DarkCideS 1.0, a global database for bats in karsts and caves

The DarkCideS database was initially conceptualised and developed by KCT, JAG, and ACH as part of the “Global Bat Cave Vulnerability and Conservation Mapping Initiative” in 2014, and later with the “Mapping Karst Biodiversity in Yunnan” and the “Southeast Asian Atlas of Biodiversity” projects. The initiative includes developing tools and methods (e.g., the Bat Cave Vulnerability Index¹⁴) and synthesis (e.g., the global bat cave vulnerability assessment¹¹) to identify conservation priorities and important bat caves in the tropics. Since 2019, the initiative has expanded and potential collaborators and contributors were invited through scientific conferences (Association for Tropical Biology and Conservation 2018, International Bat Research Conference 2019), social media platforms, and personal correspondences. At present, the database has 36 collaborators from twenty countries on six continents with expertise and research interests in bat conservation. Four main datasets for all known cave-dwelling bats were built for the DarkCideS database version 1.0.

Datasets and compilation for species checklist

The first dataset contains taxonomic checklists for all extant cave-dwelling bats species extracted from the expert-based International Union for the Conservation Union (IUCN) Red List database version 2020-1 (Table 1). We screened and included all bat species that were reported to use, roost in, or aggregate in “Caves”, “Underground”, and “Karsts” habitats in any part of their life histories. We also scanned major publicly available bat cave databases from expeditions such as “Bats in China” (http://www.bio.bris.ac.uk/research/bats/China/) and UNEP-EUROBATS (https://www.eurobats.org/) for European bats²⁴ for additional information and datasets. In addition, the first dataset contains species ecological traits, distribution range, and threatening processes (Table 1).

Information per species was pooled from the IUCN Red List versions 2020-1²⁵. Species taxonomy was then curated and updated (e.g., synonyms or merged species) using the nomenclature from Simmons and Cirranello¹². The “checklist for global cave-dwelling bats” derived from the IUCN Red List includes 679 species. Meanwhile, the DarkCideS 1.0 dataset contains occurrence data for 402 species from 16 families representing 59% of all cave-dwelling species¹¹ (Fig. 2). We found a marginally significant relationship between the species richness and proportion of threatened species between the IUCN-based global cave-dwelling bat and DarkCideS datasets (Kendall’s τ b = 0.60, P = 0.07). The highest completeness of sampled species is in the Neotropics (67.38%) and Indomalayan region (66.08%), and the greatest gaps are in Austral-Oceania (40.28%). Highest endemism was recorded in Austral-Oceania (58.62%) (χ² = 227.32, df = 5, P < 0.001) (Fig. 2a). The proportion of threatened species is highest in the Indomalayan region (16%) realm (χ² = 281.18, df = 5, P < 0.01) (Fig. 2a). Most bat families have a coverage of 30 to 60% of species, but four families had all cave-dwelling species in the DarkCideS database, and three smaller families had no species included (Fig. 2b).

Habitat preference, distribution, ecological status, and traits

We classified species distribution by biogeographical realm (Indomalaya, Austral-Oceania, Afrotropical, Neotropical, Palearctic, and Nearctic) and terrestrial biomes following Olson et al.²⁶. We described species’ major habitat breadth based on IUCN Level 1 classification https://www.iucnredlist.org/resources/habitat-classification-scheme (Caves, Forests, Savanna, Desert, Urban, Artificial, and Wetlands). Species current conservation status (Data Deficient, Least Concern, Near Threatened, Vulnerable, Endangered, and Critically Endangered) and population trends (e.g., Unknown, Decreasing, Stable, Increasing) were categorised using standard IUCN Red List assessments. Using the same criteria, we categorised species endemism as geopolitically endemic (e.g., country-endemic, and non-endemic) when a species occurs only in a single country or state territory²⁷, and island endemism was classified as island-restricted or predominantly mainland²⁸. The highest country endemism was in the Eastern Hemisphere with the highest in the Austral-Oceania (40%) region, followed by the Afrotropical (21%), then the Indomalayan region (16%). However, the highest proportion of threatened species was in the Indomalayan region (43%) and the Neotropics (22%) (Fig. 2a).

Furthermore, current geographical ranges were assembled from the Phylacine 1.2 database²⁸ based on IUCN species ranges. Three species traits were included: the adult body mass (in grams) per species were derived from Phylacine 1.2²⁸ and generation length from Pacifici et al.²⁹. For trophic groups, we derived diet information from EltonTraits 1.0³⁰. We grouped species as frugi-nectarivorous for all species that forage on plant-based resources (e.g., fruits, leaves, and nectars). As species foraging smaller vertebrates (i.e., fish, birds, and rodents) and larger invertebrates are very few, we classified them as carnivores along with insectivorous bats. Species that forage on both resources were grouped into omnivores (Table 1).

Species threatening process

We identified potential threats for each bat species listed in the checklist using the information from the IUCN Red List assessments (version 2020-1) in addition to threats highlighted in the literature. The IUCN Red List standardised its classification based on Salafsky et al.³¹, but we reclassified the threatening process into three key categories: Direct, Indirect, and Natural (Table 1) based on the drivers of threat^10,14,32. Direct threats (T_dir) refer to the threats or risks that are direct to or in cave systems with immediate and perceivable impacts on populations or behaviour of species. This category includes direct human impacts (e.g., persecution, eviction, and cave closures) and the use of caves for harvesting bats, tourism, religious visits, and mining (minerals or guano). Indirect threats (T_ind) refer to the threats outside cave systems or within cave proximity, of which the impacts to populations are secondary or non-immediate but otherwise detrimental. Examples include deforestation, agriculture, and urbanisation. Lastly, Natural threats (T_nat) refer to threats that are natural in origin, though their frequency may be impacted by human activities, and that may directly or indirectly impact populations, such as diseases (e.g., White-nose syndrome) and climate-driven risks (e.g., drought, extreme cold) (Table 1).

Bat cave georeferencing

The second dataset contains the bat cave geographical location (latitude/longitude) and recorded species (Table 2, Fig. 3a). We used the Web of Science and Google Scholar to search online literature, databases, and repositories for published information on cave-dwelling bats from 1990 to 2021. We used the following combination of keywords: (Bat* OR Chiroptera OR Chiroptera fauna*) AND (Diversity OR “Species richness” OR abundance OR distribution OR conservation OR ecology) AND (Cave* OR Cave-dwelling OR Cave-roosting OR underground* OR subterranean OR karst* OR Limestone). We also set a “create alert” in Google Scholar whenever new related papers were published. The data mining process for version 1.0 ended in June 2021. Our search returned 753 papers. We also searched using the Baidu Research engine for Chinese literature and self-archived ResearchGate to maximise search results. To ensure the precision of the datasets included in DarkCideS 1.0, we filtered all published literature to only include those papers or reports with complete species names and geographical records. We contacted corresponding authors with requests to provide us with geographical data when these were missing from their papers or supplementary materials. In the circumstance that we were unable to find the data, and the corresponding author did not respond to our request, that “cave site” was excluded from the database. We converted all species and cave latitude and longitude into WG8 84 decimal degrees with five significant figures. The second dataset of DarkCideS 1.0 contains 6746 georeferenced occurrences for 402 species¹¹ from 2002 cave sites (Fig. 3a). Cave sites occur in all continents except Antarctica, with most of the data originating from tropical and temperate biomes (Fig. 3b). We have cave records from 46 countries of which China and Brazil have the highest number of caves recorded (Fig. 3c).

Cave landscape features and vulnerabilities

The condition of surface ecosystems and the extent of threats are significant determinants of cave-dwelling bat diversity¹¹. Yet, standardising the vulnerability of caves and underground ecosystems from threats on a global scale is challenging^11,14. To address this, the surface ecosystem was mapped as a proxy to assay cave vulnerability to threats using remotely sensed landscape features. The third dataset included in the database contains the measured land-use and landscape features of the cave surroundings using the georeferenced data from the second dataset (Table 3; Fig. 4). The selected landscape features measurements of the 2002 cave sites were selected based on Tanalgo et al.¹¹. We included the estimated distance and measures of twelve landscape variables in the database, including canopy cover height³³, tree density³⁴, distance to freshwater bodies³⁵, bare ground cover change³⁶, short vegetation cover change³⁶, tall tree cover change³⁶, for vulnerabilities we included distance to urban areas³⁶, distance to roads³⁷, mine density³⁸, night light³⁹, relative pesticide exposure⁴⁰, and population density^41,42. For distance variables, the “distance to feature” tool was used in ArcMap 10.3 and distances were mapped at a 1-km resolution.

Cave bat parasites and hyperparasites

Parasites, while being among the most diverse modes of life, are often disregarded in conservation strategies⁴³. It is well established that parasites affect the stability of food webs and ecosystem health, but hyperparasites have thus far been severely understudied. For future studies on host associations across multiple trophic levels and on the effects of climatic conditions and land-use changes, parasites and hyperparasites are part of our DarkCideS 1.0 database. The fourth dataset lists the parasitic bat flies and their Laboulbeniales fungal hyperparasites associated with cave bats. Data were collected from several sources, including our fieldwork data³⁶, Haelewaters et al.⁴⁴, and de Groot et al.⁴⁵. Bat fly taxonomy followed Dick and Graciolli⁴⁶ and Graciolli and Dick⁴⁷ and fungal taxonomy followed Index Fungorum⁴⁸. In addition to the conspicuous bat flies, bats are host to several other lineages of parasites mites and ticks, lice, fleas, bugs, and earwigs^49,50. Consequently, the fourth dataset will be expanded on in future versions of DarkCideS with data on these parasitic organisms. A recent call for global collaborations among bat scientists and collaborations to generate multitrophic data of bats, bat flies, and fungi⁵⁰ along with the current DarkCideS 1.0 initiative will contribute to a general understanding of how ecological and life-history traits are correlated with bat parasitism and how host associations may change under changing conditions.

Source: Ecology - nature.com