Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

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Because the tropical regions of America harbor the highest concentration of butterfly species, its fauna has attracted considerable attention. Much less is known about the butterflies of southern South America, particularly Argentina, where over 1,200 species occur. To advance understanding of this fauna, we assembled a DNA barcode reference library for 417 butterfly species of Argentina, focusing on the Atlantic Forest, a biodiversity hotspot. We tested the efficacy of this library for specimen identification, used it to assess the frequency of cryptic species, and examined geographic patterns of genetic variation, making this study the first large-scale genetic assessment of the butterflies of southern South America. The average sequence divergence to the nearest neighbor (i.e. minimum interspecific distance) was 6.91%, ten times larger than the mean distance to the furthest conspecific (0.69%), with a clear barcode gap present in all but four of the species represented by two or more specimens. As a consequence, the DNA barcode library was extremely effective in the discrimination of these species, allowing a correct identification in more than 95% of the cases. Singletons (i.e. species represented by a single sequence) were also distinguishable in the gene trees since they all had unique DNA barcodes, divergent from those of the closest non-conspecific. The clustering algorithms implemented recognized from 416 to 444 barcode clusters, suggesting that the actual diversity of butterflies in Argentina is 3%–9% higher than currently recognized. Furthermore, our survey added three new records of butterflies for the country (Eurema agave, Mithras hannelore, Melanis hillapana). In summary, this study not only supported the utility of DNA barcoding for the identification of the butterfly species of Argentina, but also highlighted several cases of both deep intraspecific and shallow interspecific divergence that should be studied in more detail.