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Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
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Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
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Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis

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Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis
Journal Article

Comparing performance of multiple non-invasive genetic capture–recapture methods for abundance estimation: a case study with the Sonoran pronghorn Antilocapra americana sonoriensis

2020
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Overview
Demographic monitoring is required in threatened species management, yet effective and efficient monitoring is challenging for species that are difficult to capture or susceptible to capture stress. One possible monitoring approach for such species is non-invasive genetic sampling with capture–recapture methods (genetic capture–recapture). We evaluated the performance of genetic capture–recapture in a challenging model system, monitoring the threatened Sonoran pronghorn Antilocapra americana sonoriensis . In an effort to determine the best (i.e. efficient, accurate, precise, cost-effective) method for abundance estimation, we used simulations to examine the optimal genetic capture–recapture faecal sampling design for this population. We simulated encounter histories for 100–300 individuals, with 0.33–3.33 samples/individual/session, in 1–3 sampling sessions. We explored trade-offs between sample size, number of sessions and multi-session ( MARK ) versus single-session ( capwire ) closed capture–recapture abundance estimators, and an accurate and precise estimate. We also compared the cost between the genetic capture–recapture approaches and current aerial monitoring methods. Abundance was biased positively in capwire and negatively in MARK . Bias increased and precision decreased with fewer samples/individual/session. Annual genetic capture–recapture monitoring cost was nearly twice the cost of aerial surveys, although genetic capture–recapture methods provided much higher precision. However at the current estimated abundance (c. 200), the same level of precision achieved with aerial methods can be obtained by collecting 0.75 samples/individual in a single session, for an annual cost saving of > USD 4,000. This approach of comparing estimator performance and cost can easily be applied to other systems and is a useful evaluation for managers to implement prior to designing capture–recapture studies.

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