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Our knowledge of biodiversity hinges on sufficient data, reliable methods, and realistic models. Without an accurate assessment of species distributions, we cannot effectively target and stem biodiversity loss. Species range maps are the foundation of such efforts, but countless studies have failed to account for the most basic assumptions of reliable species mapping practices, undermining the credibility of their results and potentially misleading and hindering conservation and management efforts. Here, we use examples from the recent literature and broader conservation community to highlight the substantial shortfalls in current practices and their consequences for both analyses and conservation management. We detail how different decisions on data filtering impact the outcomes of analysis and provide practical recommendations and steps for more reliable analysis, whilst understanding the limits of what available data will reliably allow and what methods are most appropriate. Whilst perfect analyses are not possible for many taxa given limited data, and biases, ensuring we use data within reasonable limits and understanding inherent assumptions is crucial to ensure appropriate use. By embracing and enacting such best practices, we can ensure both the accuracy and improved comparability of biodiversity analyses going forward, ultimately enhancing our ability to use data to facilitate our protection of the natural world. [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]

Climate change is a major factor influencing the species distribution and population diversity of living creatures. In this study, the ecological niche model (ENM) MaxEnt was used to evaluate habitat suitability and predict potential habitats of two sympatric fig species, i.e., Ficus squamosa and F. heterostyla, in the Xishuangbanna region of China. Results indicated that mean diurnal range, isothermality, cation exchange capacity (at pH 7), and temperature seasonality were key variables influencing habitat suitability for F. squamosa. However, temperature seasonality and precipitation of the driest quarter showed the greatest contributions to F. heterostyla distribution. During the current period, the habitat suitability distributions of both Ficus species were considerably higher than known occurrences. In the future, potentially suitable distribution areas for both species will reduce overall across the whole study area, although some expansion may occur by 2070. Niche overlap of suitable areas for both species was initially high and then declined in the current period and future epochs in the RCP 2.6 scenario, but increased in the RCP 8.5 scenario. In short, the responses of both Ficus species to climate change differed. Thus, specific actions such as ex situ conservation and assisted migration may be needed to conserve both species. [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]

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]

Background and goal: The study is conducted to facilitate conservation of migratory wader species along the East Asian-Australasian Flyway, particularly to 1) Identify hotspots of wader species richness along the flyway and effectively map how these might change between breeding, non-breeding and migratory phases; 2) Determine if the existing network of protected areas (PA) is sufficient to effectively conserve wader biodiversity hotspots along the EAAF; 3) Assess how species distribution models can provide complementary distribution estimates to existing BirdLife range maps. Methods: We use a species distribution modelling (SDM) approach (MaxEnt) to develop temporally explicit individual range maps of 57 migratory wader species across their annual cycle, including breeding, non-breeding and migratory phases, which in turn provide the first biodiversity hotspot map of migratory waders along the EAAF for each of these phases. We assess the protected area coverage during each migration period, and analyse the dominant environmental drivers of distributions for each period. Additionally, we compare model hotspots to those existing range maps of the same species obtained from the BirdLife Internationals’ database. Results: Our model results indicate an overall higher and a spatially different species richness pattern compared to that derived from a wader biodiversity hotspot map based on BirdLife range maps. Field observation records from the eBird database for our 57 study species confirm many of the hotspots revealed by model outputs (especially within the Yellow Sea coastal region), suggesting that current richness of the EAAF may have been underestimated and certain hotspots overlooked. Less than 10% of the terrestrial zones area (inland and coastal) which support waders are protected and, only 5% of areas with the highest 10% species richness is protected. Main conclusions: The study results suggest the need for new areas for migratory wader research and conservation priorities including Yellow Sea region and Russian far-East. It also suggests a need to increase the coverage and percentage of current PA network to achieve Aichi Target 11 for Flyway countries, including giving stronger consideration to the temporal dynamics of wader migration. [ABSTRACT FROM AUTHOR]

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost-effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population- and community-level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate-induced changes, which will inform effective management actions for promoting biodiversity resilience. [ABSTRACT FROM AUTHOR]

The IUCN Red List has assessed the global distributions of the majority of the world’s amphibians, birds and mammals. Yet these assessments lack explicit reference to widely available, remotely-sensed data that can sensibly inform a species’ risk of extinction. Our first goal is to add additional quantitative data to the existing standardised process that IUCN employs. Secondly, we ask: do our results suggest species of concern—those at considerably greater risk than hitherto appreciated? Thirdly, these assessments are not only important on a species-by-species basis. By combining distributions of species of concern, we map conservation priorities. We ask to what degree these areas are currently protected and how might knowledge from remote sensing modify the priorities? Finally, we develop a quick and simple method to identify and modify the priority setting in a landscape where natural habitats are disappearing rapidly and so where conventional species’ assessments might be too slow to respond. Tropical, mainland Southeast Asia is under exceptional threat, yet relatively poorly known. Here, additional quantitative measures may be particularly helpful. This region contains over 122, 183, and 214 endemic mammals, birds, and amphibians, respectively, of which the IUCN considers 37, 21, and 37 threatened. When corrected for the amount of remaining natural habitats within the known elevation preferences of species, the average sizes of species ranges shrink to <40% of their published ranges. Some 79 mammal, 49 bird, and 184 amphibian ranges are <20,000km2—an area at which IUCN considers most other species to be threatened. Moreover, these species are not better protected by the existing network of protected areas than are species that IUCN accepts as threatened. Simply, there appear to be considerably more species at risk than hitherto appreciated. Furthermore, incorporating remote sensing data showing where habitat loss is prevalent changes the locations of conservation priorities. [ABSTRACT FROM AUTHOR]

Southeast-Asia ( SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (>80 species) at 2050-2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the 'greenest' scenario, global population peaking mid-century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3-9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2-6% of species may have no suitable niche space in 2050-2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1-13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal-limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century. [ABSTRACT FROM AUTHOR]

Insects are the focus of many recent studies suggesting population declines, but even invaluable pollination service providers such as bees lack a modern distributional synthesis. Here, we combine a uniquely comprehensive checklist of bee species distributions and >5,800,000 public bee occurrence records to describe global patterns of bee biodiversity. Publicly accessible records are sparse, especially from developing countries, and are frequently inaccurate throughout much of the world, consequently suggesting different biodiversity patterns from checklist data. Global analyses reveal hotspots of species richness, together generating a rare bimodal latitudinal richness gradient, and further analyses suggest that xeric areas, solar radiation, and non-forest plant productivity are among the most important global drivers of bee biodiversity. Together, our results provide a new baseline and best practices for studies on bees and other understudied invertebrates. • Bees show a rare bimodal latitudinal gradient with highest richness at mid-latitudes • Xeric and temperate zones host higher richness than tropical areas • Plant productivity and richness are important drivers when forests are excluded • A global bee species richness reconstruction is presented for the first time A modern, quantitative synthesis on bee distribution and its drivers at a global scale. Orr et al. show that bees exhibit a rare bimodal pattern of higher species richness at mid-latitudes, based on their great success in xeric and some temperate areas, further supported by a driver analysis. Bee species richness is also reprojected worldwide. [ABSTRACT FROM AUTHOR]

Foraging behavior frequently plays a major role in driving the geographic distribution of animals. Buzzing to extract protein-rich pollen from flowers is a key foraging behavior used by bee species across at least 83 genera (these genera comprise ∼58% of all bee species). Although buzzing is widely recognized to affect the ecology and evolution of bees and flowering plants (e.g., buzz-pollinated flowers), global patterns and drivers of buzzing bee biogeography remain unexplored. Here, we investigate the global species distribution patterns within each bee family and how patterns and drivers differ with respect to buzzing bee species. We found that both distributional patterns and drivers of richness typically differed for buzzing species compared with hotspots for all bee species and when grouped by family. A major predictor of the distribution, but not species richness overall for buzzing members of four of the five major bee families included in analyses (Andrenidae, Halictidae, Colletidae, and to a lesser extent, Apidae), was the richness of poricidal flowering plant species, which depend on buzzing bees for pollination. Because poricidal plant richness was highest in areas with low wind and high aridity, we discuss how global hotspots of buzzing bee biodiversity are likely influenced by both biogeographic factors and plant host availability. Although we explored global patterns with state-level data, higher-resolution work is needed to explore local-level drivers of patterns. From a global perspective, buzz-pollinated plants clearly play a greater role in the ecology and evolution of buzzing bees than previously predicted. • Distributional patterns differed for buzzing species compared with all bee species • Drivers of species richness differed for buzzing species compared with all bees • Poricidal species richness was a major predictor of buzzing species distributions • Poricidal species richness was highest in areas with low wind and high aridity Russell et al. find that distributional patterns and drivers of species richness differ for buzzing bee species compared with all bee species and within each major family. They also find that poricidal plant species richness (highest in areas with low wind and high aridity) was a major predictor of buzzing species distributions for 4 of 5 bee families. [ABSTRACT FROM AUTHOR]