Interpreting abundance indices: some zooarchaeological implications of Martu foraging

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

doi:10.1016/j.jas.2010.07.020

Cited by 51 publications

(23 citation statements)

References 66 publications

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“…The development of accurate resource rankings constitutes a long-running debate in anthropology (see Bird et al, 2009;Broughton et al, 2011;Codding et al, 2010, Ugan, 2005. Much of the disagreement centers on different moments of decision making-either prey selection or pursuit choices.…”

Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

“…(i.e. Bird et al, 2009;Codding et al, 2010). Resource rankings that take into account risk aversion, opportunity costs, etc.…”

Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

“…Women tend to be more risk-averse, and typically choose to pursue resources with less risk of escape, even if the potential return rate is lower. Codding et al (2010) elaborate on this gender division, cautioning archaeologists that lower abundance of highranked but highly mobile prey may indicate that a site is more representative of women's foraging rather than an overall decline in foraging efficiency. Because this study looks at the settlement system as a whole, men's and women's foraging behaviors are both included and cannot, at this stage, be differentiated.…”

Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

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Multi-scalar foraging decisions in the Santa Barbara Channel, southern California

Reeder-Myers¹

2014

Journal of Anthropological Archaeology

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Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

“…(i.e. Bird et al, 2009;Codding et al, 2010). Resource rankings that take into account risk aversion, opportunity costs, etc.…”

Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

Section: Subsistence and Resource Rankingsmentioning

confidence: 99%

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Multi-scalar foraging decisions in the Santa Barbara Channel, southern California

Reeder-Myers¹

2014

Journal of Anthropological Archaeology

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“…The average hunter spends 3 h hunting and returns with between two and three animals, yielding a long-term mean of 650 kcal per hunter-hour of search, pursuit, capture and processing. Hunters can control to some extent the harvest size by foraging for longer: there is a significant correlation with time, which explains about 30% of the variation in harvest size [19]. In a given foraging party, there are usually four to five monitor hunters, more than half of dinner-time camp members who hunt.…”

Section: (D) Foraging Data From Martumentioning

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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“…The debate on the use of optimal foraging theory in archaeology-particularly in zooarchaeology and archaeobotany-has been heated in recent years, with critiques emerging in a variety of different contexts (e.g., Codding et al 2010;Jones 2016a:9-22;Reitz et al 2009;Smith 2015;Speth 2013;Zeder 2012Zeder , 2015a. While these critiques vary both in their natures and in the bases of their arguments, many of them concern, at least in part, the use of foraging theory to identify cases of prehistoric resource depression, or decreases in foraging efficiency based on the foragers' own activities (here, we use resource depression in a large sense, including behavioral depression and microhabitat depression as well as exploitation depression; see Charnov et al 1976).…”

Section: Introductionmentioning

confidence: 99%

Beyond Depression? A Review of the Optimal Foraging Theory Literature in Zooarchaeology and Archaeobotany

Jones

Hurley

2017

EBL

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The use of optimal foraging theory in archaeology has been criticized for focusing heavily on “negative” human-environmental interactions, particularly anthropogenic resource depression, in which prey populations are reduced by foragers’ own foraging activities. In addition, some researchers have suggested the focus on resource depression is more common in the zooarchaeological literature than in the archaeobotanical literature, indicating fundamental differences in the ways zooarchaeologists and archaeobotanists approach the archaeological record. In this paper, we assess these critiques through a review of the literature between 1997 and 2017. We find that studies identifying resource depression occur at similar rates in the archaeobotanical and zooarchaeological literature. In addition, while earlier archaeological applications of optimal foraging theory did focus heavily on the identification of resource depression, the literature published between 2013 and 2017 shows a wider variety of approaches.

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Interpreting abundance indices: some zooarchaeological implications of Martu foraging

Cited by 51 publications

References 66 publications

Multi-scalar foraging decisions in the Santa Barbara Channel, southern California

Multi-scalar foraging decisions in the Santa Barbara Channel, southern California

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

Beyond Depression? A Review of the Optimal Foraging Theory Literature in Zooarchaeology and Archaeobotany

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