Abstract
Nepotism and reciprocity are not mutually exclusive explanations for cooperation; helping decisions can depend on both kinship cues and past reciprocal help. The importance of these two factors can therefore be difficult to disentangle with observational data. We developed a resampling procedure for inferring the statistical power to detect observational evidence of nepotism and reciprocity, and applied this procedure to simulated and real datasets. We simulated datasets resulting from perfect reciprocity, where the probability and duration of helping events from individual A to B equaled B to A. We also simulated varying degrees of simultaneous nepotism. We then assessed how nepotism and sampling effort influenced the probability of detecting evidence of reciprocity. We applied the same analysis to empirical data on food sharing in vampire bats and allogrooming in mandrills and Japanese macaques. Nepotism consistently masked evidence for reciprocity. With perfect reciprocity and imperfect nepotism, nepotism was more likely to be detected and overestimated. We explain the causes and consequences. To compare the relative importance of genetic and social ties, researchers should measure the relative reliability of both estimates. We provide R scripts to allow others to assess the reliability of kinship and reciprocal help estimates in their own datasets.
Footnotes
The authors wish to be identified to the reviewers.