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Data for: Fitness costs of female competition linked to resource defence and relatedness of competitors

Cite this dataset

Fischer, Stefan et al. (2022). Data for: Fitness costs of female competition linked to resource defence and relatedness of competitors [Dataset]. Dryad. https://doi.org/10.5061/dryad.j0zpc86h1

Abstract

Female reproductive success is often limited by access to resources and this can lead to social competition both within and between kin groups. Theory predicts that both resource availability and relatedness should influence the fitness consequences of social competition. However, testing key predictions requires differentiating the effects of these two factors. Here we achieve this experimentally by manipulating the social environment of house mice, a facultative communal breeding species with known kin discrimination ability. Our results support the hypothesis that resource defence can be costly for females, potentially trading off against maternal investment. When competition for nest sites was more intense, subjects: 1) were more active during resting phases, 2) responded more strongly to simulated territory intrusions via competitive signalling, and 3) produced smaller weaned offspring. However, we found no evidence that the propensity for kin to cooperate was influenced by relatedness of rivals. Communal breeding between sisters occurred independently of the relatedness of competitors, and costs of competition with non-kin were not mitigated by greater inclusive fitness benefits. Rather, communally breeding sisters weaned fewer offspring when competing with unrelated females, indicating that competition with non-kin is more costly overall. Our findings thus demonstrate that social competition has fitness costs and that associating with kin is beneficial to avoid negative fitness consequences of competing with non-kin, in addition to more widely recognised kin-selected benefits.

Usage notes

This data file contains all the data and the R-code for each of the analysis and figures presented in the main manuscript and supplementary material. Please see the README.txt file for further description of each file, including a detailed explanation of each column name. The R-file contains the annotated R-code for all the analysis and figures presented in the main manuscript and supplementary material.

Funding

Natural Environment Research Council, Award: NE/M002977/1