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Geo‐referenced species occurrences from public databases have become essential to biodiversity research and conservation. However, geographical biases are widely recognized as a factor limiting the usefulness of such data for understanding species diversity and distribution. In particular, differences in sampling intensity across a landscape due to differences in human accessibility are ubiquitous but may differ in strength among taxonomic groups and data sets. Although several factors have been described to influence human access (such as presence of roads, rivers, airports and cities), quantifying their specific and combined effects on recorded occurrence data remains challenging. Here we present sampbias, an algorithm and software for quantifying the effect of accessibility biases in species occurrence data sets. sampbias uses a Bayesian approach to estimate how sampling rates vary as a function of proximity to one or multiple bias factors. The results are comparable among bias factors and data sets. We demonstrate the use of sampbias on a data set of mammal occurrences from the island of Borneo, showing a high biasing effect of cities and a moderate effect of roads and airports. sampbias is implemented as a well‐documented, open‐access and user‐friendly R package that we hope will become a standard tool for anyone working with species occurrences in ecology, evolution, conservation and related fields.

The American tropics (the Neotropics) are the most species-rich realm on Earth, and for centuries, scientists have attempted to understand the origins and evolution of their biodiversity. It is now clear that different regions and taxonomic groups have responded differently to geological and climatic changes. However, we still lack a basic understanding of how Neotropical biodiversity was assembled over evolutionary timescales. Here we infer the timing and origin of the living biota in all major Neotropical regions by performing a cross-taxonomic biogeographic analysis based on 4,450 species from six major clades across the tree of life (angiosperms, birds, ferns, frogs, mammals, and squamates), and integrate >1.3 million species occurrences with large-scale phylogenies. We report an unprecedented level of biotic interchange among all Neotropical regions, totaling 4,525 dispersal events. About half of these events involved transitions between major environmental types, with a predominant directionality from forested to open biomes. For all taxonomic groups surveyed here, Amazonia is the primary source of Neotropical diversity, providing >2,800 lineages to other regions. Most of these dispersal events were to Mesoamerica (∼1,500 lineages), followed by dispersals into open regions of northern South America and the Cerrado and Chaco biomes. Biotic interchange has taken place for >60 million years and generally increased toward the present. The total amount of time lineages spend in a region appears to be the strongest predictor of migration events. These results demonstrate the complex origin of tropical ecosystems and the key role of biotic interchange for the assembly of regional biotas.

The lack of comprehensive and standardized taxonomic reference information is an impediment for robust plant research, e.g. in systematics, biogeography or macroecology. Here we provide an updated and much improved reference list of 1,315,562 scientific names for all described vascular plant species globally. The Leipzig Catalogue of Vascular Plants (LCVP; version 1.0.3) contains 351,180 accepted species names (plus 6,160 natural hybrids), within 13,460 genera, 564 families and 84 orders. The LCVP a) contains more information on the taxonomic status of global plant names than any other similar resource, and b) significantly improves the reliability of our knowledge by e.g. resolving the taxonomic status of ~181,000 names compared to The Plant List, the up to date most commonly used plant name resource. We used ~4,500 publications, existing relevant databases and available studies on molecular phylogenetics to construct a robust reference backbone. For easy access and integration into automated data processing pipelines, we provide an ‘R’-package ( lcvplants ) with the LCVP. Measurement(s) Plant Taxonomy Technology Type(s) digital curation Sample Characteristic - Organism Tracheophyta Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13013651

Tropical America (the Neotropics) is the most biodiverse realm on Earth and might harbour more species than tropical Asia and Africa combined. The evolutionary history generating this outstanding diversity remains poorly understood partly because data on the geographic distribution of species is scarce. Collections from museums and herbaria can overcome this gap, but uncertain data quality hampers their use, especially in historical biogeography. Here, I highlight the results from recent studies quantifying diversification and bioregion connectivity in the Neotropics using large-scale species occurrence data, and argue that (i) recently developed software to analyse large-scale data provides a methodological route forward for biogeography, and (ii) biotic connectivity within and among bioregions is a common, but underappreciated, process in the evolution of Neotropical diversity.

Due to increasing human transformation of virtually all habitats on Earth, setting global priorities for conservation is essential. The emerging disciplines of macroecology and macroevolution (MEE) can provide a global perspective and information for such prioritization but remain relatively separated from conservation prioritization, partly because MEE researchers are unaware of the requirements for effective conservation prioritization and existing approaches implementing these. Indeed, existing approaches for conservation prioritization at large scale are scattered across literature. Here, we systematically review this literature and provide a guideline for researchers in MEE as to which of approaches might be suitable for their needs. From >11 000 scientific publications, we identified 134 methods suitable for commonly used MEE data and geographic scale. Furthermore, we use a ‘trait matrix' to identify families of similar approaches and to design a guideline to select the most suitable method, given a user‐defined set of data and analysis scope. The guidelines are freely available via the conserveR R‐package (). Finally, we used our review to identify increasing scalability, continuous monitoring and the integration of molecular, remote sensing and animal movement data as key areas for future impacts of MEE in conservation prioritization. We anticipate that our review can serve as a guide to MEE researchers interested in linking their data to conservation as well as for conservation scientists interested in using MEE approaches.

The interchange between the previously disconnected faunas of North and South America was a massive experiment in biological invasion. A major gap in our understanding of this invasion is why there was a drastic increase in the proportion of mammals of North American origin found in South America. Four nonmutually exclusive mechanisms may explain this asymmetry: 1) Higher dispersal rate of North American mammals toward the south, 2) higher origination of North American immigrants in South America, 3) higher extinction of mammals with South American origin, and 4) similar dispersal rate but a larger pool of native taxa in North versus South America. We test among these mechanisms by analyzing ∼20,000 fossil occurrences with Bayesian methods to infer dispersal and diversification rates and taxonomic selectivity of immigrants. We find no differences in the dispersal and origination rates of immigrants. In contrast, native South American mammals show higher extinction. We also find that two clades with North American origin (Carnivora and Artiodactyla) had significantly more immigrants in South America than other clades. Altogether, the asymmetry of the interchange was not due to higher origination of immigrants in South America as previously suggested, but resulted from higher extinction of native taxa in southern South America. These results from one of the greatest biological invasions highlight how biogeographic processes and biotic interactions can shape continental diversity.

Insular woodiness (IW)—the evolutionary transition from herbaceousness toward woodiness on islands—is one of the most iconic features of island floras. Since pioneering work by Darwin and Wallace, a number of drivers of IW have been proposed, such as 1) competition for sunlight requiring plants with taller and stronger woody stems and 2) drought favoring woodiness to safeguard root-to-shoot water transport. Alternatively, IW may be the indirect result of increased lifespan related to 3) a favorable aseasonal climate and/or 4) a lack of large native herbivores. However, information on the occurrence of IW is fragmented, hampering tests of these potential drivers. Here, we identify 1,097 insular woody species on 375 islands and infer at least 175 evolutionary transitions on 31 archipelagos, concentrated in six angiosperm families. Structural equation models reveal that the insular woody species richness on oceanic islands correlates with a favorable aseasonal climate, followed by increased drought and island isolation (approximating competition). When continental islands are also included, reduced herbivory pressure by large native mammals, increased drought, and island isolation are most relevant. Our results illustrate different trajectories leading to rampant convergent evolution toward IW and further emphasize archipelagos as natural laboratories of evolution, where similar abiotic or biotic conditions replicated evolution of similar traits.

Aim: Massive digitalization of natural history collections is now leading to a steep accumulation of publicly available species distribution data. However, taxonomic errors and geographical uncertainty of species occurrence records are now acknowledged by the scientific community - putting into question to what extent such data can be used to unveil correct patterns of biodiversity and distribution. We explore this question through quantitative and qualitative analyses of uncleaned versus manually verified datasets of species distribution records across different spatial scales. Location: The American tropics. Methods: As test case we used the plant tribe Cinchoneae (Rubiaceae). We compiled four datasets of species occurrences: one created manually and verified through classical taxonomic work, and the rest derived from GBIF under different cleaning and filling schemes. We used new bioinformatic tools to code species into grids, ecoregions, and biomes following WWF's classification. We analysed species richness and altitudinal ranges of the species. Results: Altitudinal ranges for species and genera were correctly inferred even without manual data cleaning and filling. However, erroneous records affected spatial patterns of species richness. They led to an overestimation of species richness in certain areas outside the centres of diversity in the clade. The location of many of these areas comprised the geographical midpoint of countries and political subdivisions, assigned long after the specimens had been collected. Main conclusion: Open databases and integrative bioinformatic tools allow a rapid approximation of large-scale patterns of biodiversity across space and altitudinal ranges. We found that geographic inaccuracy affects diversity patterns more than taxonomic uncertainties, often leading to false positives, i.e. overestimating species richness in relatively species poor regions. Public databases for species distribution are valuable and should be more explored, but under scrutiny and validation by taxonomic experts. We suggest that database managers implement easy ways of community feedback on data quality.

Trees are fundamental for Earth’s biodiversity as primary producers and ecosystem engineers and are responsible for many of nature’s contributions to people. Yet, many tree species at present are threatened with extinction by human activities. Accurate identification of threatened tree species is necessary to quantify the current biodiversity crisis and to prioritize conservation efforts. However, the most comprehensive dataset of tree species extinction risk—the Red List of the International Union for the Conservation of Nature (IUCN RL)—lacks assessments for a substantial number of known tree species. The RL is based on a time-consuming expert-based assessment process, which hampers the inclusion of less-known species and the continued updating of extinction risk assessments. In this study, we used a computational pipeline to approximate RL extinction risk assessments for more than 21,000 tree species (leading to an overall assessment of 89% of all known tree species) using a supervised learning approach trained based on available IUCN RL assessments. We harvested the occurrence data for tree species worldwide from online databases, which we used with other publicly available data to design features characterizing the species’ geographic range, biome and climatic affinities, and exposure to human footprint. We trained deep neural network models to predict their conservation status, based on these features. We estimated 43% of the assessed tree species to be threatened with extinction and found taxonomic and geographic heterogeneities in the distribution of threatened species. The results are consistent with the recent estimates by the Global Tree Assessment initiative, indicating that our approach provides robust and time-efficient approximations of species’ IUCN RL extinction risk assessments.

The extinction of species can destabilize ecological processes. A way to assess the ecological consequences of species loss is by examining changes in functional diversity. The preservation of functional diversity depends on the range of ecological roles performed by species, or functional richness, and the number of species per role, or functional redundancy. However, current knowledge is based on short timescales and an understanding of how functional diversity responds to long-term biodiversity dynamics has been limited by the availability of deep-time, trait-based data. Here, we compile an exceptional trait dataset of fossil molluscs from a 23-million-year interval in the Caribbean Sea (34 011 records, 4422 species) and develop a novel Bayesian model of multi-trait-dependent diversification to reconstruct mollusc (i) diversity dynamics, (ii) changes in functional diversity, and (iii) extinction selectivity over the last 23 Myr. Our results identify high diversification between 23–5 Mya, leading to increases in both functional richness and redundancy. Conversely, over the last three million years, a period of high extinction rates resulted in the loss of 49% of species but only 3% of functional richness. Extinction rates were significantly higher in small, functionally redundant species suggesting that competition mediated the response of species to environmental change. Taken together, our results identify long-term diversification and selective extinction against redundant species that allowed functional diversity to grow over time, ultimately buffering the ecological functions of biological communities against extinction.