Optimal Foraging theory is an application of evolutionary
thinking to the behaviors of consumers (choice of patches of food, or
individual items of food).
The assumptions are that organisms maximize their fitness by
maximizing their energy intake, and by minimizing their risk of exposure to
On a foraging trip, an organism spends time traveling
between patches of food (travel time), and spends time in each patch of food
organism only gains energy when it is in the patch of food
the patch is depleted of food, and no more energy is gained by staying in
graphical analysis allows one to find the optimal length of time that the
organism should spend in the patch (Fig 9.17 in Ricklefs).
plots number of prey caught (energy gain) against time spent.
average rate of energy gain over a foraging trip can be represented by a
line running through the origin, and tangent to the instantaneous energy
optimal residence time in the patch is the time when the curves touch each
travel times favor longer times spent in the food patch.
travel times favor shorter times spent in the food patch.
The choice of individual food items is analyzed in a similar
The average rate of energy gain for an animal is
E/T where E is the
total energy gained and T is the total time spent foraging.
For each food item, the time spent is divided into Search
Time Ts and Handling Time Th.
An animal encounters a food item and must decide whether to
eat it or not. It already has found the
item, so the only further time it must spend is Th, the handling
time necessary to eat it. The animal
should add the item if E/Th for that item is greater than E/(Ts+Th)
for its preferred item. In order to get
the preferred item, it must search and then handle and consume the preferred
item. In order to consume the item in
hand, it only has to handle it.
item is added to the diet if new item E/Th > E/(Ts+Th)
for the preferred item
- If the
preferred item is rare, then Ts is large, and there may be an
advantage to eating the less preferred item.
- If the
new item is hard to eat, so Th is large, then the predator may
is consistent with the fact that people are willing to eat food from
vending machines: Preferred items
are sparse, so Ts is large, and people are willing to add junk
to their diets, because E/Th of junk food is greater than E/(Ts+Th)
for real food.