«By Nathan B. Goodale A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY WASHINGTON STATE ...»
In other words, if participating in food acquisition may impact other efforts, its costs and benefits will be weighed. Because of issues of adaptive lag and changing optimal outcomes, constrained optimization implies that humans will not always make the most efficient decisions but over the course of many decisions, behaviors will tend towards optimum. (Winterhalder and Kennett 2006). In this instance, optimization may be situational and what is an optimal outcome at one point in time may not be at another.
Strongly grounded in economic theory, HBE uses several key concepts.
These include marginal value, opportunity costs, discounting, and risk-sensitivity (Winterhalder 1983; Winterhalder and Kennett 2006) as useful explanatory frameworks in decoding decision making tactics. Specifically, this relates to
another. These concepts are useful for interpreting both short-term situational events (mostly utilized in ethnographic studies) and long-term trajectories in human decision making related to shifts in entire socioeconomic systems (seldom used but becoming more commonly applied in archaeology, e.g., Prentiss and Chatters ).
Any resource package has a total value expressing the overall utility of the package throughout the consumption process (following some total utility function) (Winterhalder 1996). However, the total value is made up of the summed marginal values. The marginal value is the return rate of a particular nth unit of a resource to a person already holding n-1 units (Rhoads 2002; Winterhalder 1996; Winterhalder and Kennett 2006). The marginal value is directly linked to where that nth unit falls on the total utility function as well as what that function looks like (such as a decaying exponential). In a given context where resources are procured, the immediate payoff when quantity is high and presumably the highest quality portions are still available to be consumed, the total utility is near maximum. As quantity (amounts) and quality (less desirable portions) decrease, the total value also decreases. In contrast, the marginal value is proportional to how much of the resource package is divided amongst the consumers. The total utility with differing unit marginal values may be illustrated by the analogy to a pot of stew. The first time that one eats from the pot of stew, its total utility will likely be high. This is because quantity is still high, the best ingredients are still available and the desire to consume it is high (Burger et al. 2005).
During the second consumption period the total utility may still be very high but as
(Burger et al. 2005:1148) assuming that the total utility function is similar to a decaying exponential.
Following Kennett and Winterhalder (2006) and Smith and Winterhalder (1992), we may envision circumstances where the marginal value in relationship to the total utility function may be applicable to a broad range of products from a single to multiple large-bodied prey (e.g., elk or bison), abundant smaller prey (salmon harvest with a variety of sizes and fat contents), to lithic raw material procurement (e.g., further from source may equate to less quantity but also less desirable pieces) (Andrefsky 2008). In all of these circumstances, the total utility will be high during the initial use, and the marginal value will be governed by the shape of the total utility function. For example, if a concave utility function is detected, during the consumption of a resource the marginal value will decrease as less desirable portions or those that will require greater energy to turn into a consumable resource are left behind. Thus, as the marginal value decreases, the decision to participate in some other activity might become increasingly likely, as its payoff (utility) may become relatively greater. In other words, the decision to switch from one activity to another is directed by opportunity costs (Smith and Winterhalder 1992; Winterhalder and Kennett 2006).
Opportunity costs are therefore strongly linked to the concept of marginal value. Opportunity costs consider when an individual chooses to switch from engaging in one enterprise to another. This is related to both the marginal value of
more productive with higher payoffs to participate in another activity (Winterhalder and Kennett 2006:11-12). Thus, a hunter may stop hunting large game if encounter rates favor small game. In another circumstance, a flintknapper may stop utilizing a core when correcting knapping errors is more costly than getting a new cobble and starting over (Brantingham 2003; Goodale et al. 2008b).
Marginal values and opportunity costs are both subject to time discounting.
Discounting is commonly associated with the discussion of immediate versus delayed food economies that has been thematically central to many models of huntergatherers socioeconomic systems (Bettinger 1991; Binford 1980). Discounting can be defined as the modification that the costs being considered undergo before a decision is made. Specifically, discounting refers to anticipated payoff discounted by the anticipated delay. The decision to invest in an activity in anticipation of future payoff is an assessment of risk that weighs the likelihood of success or failure for those investments. For example, a farmer may invest less in a crop that has less tolerance for small climatic variations (such as premature spring frosts) than one having more tolerance. This is due to the greater certainty for success in the later.
However, discounting also has a strong relationship with the marginal value of the crops as well with the opportunity cost. If the crop with a greater chance of failure will have a greater payoff (high total value) in the event of success, a trade-off must be negotiated when the opportunity cost becomes so great that the farmer will invest at least some energy in the crop more likely to succeed but with a lower payoff. The
origins of agriculture as the transition from immediate to delayed subsistence economies.
The final important concept in optimality reasoning is risk-sensitive behavior, which incorporates neutral behaviors (those that are stochastic) and the statistical likelihood of encounter rates for some given targeted resource (Brantingham 2003;
Winterhalder 1986). The important aspect of risk-sensitive models is that they take into account discount, that is, when there are shortfalls in resources and payoffs from resource capture are not averaged across the landscape. In other words, payoffs may only be specific to a few people and are not averaged out to all individuals (not everyone can capture the targeted resource every time they set out to do so). For example, Kohler and Van West (1996) argue that households will (or will not) share depending on where they are on the production function (i.e. how much they have grown). If they had a large crop they should be risk-avoiding and share. In contrast if they had a small crop they should be risk-seeking and hoard the goods that they have. In general, to be risk sensitive means to modulate one’s behavior with respect to the degree of risk depending on one’s circumstances.
Risk-sensitive models are predominantly more heuristic, having preference in computer simulated models (Brantingham 2003) and have shown to be difficult to apply to prehistoric foraging patterns such as lithic raw material procurement (Andrefsky 2009). This is not to say that risk-sensitive models examining stochastic patterns in resource procurement are impossible to apply to either living populations
endeavor (Winterhalder and Kennett 2006).
Optimization and Nutrition Researchers have only minimally integrated issues of food nutrition in discussions of foraging patterns and optimization. Rather researchers focus predominantly on package size and handling times. Package size and handling times roughly equate to the amount of kilocalories (kcals) a given resource may provide versus the energy it takes to procure and process the resource into a usable end product. However, there are recent suggestions that we should move beyond kcals (Winterhalder and Kennett 2006) and how energy may play into larger social frameworks, as is proposed for example by the concepts of tolerated theft, sharing, show-off, and costly signaling (Blurton-Jones 1991; Hawkes and Bliege Bird 2002;
Winterhalder 1996). I would argue that examining the nutrient quality of food (amounts of protein, fat, vitamins, and carbohydrates) in relationship to quantity is another line of evidence that may be a very promising avenue of research going beyond calories. As a result, food nutrient content is one of the focal points in this study.
Specifically, I want to begin to remedy a lack of concentration on the actual nutritional content of the foods that prehistoric peoples were eating. There has been some recognition of food nutritional qualities in nonhuman species’ foraging patterns (Altman and Wagner 1978; Belovsky 1978; Rapport 1980; Rapport et al. 1972;
a significant role in the general health of a population, just as (if not more) important than package size and kcals. While prehistoric hunter-gatherers did not have labels on their foods depicting the amount of calories, fat content, vitamin content, and percentage of daily requirements for certain nutrients, would humans be sensitive to changing health conditions over the long-term? In other words, as diets change due to potentially depleting resource bases (due to over-hunting, climatic shifts, etc.), shifts in food economies may be related to health and targeting resources providing a balanced diet and potentially higher fertility. While research in human diets with regard to nutritional content and optimal decision making is scarce, several studies (Altman and Wagner 1978; Belovsky 1978; Rapport 1980; Westoby 1974) have examined both generalized and specific diets and how these shifts influence reproductive success.
As noted, most HBE research focuses on the economic value of resources. In contrast, examining nutrient content of targeted foods allows us the opportunity to examine the nutritional nature of a diet. In nonhuman species, nutritional content and some food resources are argued to be complementary (Covich 1972; Leόn and Tumpson 1975; Pulliam 1975; Rapport 1980: 324; Pyke et al. 1977; Westoby 1974).
For example, Clutton-Brock (1977) found that herbivore Gorillas utilize grubs, obtaining vitamin B12, and other primates balance their diets to obtain adequate amino acids, carbohydrates, and protein. This is referred to as the synergistic effect, or the interaction of two (or more) chemicals together to have a greater influence than
this situation, it seems that humans should also be sensitive to nutrient needs, even though in prehistoric times we may or may not have been aware of the specific nutritional contents of the foods that we were eating. One significant problem that nutritional content poses in optimal foraging is how to estimate some values for nutrition, rather than just package size, although it would seem that a quantitative means should easily be attainable for important nutrients to the overall health of an individual. This is not an issue of either package size or nutritional content; rather, these issues conspire to make up the overall benefit of the resource package.
As one example of how living organisms adjust their diet to benefit reproductive success, Rapport (1980) demonstrated how predator Stentor ciliate protozoa populations and their fertility are directly impacted by diet preference in relationship to prey type and abundance. In a laboratory setting Rapport et al. (1972) found that when the relative numbers of prey Euglena (unicellular protists) to Tetrahymena (protozoa) were changed, Stentor dietary preferences changed, although not in a one-to-one relationship. When Euglena density increased in comparison to Tetrahymena, Stentor preference for Euglena declined, producing a more generalized and equal subsistence strategy. Conversely, when Tetrahymena increased in relation to Euglena, Stentor preference shifted to favor Tetrahymena potentially signaling that Stentor preferences distinguished the need for a balanced diet and the nutrients that each resource provides (Rapport 1980:345).
prey abundance, preference shifted but complete specialization in consuming one prey item did not emerge. In the case of Stentor economic strategies, the consumption and preference of certain prey items is related not only to a trade-off between energy gain but also considers nutrient content. Lastly, Stentor’s reproductive success was much higher under diets that included more Tetrahymena and was decreased when Euglena were present in higher numbers proportional to Tetrahymena. While this case is much more simplistic that human foraging, it provides direct evidence that organisms will shift their diets to enhance reproductive success based upon what foods are available. The other important parameter here is that Stentor strategies for enhancing reproductive success were related to both the quantity and quality of the available prey. This suggests that not only food quantity, but also quality, may have played an important part in the reproductive success of humans in the past. Ultimately, the impacts of changing prey targets may have been correlated to increasing reproductive success.
Natural selection has shaped humans to be behaviorally and cognitively plastic, enabling us to adaptively adjust to changing socioeconomic conditions (Flinn 1996). Under optimality reasoning, it is plausible to suggest that humans would be prone to seeking diets that are balanced, to the extent that these produce the greatest reproductive success. If one resource providing a major portion of the protein contribution to their diet becomes scarce, or if another resource becomes attainable through a technological invention that provides greater reproductive success, we
the resource contributing greater reproductive success.