By TAMARA C. GRAND
Animal Behaviour, Volume 53, Issue 1, January 1997, Pages 185-196, ISSN 0003-3472, DOI: 10.1006/anbe.1996.0287.

When individuals differ in competitive ability, ideal free distribution theory predicts that animals should be distributed between habitats such that the distribution of their relative competitive abilities (or `weights') matches the distribution of resources. At equilibrium, the unequal competitors model predicts that the payoff per unit of competitive weight will be the same in all habitats, such that no individual can increase its payoff by moving. These predictions were tested in juvenile coho salmon,Oncorhynchus kisutchby allowing 15 groups of eight individuals to compete for drifting prey in a two-patch stream channel environment. Competitive weights were quantified a priori as the proportion of prey obtained by each individual when competing with all other members of the group in a single patch. At equilibrium, the distributions of competitive weights did not differ significantly from the distributions of resources, although in most groups, slightly too many competitive weights were in the poor patch relative to that predicted by the model. The mean payoff per unit of competitive weight did not differ between patches. In the good patch, however, `poor' competitors tended to receive higher payoffs per unit of competitive weight than `good' competitors, which suggests that competitive abilities did not remain constant across patches as assumed by the model. Although evidence exists for the original, equal competitors ideal free distribution model (i.e. total competitor numbers match the distribution of resources) despite the presence of competitive inequalities, the present results suggest that this will not always be true. Distributions of coho salmon numbers were significantly different from both the distributions of resources and the distributions of competitive weights. These results suggest that the incorporation of competitive inequalities into habitat selection models will enhance our ability to predict animal distributions.

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