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

Abstract

Biases in data availability have serious consequences on scientific inferences that can be derived. The potential consequences of these biases could be more detrimental in the less‐studied megadiverse regions, often characterized by high biodiversity and serious risks of human threats, as conservation and management actions could be misdirected. Here, focusing on 134 bat species in Mexico, we analyze spatial and taxonomic biases and their drivers in occurrence data; and identify priority areas for further data collection which are currently under‐sampled or at future environmental risk. We collated a comprehensive database of 26,192 presence‐only bat records in Mexico to characterize taxonomic and spatial biases and relate them to species' characteristics (range size and foraging behavior). Next, we examined variables related to accessibility, species richness and security to explain the spatial patterns in occurrence records. Finally, we compared the spatial distributions of existing data and future threats to these species to highlight those regions that are likely to experience an increased level of threats but are currently under‐surveyed. We found taxonomic biases, where species with wider geographical ranges and narrow‐space foragers (species easily captured with traditional methods), had more occurrence data. There was a significant oversampling toward tropical regions, and the presence and number of records was positively associated with areas of high topographic heterogeneity, road density, urban, and protected areas, and negatively associated with areas which were predicted to have future increases in temperature and precipitation. Sampling efforts for Mexican bats appear to have focused disproportionately on easily captured species, tropical regions, areas of high species richness and security; leading to under‐sampling in areas of high future threats. These biases could substantially influence the assessment of current status of, and future anthropogenic impacts on, this diverse species group in a tropical megadiverse country.

Developing a database of Australian grasshopper occurrences from historic field survey notebooks spanning 54 years (Orthoptera: Acrididae, Morabidae, Pyrgomorphidae, Tetrigidae)

“…For the latter bias type, we assessed sampling effort relative to bioregions (Ebach 2012) as defined by the Interim Biogeographic Regionalization for Australia (version 7, retrieved from: http://www.environment.gov.au/fed/catalog/search/resource/downloadData.page?uuid=%7B8B9E3F42-9856-4487-AE9E-C76A322809A1%7D). To quantify bias towards a bioregion, we used the following equation developed by Kadmon et al (2004), also illustrated in Zamora‐Gutierrez et al (2019). Here, is the number of grid cells with survey locations in the bioregion , is the proportion of grid cells in the focal area that fall in bioregion , and is the total number of sampled grid cells ( = 1148 for WA and = 166 for Tasmania).…”

Developing global vulnerabilities and conservation priorities for cave-dwelling bats

“…The inclusion of these measures enables prioritisation of cave ecosystems with rare and higher functional diversity attributes 67,68 complimenting the metrics based on geopolitical endemism and conservation status from IUCN [68][69][70] which are commonly used within prioritisation schemes. While the expert-based Redlist developed by the IUCN is the most comprehensive basis for conservation and species protection, it is not free from biases [71][72][73] , especially for bats, in which a large proportion of species are either taxonomically and spatially under-sampled or disproportionately studied particularly in most megadiverse and developing countries 74 . Overall, our observed patterns are consistent with previous global studies comparing the value of broad-and fine-scale analyses in identifying priorities.…”

“…This is particularly challenging to pinpoint in the context of cave biota, in which even a single disturbance may alter the entire sensitive biota and ecosystems, and as such events cannot be identified vulnerability (e.g accessibility) must be used as an indicator 31,50,77 . Furthermore, the degree of expertise required for bat and cave studies means less data is available compared to other taxonomic groups 74,78 . For instance, in our cave prioritisation, we only accounted the 59% of the global cave-dwelling species, and species coverage varied by region, for example, Indonesia has some of the highest estimated bat cave species richness yet its contribution to the dataset based on surveys and assessments is among the lowest.…”

Using bats as surrogates to effectively target global hotspots for subterranean conservation and monitoring

“…The inclusion of these measures enables prioritisation of cave habitats with rare and higher functional diversity attributes (Jetz et al, 2014;Srivastava et al, 2012) complimenting the metrics based on geopolitical endemism and conservation status from IUCN (Isaac et al, 2007;Jetz et al, 2014;Martín-López et al, 2009) which are commonly used within prioritisation schemes. While the expert-based Red list developed by the IUCN is the most comprehensive basis for conservation and species protection, it is not free from biases (Hughes et al, 2021;Martín-López et al, 2011;Trimble and Aarde, 2010), especially for bats, in which a large proportion of species are either taxonomically and spatially under-sampled particularly in most megadiverse and developing countries (Zamora-Gutierrez et al, 2019).…”

“…accessibility) must be used as indicators (Cajaiba et al, 2021;De Oliveira et al, 2018;Phelps et al, 2018). Furthermore, the degree of expertise required for bat and cave studies means less data is available compared to other taxonomic groups (Herkt et al, 2017;Zamora-Gutierrez et al, 2019). For instance, in our cave prioritisation, we only accounted the 59% of the global cave-dwelling species, and species coverage varied by region, for example, Indonesia has some of the highest estimated bat cave species richness yet its contribution to the dataset based on surveys and assessments is among the lowest.…”