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Are offspring begging levels exaggerated beyond the parental optimum? Evidence from a bidirectional selection experiment

Journal Contribution - Journal Article

Parental care involves elaborate behavioural interactions between parents and their offspring, with offspring stimulating their parents via begging to provision resources. Thus, begging has direct fitness benefits as it enhances offspring growth and survival. It is nevertheless subject to a complex evolutionary trajectory, because begging may serve as a means for the offspring to manipulate parents in the context of evolutionary conflicts of interest. Furthermore, it has been hypothesized that begging is coadapted and potentially genetically correlated with parental care traits as a result of social selection. Further experiments on the causal processes that shape the evolution of begging are therefore essential. We applied bidirectional artificial selection on begging behaviour, using canaries (Serinus canaria) as a model species. We measured the response to selection, the consequences for offspring development, changes in parental care traits, here the rate of parental provisioning, as well as the effects on reproductive success. After three generations of selection, offspring differed in begging behaviour according to our artificial selection regime: nestlings of the high begging line begged significantly more than nestlings of the low begging line. Intriguingly, begging less benefitted the nestlings, as reflected by on average significantly higher growth rates, and increased reproductive success in terms of a higher number of fledglings in the low selected line. Begging could thus represent an exaggerated trait, possibly because parent-offspring conflict enhanced the selection on begging. We did not find evidence that we co-selected on parental provisioning, which may be due to the lack of power, but may also suggest that the evolution of begging is probably not constrained by a genetic correlation between parental provisioning and offspring begging.
Journal: Journal of evolutionary biology
ISSN: 1010-061X
Volume: 99
Pages: 1 - 12
Publication year:2020
Keywords:A1 Journal article
BOF-publication weight:1
CSS-citation score:1
Authors from:Higher Education