The evolution of insular woodiness.

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.

Modelling the probability of meeting IUCN Red List criteria to support reassessments.

Comparative extinction risk analysis-which predicts species extinction risk from correlation with traits or geographical characteristics-has gained research attention as a promising tool to support extinction risk assessment in the IUCN Red List of Threatened Species. However, its uptake has been very limited so far, possibly because existing models only predict a species' Red List category, without indicating which Red List criteria may be triggered. This prevents such approaches to be integrated into Red List assessments. We overcome this implementation gap by developing models that predict the probability of species meeting individual Red List criteria. Using data on the world's birds, we evaluated the predictive performance of our criterion-specific models and compared it with the typical criterion-blind modelling approach. We compiled data on biological traits (e.g. range size, clutch size) and external drivers (e.g. change in canopy cover) often associated with extinction risk. For each specific criterion, we modelled the relationship between extinction risk predictors and species' Red List category under that criterion using ordinal regression models. We found criterion-specific models were better at identifying threatened species compared to a criterion-blind model (higher sensitivity), but less good at identifying not threatened species (lower specificity). As expected, different covariates were important for predicting extinction risk under different criteria. Change in annual temperature was important for criteria related to population trends, while high forest dependency was important for criteria related to restricted area of occupancy or small population size. Our criteria-specific method can support Red List assessors by producing outputs that identify species likely to meet specific criteria, and which are the most important predictors. These species can then be prioritised for re-evaluation. We expect this new approach to increase the uptake of extinction risk models in Red List assessments, bridging a long-standing research-implementation gap.

The big four of plant taxonomy - a comparison of global checklists of vascular plant names.

Taxonomic checklists used to verify published plant names and identify synonyms are a cornerstone of biological research. Four global authoritative checklists for vascular plants exist: Leipzig Catalogue of Vascular Plants, World Checklist of Vascular Plants, World Flora Online (successor of The Plant List, TPL), and WorldPlants. We compared these four checklists in terms of size and differences across taxa. We matched taxon names of these checklists and TPL against each other, identified differences across checklists, and evaluated the consistency of accepted names linked to individual taxon names. We assessed geographic and phylogenetic patterns of variance. All checklists differed strongly compared with TPL and provided identical information on c. 60% of plant names. Geographically, differences in checklists increased from low to high latitudes. Phylogenetically, we detected strong variability across families. A comparison of name-matching performance on taxon names submitted to the functional trait database TRY, and a check of completeness of accepted names evaluated against an independent, expert-curated checklist of the family Meliaceae, showed a similar performance across checklists. This study raises awareness on the differences in data and approach across these checklists potentially impacting analyses. We propose ideas on the way forward exploring synergies and harmonizing the four global checklists.

Slow and steady wins the race: Diversification rate is independent from body size and lifestyle in Malagasy skinks (Squamata: Scincidae: Scincinae).

Most of the unique and diverse vertebrate fauna that inhabits Madagascar derives from in situ diversification from colonisers that reached this continental island through overseas dispersal. The endemic Malagasy Scincinae lizards are amongst the most species-rich squamate groups on the island. They colonised all bioclimatic zones and display many ecomorphological adaptations to a fossorial (burrowing) lifestyle. Here we propose a new phylogenetic hypothesis for their diversification based on the largest taxon sampling so far compiled for this group. We estimated divergence times and investigated several aspects of their diversification (diversification rate, body size and fossorial lifestyle evolution, and biogeography). We found that diversification rate was constant throughout most of the evolutionary history of the group, but decreased over the last 6-4 million years and independently from body size and fossorial lifestyle evolution. Fossoriality has evolved from fully quadrupedal ancestors at least five times independently, which demonstrates that even complex morphological syndromes - in this case involving traits such as limb regression, body elongation, modification of cephalic scalation, depigmentation, and eyes and ear-opening regression - can evolve repeatedly and independently given enough time and eco-evolutionary advantages. Initial diversification of the group likely occurred in forests, and the divergence of sand-swimmer genera around 20 Ma appears linked to a period of aridification. Our results show that the large phenotypic variability of Malagasy Scincinae has not influenced diversification rate and that their rich species diversity results from a constant accumulation of lineages through time. By compiling large geographic and trait-related datasets together with the computation of a new time tree for the group, our study contributes important insights on the diversification of Malagasy vertebrates.

Spiny but photogenic: Amateur sightings complement herbarium specimens to reveal the bioregions of cacti.

PREMISE: Cacti are characteristic elements of the Neotropical flora and of major interest for biogeographic, evolutionary, and ecological studies. We tested global biogeographic boundaries for Neotropical Cactaceae using specimen-based occurrences, coupled with data from visual observations, as a means to tackle the known collection biases in the family. METHODS: Species richness and record density were assessed for preserved specimens and human observations, and a bioregional scheme tailored to Cactaceae was produced using the interactive web application Infomap Bioregions, based on data from 261,272 point records cleaned through automated and manual steps. RESULTS: We found that areas in Mexico and southwestern USA, in eastern Brazil, and along the Andean region have the greatest density of records and the highest species richness. Human observations complement information from preserved specimens substantially, especially along the Andes. We propose 24 cactus bioregions, among which the most species-rich are northern Mexico/southwestern USA, central Mexico, southern central Mexico, Central America, Mexican Pacific coast, central and southern Andes, northwestern Mexico/extreme southwestern USA, southwestern Bolivia, northeastern Brazil, and Mexico/Baja California. CONCLUSIONS: The bioregionalization proposed shows biogeographic boundaries specific to cacti and can thereby aid further evolutionary, biogeographic, and ecological studies by providing a validated framework for further analyses. This classification builds upon, and is distinctive from, other expert-derived regionalization schemes for other taxa. Our results showcase how observation data, including citizen-science records, can complement traditional specimen-based data for biogeographic research, particularly for taxa with specific specimen collection and preservation challenges and those that are threatened or internationally protected.

Prioritizing the reassessment of data-deficient species on the IUCN Red List.

Despite being central to the implementation of conservation policies, the usefulness of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species is hampered by the 14% of species classified as data-deficient (DD) because information to evaluate these species' extinction risk was lacking when they were last assessed or because assessors did not appropriately account for uncertainty. Robust methods are needed to identify which DD species are more likely to be reclassified in one of the data-sufficient IUCN Red List categories. We devised a reproducible method to help red-list assessors prioritize reassessment of DD species and tested it with 6887 DD species of mammals, reptiles, amphibians, fishes, and Odonata (dragonflies and damselflies). For each DD species in these groups, we calculated its probability of being classified in a data-sufficient category if reassessed today from covariates measuring available knowledge (e.g., number of occurrence records or published articles available), knowledge proxies (e.g., remoteness of the range), and species characteristics (e.g., nocturnality); calculated change in such probability since last assessment from the increase in available knowledge (e.g., new occurrence records); and determined whether the species might qualify as threatened based on recent rate of habitat loss determined from global land-cover maps. We identified 1907 species with a probability of being reassessed in a data-sufficient category of >0.5; 624 species for which this probability increased by >0.25 since last assessment; and 77 species that could be reassessed as near threatened or threatened based on habitat loss. Combining these 3 elements, our results provided a list of species likely to be data-sufficient such that the comprehensiveness and representativeness of the IUCN Red List can be improved.

Priorización de la reevaluación de las especies con datos deficientes en la Lista Roja de la UICN Resumen No obstante que es fundamental para la implementación de políticas de conservación, la utilidad de la Lista Roja de Especies Amenazadas de la Unión Internacional para la Conservación de la Naturaleza (UICN) está limitada por el 14% de especies clasificadas con datos deficientes (DD) debido a que la información para evaluar el riesgo de extinción de estas especies no existía cuando fueron evaluadas la última vez o porque los evaluadores no consideraron la incertidumbre apropiadamente. Se requieren métodos robustos para identificar las especies DD con mayor probabilidad de ser reclasificadas en alguna de las categorías en la Lista Roja UICN con datos suficientes. Diseñamos un método reproducible para ayudar a que los evaluadores de la lista roja prioricen la reevaluación de especies DD y lo probamos con 6,887 especies DD de mamíferos, reptiles, anfibios, peces y Odonata (libélulas y caballitos del diablo). Para cada una de las especies DD en estos grupos, calculamos la probabilidad de ser clasificadas en una categoría con datos suficientes si fuera reevaluada hoy a partir de covariables que miden el conocimiento disponible (e.g., número de registros de ocurrencia o artículos publicados disponibles), sustitutos de conocimiento (e.g., extensión del rango de distribución) y características de la especie ((e.g., nocturnidad); calculamos el cambio en tal probabilidad desde la última reevaluación a partir del incremento en el conocimiento disponible (e.g., registros de ocurrencia nuevos); y determinamos si las especies podrían calificar como amenazadas con base en pérdidas de hábitat recientes a partir de mapas globales de cobertura de suelo recientes. Identificamos 1,907 especies con una probabilidad >0.5 de ser reclasificados en una categoría con datos suficientes; 624 especies cuya probabilidad aumentó en >0.25 desde la última evaluación, y 77 especies que podrían ser reclasificadas como casi en peligro con base en la pérdida de hábitat. Combinando estos 3 elementos, nuestros resultados proporcionaron una lista de especies probablemente con datos suficientes de tal modo que la exhaustividad y la representatividad de la Lista Roja de la UICN pueden ser mejoradas.

Disproportionate extinction of South American mammals drove the asymmetry of the Great American Biotic Interchange.

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.

Global patterns in endemicity and vulnerability of soil fungi.

Fungi are highly diverse organisms, which provide multiple ecosystem services. However, compared with charismatic animals and plants, the distribution patterns and conservation needs of fungi have been little explored. Here, we examined endemicity patterns, global change vulnerability and conservation priority areas for functional groups of soil fungi based on six global surveys using a high-resolution, long-read metabarcoding approach. We found that the endemicity of all fungi and most functional groups peaks in tropical habitats, including Amazonia, Yucatan, West-Central Africa, Sri Lanka, and New Caledonia, with a negligible island effect compared with plants and animals. We also found that fungi are predominantly vulnerable to drought, heat and land-cover change, particularly in dry tropical regions with high human population density. Fungal conservation areas of highest priority include herbaceous wetlands, tropical forests, and woodlands. We stress that more attention should be focused on the conservation of fungi, especially root symbiotic arbuscular mycorrhizal and ectomycorrhizal fungi in tropical regions as well as unicellular early-diverging groups and macrofungi in general. Given the low overlap between the endemicity of fungi and macroorganisms, but high conservation needs in both groups, detailed analyses on distribution and conservation requirements are warranted for other microorganisms and soil organisms.

Automated conservation assessment of the orchid family with deep learning.

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.

Evaluación Automatizada de la Conservación de la Familia Orchidaceae mediante Aprendizaje Profundo Resumen Los análisis de la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) son esenciales para la priorización de las necesidades de conservación, pero requieren de muchos recursos y por lo tanto están disponibles sólo para una fracción de la riqueza mundial de especies. Las evaluaciones automatizadas de la conservación basadas en los registros disponibles de presencia geográfica pueden ser una alternativa rápida pero no está claro cuán confiables son estas evaluaciones. Realizamos evaluaciones automatizadas de la conservación para 13,910 especies (47.3% de las especies conocidas de la familia) de la diversa y mundialmente distribuida familia de las orquídeas (Orchidaceae), en la cual la mayoría de las especies (13,049) no tenían una valoración previa por parte de la UICN. Usamos un método novedoso basado en una red neural profunda (IUC-NN). Identificamos 4,342 especies de orquídeas (31.2% de las especies evaluadas) como posiblemente amenazadas por la extinción (equivalente a las categorías de la UICN en peligro crítico [CR], en peligro [EN] o vulnerable [VU]) y a Madagascar, África Occidental, el sudeste de Asia y varias islas oceánicas como áreas prioritarias para la conservación de orquídeas. La familia Orchidaceae proporcionó un modelo con el cual probar la sensibilidad de los métodos de evaluación automatizada ante problemas con la disponibilidad de datos, la calidad de los datos y los sesgos de muestreo geográfico. La IUC-NN identificó posibles especies amenazadas con una certeza de 84.3% con un sesgo de evaluación geográfica significativamente más bajo en relación con la Lista Roja de la UICN y mostró solidez incluso cuando la disponibilidad de datos fue baja y hubo errores geográficos en los datos de entrada. En general, nuestros resultados demostraron que las evaluaciones automatizadas tienen un papel importante que desempeñar en la identificación de especies con mayor riesgo de extinción.

Amazonia is the primary source of Neotropical biodiversity.

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.

Selective extinction against redundant species buffers functional diversity.

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.

Early Arrival and Climatically-Linked Geographic Expansion of New World Monkeys from Tiny African Ancestors.

New World Monkeys (NWM) (platyrrhines) are one of the most diverse groups of primates, occupying today a wide range of ecosystems in the American tropics and exhibiting large variations in ecology, morphology, and behavior. Although the relationships among the almost 200 living species are relatively well understood, we lack robust estimates of the timing of origin, ancestral morphology, and geographic range evolution of the clade. Herein, we integrate paleontological and molecular evidence to assess the evolutionary dynamics of extinct and extant platyrrhines. We develop novel analytical frameworks to infer the evolution of body mass, changes in latitudinal ranges through time, and species diversification rates using a phylogenetic tree of living and fossil taxa. Our results show that platyrrhines originated 5-10 million years earlier than previously assumed, dating back to the Middle Eocene. The estimated ancestral platyrrhine was small-weighing 0.4 kg-and matched the size of their presumed African ancestors. As the three platyrrhine families diverged, we recover a rapid change in body mass range. During the Miocene Climatic Optimum, fossil diversity peaked and platyrrhines reached their widest latitudinal range, expanding as far South as Patagonia, favored by warm and humid climate and the lower elevation of the Andes. Finally, global cooling and aridification after the middle Miocene triggered a geographic contraction of NWM and increased their extinction rates. These results unveil the full evolutionary trajectory of an iconic and ecologically important radiation of monkeys and showcase the necessity of integrating fossil and molecular data for reliably estimating evolutionary rates and trends.

Infomap Bioregions: Interactive Mapping of Biogeographical Regions from Species Distributions.

Biogeographical regions (bioregions) reveal how different sets of species are spatially grouped and therefore are important units for conservation, historical biogeography, ecology, and evolution. Several methods have been developed to identify bioregions based on species distribution data rather than expert opinion. One approach successfully applies network theory to simplify and highlight the underlying structure in species distributions. However, this method lacks tools for simple and efficient analysis. Here, we present Infomap Bioregions, an interactive web application that inputs species distribution data and generates bioregion maps. Species distributions may be provided as georeferenced point occurrences or range maps, and can be of local, regional, or global scale. The application uses a novel adaptive resolution method to make best use of often incomplete species distribution data. The results can be downloaded as vector graphics, shapefiles, or in table format. We validate the tool by processing large data sets of publicly available species distribution data of the world's amphibians using species ranges, and mammals using point occurrences. We then calculate the fit between the inferred bioregions and WWF ecoregions. As examples of applications, researchers can reconstruct ancestral ranges in historical biogeography or identify indicator species for targeted conservation. [Biogeography; bioregionalization; conservation; mapping].

SpeciesGeoCoder: Fast Categorization of Species Occurrences for Analyses of Biodiversity, Biogeography, Ecology, and Evolution.

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space constitutes a major scientific challenge in systematic biology and biogeography, which largely relies on effectively mapping and making sense of rapidly increasing species occurrence data. There is thus an urgent need for making the process of coding species into spatial units faster, automated, transparent, and reproducible. Here we present SpeciesGeoCoder, an open-source software package written in Python and R, that allows for easy coding of species into user-defined operational units. These units may be of any size and be purely spatial (i.e., polygons) such as countries and states, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include elevation ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data obtained from online databases, and for testing the impact of incorrect identification of specimens on the spatial coding of species. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and files that can be used directly in many phylogeny-based applications for ancestral range reconstruction, investigations of biome evolution, and other comparative methods. Our simulations indicate that even datasets containing hundreds of millions of records can be analyzed in relatively short time using a standard computer. We exemplify the use of SpeciesGeoCoder by inferring the historical dispersal of birds across the Isthmus of Panama, showing that lowland species crossed the Isthmus about twice as frequently as montane species with a marked increase in the number of dispersals during the last 10 million years. [ancestral area reconstruction; biodiversity patterns; ecology; evolution; point in polygon; species distribution data.].

Patterns, biases and prospects in the distribution and diversity of Neotropical snakes.

Motivation: We generated a novel database of Neotropical snakes (one of the world's richest herpetofauna) combining the most comprehensive, manually compiled distribution dataset with publicly available data. We assess, for the first time, the diversity patterns for all Neotropical snakes as well as sampling density and sampling biases. Main types of variables contained: We compiled three databases of species occurrences: a dataset downloaded from the Global Biodiversity Information Facility (GBIF), a verified dataset built through taxonomic work and specialized literature, and a combined dataset comprising a cleaned version of the GBIF dataset merged with the verified dataset. Spatial location and grain: Neotropics, Behrmann projection equivalent to 1° × 1°. Time period: Specimens housed in museums during the last 150 years. Major taxa studied: Squamata: Serpentes. Software format: Geographical information system (GIS). Results: The combined dataset provides the most comprehensive distribution database for Neotropical snakes to date. It contains 147,515 records for 886 species across 12 families, representing 74% of all species of snakes, spanning 27 countries in the Americas. Species richness and phylogenetic diversity show overall similar patterns. Amazonia is the least sampled Neotropical region, whereas most well-sampled sites are located near large universities and scientific collections. We provide a list and updated maps of geographical distribution of all snake species surveyed. Main conclusions: The biodiversity metrics of Neotropical snakes reflect patterns previously documented for other vertebrates, suggesting that similar factors may determine the diversity of both ectothermic and endothermic animals. We suggest conservation strategies for high-diversity areas and sampling efforts be directed towards Amazonia and poorly known species.

Estimating species diversity and distribution in the era of Big Data: to what extent can we trust public databases?

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.

Chloroplast genome and nuclear loci data for 71 Medicago species.

We present a dataset containing nuclear and chloroplast sequences for 71 species in genus Medicago (Fabaceae), as well as for 8 species in genera Melilotus and Trigonella. Sequence data for a total of 130 samples was obtained with high-throughput sequencing of enriched genomic DNA libraries targeting 61 single-copy nuclear genes from across the Medicago truncatula genome. Chloroplast sequence reads were also generated, allowing for the recovery of chloroplast genome sequences for all 130 samples. A fully-resolved phylogenetic tree was inferred from the chloroplast dataset using maximum-likelihoood methods. More than 80% of accepted Medicago species are represented in this dataset, including three subspecies of Medicago sativa (alfalfa). These data can be further utilised for phylogenetic analyses in Medicago and related genera, but also for probe and primer design and plant breeding studies.