Worker bees forage nectar not only for themselves, but for their whole hive community. Optimal foraging theory predicts that this bee will forage in a way that will maximize its hive's net yield of energy.
Optimal foraging theory (OFT) is a behavioral ecology model that helps predict how an animal behaves when searching for food. Although obtaining food provides the animal with energy, searching for and capturing the food require both energy and time. To maximize fitness, an animal adopts a foraging strategy that provides the most benefit (energy) for the lowest cost, maximizing the net energy gained. OFT helps predict the best strategy that an animal can use to achieve this goal.
OFT is an ecological application of the optimality model. This theory assumes that the most economically advantageous foraging pattern will be selected for in a species through natural selection.[1] When using OFT to model foraging behavior, organisms are said to be maximizing a variable known as the currency, such as the most food per unit time. In addition, the constraints of the environment are other variables that must be considered. Constraints are defined as factors that can limit the forager's ability to maximize the currency. The optimal decision rule, or the organism's best foraging strategy, is defined as the decision that maximizes the currency under the constraints of the environment. Identifying the optimal decision rule is the primary goal of the OFT.[2] The connection between OFT and biological evolution has garnered interest over the past decades. Studies on optimal foraging behaviors at the population level have utilized evolutionary birth-death dynamics models. While these models confirm the existence of objective functions, such as "currency" in certain scenarios, they also prompt questions regarding their applicability in other limits such as high population interactions.[3]
^Werner, E. E.; Hall, D. J. (1974). "Optimal Foraging and the Size Selection of Prey by the Bluegill Sunfish (Lepomis macrochirus)". Ecology. 55 (5): 1042. doi:10.2307/1940354. JSTOR 1940354.
^Sinervo, Barry (1997). "Optimal Foraging Theory: Constraints and Cognitive Processes" Archived 23 November 2015 at the Wayback Machine, pp. 105–130 in Behavioral Ecology. University of California, Santa Cruz.
^Liang, Tong; Brinkman, Braden A. W. (14 March 2022). "Evolution of innate behavioral strategies through competitive population dynamics". PLOS Computational Biology. 18 (3): e1009934. doi:10.1371/journal.pcbi.1009934. ISSN 1553-7358. PMC 8947601. PMID 35286315.
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