Deciphering genetic mate choice: Not so simple in group-housed conservation breeding programs.

Incorporating mate choice into conservation breeding programs can improve reproduction and the retention of natural behaviors. However, different types of genetic-based mate choice can have varied consequences for genetic diversity management. As a result, it is important to examine mechanisms of mate choice in captivity to assess its costs and benefits. Most research in this area has focused on experimental pairing trials; however, this resource-intensive approach is not always feasible in captive settings and can interfere with other management constraints. We used generalized linear mixed models and permutation approaches to investigate overall breeding success in group-housed Tasmanian devils at three nonmutually exclusive mate choice hypotheses: (a) advantage of heterozygous individuals, (b) advantage of dissimilar mates, and (c) optimum genetic distance, using both 1,948 genome-wide SNPs and 12 MHC-linked microsatellites. The managed devil insurance population is the largest such breeding program in Australia and is known to have high variance in reproductive success. We found that nongenetic factors such as age were the best predictors of breeding success in a competitive breeding scenario, with younger females and older males being more successful. We found no evidence of mate choice under the hypotheses tested. Mate choice varies among species and across environments, so we advocate for more studies in realistic captive management contexts as experimental or wild studies may not apply. Conservation managers must weigh up the need to wait for adequate sample sizes to detect mate choice with the risk that genetic changes may occur during this time in captivity. Our study shows that examining and integrating mate choice into the captive management of species housed in realistic, semi-natural group-based contexts may be more difficult than previously considered.
Competing Interests: None declared.
(© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)