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Meta-analytic evidence that animals rarely avoid inbreeding


Animals are usually expected to avoid mating with relatives (kin avoidance) as incestuous mating can lead to the expression of inbreeding depression. Yet, theoretical models predict that unbiased mating with regards to kinship should be common, and that under some conditions, the inclusive fitness benefits associated with inbreeding can even lead to a preference for mating with kin. This mismatch between empirical and theoretical expectations generates uncertainty as to the prevalence of inbreeding avoidance in animals. Here, we synthesized 677 effect sizes from 139 experimental studies of mate choice for kin versus non-kin in diploid animals, representing 40 years of research, using a meta-analytical approach. Our meta-analysis revealed little support for the widely held view that animals avoid mating with kin, despite clear evidence of publication bias. Instead, unbiased mating with regards to kinship appears widespread across animals and experimental conditions. The significance of a variety of moderators was explored using meta-regressions, revealing that the degree of relatedness and prior experience with kin explained some variation in the effect sizes. Yet, we found no difference in kin avoidance between males and females, choice and no-choice experiments, mated and virgin animals or between humans and animals. Our findings highlight the need to rethink the widely held view that inbreeding avoidance is a given in experimental studies.

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Fig. 1: Funnel plot of effect sizes to assess publication bias in the dataset.
Fig. 2: Meta-analytical means for different subsets of the dataset.
Fig. 3: The effect of relatedness and previous experience with kin on effect size estimates.

Data availability

The datasets generated and analysed during the current study are available at the OSF platform under the following identifier:

Code availability

The R code used to analyse the data in the current study is available at the OSF platform under the following identifier:


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We thank S. Nakagawa for his valuable and excellent course on meta-analyses, R. O’Dea for her help with coding and statistical advice and A. Silva for helping create the phylogenetic figure. R.A.d.B. was funded by the Carl Tryggers Foundation (17:152), R.V.-T. and A.K. by the Swedish Research Council (2017-04957) and J.L.F. by the Knut and Alice Wallenberg Foundation and the Swedish Research Council (2017–04680).

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All authors conceived the study and contributed to the design of the study. R.A.d.B. and R.V.-T. collected the data, performed the analyses and wrote the first draft. J.L.F. contributed to interpreting the data and writing the final manuscript. A.K. helped improve the final manuscript.

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Correspondence to Raïssa A. de Boer or Regina Vega-Trejo.

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Peer review information Nature Ecology & Evolution thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Phylogenetic distribution of the species included in the dataset.

Primary study references and graphical summary of the phylogenetic distribution of (a) invertebrate and (b) vertebrate species contributing statistical effects addressing inbreeding avoidance. Depicted are phylogenetic relatedness, scientific names, number of effect sizes for precopulatory, during mating, and postcopulatory estimates, and number of studies for each species. Larger numbers of effect sizes are highlighted with darker colouration. Animal silhouettes obtained from

Extended Data Fig. 2 Assessing publication bias.

The results of Egger’s regressions and adjusted estimates obtained using trim-and-fill methods when assessing the (a) full dataset and (b-d) different subsets of the full dataset. The full dataset was subsetted (as described in the main text and Table 1 legend) to focus only on (b) internal fertilizers, (c) internal fertilizers where kin at relatedness levels of r = 0.5 were assessed, and (d) internal fertilizers where kin at relatedness levels of r = 0.5 were assessed and where kin were familiar and non-kin unfamiliar. For each Egger’s regression model, the intercept, t-value (t), and P-value (P) are provided. Positive intercepts in Egger’s regressions that are significantly different from zero indicate publication bias towards studies confirming kin avoidance. Publication bias in favour of studies reporting kin avoidance was evident in the full dataset and every subset of the dataset examined. In addition, the adjusted estimate (Hedges’ g) and it’s 95% confidence interval [95% CI] for each meta-analytic model is presented, after assessing publication bias using three different estimators (L0, R0 and Q0) to apply the trim-and-fill method.

Extended Data Fig. 3

PRISMA diagram describing the search results in Scopus and Web of Science and the different steps of selecting articles for inclusion in the meta-analysis. In Search A – D different sets of keywords were used to target a wide range of animal studies, and Search E specifically targeted studies on inbreeding avoidance in humans. A backward search was performed on the 10 most recent papers selected for inclusion, and a forward search on the 10 most cited papers selected for inclusion. Details of each search are provided at

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de Boer, R.A., Vega-Trejo, R., Kotrschal, A. et al. Meta-analytic evidence that animals rarely avoid inbreeding. Nat Ecol Evol (2021).

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