•Glances are more common with leader, and laggard pairs. And the
response time the leader takes with a laggard is slower because
they are constantly looking at the laggard, and glancing at them.
So they are recognizing that they are with a coward. So why
doesn’t this foolow the model of recip altri? Why don’t the females
punish the cheater?
•What happens if the leader defect? An opposing pride will displace
them. So that cost maybe too high for leaders to punish the
laggard. So punishing laggards is costly to the leading female and
the laggard. So why aren’t most females laggards? They should be
selection of all females to be laggards, because ethey are reducing
their risk and if someone is a leader, then they have someone to
defend the territory.y
•Maybe the females are sometimes leaders and sometimes
laggards? That isn’t the case. Ind have consistent behav
throughout their life.
oGraph shows diff tactics seen in females. They manipulated
the risk to the leader. The more individuals that are
challending the lion, there is a higher risk that the leader
will be injured. X-axis :# defending versus # intruder, and
as this increases there is a low risk of injury. Individuals
chge their lagging behiur according to the risk they assess.
And some individual do the opposite, some lag more when it
is riskier, and when there is no risk, their lag time is
minimal. When there is a serious risk, their lag time
increases. There seems to be almost a personality in the
lions. And there are also other that don’t change as a
function of the risk. So there are 3 different patterns among
the lions. And no one knows why? They know that
individuals have the same tactic throughout their life, and
it isn’t heritable, it is decided earlier in life.
•Conditional and unconditional strategies : conditional : when the
behaviour depends on an external strategy ( risk) in unconditional,
it doesn’t depend on the risk.
•It may not be reciprocal altruism because females are in a trap. We
don’t see reciprocal altruism with leading and lagging, but many