“…As Chinese pangolins are nocturnal and elusive (DNPWC & DoF, 2018), occupancy estimates of pangolins based on direct observation are difficult (Willcox et al, 2019). We found that using an indirect sign survey was suitable for estimating the occupancy of Chinese pangolin to address the problem of inadequate direct sightings.…”
Chinese pangolin is the world's most heavily trafficked small mammal for luxury food and traditional medicine. Although their populations are declining worldwide, it is difficult to monitor their population status because of its rarity and nocturnal behavior. We used site occupancy (presence/absence) sampling of pangolin sign (i.e., active burrows) in a protected (Gaurishankar Conservation Area) and non‐protected area (Ramechhap District) of central Nepal with multiple environmental covariates to understand factors that may influence occupancy of Chinese pangolin. The average Chinese pangolin occupancy and detection probabilities were
trueΨ^
± SE = 0.77 ± 0.08;
truep^
± SE = 0.27 ± 0.05, respectively. The detection probabilities of Chinese pangolin were higher in PA (
truep^
± SE = 0.33 ± 0.03) than compared to non‐PA (
truep^
± SE = 0.25 ± 0.04). The most important covariates for Chinese pangolin detectability were red soil (97%), food source (97.6%), distance to road (97.9%), and protected area (97%) and with respect to occupancy was elevation (97.9%). We recommended use of remote cameras and potentially GPS collar surveys to further investigate habitat use and site occupancy at regular intervals to provide more reliable conservation assessments.
“…As Chinese pangolins are nocturnal and elusive (DNPWC & DoF, 2018), occupancy estimates of pangolins based on direct observation are difficult (Willcox et al, 2019). We found that using an indirect sign survey was suitable for estimating the occupancy of Chinese pangolin to address the problem of inadequate direct sightings.…”
Chinese pangolin is the world's most heavily trafficked small mammal for luxury food and traditional medicine. Although their populations are declining worldwide, it is difficult to monitor their population status because of its rarity and nocturnal behavior. We used site occupancy (presence/absence) sampling of pangolin sign (i.e., active burrows) in a protected (Gaurishankar Conservation Area) and non‐protected area (Ramechhap District) of central Nepal with multiple environmental covariates to understand factors that may influence occupancy of Chinese pangolin. The average Chinese pangolin occupancy and detection probabilities were
trueΨ^
± SE = 0.77 ± 0.08;
truep^
± SE = 0.27 ± 0.05, respectively. The detection probabilities of Chinese pangolin were higher in PA (
truep^
± SE = 0.33 ± 0.03) than compared to non‐PA (
truep^
± SE = 0.25 ± 0.04). The most important covariates for Chinese pangolin detectability were red soil (97%), food source (97.6%), distance to road (97.9%), and protected area (97%) and with respect to occupancy was elevation (97.9%). We recommended use of remote cameras and potentially GPS collar surveys to further investigate habitat use and site occupancy at regular intervals to provide more reliable conservation assessments.
“…Pangolins (Pholidota: Manidae) are among the most trafficked mammals in the world (Challender et al , Ingram et al , ). Unfortunately, pangolins are also difficult to study in the wild because they are shy and predominately nocturnal (Willcox et al , ), so surprisingly little is known about their basic biology. Much of the limited information we do have about longevity, gestation, reproductive output, etc., comes from captive individuals (Hua et al , ).…”
Conservation of rare and declining species requires reliable information about life‐history traits and population growth characteristics. Unfortunately, long‐term studies necessary to obtain such data are often difficult or impossible for species of concern. In such cases, data that can be collected during limited capture events can serve as valuable proxies. We measured metabolic characteristics of Temminck’s ground pangolin Smutsia temminckii because metabolic traits provide clues about relative gestation length, reproductive output and population growth, all of which were largely unknown for this species. As expected, both basal and field metabolic rates are considerably lower than would be predicted from body mass alone, suggesting pangolins are likely to have slow life histories and low intrinsic population growth. Such characteristics suggest Temminck’s ground pangolins (and likely all pangolins) are less able to persist under heavy poaching and trafficking than other similarly sized mammals and will likely recover slowly even if poaching and trafficking are stopped. While physiological data cannot be used to directly calculate population growth rates, we believe they may provide a tangible data source to inform management decisions for critically endangered, difficult‐to‐study species.
Accurate morphological description of species has essential implications in field identification and cladistics. Pangolins (Mammalia: Pholidota) are considered the world's most trafficked mammals. The Indian pangolin has a wide geographical distribution in the Indian subcontinent. However, morphoanatomical variations of
M. crassicaudata
across its range are poorly understood. The published morphoanatomical descriptions have disparities, partly due to the lack of standard protocols and procedures in morphometric data collection and reporting, thus making comparisons among different records less meaningful. This Method Article presents protocols and procedures to follow in morphometric data collection and reporting for
M. Crassicaudata.
Morphometric parameters can be measured and reported under three age classes; juvenile, sub-adult, and adult, as well as the sex to describe the species' sexual dimorphism. The proposed protocol includes 13 morphometric measurements of a pangolin body. Procedures to count and report the number of body scales with special reference to the body region of a pangolin and scale morph-type are described. Morphometry of the claws of forelimbs is described using the Curvature Linear Index
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