Spatial and taxonomic biases in bat records: Drivers and conservation implications in a megadiverse country

Drivers of systematic bias in alien plant species distribution data

Among the main challenges in modelling biological invasion is a lack of valid data on the absence of invasive species. Absence data are important for assessing the reliability of models, but multiple surveys at a location are needed. In practice, omission errors are more frequent than commission errors. We therefore quantified how eliminating potentially biased areas from invasive species distribution models (iSDMs) affected the models' performance, and we assessed how the distribution of biased areas correlated with environmental factors. We hypothesized that for neophytes, the distribution of biased areas corresponds to specific land relief and/or particular landscape and land use, but not the density of roads and urbanized areas. The data on neophytes were obtained from a distribution atlas covering approximately 31,000 km² in Central Europe overlaid with a 2 × 2 km square grid. One hundred fifty-three species were used for modelling neophyte richness, and negative residuals from the model were assumed to indicate biased squares. Twenty invasive species were used as an independent dataset for testing the effect of excluding the biased squares on iSDM performance. The exclusion of biased squares increased the iSDM performance from an area under the curve value of 0.73 to 0.78. The best results were obtained by excluding 30 % of the squares from the original dataset. The presence of damp sites explained the distribution of biased squares; the density of roads and urbanized areas had no impact. The applied method allows distinguishing biased, plausibly undersampled squares in a species distribution atlas, the exclusion of which significantly improves iSDM performance. The results suggest that the commonly observed low sampling effort in areas distant from communication routes and urbanized areas was not crucial in modelling invasive species distribution, which can be related to smaller neophyte richness in remote areas resulting from low propagule pressure.

Mapping global conservation priorities and habitat vulnerabilities for cave-dwelling bats in a changing world

Research and media attention is disproportionately focused on taxa and ecosystems perceived as charismatic, while other equally diverse systems such as caves and subterranean ecosystems are often neglected in biodiversity assessments and prioritisations. Highlighting the urgent need for protection, an especially large fraction of cave endemic species may be undescribed. Yet these more challenging systems are also vulnerable, with karsts for example losing a considerable proportion of their area each year. Bats are keystone to cave ecosystems making them potential surrogates to understand cave diversity patterns and identify conservation priorities. On a global scale, almost half (48 %) of known bat species use caves for parts of their life histories, with 32 % endemic to a single country, and 15 % currently threatened. We combined global analysis of cave bats from the IUCN spatial data with site-specific analysis of 1930 bat caves from 46 countries to develop global priorities for the conservation of the most vulnerable subterranean ecosystems. Globally, 28 % of caves showed high bat diversity and were highly threatened. The highest regional concentration of conservation priority caves was in the Palearctic and tropical regions (except the Afrotropical, which requires more intensive cave data sampling). Our results further highlight the importance of prioritising bat caves by incorporating locally collected data and optimising parameter selection (i.e., appropriate landscape features and threats). Finally, to protect and conserve these ecosystems it is crucial that we use frameworks such as this to identify priorities in species and habitat-level and map vulnerable underground habitats with the highest biodiversity and distinctiveness.