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Dryad

Giant babax (Babax Waddelli) helpers cheat at provisioning nestlings in poor conditions

Cite this dataset

Du, Bo et al. (2023). Giant babax (Babax Waddelli) helpers cheat at provisioning nestlings in poor conditions [Dataset]. Dryad. https://doi.org/10.5061/dryad.ffbg79cxc

Abstract

In cooperatively breeding species, helpers take higher risks of getting lower return of investment than breeders due to the incongruity between helping and breeding. Helpers can deal with the risk by curtailing their investment or, if possible, claiming immediate rewards in the cooperation. Given breeders may rely largely on the aid of helpers to raise their offspring, it can be hypothesized that helpers are more likely to make adaptive responses to the incongruity-associated risk in adverse habitats than in good ones. This hypothesis was tested in the giant babax (Babax waddelli) by comparing helpers' provisioning behaviors between two breeding populations in adverse high-altitude and good low-altitude environments. These two populations differed significantly in their egg size and nestlings’ growth patterns. Helpers in both populations made great contributions to the raising of offspring. During provisioning, helpers in the high-altitude population exhibited significantly higher feeding rates but delivered fewer insects per feeding bout than their counterparts in the low-altitude population. Helpers in both populations displayed a cheating strategy of 'non-feeding' to reduce investment in provisioning. They pursued immediate excess rewards via kleptoparasitism of nestling fecal sacs in the high-altitude population but not in the low-altitude one. Accordingly, breeders made different antagonistic actions toward the cheating helpers between populations. Our findings confirm that helpers are prone to deceiving cooperation under poor breeding conditions and that breeders' tolerance of the cheating behavior of helpers is determined by their dependence on the helpers' aid.

Methods

We collected the dataset in the field. It has been processed according to the methods of different statistical analyses.

Funding

National Natural Science Foundation of China, Award: 31572271

National Natural Science Foundation of China, Award: 31672299

National Natural Science Foundation of China, Award: 31772465

National Natural Science Foundation of China, Award: 32071491

Natural Science Foundation of the Tibetan, Award: XZ202101ZR0051G