AVONET: morphological, ecological and geographical data for all birds

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

The impacts of fine-tuning, phylogenetic distance, and sample size on big-data bioacoustics

Vocalizations in animals, particularly birds, are critically important behaviors that influence their reproductive fitness. While recordings of bioacoustic data have been captured and stored in collections for decades, the automated extraction of data from these recordings has only recently been facilitated by artificial intelligence methods. These have yet to be evaluated with respect to accuracy of different automation strategies and features. Here, we use a recently published machine learning framework to extract syllables from ten bird species ranging in their phylogenetic relatedness from 1 to 85 million years, to compare how phylogenetic relatedness influences accuracy. We also evaluate the utility of applying trained models to novel species. Our results indicate that model performance is best on conspecifics, with accuracy progressively decreasing as phylogenetic distance increases between taxa. However, we also find that the application of models trained on multiple distantly related species can improve the overall accuracy to levels near that of training and analyzing a model on the same species. When planning big-data bioacoustics studies, care must be taken in sample design to maximize sample size and minimize human labor without sacrificing accuracy

Data from: Resolving a phylogenetic hypothesis for parrots: implications from systematics to conservation

Advances in sequencing technology and phylogenetics have revolutionised avian biology by providing an evolutionary framework for studying natural groupings. In the parrots (Psittaciformes), DNA-based studies have led to a reclassification of clades, yet substantial gaps remain in the data gleaned from genetic information. Here we provide an overview of published genetic data of parrots, characterise sampling depth across the phylogeny, and evaluate support for existing systematic treatments. We inferred a concatenated tree with 307 species from a 30-gene supermatrix. We recovered well-supported relationships among recently proposed clades. Taxonomic groups were more stable towards the base of the tree and increased sampling will be required to clarify relationships at the tips, particularly below the generic level. Only a third of species have been sampled intraspecifically in population genetic or phylogeographic surveys. Intraspecific sampling has not been geographically or phylogenetically even across Psittaciformes, especially poor in the cockatoos, Southeast Asia, and parts of Australo-Papua. Threatened species are poorly sampled in the Neotropics. We highlight where effort should be focused to improve sampling based on geography and conservation status. In sum, phylogenetic relationships among the major parrot clades are robust, but relationships within and between genera and species provide opportunities for future investigations

Data from: Genomic divergence in allopatric Northern Cardinals of the North American warm deserts is linked to behavioral differentiation

Biogeographic barriers are thought to be important in initiating speciation through geographic isolation, but they rarely indiscriminately and completely reduce gene flow across the entire community. Understanding which species’ attributes regulate a barrier could help elucidate how speciation is initiated and isolation maintained. Here, we investigated the association of behavioral isolation on population differentiation in Northern Cardinals (Cardinalis cardinalis) distributed across the Cochise Filter Barrier, a region of transitional habitat which separates the Sonoran and Chihuahuan deserts of North America. Using genome-wide markers, we modeled demographic history by fitting the data to isolation and isolation-with-migration models. The best-fit model indicated that desert populations diverged in the Pleistocene with low, historic, and asymmetric gene flow across the barrier. We then tested behavioral isolation using reciprocal call-broadcast experiments to compare song recognition between deserts, controlling for song dialect changes within deserts. We found that male Northern Cardinals in both deserts were most aggressive to local songs and failed to recognize across-barrier songs. A correlation of genomic differentiation despite historic introgression and strong song discrimination is consistent with a model where speciation is initiated across a barrier and maintained by behavioral isolation

Subset_XX_Genes_100bp.fasta Alignment Files

This zip file contains 15 fasta-formatted alignment files. These are supermatrices produced from GenBank sequence data. They are subsets of the main supermatrix (a.k.a. Subset_01) where each subset requires that all individual species retained in the supermatrix have at least XX genes, with XX ranging from 01 to 15

best_scheme_Subset_XX_Genes_rcluserf.part Partition files

This zip file contains our results from PartitionFinder2. It gives the nucleotide partitions for use in later phylogenetic analyses such as RAxML. Each file is associated with one of the gene subsets from "Subset_XX_Genes_100bp.fasta Alignment Files.zip"

extractReferencesFromGenbank

This Python script is used to extract all of the reference information from a large GenBank-formatted (.gb) file and place it into a CSV for ease of access later on. This was used to create Supplementary Table 1

Map Making Scripts

This zip file contains within it three R scripts which are used to make the ASCII-formatted Raster files used in our manuscript. For the purposes of our research, these are used to describe IUCN status, within-species sampling, GenBank sampling, and species richness of parrot species per spatial grid cell

RunPartitionFinder_Subset_XX_Genes_rclusterf.cfg Config Files

This zip file contains config files for the program PartitionFinder2. They are associated with the gene subsets found in "Subset_XX_Genes_100bp.fasta Alignment Files.zip"

Intraspecific_Genetic_Sampling_Citations

This CSV file represents our dataset used to determine whether parrot species had intraspecific within-species genetic sampling done. If within-species sampling was found, we cite the reference. We also note situations in which we are aware of ongoing but unpublished work on this subject. In some cases due to taxonomic uncertainty, whether a species has been sampled is unclear, indicated by a "?"