Using species distribution models to gauge the completeness of the bat checklist of Eswatini

Abstract

National species checklists are important for a variety of reasons, including biodiversity conservation. However, these national checklists are rarely complete, and it is not easy to gauge how many species have been overlooked or what the taxonomic identities of overlooked species would be. This is particularly the case for small, elusive, or nocturnal species such as bats. Despite their diversity and importance as ecosystem service providers, bat distributions are poorly known throughout much of Africa. We present a national checklist of bats for a small African country, Eswatini, by compiling species from museum specimens and literature records. A total of 32 species of bats have been recorded from the country. Since 1995, new species have continued to be 1 recorded in the country, with five additional species added since the last published checklist in 2016, suggesting that some species may have still been overlooked. In order to determine what species these may be, we used species distribution models based on the occurrence records of bats from southern Africa to predict what species would occur in Eswatini, which was then compared with what has been collected and deposited in museums. Our models predicted that a total of 47 species are likely to occur in Eswatini compared with 32 species collected to date. Our data suggest that the national checklist of bats of Eswatini is not yet complete and that further species are expected to be recorded for the country. We suggest that species distribution models can be useful in gauging the completeness of national checklists and in predicting which species may have been overlooked.

Metagenomic Analysis Reveals Previously Undescribed Bat Coronavirus Strains in Eswatini

“…Therefore, we investigated the prevalence of coronaviruses in bats belonging to eight species from four families (Pteropodidae: Epomophorus wahlbergi ; Emballonuridae: Taphozous mauritianus ; Molossidae: Chaerephon pumilus , Mops condylurus , and Mops midas ; and Vespertilionidae: Afronycteris nana , Scotophilus dinganii , and Scotophilus viridis ). These species are all widely distributed and abundant across southeastern Africa and are commonly found in or near human settlements in northeast Eswatini (Monadjem et al 2020b , 2021 ; Shapiro et al 2020 ). We subjected fecal samples to virion enrichment followed by RNA sequencing to noninvasively investigate the prevalence and types of coronavirus in the bats of this region.…”

Testing the efficacy of bat monitoring methods for identification and species surveys in KwaZulu-Natal province, South Africa

“…These results support the notion that neither capture-based nor acoustic surveying techniques alone provide a complete estimate of bat species richness of an area and both methods are required to ensure maximum sampling efficiency (Lintott et al 2013; Taylor et al 2013). It is suggested that historical museum records be collated to model potential species distributions before any active sampling to best adapt assessment and identification methods, selection of sampling sites and seasons to the potential species present (Monadjem et al 2021a). This could facilitate targeted roost searches which should be included in future studies as they yielded the highest numbers of species detections compared to active and passive sampling by Flaquer et al (2007).…”

“…These collections have played an important role in the process of mapping species distributions in the past. There has been a recent revival and increased use of these historic natural history databases for species distribution models (SDMs), which is a widely applied, remote mapping tool that uses occurrence data with bioclimatic and environmental variables for predictive modelling of geographic distributions of species (Anderson and Gonzalez 2011; Bradley et al 2014; Monadjem et al 2021a). This remote estimation of species distributions based on natural history museum records may best inform the species predicted to be present at a site, and hence the potential sampling sites to aim for during surveys and monitoring assessments (Smeraldo et al 2018; Monadjem et al 2021a).…”

Assessing habitat connectivity of rare species to inform urban conservation planning

“…We used a 10 km buffer for background point selection (10,000 random points) for all species except Henslow's Sparrow and Northern Long‐Eared Bat, which had a 25 km buffer. The background point selection for presence only models should represent accessible area for the modeled species and, despite the low to moderate dispersal distances, we believe that the broader extent buffers are a better match to the scale of habitat selection for these volant species (Gómez‐Ruiz & Lacher, 2016 ; Monadjem et al., 2021 ; Virkkala et al., 2022 ; Zhang et al., 2018 ). These buffered regions served as the area for background point selection in all models.…”