Data from: Extreme elevational migration spurred cryptic speciation in giant hummingbirds
Data files
Apr 23, 2024 version files 80.66 KB
Abstract
The eco-evolutionary drivers of species niche expansion or contraction are critical for biodiversity but challenging to infer. Niche expansion may be promoted by local adaptation or constrained by physiological performance trade-offs. For birds, evolutionary shifts in migratory behavior permit broadening of the climatic niche by expansion into varied, seasonal environments. Broader niches can be short-lived if diversifying selection and geography promote speciation and niche subdivision across climatic gradients. To illuminate niche breadth dynamics, we can ask how ‘outlier’ species defy constraints. Of the 363 hummingbird species, the giant hummingbird (Patagona gigas) has the broadest climatic niche by a large margin. To test the roles of migratory behavior, performance trade-offs, and genetic structure in maintaining its exceptional niche breadth, we studied its movements, respiratory traits, and population genomics. Satellite and light-level geolocator tracks revealed an >8,300-km loop migration over the Central Andean Plateau. This migration included a three-week, ~4,100 m ascent punctuated by upward bursts and pauses, resembling the acclimatization routines of human mountain climbers, and accompanied by surging blood-hemoglobin concentrations. Extreme migration was accompanied by deep genomic divergence from high-elevation resident populations, with decisive postzygotic barriers to gene flow. The two forms occur side-by-side but differ almost imperceptibly in size, plumage, and respiratory traits. The high-elevation resident taxon is the world’s largest hummingbird, a new species that we describe and name here. The giant hummingbirds demonstrate evolutionary limits on niche breadth: When the ancestral niche expanded due to evolution (or loss) of an extreme migratory behavior, speciation followed.
README: Extreme elevational migration spurred cryptic speciation in giant hummingbirds
Williamson et al. 2024, Extreme elevational migration spurred cryptic speciation in giant hummingbirds, PNAS
This data deposit contains raw data used in a study of latitudinal and elevational migration, blood physiology, morphology, and genomics of giant hummingbirds (Patagona spp.) in South America. In our paper, we report the world's longest hummingbird migration with the most extreme elevational shift, and describe the world's largest hummingbird species, a distinct species that was previously undescribed. Field sampling spanned Chile to Peru and involved collaborative teams from the Museum of Southwestern Biology at the University of New Mexico, Centro de Ornitología y Biodiversidad (CORBIDI), and Pontificia Universidad Católica de Chile.
DATASETS
File name: WilliamsonEtAl2024_PNAS_patagona_blood_dryad.csv
Description: Raw blood data used in Williamson et al. 2024. In addition to locality and individual identifiers provided for sampled individuals, we report data on blood parameters analyzed in our paper: six blood traits known to affect O2 carrying functions (hemoglobin concentration ([Hb]), hematocrit (Hct), total red blood cell count (TRBC), mean cell volume (MCV), mean cell hemoglobin (MCH), and mean cell hemoglobin concentration (MCHC)).
File name: WilliamsonEtAl2024_PNAS_patagona_morpho_dryad.csv
Description: Raw morphological data used in Williamson et al. 2024. In addition to locality and individual identifiers provided for sampled individuals, we report measurements for important morphological traits (bill length, wing chord, tail length, tarsus length) taken from wild-caught individuals and museum specimens.
METADATA
File name: WilliamsonEtAl2024_PNAS_patagona_blood_dryad_METADATA.csv
Description: The metadata .csv file describes each column and type of data included in the full data file, "WilliamsonEtAl2024_PNAS_patagona_blood_dryad.csv".
File name: WilliamsonEtAl2024_PNAS_patagona_morpho_dryad_METADATA.csv
Description: The metadata .csv file describes each column and type of data included in the full data file, "WilliamsonEtAl2024_PNAS_patagona_morpho_dryad.csv".
DATA ARCHIVING
Analysis code is available on GitHub: https://github.com/jlwilliamson/jlwilliamson-patagona-blood-migration-genomics; DOI: 10.5281/zenodo.10975589. See GitHub repository README.md file for full description of all scripts and code.
This project would not have been possible without the tremendous efforts of museum collections. We are deeply grateful to the following collections for contributions to this project: Museum of Southwestern Biology, American Museum of Natural History, Centro de Ornitología y Biodiversidad, Cornell University Museum of Vertebrates, Louisiana State University Museum of Natural Science, Florida Museum of Natural History, University of Kansas Biodiversity Institute, Harvard University Museum of Comparative Zoology, Smithsonian National Museum of Natural History, and the University of Washington Burke Museum. Data are linked to vouchered specimens. Specimen records are accessible in the Artcos database (https://www.arctosdb.org) or in specific collections databases, as appropriate.
Data are archived on Dryad: https://doi.org/10.5061/dryad.44j0zpcnp
Questions? Contact me at jlw432 [at] cornell.edu.
Methods
Data were collected from wild-caught individuals in the field and from museum specimens spanning 154 years. We used satellite transmitters and geolocators to track giant hummingbirds from sea-level breeding areas in Chile to non-breeding areas. We collected respiratory trait data from >175 individuals across the elevational range and from Chile to Peru from 2006–2021. We analyzed genomic sequences from 101 individuals (whole genomes and ultra-conserved elements) across the geographic range; genomic data were taken from flash-frozen tissues and toe pads of historic museum specimens. All analysis code and scripts may be found on GitHub (https://github.com/jlwilliamson/jlwilliamson-patagona-blood-migration-genomics; DOI: 10.5281/zenodo.10975589); genomic data on Sequence Read Archive; and migration data on MoveBank (Project ID 3594892529). Specimen data are available in the Arctos database (www.arctosdb.org).