Friday, August 6, 2010 - 9:20 AM

COS 119-5: Reproductive parameters of the endangered Florida panther: Effects of genetic introgression

Jeffrey A. Hostetler, University of Florida, David P. Onorato, Florida Fish and Wildlife Conservation Commission, and Madan K. Oli, University of Florida.

Background/Question/Methods

Concerns about potential inbreeding depression in the endangered Florida panther (Puma concolor coryi) led to the release of 8 female Texas pumas (P. c. stanleyana) into the population in 1995. The demographic effects of this introgression program have not been thoroughly evaluated. We used long-term reproductive data (1995-2008) collected from 61 female Florida panthers radio-tracked for a total of 2,414 panther-months to estimate and model breeding probability (probability of producing a litter) and litter size, and to investigate the influence of intentional genetic introgression, season, and abundance index on these parameters.  

Results/Conclusions

Overall, 6-month probability of breeding (±1SE) was 0.232 ± 0.021 (annual breeding probability: 0.410 ± 0.032) and average litter size was 2.596 ± 0.144.    Panthers were more likely to give birth in the dry season (December – May) than in the wet season (June – November).  There was little evidence that season or abundance index influenced litter size. Although F1 admixed females had lower breeding probability than females with other ancestries, it was most likely because kittens born to F1 females survive better; consequently, these females are not available for breeding until kittens are independent. There was no evidence for the effect of ancestry on litter size, or of heterozygosity on probability of breeding or litter size.  Finally, we found that abundance index positively influenced breeding probability (β = 0.008 ± 0.004), due perhaps to mate-finding Allee effect.  Our results clearly suggest that genetic introgression and population density can have differential effects on components of fitness and highlight the importance of examining multiple demographic parameters when evaluating the effects of these factors.