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Spatial patterns of biodiversity are inextricably linked to their collection methods, yet no synthesis of bias patterns or their consequences exists. As such, views of organismal distribution and the ecosystems they make up may be incorrect, undermining countless ecological and evolutionary studies. Using 742 million records of 374 900 species, we explore the global patterns and impacts of biases related to taxonomy, accessibility, ecotype and data type across terrestrial and marine systems. Pervasive sampling and observation biases exist across animals, with only 6.74% of the globe sampled, and disproportionately poor tropical sampling. High elevations and deep seas are particularly unknown. Over 50% of records in most groups account for under 2% of species and citizen‐science only exacerbates biases. Additional data will be needed to overcome many of these biases, but we must increasingly value data publication to bridge this gap and better represent species' distributions from more distant and inaccessible areas, and provide the necessary basis for conservation and management. [ABSTRACT FROM AUTHOR]

Aim: The aim was to understand the representativeness and accuracy of expert range maps and to explore alternative methods for mapping species distributions accurately. Location: Global. Time period: Contemporary. Major taxa studied: Terrestrial vertebrates and Odonata. Methods: We analysed the biases in 50,768 animal International Union for Conservation of Nature, Global Assessment of Reptile Distributions and BirdLife species maps and assessed the links between these maps and existing political boundaries and various non‐ecological boundaries to assess their accuracy for certain types of analyses. We cross‐referenced each species map with data from the Global Biodiversity Information Facility to assess whether maps captured the whole range of a species and what percentage of occurrence points fell within the assessed range of the species. In addition, we used a number of different methods to map diversity patterns and compared these with high‐resolution models of distribution patterns. Results: On average, 20–30% of the non‐coastal range boundaries of species overlapped with administrative national boundaries. In total, 60% of areas with the highest spatial turnover in species (high densities of species range boundaries marking high levels of shift in the community of species present) occurred at political boundaries, which was especially common in Southeast Asia. Different biases existed for different taxa, with gridded analysis in reptiles, river basins in Odonata (except the Americas) and county boundaries for amphibians in the USA. On average, up to half (25–46%) of the recorded range points of species fell outside their mapped distributions. Filtered minimum convex polygons performed better than expert range maps in reproducing modelled diversity patterns. Main conclusions: Expert range maps showed high bias at administrative borders in all taxa, but this was highest at the transition from tropical to subtropical regions. The methods used were inconsistent across space, time and taxa, and the ranges mapped did not match species distribution data. Alternative approaches can reconstruct patterns of distribution better than expert maps, and data‐driven approaches are needed to provide reliable alternatives to gain a better understanding of species distributions. [ABSTRACT FROM AUTHOR]

Understanding patterns of species distribution and diversity plays a vital role in biodiversity conservation. Such documentation is frequently lacking for bats, which are relatively little studied and often threatened. The Western Ghats biodiversity hotspot in peninsular India is a bat hotspot with 63 species. We conducted a comprehensive bat survey across the southern Western Ghats and used maximum entropy modeling (MaxEnt) to model the potential distribution of 37 bat species for which sufficient data were available. We generated binary maps of each species using species-specific thresholds to estimate suitable habitat areas and overlaid binary maps of species to produce bat hotspots (we use the term "bat hotspot" for regions that were suitable for more than 25 bat species). We also estimated species richness across protected area networks in the southern Western Ghats to assess the level of protection. The highest levels of species richness were found mainly along the southmost Periyar–Agastyamalai landscape. The study also identified a 1,683 km2 area of potential bat hotspot and 726 km2 (43%) of the total bat hotspots are currently within the protected area network. However, more than 50% of suitable habitats for each of the 37 species remain unprotected. Therefore, conservation decisions are needed to take into account both bat hotspots and species with restricted distributions. [ABSTRACT FROM AUTHOR]

Wildlife trade is a major driver of biodiversity loss, yet whilst the impacts of trade in some species are relatively well-known, some taxa, such as many invertebrates are often overlooked. Here we explore global patterns of trade in the arachnids, and detected 1,264 species from 66 families and 371 genera in trade. Trade in these groups exceeds millions of individuals, with 67% coming directly from the wild, and up to 99% of individuals in some genera. For popular taxa, such as tarantulas up to 50% are in trade, including 25% of species described since 2000. CITES only covers 30 (2%) of the species potentially traded. We mapped the percentage and number of species native to each country in trade. To enable sustainable trade, better data on species distributions and better conservation status assessments are needed. The disparity between trade data sources highlights the need to expand monitoring if impacts on wild populations are to be accurately gauged and the impacts of trade minimised. Trade in arachnids includes millions of individuals and over 1264 species, with over 70% of individuals coming from the wild. [ABSTRACT FROM AUTHOR]