Population models can incorporate genetic data to assess potential impacts of different management strategies on connectivity, effective population size, and genetic diversity.
Incorporating Genetic Data into Spatially-explicit Population Viability Models for Gunnison Sage-grouse - Principal Investigator - Sara Oyler-McCance
This goal of this study is to develop a spatially explicit habitat-population modeling framework to assess the viability of Gunnison Sage-grouse and each of the seven populations (Gunnison Basin and six satellite populations). Components of this process include 1) characterizing habitat for the Gunnison Basin and satellite populations, 2) developing a spatially explicit individual-based model, 3) simulating population dynamics and persistence to identify population thresholds and characterize population resiliency, redundancy, and representation (and indicating possible strategies for improvements to these), 4) quantifying the impacts of alternative habitat restoration and translocation strategies on regional and local population persistence, 5) comparing model outcomes to previous PVA approaches and results, and 6) setting the stage for future model applications that comprehensively address specific threats and stressors (e.g., climate change). This research is in collaboration with Colorado State University.
Completed Research
Investigating the Impact of Contraception on Demographic and Genetic Characteristics of Wild Horse Herds - Principal Investigator - Butch Roelle
Wild horse populations can increase rapidly, resulting in the need for removal of animals in order to protect the habitat that horses share with numerous other species. As an alternative, BLM is seeking to develop a contraceptive to reduce population growth rates. With long-term efficacy of contraception, however, comes increased concern about the genetic health of populations and about the potential for local extirpation. We used simulation modeling to examine the potential demographic and genetic consequences of applying a mare sterilant to wild horse populations.
Population models can incorporate genetic data to assess potential impacts of different management strategies on connectivity, effective population size, and genetic diversity.
Incorporating Genetic Data into Spatially-explicit Population Viability Models for Gunnison Sage-grouse - Principal Investigator - Sara Oyler-McCance
This goal of this study is to develop a spatially explicit habitat-population modeling framework to assess the viability of Gunnison Sage-grouse and each of the seven populations (Gunnison Basin and six satellite populations). Components of this process include 1) characterizing habitat for the Gunnison Basin and satellite populations, 2) developing a spatially explicit individual-based model, 3) simulating population dynamics and persistence to identify population thresholds and characterize population resiliency, redundancy, and representation (and indicating possible strategies for improvements to these), 4) quantifying the impacts of alternative habitat restoration and translocation strategies on regional and local population persistence, 5) comparing model outcomes to previous PVA approaches and results, and 6) setting the stage for future model applications that comprehensively address specific threats and stressors (e.g., climate change). This research is in collaboration with Colorado State University.
Completed Research
Investigating the Impact of Contraception on Demographic and Genetic Characteristics of Wild Horse Herds - Principal Investigator - Butch Roelle
Wild horse populations can increase rapidly, resulting in the need for removal of animals in order to protect the habitat that horses share with numerous other species. As an alternative, BLM is seeking to develop a contraceptive to reduce population growth rates. With long-term efficacy of contraception, however, comes increased concern about the genetic health of populations and about the potential for local extirpation. We used simulation modeling to examine the potential demographic and genetic consequences of applying a mare sterilant to wild horse populations.