Multiple methods increase detection of large and medium-sized mammals: working with volunteers in south-eastern Oman

• Published in: Oryx
• Main Authors: Mazzolli, Marcelo, Haag, Taiana, Lippert, Beatriz G., Eizirik, Eduardo, Hammer, Matthias L.A., Al Hikmani, Khalid
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press (CUP) 2016
• Subjects: Canis lupus
• Online Access: http://dx.doi.org/10.1017/s0030605315001003; https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0030605315001003

Abstract We compared the effectiveness of various methods for surveying medium and large wild mammals in southern Oman. Working with volunteers recruited by Biosphere Expeditions, wildlife professionals and local rangers, we used direct observation, camera traps, sign surveys (tracks and/or dung) and molecular scatology to study 66 sampling units of 2 × 2 km (grid cells) in an area of 32 × 36 km during a 4-week period in February–March 2011. Sixteen mammal species were recorded, and the largest numbers of species were recorded by sign surveys and camera traps (both n = 9); sign surveys, direct sightings and DNA scatology recorded species across the largest number of grid cells. For species with a sample size large enough for comparison (i.e. detected in ≥ 8 grid cells), DNA scatology proved most effective for detecting caracal Caracal caracal , signs for hyaena Hyaena hyaena , ibex Capra nubiana , porcupine Hystrix indica and hyrax Procavia capensis , and signs and direct sightings for mountain gazelle Gazella gazella . Clustering, in which records from multiple methods are either adjacent or overlapping, was highest (≥ 76%) for the wolf Canis lupus , porcupine, ibex and gazelle. Our results indicate the best methods to detect and record the distributions of individual species in the study area, and demonstrate the advantage of using multiple methods to reduce the risk of false absences or partial detections. Our findings also highlight the potential of clustering as a means of cross-checking results of observations that are skill-dependent, which is particularly useful when employing a large workforce.