The specifics of the organism’s capabilities and the environmental features that structure resource selection opportunities are constraints. In the diet breadth model constraints include things like the size of the forager, the hunting and gathering technology used, and the distribution and caloric value of the targeted resources. Constraints are all of the elements of the situation that are taken for granted , in order to focus analysis on one set of effects. The measure we use to assess costs and benefits is known as the currency. While the currency might be any feature of a resource that gives it value, foraging theorists typically assume that food energy is the most important attribute. After oxygen and water, mammals require metabolic energy in large amounts on a nearly continuous basis. The omnivorous diet of most hunter-gatherers makes it likely that meeting one’s need for energy entails meeting the needs for other nutrients. This may be more problematic with agriculturalists. The kcal currency is expressed as an efficiency, the net acquisition rate of energy. Where energy is not limiting or is less limiting than some other factor—e.g., protein—then that can be used as the currency. For instance, we know that some forms of energy, especially those from large or dangerous game animals, are more prestigious than others , suggesting that not all kilocalories are equal. Prestige might enter into the currency in some cases. Behavioral ecologists generally emphasize secondary currencies like kcals or mating success because they are more tractable than the primary neo-Darwinian measure of reproductive fitness . The final feature of models is the goal. A deterministic foraging model likely would have the goal of maximizing energy capture while foraging. A risk-sensitive model would emphasize the goal of avoiding harmful shortfalls of energy. Behavioral ecology models of food transfers in a social group might stress the evolutionarily stable equilibrium of distribution tactics.
The polygyny threshold model for mating tactics would emphasize the goal of reproductive success. Different goals usually imply different methods: simple optimization analysis for energy maximization; stochastic models for risk minimization; game theory for frequency dependent behaviors, like intragroup transfers, best indoor plant pots that result in evolutionarily stable strategies. The optimization assumption ties together constraints, currency, goal, and the costs and benefits of the alternative set. For instance, given constraints of resource densities and values, and their associated costs and benefits, we predict that organisms will select the alternative that provides them the highest available net acquisition rate of energy. As noted earlier, even when there is no particular shortage of foodstuffs, efficient foraging frees time for alternative activities and lessens exposure to risks associated with foraging. While we don’t expect the organism always to engage in the optimal behavior, models based on this assumption have proven to be robust when compared to ethnographic and archaeological datasets .The diet breadth or resource selection model is one of the oldest and most commonly used , particularly by archaeologists . It is sometimes called the encounter contingent model because it focuses on the decision to pursue or not to pursue, to harvest or not harvest, a resource once it is encountered. The decision entails an immediate opportunity cost comparison: pursue the encountered resource, or continue searching with the expectation of locating more valuable resources to pursue. If the net return to is greater than , even after allowing for additional search time, then the optimizing forager will elect to pass by the encountered resource, and will continue to do so no matter how frequently this type of resource is encountered. The general solution to this trade-off is devised as follows: each of k potential resources is ranked in descending order by its net return rate for the post-encounter work to obtain it. This represents a resource’s net profitability with respect to pursuit, harvest, and handling costs.
The derivation of the best-choice diet begins with the most profitable resource , and, stepwise, adds resource types, continuing until the first resource with a profitability less than the overall foraging efficiency of the diet that does not include it . Resources ranked are excluded because to pursue them would impose an unacceptable opportunity cost: a lower return rate for time spent pursuing them relative to the expected benefits from ignoring them in favor of both searching for and pursuing more profitable types. Think of picking up change in tall grass: if there are enough silver dollars and quarters the income-minded gleaner will ignore the dimes, nickles, and pennies, no matter how frequently they are encountered. Notice that the DBM also entails a marginal decision: It asks, is the profitability of the next ranked item above or below the marginal value of foraging for all resources ranked above it? Creative use of this or any foraging model entails thought experiments of the form: how will an optimizing forager respond to a change in independent variable x. Predicted responses are confined to options with the alternative set, but the independent variable x might be any change in the environment or the behavioral capacities of the forager that affects the primary model variables: resource encounter rates and profitability. For instance, resource depression,environmental change, and other factors which diminish encounter rates with highly ranked resources will increase search costs, lower overall foraging efficiency, and as a result, may cause the diet breadth of a forager to expand to include items of lower rank. One or more items that previously ranked below that boundary may now lie above it, making these resources worth pursing when encountered. The converse is also true. Sufficiently large increases in the density of highly ranked resources should lead to exclusion from the diet of low ranked items. A seasonal elevation of fat content, or adoption of a technology that makes its pursuit, harvest or processing more efficient or any factor that raises the profitability of a particular resource will elevate its ranking, perhaps enough to move into the best-choice diet. It may, in fact, displace resource items previously consumed. Winterhalder and Goland provide an extended list of factors that might operate through encounter rate and pursuit and handling costs to change resource selectivity. The diet breadth model also implies that, under a given set of conditions, resources within the optimal diet are always pursued when encountered; those outside the optimal diet will always be ignored. There are no “partial preferences,” such as “take this organism 50% of the time it is encountered.” Likewise, the decision to include a lower-ranked item is not based on its abundance, but on the abundances of resources of higher rank. Think of the small change mentioned earlier.In the diet breadth model, we envision a resource that is harvested as a unit with a fixed value .
By contrast, a patch is a resource or set of resources which is harvested at a diminishing rate, either because it is depleted in such a way that makes continued harvesting more difficult; the densest and ripest berries are picked first, blueberry container size or because the continuing presence of the forager disperses or increases the wariness of remaining resource opportunities as in the second or third shot at a dispersing flock of grouse. Patches can be ranked like resources, by their profitability upon encounter. As a first approximation, the same predictions apply. However, predictions are somewhat less clear for the selection of patches than for resources, because a definitive prediction about patch choice is interdependent with a decision about patch residence time, the focus of the next model.If a resource patch—which we envision as a small area of relatively homogeneous resource opportunities, separated by some travel distance from other such locales—is harvested at a diminishing rate of return, it is obvious to ask when the forager should abandon its efforts and attempt to find a fresh opportunity. By moving on, he or she will incur the cost of finding a new patch, but upon locating it, will be rewarded with a higher rate of return, at least for a while. The marginal value theorem postulates a decline in return rates for time spent in the patch, usually approximated by a negative exponential curve. The optimizing solution specifies that the forager will leave the present patch when the rate of return there has dropped to the average foraging rate. The average foraging rate encompasses the full set of patches being harvested and the travel costs associated with movement among them. To stay longer incurs unfavorable opportunity costs because higher returns were available elsewhere. To stay a shorter duration is also sub-optimal, because rates of return are, on average, higher when compared to the costs of moving on to another resource patch. In this model, short travel times are associated with short patch residence ; long travel times with longer residence times. The forager optimizing his or her patch residence time rarely will completely deplete a patch;the resources left behind are significant for the recovery of the patch. Finally, the value of harvested patches, upon departure, is the same. The inter-dependence between the two patch related models should now be more apparent. Predictions about patch residence time depend on patch choice; reciprocally, predictions about patch choice depend on residence time. Use of one of these models must assume the other; Stephens and Krebs give a more detailed discussion of this model.The ideal free distribution is a model of habitat choice . The distinction between patches and habitats is one of scale: patches are isolated areas of homogenous resource opportunities on a scale such that a forager may encounter several to several dozen in a daily foraging expedition. Habitats are similarly defined by their aggregate resource base, but at a regional scale. As suggested by their greater relative size, habitats also invoke somewhat different questions, such as where to establish and when to move settlements, and when to relocate by migration. Generally, we ask how populations will distribute themselves with respect to major landscape features like habitats. In the ideal free distribution, the quality of a habitat depends on resource abundance and the density of the population inhabiting and using it. The model assumes that the initial settlers pick the best habitat, say “A.” Further immigration and population growth in habitat A reduce the availability of resources and the quality of the habitat drops for everyone. Crowding, depletion of resources, and competition are possible reasons for this. The marginal quality of habitat A eventually will drop to that of the second-ranked, but yet unsettled, habitat B. If each individual in the population seeks the best habitat opportunity, further growth or immigration will be apportioned between habitats A and B such that their marginal value to residents is equalized. Lower ranked habitats will be occupied in a similar manner. This model predicts that habitats will be occupied in their rank order, that human densities at equilibrium will be proportional to the natural quality of their resources, and that the suitability of all occupied habitats will be the same at equilibrium. In the IFD the creative element resides in imaging how various socioenvironmental settings might affect the shape of the curves representing the impact of settlement density on habitat quality. For instance, it is possible that settlement at low densities actually increases the suitability of a habitat. Forest clearing by the newcomers leading to secondary growth might increase the density of game available to them and to emigrants. This is known as the Allee effect. Likewise, some habitats may be quickly affected by settlement, generating a sharply declining curve of suitability as population densities increase, whereas others may be much more resilient. If immigrants to a habitat successfully defend a territory there, then newly arriving individuals will more quickly be displaced to lower ranked habitats, a variant known as the ideal despotic distribution .Many foragers, human and nonhuman, locate at a dry rock shelter, potable water, or a valuable or dense food source or other particularly critical resource—e.g., an attractive habitation site, or perhaps at a location central to a dispersed array of required resources—and then forage in a radial pattern from that site. Central place foraging models address this circumstance. They assume that a forager leaving such a home base must travel a certain distance through unproductive habitat to reach productive foraging zones.