Data for: Giant babax helpers claim excess immediate reward in barren high-altitude habitat
Du, Bo (2022), Data for: Giant babax helpers claim excess immediate reward in barren high-altitude habitat, Dryad, Dataset, https://doi.org/10.5061/dryad.ffbg79cxc
In cooperatively breeding species, helpers take higher risk of getting deficit than dominant breeders because of the time-lag between helping and rewarding. Helpers can deal with the risk by curtailing investment or claiming immediate rewards in the cooperation. Given that dominant breeders may rely largely on the aids of helpers in raising their offspring under barren conditions, it can be hypothesized that helpers are more likely to adopt these two adaptive strategies in a barren habitat than in fertile ones. We tested this hypothesis in the giant babax (Babax waddelli) by comparing helpers’ provisioning behaviors between two populations breeding in a harsh high-altitude and good low-altitude environment, respectively. Breeding parameters differed significantly between these two population, wherein helpers made equally great contributions to raising offspring. During the process of provisioning, helpers in the high-altitude population had significantly higher feeding rate 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 the provisioning. Helpers tended to pursue excess immediate rewards via the contested kleptoparasitism of nestling fecal sacs in the high-altitude population but not in the low-altitude one. Accordingly, dominant breeders made different antagonistic actions to the cheating helpers between two populations. Our findings confirm that helpers are prone of cheating in the cooperation under a barren breeding condition, and that dominants’ tolerance on the cheating of helpers is determined by their dependence on the aids of helpers.
We collected the dataset in the field. It has been processed according to the methods of different statistical analyses.
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