Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate
The persistence of an invasive species is influenced by its reproductive ecology, and a successful control program must operate on this premise. However, the reproductive ecology of invasive species may be enigmatic due to factors that also limit their management, such as cryptic coloration and behavior. We explored the mating and reproductive ecology of the invasive Brown Treesnake (BTS: Boiga irregularis) by reconstructing a multigenerational genomic pedigree based on 654 single nucleotide polymorphisms for a geographically closed population established in 2004 on Guam (N = 426). The pedigree allowed annual estimates of individual mating and reproductive success to be inferred for snakes in the study population over a 14‐year period. We then employed generalized linear mixed models to gauge how well phenotypic and genomic data could predict sex‐specific annual mating and reproductive success. Average snout–vent length (SVL), average body condition index (BCI), and trappability were significantly related to annual mating success for males, with average SVL also related to annual mating success for females. Male and female annual reproductive success was positively affected by SVL, BCI, and trappability. Surprisingly, the degree to which individuals were inbred had no effect on annual mating or reproductive success. When juxtaposed with current control methods, these results indicate that baited traps, a common interdiction tool, may target fecund BTS in some regards but not others. Our study emphasizes the importance of reproductive ecology as a focus for improving BTS control and promotes genomic pedigree reconstruction for such an endeavor in this invasive species and others.
|Publication Subtype||Journal Article|
|Title||Genomic pedigree reconstruction identifies predictors of mating and reproductive success in an invasive vertebrate|
|Series title||Ecology and Evolution|
|Contributing office(s)||Fort Collins Science Center|
|Google Analytic Metrics||Metrics page|