Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

agricultural and biological sciences

Argali abundance in the Afghan pamir using capturerecapture modeling from fecal DNA

Journal of Wildlife Management, Volume 74, No. 4, Year 2010

Estimating population size in a markrecapture framework using DNA obtained from remotely collected genetic samples (e.g., feces) has become common in recent years but rarely has been used for ungulates. Using DNA extracted from fecal pellets, we estimated the size of an argali (Ovis ammon) population that was believed to be isolated from others within the Big Pamir Mountains, Afghanistan, an area where access was difficult and expensive. We used closed-capture models to estimate abundance, and Pradel models to examine closure assumptions, both as implemented in Program MARK. We also made visual counts of argali in the Big Pamirs, allowing comparison of count indices of abundance with modeled estimates. Our model-averaged estimate for female argali in the Big Pamir was 172 (95 CI 117232), which was about 23 higher than our best assessment using uncorrected visual counts. However, markrecapture models suggested that males were not a closed population; thus, we were unable to provide a meaningful estimate of overall population size. Males either suffered much higher mortality than females during the sampling period, or, more likely, males moved in and out of the Big Pamir area. Although information from DNA did not provide a clear overall population estimate, it suggested that the Big Pamir was not isolated from other argali populations, which could not have been confirmed with visual observations alone. Estimating argali population size using markrecapture models and fecal DNA is feasible but may be too expensive for frequent monitoring of large and remote populations. Our study demonstrates the importance of sex identification and separate abundance estimation for each sex, especially if movement ecology differs by sex. © The Wildlife Society.

Statistics
Citations: 52
Authors: 6
Affiliations: 3
Identifiers
Research Areas
Genetics And Genomics
Health System And Policy
Study Design
Cross Sectional Study
Participants Gender
Female