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[Vol. 95 
and more active individuals, may reflect advantages of staying with 
the group (e.g. for defense and thermoregulation). In this scenario, 
when the level of hunger is skewed (i.e. some individuals are hungry 
but most are still digesting food) we would expect a temporary 
pattern of leaders and followers; when the level of hunger is distrib- 
uted normally among individuals in a foraging group we would 
expect no clear pattern of leaders and followers. Some caterpillar 
species alter searching behavior when the larvae are starved (Jones, 
1977; Cain et al., 1985). But the idea that consistency in leadership 
reflects a skewed distribution in hunger-levels remains untested here 
because we did not attempt to assess state of hunger. However, in 
our study all groups were deprived of food for 24 h before testing. 
Thus, individuals should have been approaching equal hunger lev- 
els, but even with 24-h starvation, the amount of food in the gut of 
third and fourth instar H. lucina varies considerably (Bowers and 
Stamp, unpubl. data). 
In these experiments, we used Lorenz curves and Gini coefficients 
to evaluate behavioral data, in this case skewed distributions of 
distance traveled. Previously, these techniques have been applied to 
questions of market-share and distribution of wealth in economics 
and biomass or size distributions in plant populations (Weiner and 
Solbrig, 1984, and references therein). The market-share concept 
does not apply to distances traveled by aggregated caterpillars per se 
because there does not seem to be a premium on obtaining a larger 
share, or in this case, being more active or traveling faster than other 
group members. But it is a similar situation in that the distributions 
of interest here tend to be skewed. That is, during the course of the 
experiments, the most active larvae leave the aggregation first and 
travel farthest, whereas other larvae remain quiescent longer and 
travel shorter distances. Therefore, these techniques are appropriate 
for our study and allow us to address the biological question of 
interest (i.e. what is the pattern of inequality or variation among 
individuals), which other measurements of skewness do not (Weiner 
and Solbrig, 1984). Lorenz curves and Gini statistics are applicable 
to other kinds of behavioral data, in particular situations where 
resources are limiting, and as a result, measurements of individuals 
yield a skewed distribution (e.g. number of matings, number of 
offspring). 
