecologies, and uncovering how social networks foster and transmit adaptations (Pisor and Jones Reference Pisor and Jones2021). Given that globalization is increasing the pace and scope of change, HBE should continue to have an important role in studies of human behavior around the world.
