Tools and Technology Article Validating Aerial Photographic Mark–Recapture for Naturally Marked Feral Horses BRUCE C. LUBOW, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA JASON I. RANSOM, 1 United States Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, CO 80526, USA ABSTRACT 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 26.7%, 2.6%, and 28.6% of known truth (24.2% 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. (JOURNAL OF WILDLIFE MANAGEMENT 73(8):1420–1429; 2009) DOI: 10.2193/2008-538 KEY WORDS aerial survey, Equus caballus, feral horse, heterogeneity, mark–recapture, population estimation, sighting probability, validation. Accurately estimating population sizes of large free-roaming animals is a challenging and critical task for successful wildlife management (Williams et al. 2002), yet up to one third of ungulates in the western United States are missed by standard visual aerial surveys (Samuel et al. 1987, Ackerman 1988, Singer and Garton 1994, Bodie et al. 1995, Bowden and Kufeld 1995). Visibility of ungulates can vary tremendously among survey sites and occasions, depending upon transect spacing and sighting factors such as snow cover, group size, activity of the animals, tree cover, and experience of the observers (Pollock and Kendall 1987, Samuel et al. 1987, Unsworth et al. 1994, Bodie et al. 1995, Lubow and Ransom 2007). Despite these well-known biases that result in variable and unknown degrees of undercount- ing, the use of so-called census methods that make the unjustified assumption of 100% sighting probability remains commonplace (Rabe et al. 2002), while published evalua- tions of population estimation methods for feral horses (Equus caballus) are rare. Modern survey methods based on statistical models have been applied in Australia (Bayliss and Yeomans 1989, Graham and Bell 1989, Walter and Hone 2003, Laake et al. 2008), and recently Lubow and Ransom (2007) applied a technique to a North American feral horse population. All of these studies employed the simultaneous double-count method of mark–recapture and were limited by incorporating only 2 occasions (mark and recapture sightings), making testing for and correcting of biases due to unmodeled heterogeneity impossible. Furthermore, none of these prior studies was able to validate the methods in a population of accurately known size. Our study focuses on a form of mark–recapture sampling technique that adjusts for sightability bias similar to a sightability bias correction model. Mark–recapture methods do not necessarily require physically capturing animals, only that individual animals or coherent groups can be reliably identified by natural or artificial marks or other unique characteristics on L 2 occasions; individual capture histories can thus be recorded and used to estimate the number of unobserved animals (Seber 1973; Huggins 1989, 1991; Neal et al. 1993; Pledger 2000). Repeated observations can be made simultaneously by multiple observers or at different times. Sighting heterogeneity among individual animals or groups is common; some groups, due to their size, distance, coloration, location within cover, or other factors, are easier or more difficult for observers to see (Pollock and Kendall 1987). Unless heterogeneity is measured and modeled to correct for these differences, the unmodeled heterogeneity will result in underestimating population size (Borchers et al. 2006, Laake et al. 2008). There are 2 fundamental approaches to modeling heterogeneity, which we refer to as explicit and implicit. The more intuitive explicit method is to record a set of covariates that can be used to explicitly model the differing sighting probabilities of different animals or groups (Samuel et al. 1987). The alternative method requires more sighting occasions (typically .4) and estimates heterogeneity implicitly from the distribution of 1 E-mail: ransomj@usgs.gov 1420 The Journal of Wildlife Management N 73(8)