Optimal Foraging Optimal foraging theory OFT is a

Optimal Foraging

• 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 • 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.

Different feeding systems and classes of predators • Optimal foraging theory is widely applicable to feeding systems throughout the animal kingdom. Under the OFT, any organism of interest can be viewed as a predator that forages prey. There are different classes of predators that organisms fall into and each class has distinct foraging and predation strategies. • True predators attack large numbers of prey throughout their life. They kill their prey either immediately or shortly after the attack. They may eat all or only part of their prey. True predators include tigers, lions, whales, sharks, seed-eating birds, ants • Grazers eat only a portion of their prey. They harm the prey, but rarely kill it. Grazers include antelope, cattle, and mosquitoes. • Parasites like grazers, eat only a part of their prey (host), but rarely the entire organism. They spend all or large portions of their life cycle living in/on a single host. This intimate relationship is typical of tapeworms, liver flukes, and plant parasites, such as the potato blight

• Parasitoids are mainly typical of wasps (order Hymenoptera), and some flies (order Diptera). Eggs are laid inside the larvae of other arthropods which hatch and consume the host from the inside, killing it. This unusual predator–host relationship is typical of about 10% of all insects. Many viruses that attack single-celled organisms (such as bacteriophages) are also parasitoids; they reproduce inside a single host that is inevitably killed by the association.

Optimal foraging in bees • Worker bees provide another example of the use of marginal value theorem in modeling optimal foraging behavior • Bees forage from flower to flower collecting nectar to carry back to the hive • While this situation is similar to that of the starlings, both the constraints and currency are actually different for the bees • A bee does not experience diminishing returns because of nectar depletion or any other characteristic of the flowers themselves • The total amount of nectar foraged increases linearly with time spent in a patch • However, the weight of the nectar adds a significant cost to the bee's flight between flowers and its trip back to the hive.

• Wolf and Schmid-Hempel showed, by experimentally placing varying weights on the backs of bees, that the cost of heavy nectar is so great that it shortens the bees' lifespan. • The shorter the lifespan of a worker bee, the less overall time it has to contribute to its colony. • Thus, there is a curve of diminishing returns for the net yield of energy that the hive receives as the bee gathers more nectar during one trip • The cost of heavy nectar also impacts the currency used by the bees. • Unlike the starlings in the previous example, bees maximize energy efficiency (energy gained per energy spent) rather than net rate of energy gain (net energy gained per time).

• This is because the optimal load predicted by maximizing net rate of energy gain is too heavy for the bees and shortens their lifespan, decreasing their overall productivity for the hive, as explained earlier. • By maximizing energy efficiency, the bees are able to avoid expending too much energy per trip and are able to live long enough to maximize their lifetime productivity for their hive. • In a different paper, Schmid-Hempel showed that the observed relationship between load size and flight time is well correlated with the predictions based on maximizing energy efficiency, but very poorly correlated with the predictions based on maximizing net rate of energy gain.