Biology Reference
In-Depth Information
teach pups prey-handling skills by gradually introducing them to live prey and
monitoring the pups' handling performance, retrieving prey that the pups have dropped
or lost. Adults first provision pups with dead scorpions. Then, as the pups improve their
skills, they bring live scorpions with the stings removed, before finally presenting intact
scorpions. Hand feeding experiments confirmed that this teaching improved the pups'
handling skills. Pups provided on three consecutive days with live, stingless scorpions
were then more likely to handle a scorpion correctly and quickly than other pups who
were provided with either dead scorpions or hard boiled egg, as a control.
As with the ants, the adult meerkat's teaching behaviour is likely to involve simple
behavioural rules rather than complex cognitive mechanisms, such as recognizing the
ignorance of pupils. For example, playback experiments showed that adults modified
their presentation of prey in response to the maturation of the pups' begging calls.
Playback of recorded calls of old pups caused adults to provision live scorpions, while
playback of young pups' calls caused them to bring dead prey.
Teaching using
simple rules
Optimality models and behaviour:
an overview
In this chapter we have seen how optimality models can be used to analyse decisions
about foraging and mating (Table 3.1). This approach is an extension of the idea of
interpreting behaviour in terms of costs and benefits that we introduced in the last
chapter. Let us now try to summarize some of the advantages and limitations of
optimality modelling. Three main advantages illustrated by this chapter are:
(1)
Optimality models often make testable, quantitative predictions so that it is
relatively easy to tell whether the hypotheses that are represented in the model are
right or wrong. For example, the honeybee workers were shown not to be
maximizing net rate of energy delivery to the hive, but were maximizing efficiency
in their foraging. The hypotheses that were tested in the bee study, and in all
optimality studies, were hypotheses about the
currency
(what is being optimized)
and about the
constraints
on the animal's performance (energy costs, handling
times and so on). The currency is a hypothesis about the costs and benefits
impinging on the animal; for example, for bees energetic costs and benefits seem to
be much more important than, say, predation and other dangers. The constraints
are hypotheses about the mechanisms of behaviour and the physiological
limitations of the animal, whether it is able to recognize differences in nectar
concentration, how fast it can fly and so on.
(2)
A second advantage is that the assumptions underlying the currency and constraint
hypotheses are made explicit. In the model used to analyse load size of starlings, for
example, we had to make explicit assumptions about the loading curve, about the
fact that the bird could encounter only one patch at a time, about the time taken to
fly to the nest and so on. By making these things explicit in the model one is forced
to think clearly about the problem.
(3)
Finally, optimality models emphasize the generality of simple decisions facing
animals. For example, foraging starlings and copulating dung flies face the same
general problem of when to give up from a curve of diminishing returns.
Optimality
models:
testability, explicit
assumptions,
generality
