Ma. Rodriguezgirones et Ra. Vasquez, DENSITY-DEPENDENT PATCH EXPLOITATION AND ACQUISITION OF ENVIRONMENTALINFORMATION, Theoretical population biology, 52(1), 1997, pp. 32-42
We study density-dependent resource harvest patterns due to Bayesian f
oraging for different distributions of resources. We first consider a
forager with information about the stochastic properties of its enviro
nment. In this case we show that when the number of food items per pat
ch follows a distribution from the exponential family, the density dep
endance is given by the ratio sigma(2)/mu of the distribution of numbe
r of food items per patch, Bayesian foraging can therefore lead to pos
itive (negative binomial distributional) or negative (binomial distrib
ution) density dependent resource harvest and even to density independ
ent (Poisson distribution) resource harvest, depending on the distribu
tion of resources in the environment. In a second stage we incorporate
learning about the distribution of resources ire the whole environmen
t, The mean of the distribution of number of food items per patch of a
given environment is learnt faster than the variance if the distribut
ion. Learning occurs faster in poorer than richer environments. (C) 19
97 Academic Press.