To kill a kangaroo: understanding the decision to pursue high-risk/high-gain resources

Socio-economic predictors of Inuit hunting choices and their implications for climate change adaptation

In the Arctic, seasonal variation in the accessibility of the land, sea ice and open waters influences which resources can be harvested safely and efficiently. Climate stressors are also increasingly affecting access to subsistence resources. Within Inuit communities, people differ in their involvement with subsistence activities, but little is known about how engagement in the cash economy (time and money available) and other socio-economic factors shape the food production choices of Inuit harvesters, and their ability to adapt to rapid ecological change. We analyse 281 foraging trips involving 23 Inuit harvesters from Kangiqsujuaq, Nunavik, Canada using a Bayesian approach modelling both patch choice and within-patch success. Gender and income predict Inuit harvest strategies: while men, especially men from low-income households, often visit patches with a relatively low success probability, women and high-income hunters generally have a higher propensity to choose low-risk patches. Inland hunting, marine hunting and fishing differ in the required equipment and effort, and hunters may have to shift their subsistence activities if certain patches become less profitable or less safe owing to high costs of transportation or climate change (e.g. navigate larger areas inland instead of targeting seals on the sea ice). Our finding that household income predicts patch choice suggests that the capacity to maintain access to country foods depends on engagement with the cash economy. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Want climate-change adaptation? Evolutionary theory can help

The idea of adaptation, in which an organism or population becomes better suited to its environment, is used in a variety of disciplines. Originating in evolutionary biology, adaptation has been a central theme in biological anthropology and human ecology. More recently, the study of adaptation in the context of climate change has become an important topic of research in the social sciences. While there are clearly commonalities in the different uses of the concept of adaptation in these fields, there are also substantial differences. We describe these differences and suggest that the study of climate-change adaptation could benefit from a re-integration with biological and evolutionary conceptions of human adaptation. This integration would allow us to employ the substantial theoretical tools of evolutionary biology and anthropology to understand what promotes or impedes adaptation. The evolutionary perspective on adaptation focuses on diversity because diversity drives adaptive evolution. Population structures are also critical in facilitating or preventing adaptation to local environmental conditions. This suggests that climate-change adaptation should focus on the sources of innovation and social structures that nurture innovations and allow them to spread. Truly innovative ideas are likely to arise on the periphery of cohesive social groups and spread inward. The evolutionary perspective also suggests that we pay careful attention to correlated traits, which can distort adaptive trajectories, as well as to the importance of risk management in adaptations to variable or uncertain environments. Finally, we suggest that climate-change adaptation could benefit from a broader study of how local groups adapt to their dynamic environments, a process we call "autochthonous adaptation."

Fitness-maximizers employ pessimistic probability weighting for decisions under risk

The standard theory of rationality posits that agents order preferences according to average utilities associated with different choices. Expected utility theory has repeatedly failed as a predictive theory, as reflected in a growing literature in behavioural economics. Evolutionary theorists have suggested that seemingly irrational behaviours in contemporary contexts may have once served important functions, but existing work linking fitness and choice has not adequately addressed the challenges of constructing an evolutionary theory of decision making. In particular, fitness itself is not a reasonable metric for decision making since its timescale exceeds the lifespan of the decision-maker. Consequently, organisms use proximate systems that work on appropriate timescales and are amenable to feedback and learning. We develop an evolutionary principal-agent model in which individuals utilize a set of proximal choice variables to account for the non-linear dependence of these variables on consumption. While this is insufficient to maximize fitness in the presence of environmental stochasticity, maximum fitness can be achieved by adopting pessimistic probability weightings compatible with the rank-dependent expected utility family of choice models. In particular, pessimistic probability weighting emerges naturally in an evolutionary framework because of extreme intolerance to zeros in multiplicative growth processes.

Pursuit : A Foraging Simulation Tool for Research and Teaching

This article describes a software tool called "Pursuit" that is intended to be used for both research and teaching on the topic of optimal foraging theory. The tool provides a dynamic graphical and auditory interface in which users encounter different prey animals and then must decide whether to pursue or ignore the encountered prey. Based on the characteristics of the prey in the foraging environment and the decisions of the player, each user harvests a set of prey per round and achieves a corresponding foraging return rate. Administrators of Pursuit specify the environmental parameters that determine what prey users will encounter. All environmental parameters and user decisions are tracked and logged for analysis. We created this tool for laboratory experiments, but we believe Pursuit could also be an engaging and effective teaching tool, whereby students adopt the role of forager, and through such play, experience a simulated foraging context and learn about foraging theory. Pursuit is freely available and can run on any platform that supports Java, including Mac OS, Windows, and Linux.

Disturbance, Complexity, Scale: New Approaches to the Study of Human–Environment Interactions

New approaches to human–environment interactions are beginning to move beyond a narrow focus on individuals and simple (patch-level) predatory or competitive interactions. These approaches link nonequilibrium theory from community and landscape ecology with theories of individual decision making from behavioral ecology to explore new ways of approaching complex issues of diachronic change in behavior, subsistence, and social institutions. I provide an overview of two such approaches, one to understand long-term hunting sustainability among mixed forager-horticulturalists in the wet tropics and the other to understand how foragers act as ecosystem engineers in a dry perennial grassland in Australia. I conclude by describing the implications of new approaches that incorporate anthropogenic “intermediate” disturbance (an emergent property of human–environment interaction) as a force shaping environments through time and space, and in so doing patterning the sustainability of subsistence, ways of sharing, ownership norms, and even structures of gendered production.

Using multilevel models to estimate variation in foraging returns. Effects of failure rate, harvest size, age, and individual heterogeneity

Distributions of human foraging success across age have implications for many aspects of human evolution. Estimating the distribution of foraging returns is complicated by (1) the zero-inflated nature of hunting returns, as many if not most trips fail, and (2) the substantial variation among hunters, independent of age. We develop a multilevel mixture analysis of human foraging data to address these difficulties. Using a previously published 20-year record of hunts by 147 individual Aché hunters in eastern Paraguay, we estimate returns-by-age functions for both hunting failures and the size of harvests, while also estimating the heterogeneity among hunters. Consistent with previous analyses, we find that most hunters peak around 40 years of age. We can also show, however, that much more of the variation among Aché hunters arises from heterogeneity in failure rates (zero returns), not harvest sizes. We also introduce a new R package, glmer2stan, to assist in defining and fitting similar multilevel mixture models.