Application to Optimal Foraging Theory to Real-Life Eating Decision

Optimal foraging theory purports that a forager opts for behavior that maximizes net benefits compared to other choices. The other feasible options available to the forager constitute the decision or strategy set. The forager must choose an optimal strategy from the set. The theory has been extensively used to study foraging behaviors of animals and human hunters. However, the same can be extended to comprehend day to day eating decisions. Diet breadth model has been used to decipher the optimal strategy in the given incident. This model presumes prior knowledge of prey or in my case food item. Additionally, it requires awareness of search costs i.e. rate of encounter or time spent looking for prey and handling costs i.e. return rate on encounter or time spent in pursuit, capture, processing and eating of the food item.
For this eating decision, I find myself in a marketing complex foraging for food. For simplicity only three acceptable food items are available in the market namely cheeseburgers, dairy milk chocolates and apples. Assuming that at least some quantity of each food item or prey type is available in the market, I constitute my decision or strategy set. This set includes options of consuming only single food item i.e. only apples, burger or chocolates, a combination of two out of three items or a mix of all three food items. The measurement of scale or currency is taken to be energy. Energy obtained from each food item is mentioned in table 1. In the first case, I am standing next to a food stall containing all the three items. No search costs are involved as the required items are next to me and handling costs of all three items are assumed to be the same, 1 item in 6 minutes. For case 1, return rate or net benefits are also shown. Here invariably the optimal strategy involves preference for chocolates alone to maximize my net benefit.

Foot ItemEnergy per unitCase 1 Return Rate (calhr)Case 2 Return Rate (calhr)Case 3 Return Rate (calhr)Cheeseburger360 cal36003600720Dairy milk 520 cal52002600520Apple60 cal600600900Table 1
In the second case, I find that some of the materials on the food stall are actually artificial in nature and not edible. Thus, density of items which was constant in the first case now varies for different items. Earlier, chocolate density was 10 chocolates1 hour. However, I noticed that 5 of them were artificial, reducing their density to 5hour. Now the ranking criterion denotes that average of cheeseburger and chocolate return rate is 3100 calhr, less than that of cheeseburgers. Therefore, diet breadth model will suggest increase in diet breadth and I will prefer both chocolates and cheeseburgers. The two aforementioned food items are still not rare enough for inclusion of apples in my preferred diet. Still, in a third case, four out of five available chocolates were purchased by a customer before me along with 8 burgers. Further, I notice a crate of 5 apples lying next to the stall increasing apple density to 15hr. This leaves me with a chocolate density of onehr while that of cheeseburger falls to 2hr. Return rates for cheeseburgers and chocolate becomes 620 calhr, while the average of all three items becomes 713 calhr, suggesting that diet should again be increased and I should forage for all three food items. In this way, optimal foraging theory can help to understand my eating decision in the market place.


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