Direct counts underestimate mountain ungulate population size

crossref(2024)

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摘要
Abstract The topography of mountain habitats limits the accuracy of methods to assess the population size of mountain ungulates. This fact hampers decision-making for monitoring and conservation purposes and thus any attempt to evaluate the precision in known-size populations is more than welcome. In this work, we tested the accuracy of direct counts and distance sampling to assess the size of an Iberian ibex (Capra pyrenaica) flock of known size. We evaluated the influence of observer expertise (beginners and experts) on the detection error of female and male ibexes and whether the training of observers contributes to boosting the accuracy of density estimates. The ibex flock was comprised of 18 individuals (9 males, 8 females, and a male yearling) living in a 17 ha enclosure with natural Mediterranean vegetation in the National Game Reserve of Els Ports de Tortosa i Beseit, northeast Spain. After 27 surveys, experts detected 16% more ibexes than beginners. Male ibexes were ~ 13% easier to detect than females, and experts were more accurate than beginners in sexing. Additionally, the detection error in absolute counts was quite similar among beginners, but different among experts (> 10%). Despite the reduction in detection error over increasing effort scenarios, under-detection was greater than 50% in all events (> 85% for beginners and > 67% for experts). This study suggests the systematic underestimation of direct counts and density estimates of mountain ungulate populations in Mediterranean landscapes and the contribution of expertise to the improvement of the direct observation method. Our results show that wildlife managers assessing mountain ungulate populations for managing purposes should consider completing direct counts with alternative methods to minimize this systematic underestimation. Furthermore, surveys of the impact of infectious diseases on ungulate populations by direct observations may also result in the underestimation of the disease's impact on the host population.
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