Abstract
Pangolins, often considered the world’s most trafficked wild mammals, have continued to experience rapid declines across Asia and Africa. All eight species are classed as either Vulnerable, Endangered or Critically Endangered by the International Union for Conservation of Nature (IUCN) Red List. Alongside habitat loss, they are threatened mainly by poaching and/or legal hunting to meet the growing consumer demand for their meat and keratinous scales. Species threat assessments heavily rely on changes in species distributions which are usually expensive and difficult to monitor, especially for rare and cryptic species like pangolins. Furthermore, recent assessments of the threats to pangolins focus on characterising their trade using seizure data which provide limited insights into the true extent of global pangolin declines. As the consequences of habitat modifications and poaching/hunting on species continues to become apparent, it is crucial that we frequently update our understanding of how species distributions change through time to allow effective identification of geographic regions that are in need of urgent conservation actions. Here we show how georeferencing pangolin specimens from natural history collections can reveal how their distributions are changing over time, by comparing overlap between specimen localities and current area of habitat maps derived from IUCN range maps. We found significant correlations in percentage area overlap between species, continent, IUCN Red List status and collection year, but not ecology (terrestrial or arboreal/semi-arboreal). Human population density (widely considered to be an indication of trafficking pressure) and changes in primary forest cover, were weakly correlated with percentage overlap. Our results do not suggest a single mechanism for differences among historical distributions and present-day ranges, but rather show that multiple explanatory factors must be considered when researching pangolin population declines as variations among species influence range fluctuations. We also demonstrate how natural history collections can provide temporal information on distributions and discuss the limitations of collecting and using historical data.
Highlights
Pangolins (Pholidota: Manidae) are insectivorous mammals found in parts of Africa and Asia (Hua et al, 2015)
They are considered the world’s most trafficked wild mammal due to significant consumer demand for their scales and meat (Challender, Harrop & MacMillan, 2015; Cheng, Xing & Bonebrake, 2017). Both African and Asian species have locally been traded for consumption, but as local population levels have declined in parts of Asia (Irshad et al, 2015; Challender, Nash & Waterman, 2020; Wu et al, 2004), researchers have documented a shift in demand from Asia for African pangolins (Challender, Harrop & MacMillan, 2015; Heinrich et al, 2016) which is believed to be the leading cause of declines in African pangolin populations (IUCN, 2020)
When modelling the number of localities overlapping with species area of habitat (AOH) and those that did not overlap as a binomial response, we found a significant correlation with ecology
Summary
Pangolins (Pholidota: Manidae) are insectivorous mammals found in parts of Africa and Asia (Hua et al, 2015) They are considered the world’s most trafficked wild mammal due to significant consumer demand for their scales and meat (Challender, Harrop & MacMillan, 2015; Cheng, Xing & Bonebrake, 2017). Both African and Asian species have locally been traded for consumption, but as local population levels have declined in parts of Asia (Irshad et al, 2015; Challender, Nash & Waterman, 2020; Wu et al, 2004), researchers have documented a shift in demand from Asia for African pangolins (Challender, Harrop & MacMillan, 2015; Heinrich et al, 2016) which is believed to be the leading cause of declines in African pangolin populations (IUCN, 2020). Understanding how pangolin distributions have changed in the past decades will provide more insights into their possible population declines and inform science-based conservation actions
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