Provisioning offspring and others: risk–energy trade-offs and gender differences in hunter–gatherer foraging strategies

Codding, Brian F.; Bird, Rebecca Bliege; Bird, Douglas W.

doi:10.1098/rspb.2010.2403

Cited by 85 publications

(99 citation statements)

References 42 publications

(49 reference statements)

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“…5 Effort Motivation, time, energy, and resources expended by the residential population to obtain food resources (McCarthy and McArthur 1960, Meehan 1982, Altman 1987, Walsh 2008, Codding et al 2011. Sufficient habitat and available technology are assumed.…”

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confidence: 99%

The persistence of subsistence: qualitative social-ecological modeling of indigenous aquatic hunting and gathering in tropical Australia

Barber¹,

Jackson²,

Dambacher³

et al. 2015

E&S

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ABSTRACT. Subsistence remains critical to indigenous people in settler-colonial states such as Australia, providing key foundations for indigenous identities and for wider state recognition. However, the drivers of contemporary subsistence are rarely fully articulated and analyzed in terms of likely changing conditions. Our interdisciplinary team combined past research experience gained from multiple sites with published literature to create two generalized qualitative models of the socio-cultural and environmental influences on indigenous aquatic subsistence in northern Australia. One model focused on the longer term (inter-year to generational) persistence of subsistence at the community scale, the other model on shorter term (day to season) drivers of effort by active individuals. The specification of driver definitions and relationships demonstrates the complexities of even generalized and materialist models of contemporary subsistence practices. The qualitative models were analyzed for emergent properties and for responses to plausible changes in key variables: access, habitat degradation, social security availability, and community dysfunction. Positive human community condition is shown to be critical to the long-term persistence of subsistence, but complex interactions of negative and positive drivers shape subsistence effort expended at the individual scale and within shorter time frames. Such models enable motivations, complexities, and the potential management and policy levers of significance to be identified, defined, causally related, and debated. The models can be used to augment future models of human-natural systems, be tested against case-specific field conditions and/or indigenous perspectives, and aid preliminary assessments of the effects on subsistence of changes in social and environmental conditions, including policy settings.

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mentioning

confidence: 99%

The persistence of subsistence: qualitative social-ecological modeling of indigenous aquatic hunting and gathering in tropical Australia

Barber¹,

Jackson²,

Dambacher³

et al. 2015

E&S

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show abstract

“…This means that optimal behavioral decisions are universally risk-averse. However, risk-prone behavior has also been observed in some empirical studies in a variety of animal species, including insects (Moses and Sih 1998), fish (Sih 1994), squirrels (Bowers and Breland 1994), chimpanzees (Gilby and Wrangham 2007) and humans (Codding et al 2011). The theory of dynamic utility is an important and basic principle of dynamic decision-making and merits further theoretical and empirical contributions.…”

Section: Discussionmentioning

confidence: 99%

Dynamic decision-making in uncertain environments I. The principle of dynamic utility

Yoshimura

Ito

Miller

et al. 2013

J Ethol

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Understanding the dynamics or sequences of animal behavior usually involves the application of either dynamic programming or stochastic control methodologies. A difficulty of dynamic programming lies in interpreting numerical output, whereas even relatively simple models of stochastic control are notoriously difficult to solve. Here we develop the theory of dynamic decisionmaking under probabilistic conditions and risks, assuming individual growth rates of body size are expressed as a simple stochastic process. From our analyses we then derive the optimization of dynamic utility, in which the utility of weight gain, given the current body size, is a logarithmic function: hence the fitness function of an individual varies depending on its current body size. The dynamic utility function also shows that animals are universally sensitive to risk and display risk-averse behaviors. Our result proves the traditional use of expected utility theory and game theory in behavioral studies is valid only as a static model.

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“…This perspective may explain why men often prefer to hunt prey associated with high rates of failure, and why women often do not hunt and, when they do, take mainly smaller, less mobile prey with lower rates of failure [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

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

Jones

Bird

2013

Proc. R. Soc. B.

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In this paper, we attempt to understand hunter-gatherer foraging decisions about prey that vary in both the mean and variance of energy return using an expected utility framework. We show that for skewed distributions of energetic returns, the standard linear variance discounting (LVD) model for risk-sensitive foraging can produce quite misleading results. In addition to creating difficulties for the LVD model, the skewed distributions characteristic of hunting returns create challenges for estimating probability distribution functions required for expected utility. We present a solution using a twocomponent finite mixture model for foraging returns. We then use detailed foraging returns data based on focal follows of individual hunters in Western Australia hunting for high-risk/high-gain (hill kangaroo) and relatively lowrisk/low-gain (sand monitor) prey. Using probability densities for the two resources estimated from the mixture models, combined with theoretically sensible utility curves characterized by diminishing marginal utility for the highest returns, we find that the expected utility of the sand monitors greatly exceeds that of kangaroos despite the fact that the mean energy return for kangaroos is nearly twice as large as that for sand monitors. We conclude that the decision to hunt hill kangaroos does not arise simply as part of an energetic utility-maximization strategy and that additional social, political or symbolic benefits must accrue to hunters of this highly variable prey.

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Provisioning offspring and others: risk–energy trade-offs and gender differences in hunter–gatherer foraging strategies

Cited by 85 publications

References 42 publications

The persistence of subsistence: qualitative social-ecological modeling of indigenous aquatic hunting and gathering in tropical Australia

The persistence of subsistence: qualitative social-ecological modeling of indigenous aquatic hunting and gathering in tropical Australia

Dynamic decision-making in uncertain environments I. The principle of dynamic utility

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

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