Global field collection data confirm an affinity of brown rot fungi for coniferous habitats and substrates.

Unlike 'white rot' (WR) wood-decomposing fungi that remove lignin to access cellulosic sugars, 'brown rot' (BR) fungi selectively extract sugars and leave lignin behind. The relative frequency and distribution of these fungal types (decay modes) have not been thoroughly assessed at a global scale; thus, the fate of one-third of Earth's aboveground carbon, wood lignin, remains unclear. Using c. 1.5 million fungal sporocarp and c. 30 million tree records from publicly accessible databases, we mapped and compared decay mode and tree type (conifer vs angiosperm) distributions. Additionally, we mined fungal record metadata to assess substrate specificity per decay mode. The global average for BR fungi proportion (BR/(BR + WR records)) was 13% and geographic variation was positively correlated (R2 = 0.45) with conifer trees proportion (conifer/(conifer + angiosperm records)). Most BR species (61%) were conifer, rather than angiosperm (22%), specialists. The reverse was true for WR (conifer: 19%; angiosperm: 62%). Global BR proportion patterns were predicted with greater accuracy using the relative distributions of individual tree species (R2 = 0.82), rather than tree type. Fungal decay mode distributions can be explained by tree type and, more importantly, tree species distributions, which our data suggest is due to strong substrate specificities.

Capability of big data to capture threatened vertebrate diversity in protected areas.

Protected areas (PAs) are an essential tool for conservation amid the global biodiversity crisis. Optimizing PAs to represent species at risk of extinction is crucial. Vertebrate representation in PAs is assessed using species distribution databases from the International Union for Conservation of Nature (IUCN) and the Global Biodiversity Information Facility (GBIF). Evaluating and addressing discrepancies and biases in these data sources are vital for effective conservation strategies. Our objective was to gain insights into the potential constraints (e.g., differences and biases) of these global repositories to objectively depict the diversity of threatened vertebrates in the global system of PAs. We assessed differences in species richness (SR) of threatened vertebrates as reported by IUCN and GBIF in PAs globally and then compared how biased this information was with reports from independent sources for a subset of PAs. Both databases showed substantial differences in SR in PAs (t = -62.35, p ≤ 0.001), but differences varied among regions and vertebrate groups. When these results were compared with data from independent assessments, IUCN overestimated SR by 575% on average and GBIF underestimated SR by 63% on average, again with variable results among regions and groups. Our results indicate the need to improve analyses of the representativeness of threatened vertebrates in PAs such that robust and unbiased assessments of PA effectiveness can be conducted. The scientific community and decision makers should consider these regional and taxonomic disparities when using IUCN and GBIF distributional data sources in PA assessment. Overall, supplementing information in these databases could lead to more robust and reliable analyses. Additional efforts to acquire more comprehensive and unbiased data on species distributions to support conservation decisions are clearly needed.

Capacidad de los macrodatos para capturar la diversidad de vertebrados amenazados en las áreas protegidas Resumen Las áreas protegidas (AP) son una herramienta esencial para la conservación en medio de la crisis mundial de biodiversidad. Es crucial optimizar las AP para que representen a las especies en peligro de extinción. La representación de vertebrados en las AP se evalúa con las bases de datos de distribución de especies de la Unión Internacional para la Conservación de la Naturaleza (UICN) y del Sistema Global de Información sobre Biodiversidad (GBIF). Es muy importante evaluar y abordar las discrepancias y sesgos en estas fuentes de datos para tener estrategias de conservación eficaces. Nuestro objetivo es conocer las limitaciones potenciales (por ejemplo, diferencias y sesgos) de estos repositorios globales para representar objetivamente la diversidad de vertebrados amenazados en el sistema global de AP. Analizamos las diferencias en la riqueza de especies (RE) de vertebrados amenazados según los informes de la UICN y GBIF en AP a nivel mundial y luego comparamos el grado de sesgo de esta información con los informes de fuentes independientes para un subconjunto de AP. Ambas bases de datos mostraron diferencias sustanciales en la RE en las AP (t = ­62.35, p = <0.001), pero las diferencias variaron entre regiones y grupos de vertebrados. Cuando comparamos estos resultados con datos de evaluaciones independientes, la UICN sobreestimó la RE en un 575% en promedio y el GBIF la subestimó en un 63% en promedio, de nuevo con resultados variables entre regiones y grupos. Nuestros resultados indican la necesidad de mejorar los análisis de representación de los vertebrados amenazados en las AP para que se puedan llevar a cabo evaluaciones sólidas e imparciales de la efectividad de las AP. La comunidad científica y los responsables de la toma de decisiones deberían tener en cuenta estas disparidades regionales y taxonómicas al utilizar las fuentes de datos distribucionales de la UICN y del GBIF en la evaluación de AP. En general, complementar la información de estas bases de datos podría conducir a análisis más sólidos y fiables. Está claro que se necesitan esfuerzos adicionales para adquirir datos más completos e imparciales sobre la distribución de las especies para apoyar las decisiones de conservación.

Data integration enables global biodiversity synthesis.

The accessibility of global biodiversity information has surged in the past two decades, notably through widespread funding initiatives for museum specimen digitization and emergence of large-scale public participation in community science. Effective use of these data requires the integration of disconnected datasets, but the scientific impacts of consolidated biodiversity data networks have not yet been quantified. To determine whether data integration enables novel research, we carried out a quantitative text analysis and bibliographic synthesis of >4,000 studies published from 2003 to 2019 that use data mediated by the world's largest biodiversity data network, the Global Biodiversity Information Facility (GBIF). Data available through GBIF increased 12-fold since 2007, a trend matched by global data use with roughly two publications using GBIF-mediated data per day in 2019. Data-use patterns were diverse by authorship, geographic extent, taxonomic group, and dataset type. Despite facilitating global authorship, legacies of colonial science remain. Studies involving species distribution modeling were most prevalent (31% of literature surveyed) but recently shifted in focus from theory to application. Topic prevalence was stable across the 17-y period for some research areas (e.g., macroecology), yet other topics proportionately declined (e.g., taxonomy) or increased (e.g., species interactions, disease). Although centered on biological subfields, GBIF-enabled research extends surprisingly across all major scientific disciplines. Biodiversity data mobilization through global data aggregation has enabled basic and applied research use at temporal, spatial, and taxonomic scales otherwise not possible, launching biodiversity sciences into a new era.

Environmental modulation of plant mycorrhizal traits in the global flora.

Mycorrhizal symbioses are known to strongly influence plant performance, structure plant communities and shape ecosystem dynamics. Plant mycorrhizal traits, such as those characterising mycorrhizal type (arbuscular (AM), ecto-, ericoid or orchid mycorrhiza) and status (obligately (OM), facultatively (FM) or non-mycorrhizal) offer valuable insight into plant belowground functionality. Here, we compile available plant mycorrhizal trait information and global occurrence data ( ∼ 100 million records) for 11,770 vascular plant species. Using a plant phylogenetic mega-tree and high-resolution climatic and edaphic data layers, we assess phylogenetic and environmental correlates of plant mycorrhizal traits. We find that plant mycorrhizal type is more phylogenetically conserved than plant mycorrhizal status, while environmental variables (both climatic and edaphic; notably soil texture) explain more variation in mycorrhizal status, especially FM. The previously underestimated role of environmental conditions has far-reaching implications for our understanding of ecosystem functioning under changing climatic and soil conditions.

Temporal analysis of GBIF data reveals the restructuring of communities following climate change.

Multiple studies revealed an effect of climate change on biodiversity by investigating long-term changes in species distributions and community composition. However, many taxa do not benefit from systematic long-term monitoring programmes, leaving gaps in our current knowledge of climate-induced community turnover. We used data extracted from the Global Biodiversity Information Facility to characterize community reorganization under climate change for nine animal taxonomic groups (ants, bats, bees, birds, butterflies, earthworms, frogs, rodents and salamanders), which, for most of them, had never been studied before in this regard. Using a presence-only community temperature index (CTI), reflecting the relative proportion of warm- and cold-adapted species, we tested whether and how species' assemblages were affected by climate change over the last 30 years. Across Europe and North America, we observed an average increase in CTI, consistent with a gradual species turnover driven by climate change. At the local scale, we could observe that the composition of most species assemblages changed according to temperature variations. However, this change in composition always occurred with a lag compared to climate change, suggesting that communities are experiencing a climatic debt. Results suggest that anthropization may play a role in the decoupling between the change in CTI and the change in local temperature. The results of our study highlight an overall thermophilization of assemblages as a response of temperature warming. We demonstrated that this response may exist for a large range of understudied terrestrial animals, and we introduced a framework that can be used in a broader context, opening new opportunities for global change research.

Region-wide retreats from lower elevations of range-restricted birds across the Northern Andes.

Local studies show upslope shifts in the distribution of tropical birds in response to warming temperatures. Unanswered is whether these upward shifts occur regionally across many species. We considered a nearly 2000-km length of the Northern Andes, where deforestation, temperature, and extreme weather events have increased during the past decades. Range-restricted bird species are particularly vulnerable to such events and occur in exceptionally high numbers in this region. Using abundant crowd-sourced data from the Cornell Lab of Ornithology database, eBird, and the Global Biodiversity Information Facility, we documented distributions of nearly 200 such species. We examined whether species shifted their elevational ranges over time by comparing observed versus expected occurrences below a low elevational threshold and above a high elevational threshold for 2 periods: before and after 2005. We predicted fewer observations at lower elevations (those below the threshold) and more at upper elevations (those above the threshold) after 2005. We also tested for deforestation effects at lower elevations within each species' distribution ranges. We compared relative forest loss with the differences between observed and expected occurrences across the elevational range. Species' retreats from lower elevations were ubiquitous and involved a 23-40% decline in prevalence at the lowest elevations. Increases at higher elevations were not consistent. The retreats occurred across a broad spectrum of species, from predominantly lowland to predominantly highland. Because deforestation showed no relationship with species retreats, we contend that a warming climate is the most parsimonious explanation for such shifts.

Repliegues regionales desde elevaciones más bajas de aves de distribución restringida en los Andes septentrionales Resumen Los estudios locales muestran cambios en la distribución altitudinal de las aves tropicales como respuesta al aumento de la temperatura. No sabemos si estos cambios suceden en muchas especies a nivel regional. Consideramos casi 2000 km de los Andes septentrionales, en donde la deforestación y los eventos climáticos extremos han incrementado en las últimas décadas. Las aves con distribución restringida son particularmente vulnerables a dichos eventos y su presencia es numerosa en esta región. Usamos datos abundantes de origen colectivo tomados de la base de datos del Laboratorio de Ornitología de Cornell, eBird y el Sistema Global de Información sobre Biodiversidad para documentar la distribución de aproximadamente 200 de estas especies. Analizamos si las especies cambiaron su distribución altitudinal con el tiempo al comparar entre la presencia observada y la esperada bajo un umbral de elevación reducida y por encima de un umbral de elevación alta durante dos periodos: antes y después de 2005. Pronosticamos una cantidad menor de observaciones por debajo del umbral y una mayor cantidad por encima del umbral para después de 2005. También analizamos los efectos de la deforestación en elevaciones más bajas dentro de los rangos de distribución de las especies y comparamos la pérdida relativa del bosque con las diferencias entre la presencia observada y la esperada en todo el rango altitudinal. El repliegue de las especies a partir de las elevaciones más bajas fue ubicuo e involucró una declinación del 23-40% de la prevalencia en las elevaciones más bajas. Los incrementos en las elevaciones más altas no fueron uniformes. Los repliegues ocurrieron a lo largo de un espectro amplio de especies, desde las que predominan en las tierras bajas hasta las que predominan en las tierras altas. Ya que la deforestación no se relacionó con el repliegue, sostenemos que un clima más cálido es la explicación más parsimoniosa para estos cambios.

Urban affinity and its associated traits: A global analysis of bats.

Urbanization is a major contributor to the loss of biodiversity. Its rapid progress is mostly at the expense of natural ecosystems and the species inhabiting them. While some species can adjust quickly and thrive in cities, many others cannot. To support biodiversity conservation and guide management decisions in urban areas, it is important to find robust methods to estimate the urban affinity of species (i.e. their tendency to live in urban areas) and understand how it is associated with their traits. Since previous studies mainly relied on discrete classifications of species' urban affinity, often involving inconsistent assessments or variable parameters, their results were difficult to compare. To address this issue, we developed and evaluated a set of continuous indices that quantify species' urban affinity based on publicly available occurrence data. We investigated the extent to which a species' position along the urban affinity gradient depends on the chosen index and how this choice affects inferences about the relationship between urban affinity and a set of morphological, sensory and functional traits. While these indices are applicable to a wide range of taxonomic groups, we examined their performance using a global set of 356 bat species. As bats vary in sensitivity to anthropogenic disturbances, they provide an interesting case study. We found that different types of indices resulted in different rankings of species on the urban affinity spectrum, but this had little effect on the association of traits with urban affinity. Our results suggest that bat species predisposed to urban life are characterized by low echolocation call frequencies, relatively long call durations, small body size and flexibility in the selection of the roost type. We conclude that simple indices are appropriate and practical, and propose to apply them to more taxa to improve our understanding of how urbanization favours or filters species with particular traits.

Radical pruning of distribution data may result in loss of knowledge (Response to Larsen & Shirey).

Larsen & Shirey (2020) criticised our analysis of latitudinal changes in butterfly phenology on the grounds of improper data management. We admit some imprecisions, but show that stringent reanalyses did not change the overall results. We also show that unreasonable treatment of data may result in critical information loss.

Method matters: pitfalls in analysing phenology from occurrence records.

Large occurrence datasets provide a sizable resource for ecological analyses, but have substantial limitations. Phenological analyses in Fric et al. (2020) were misleading due to inadequate curation and improper statistics. Reanalysing 22 univoltine species with sufficient data for independent analysis, we found substantively different macroscale phenological patterns, including later onset at higher latitude for most species.

Combining molecular and geographical data to infer the phylogeny of Lamiales and its dispersal patterns in and out of the tropics.

Lamiales is one of the most intractable orders of flowering plants, with several changes in family composition, and circumscription throughout history. The order is worldwide distributed, occurring in tropical forests and frozen habitats. In this study, a comprehensive phylogeny of Lamiales was reconstructed using DNA sequences. The tree was used to infer dispersal patterns, focusing on the tropics and extratropics. Molecular and species geographic data available from public repositories were combined to address both objectives. A total of 6,910 species, and 842 genera of Lamiales were sampled using the Python tool PyPHLAWD. The tree was inferred using RAxML, and recovered a monophyletic Lamiales. All 26 families were recovered as monophyletic with high support. The families Bignoniaceae, and Plantaginaceae are remarkable examples. The first emerged as monophyletic and included tribe Jacarandeae, while the later emerged as monophyletic in its sensu lato and included both the tribes Angelonieae, and Gratioleae. Distribution points for all species were retrieved from GBIF. After filtering, 1,136,425 records were retained. Species were coded as present in extratropical or tropical environments. The in and out of the tropics dispersal patterns were inferred using a maximum likelihood approach that identifies hidden rate changes. The model recovered higher rates of transition from extratropics to tropics, estimating two rates of state transitions. When ancestral states are considered, more discrete transitions from extratropics to tropics were observed. The extratropical state was also inferred for the crown node of Lamiales and old nested nodes, revealing a rare pattern of transitions to the tropics throughout the upper Cretaceous and Tertiary. A significant phylogenetic signal was recovered for the in and out of the tropics dispersal patterns, showing that state transitions are not frequent enough to erase the effect of tree structure on the data.

Thermal flexibility and a generalist life history promote urban affinity in butterflies.

Urban expansion poses a serious threat to biodiversity. Given that the expected area of urban land cover is predicted to increase by 2-3 million km2 by 2050, urban environments are one of the most widespread human-dominated land-uses affecting biodiversity. Responses to urbanization differ greatly among species. Some species are unable to tolerate urban environments (i.e., urban avoiders), others are able to adapt and use areas with moderate levels of urbanization (i.e., urban adapters), and yet others are able to colonize and even thrive in urban environments (i.e., urban exploiters). Quantifying species-specific responses to urbanization remains an important goal, but our current understanding of urban tolerance is heavily biased toward traditionally well-studied taxa (e.g., mammals and birds). We integrated a continuous measure of urbanization-night-time lights-with over 900,000 species' observations from the Global Biodiversity Information Facility to derive a comprehensive analysis of species-specific (N = 158 species) responses of butterflies to urbanization across Europe. The majority of butterfly species included in our analysis avoided urban areas, regardless of whether species' urban affinities were quantified as a mean score of urban affinity across all occurrences (79%) or as a species' response curve to the whole urbanization gradient (55%). We then used species-specific responses to urbanization to assess which life history strategies promote urban affinity in butterflies. These trait-based analyses found strong evidence that the average number of flight months, likely associated with thermal niche breath, and number of adult food types were positively associated with urban affinity, while hostplant specialism was negatively associated with urban affinity. Overall, our results demonstrate that specialist butterflies, both in terms of thermal and diet preferences, are most at risk from increasing urbanization, and should thus be considered in urban planning and prioritized for conservation.

Alkaloids Used as Medicines: Structural Phytochemistry Meets Biodiversity-An Update and Forward Look.

Selecting candidates for drug developments using computational design and empirical rules has resulted in a broad discussion about their success. In a previous study, we had shown that a species' abundance [as expressed by the GBIF (Global Biodiversity Information Facility)] dataset is a core determinant for the development of a natural product into a medicine. Our overarching aim is to understand the unique requirements for natural product-based drug development. Web of Science was queried for research on alkaloids in combination with plant systematics/taxonomy. All alkaloids containing species demonstrated an average increase of 8.66 in GBIF occurrences between 2014 and 2020. Medicinal Species with alkaloids show higher abundance compared to non-medicinal alkaloids, often linked also to cultivation. Alkaloids with high biodiversity are often simple alkaloids found in multiple species with the presence of 'driver species' and are more likely to be included in early-stage drug development compared to 'rare' alkaloids. Similarly, the success of an alkaloid containing species as a food supplement ('botanical') is linked to its abundance. GBIF is a useful tool for assessing the druggability of a compound from a certain source species. The success of any development programme from natural sources must take sustainable sourcing into account right from the start.

A new baseline for countrywide α-diversity and species distributions: illustration using >6,000 plant species in Panama.

Estimating α-diversity and species distributions provides baseline information to understand factors such as biodiversity loss and erosion of ecosystem services. Yet, species surveys typically cover a small portion of any country's landmass. Public, global databases could help, but contain biases. Thus, the magnitude of bias should be identified and ameliorated, the value of integration determined, and application to current policy issues illustrated. The ideal integrative approach should be powerful, flexible, efficient, and conceptually straightforward. We estimated distributions for >6,000 species, integrating species sightings (S) from the Global Biodiversity Information Facility (GBIF), systematic survey data (S2 ), and "bias-adjustment kernels" (BaK) using spatial and species trait databases (S2 BaK). We validated our approach using both locational and species holdout sets, and then applied our predictive model to Panama. Using sightings alone (the most common approach) discriminated relative probabilities of occurrences well (area under the curve [AUC] = 0.88), but underestimated actual probabilities by ~4,000%, while using survey data alone omitted over three-quarters of the >6,000 species. Comparatively, S2 BaK had no systematic underestimation, and substantially stronger discrimination (AUC = 0.96) and predictive power (deviance explained = 47%). Our model suggested high diversity (~200% countrywide mean) where urban development is projected to occur (the Panama Canal watershed) and also suggested this is not due to higher sampling intensity. However, portions of the Caribbean coast and eastern Panama (the Darién Gap) were even higher, both for total plant biodiversity (~250% countrywide mean), and CITES listed species. Finally, indigenous territories appeared half as diverse as other regions, based on survey observations. However, our model suggested this was largely due to site selection, and that richness in and out of indigenous territories was roughly equal. In brief, we provide arguably the best estimate of countrywide plant α-diversity and species distributions in the Neotropics, and make >6,000 species distributions available. We identify regions of overlap between development and high biodiversity, and improve interpretation of biodiversity patterns, including for policy-relevant CITES species, and locations with limited access (i.e., indigenous territories). We derive a powerful, flexible, efficient and simple estimation approach for biodiversity science.

Predicting the timing of ecological phenomena using dates of species occurrence records: a methodological approach and test case with mushrooms.

Spatiotemporal predictions of ecological phenomena are highly useful and significant in scientific and socio-economic applications. However, the inadequate availability of ecological time-series data often impedes the development of statistical predictions. On the other hand, considerable amounts of temporally discrete biological records (commonly known as 'species occurrence records') are being stored in public databases, and often include the location and date of the observation. In this paper, we describe an approach to develop spatiotemporal predictions based on the dates and locations found in species occurrence records. The approach is based on 'time-series classification', a field of machine learning, and consists of applying a machine-learning algorithm to classify between time series representing the environmental variation that precedes the occurrence records and time series representing the full range of environmental variation that is available in the location of the records. We exemplify the application of the approach for predicting the timing of emergence of fruiting bodies of two mushroom species (Boletus edulis and Macrolepiota procera) in Europe, from 2009 to 2015. Predictions made from this approach were superior to those provided by a 'null' model representing the average seasonality of the species. Given the increased availability and information contained in species occurrence records, particularly those supplemented with photographs, the range of environmental events that could be possible to predict using this approach is vast.

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.

Geographical range size and latitude predict population genetic structure in a global survey.

While genetic diversity within species is influenced by both geographical distance and environmental gradients, it is unclear what other factors are likely to promote population genetic structure. Using a machine learning framework and georeferenced DNA sequences from more than 8000 species, we demonstrate that geographical attributes of the species range, including total size, latitude and elevation, are the most important predictors of which species are likely to contain structured genetic variation. While latitude is well known as an important predictor of biodiversity, our work suggests that it also plays a key role in shaping diversity within species.

Clock-dated phylogeny for 48% of the 700 species of Crotalaria (Fabaceae-Papilionoideae) resolves sections worldwide and implies conserved flower and leaf traits throughout its pantropical range.

BACKGROUND: With some 700 species, the pantropical Crotalaria is among the angiosperm's largest genera. We sampled 48% of the species from all sections (and representatives of the 15 remaining Crotalarieae genera) for nuclear and plastid DNA markers to infer changes in climate niches, flower morphology, leaf type, and chromosome numbers. RESULTS: Crotalaria is monophyletic and most closely related to African Bolusia (five species) from which it diverged 23 to 30 Ma ago. Ancestral state reconstructions reveal that leaf and flower types are conserved in large clades and that leaf type is uncorrelated to climate as assessed with phylogenetically-informed analyses that related compound vs. simple leaves to the mean values of four Bioclim parameters for 183 species with good occurrence data. Most species occur in open habitats <1000 m alt., and trifoliolate leaves are the ancestral condition, from which unifoliolate and simple leaves each evolved a few times, the former predominantly in humid, the latter mainly in dry climates. Based on chromosome counts for 36% of the 338 sequenced species, most polyploids are tetraploid and belong to a neotropical clade. CONCLUSIONS: An unexpected finding of our study is that in Crotalaria, simple leaves predominate in humid climates and compound leaves in dry climates, which points to a different adaptive value of these morphologies, regardless of whether these two leaf types evolved rarely or frequently in our focal group.

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.

Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

UNLABELLED: • PREMISE OF THE STUDY: Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• METHODS: Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• KEY RESULTS: Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CONCLUSIONS: CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies.