AimMassive 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.LocationThe American tropics.MethodsAs 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.ResultsAltitudinal 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 conclusionOpen 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.

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Considerable inter- and intraspecific variation with respect to the quantity and composition of plant natural products exists. The processes that drive this variation remain largely unknown. Understanding which factors determine chemical diversity has the potential to shed light on plant defenses against herbivores and diseases and accelerate drug discovery. For centuries, Cinchona alkaloids were the primary treatment of malaria. Using Cinchona calisaya as a model, we generated genetic profiles of leaf samples from four plastid (trnL-F, matK, rps16, and ndhF) and one nuclear (ITS) DNA regions from twenty-two C. calisaya stands sampled in the Yungas region of Bolivia. Climatic and soil parameters were characterized and bark samples were analyzed for content of the four major alkaloids using HPLC-UV to explore the utility of evolutionary history (phylogeny) in determining variation within species of these compounds under natural conditions. A significant phylogenetic signal was found for the content of two out of four major Cinchona alkaloids (quinine and cinchonidine) and their total content. Climatic parameters, primarily driven by changing altitude, predicted 20.2% of the overall alkaloid variation, and geographical separation accounted for a further 9.7%. A clade of high alkaloid producing trees was identified that spanned a narrow range of altitudes, from 1,100 to 1,350 m. However, climate expressed by altitude was not a significant driver when accounting for phylogeny, suggesting that the chemical diversity is primarily driven by phylogeny. Comparisons of the relative effects of both environmental and genetic variability in determining plant chemical diversity have scarcely been performed at the genotypic level. In this study we demonstrate there is an essential need to do so if the extensive genotypic variation in plant biochemistry is to be fully understood.