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Chapter 7. Evolution of feeding behavior. A large amount of research has focused on applying optimality theory to foraging behavior. Costs and benefits can be translated into energy and so can be evaluated quite easily. Optimal foraging by crows.
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Chapter 7. Evolution of feeding behavior. • A large amount of research has focused on applying optimality theory to foraging behavior. • Costs and benefits can be translated into energy and so can be evaluated quite easily.
Optimal foraging by crows • Northwestern crows commonly eat whelks and other shellfish and usually open them by flying up and dropping them onto a hard surface.
Optimal foraging by crows • Reto Zach studied the crow’s behavior. • Noted that crows choose only large whelks (3.5-4.4 cm). • Crows flew to 5m height to drop whelk • Persisted in dropping until whelk broke.
Optimal foraging by crows • Are crows behaving optimally? • If so, large whelks should be more likely to break than small ones, 5m drops should yield best chance of breaking whelk, and the likelihood of a whelk breaking should not depend on the number of previous drops.
Optimal foraging by crows • Zach experimentally dropped different size whelks from different heights and confirmed the three predictions. Fig 7.1
Optimal foraging by crows • Zach also calculated the caloric yields of different size whelks. • He found that when the costs of opening a whelk were deducted from the energy gained, large whelks yielded by far the highest energy return.
Young juncos clumsy at handling large prey, but can eat small items. Adults can handle larger prey. Different abilities result in different optimal choices for age classes.
Young birds choose small prey. Adults select larger items
Optimal prey delivery. Birds feeding young have to deliver food Items to their nestlings. Must travel to food patch and feed. How many food items should be brought back? What factors affect decision?
Declining ability to catch food as bill fills up. Prey in patch becomes depleted. Costs of travel to patch.
Marginal Value Theorem (MVT) can be used to analyze when it is optimal to leave patch. At what point does it not pay to search for one more item? Marginal value is a central idea in Economics. It is the amount you will pay for one more of a particular item.
Value of one more item to you declines the more items you have. This explains why you pay a lower price for more of a good. Can use the MVT to solve the bird’s problem.
Solving problem with MVT • To solve the problem graphically you first plot the cumulative gain curve which is the rate at which the bird gains food. • The X-axis is time and the Y-axis is food intake. • Note the curve flattens as the rate at which food is acquired slows.
Food intake Food gain curve Short Long Arrival time in patch
Solving problem with MVT • To identify the optimal number of food items to take and the optimal time to spend in the patch draw a straight line from the travel time that intersects the gain curve at one point only (i.e. is a tangent). • From this intersection point drop straight lines to the X and Y axes to figure out the optimal time to spend in the patch and the optimal number of food items to consume respectively.
Food gain curve Short Long Arrival time in patch
Solving problem with MVT • As travel time to the patch increases it is predicted that the forager will stay longer in the patch and consume fewer items.
Alejandro Kajelnik trained starlings to visit a feeder where mealworms were dispensed.
Varied distance of feeder from nest. Recorded load sizes. Load size increased with distance to nest.
Optimizing things other than food. Optimal site choice for food consumption Animals attempt to optimize more than just food intake. Food intake may be traded off against survival.
Chickadees generally carry items to cover to eat them in safety.
A chickadee’s decision whether to carry an item to cover is affected by its distance to cover (energetic costs) and its perceived risk of predation.
Steve Lima observed feeding behavior of chickadees at sites 2m, 10m, and 18m from cover. Chickadees were less likely to carry items to cover as distance increased. However, when a “predator” was flown overhead the probability of carrying food to cover increased.
Predator present No predator present
Risk avoidance by foraging leaf cutter ants • Leaf cutter ants harvest leaves that they then use to grow fungi, which they then eat. • The ants do most of their foraging for leaves at night and only small inefficient ants search for leaves during the day. At night the larger, most efficient ants forage for leaves. • Why do the large ants not forage during the day?
Risk avoidance by foraging leaf cutter ants • Ants with head widths of 1.8mm or more are parasitized by a parasitic fly that lays its eggs in the ants head with lethal consequences for the ant. • These flies are active only during the day, so large ants avoid them by foraging at night. Smaller ants are not parasitized and so can forage during daylight.
Risk avoidance by skinks • In a similar fashion garden skinks (a lizard) that were reared in experimental enclosures that contained the scent of a predatory snake moved around less and avoided open areas more than skinks reared in similar, but scent-free enclosures.
Game theory and foraging behavior • Game theory examines situations in which individuals play different strategies. • For example, roseate terns catch fish by diving for them, but an alternative approach is to steal fish from successful birds.
Foraging Roseate Terns • Often one would expect one strategy to be superior and for it to become fixed in the population. • In the Roseate Tern case frequency-dependent selection appears to maintain the two strategies.
Foraging Roseate Terns • The fish stealing phenotype is going to be most successful when rare and least successful when common (too much competition and too few fish being caught). • The fish hunting phenotype will be most successful when common (few fish being lost to thieves) and least successful when rare.
Foraging Roseate Terns • As a result, the fitness curves for the two strategies will intersect and this will be an equilibrium point at which the payoffs to the two strategies will be the same. • Any deviation from this optimal ratio of hunters to thieves will result in a lower payoff and the system should return to the equilibrium point.
Another game theory example Perissodusmicrolepis in Lake Tanganyika has an unusual foraging technique.
Population divided into two phenotypes whose jaws are angled left or right.
Jaw orientation heritable, as is behavioral phenotype -- attack left flank or attack right flank. Genes for both probably closely linked on chromosome. These strategies are fixed and their success depends on their relative frequency in the Population.
Rarer phenotype has an advantage in attacking prey. It becomes more common, and then the advantage switches. This is example of frequency-dependent selection. Frequency-dependent selection occurs when a phenotype’s success is affected by its frequency in the population.
Conditional strategies • Sometimes as in the case of Perissodus an individual is locked into one strategy. • However, in other cases an individuals strategy is contingent on what its circumstances are.
Conditional strategies • For example, turnstones (a small wading bird) foraging in flocks on beaches use different techniques and parts of the beach depending on their status in the flock. • Dominant birds forage in patches of seaweed which contain lots of invertebrates, but subordinates instead probe in mud or sand for food.
Hunting in Groups Prey benefit from grouping. Predators also can benefit by cooperating to attack prey. Lions, hyenas, African hunting dogs, wolves all hunt cooperatively.
Main advantages of cooperative hunting: 1. Hunting success rate is increased. 2. Larger prey can be tackled.
Some birds also hunt cooperatively. Pelicans cooperate to herd schools of fish.
