Accurately estimating large mammal populations is a difficult challenge because species of interest often occupy vast areas and exhibit low and heterogeneous visibility. Population estimation techniques using aerial surveys and statistical design and analysis methods provide a means for meeting this challenge, yet they have only rarely been validated because wild populations of known size suitable for field tests are rare. Our study presents field validations of a photographic aerial mark–recapture technique that takes advantage of the recognizable natural markings on free-roaming feral horses (Equus caballus) to accurately identify individual animals and groups of animals sighted on multiple occasions. The 3 small populations of feral horses (<400 animals each) in the western United States used in the study were all closely monitored on a weekly basis by local researchers, thus providing test populations of known size. We were able to accurately estimate these population sizes with aerial surveys, despite rugged terrain and dense vegetation that created substantial heterogeneity of sighting probability among horse groups. Our best estimates at the 3 sites were within −6.7%, 2.6%, and −8.6% of known truth (−4.2% mean error, 6.0% mean absolute error). In contrast, we found undercount bias as large as 32% before any statistical corrections. The necessary corrections varied both temporally and spatially, in response to previous sighting history (behavioral response), and by the number of horses in a group. Despite modeling some of the differences in horse-group visibility with sighting covariates, we found substantial residual unmodeled heterogeneity that contributed to underestimation of the true population by as much as 22.7% when we used models that did not fully account for these unmeasured sources. We also found that the cost of the accurate and validated methods presented here is comparable to that of raw count (so called, census) methods commonly employed across feral horse ranges in 10 western states. We believe this technique can assist managers in accurately estimating many feral horse populations and could be applied to other species with sufficiently diverse and distinguishable visible markings.
You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither BioOne nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the BioOne website.
Vol. 73 • No. 8