Climatic niche variation in genetically distinct populations throughout the annual cycle for a migratory parulid bird, Cardellina pusilla
Data files
Jan 04, 2026 version files 425.67 KB
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README.md
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wiwa-96snp-genotypes.breeding.rubias_input.txt
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WIWA.env_vals.breed_nonbreeding.combined.csv
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WIWA.Genaro_samples107.Master_meta.txt
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WIWA107.FinalPanel.GP1_3.fixed.rubias_input.txt
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Abstract
In the current study, we investigate in greater detail the potential for among-population differentiation in climate use and preferences through the annual cycle. Our aims were to: (i) analyze variation in the realized climatic niche among the six genetically distinct populations of Cardellina pusilla, and (ii) determine whether the populations within the species have a specific niche-following or niche-switching migratory behavior, in order to understand how this could shape the migratory connectivity and population trends of each population.
Dataset DOI: 10.5061/dryad.4j0zpc8qx
Description of the data and file structure
The samples that correspond to the winter time were genotyped using SNPtype Assays (Fluidigm Inc.) on a FluidigmTM 96.96 IFC controller using a panel of 96 loci that Ruegg et al. (2014) determined to be strongly diagnostic of distinct genetic units. We then used the EP1 Array Reader and Fluidigm’s automated Genotyping Analysis Software (Fluidigm Inc.) to call alleles with a confidence threshold of 90 %. Each genotype was also visually inspected for potential irregularities, manually called, and uncertain genotype calls were removed from the analysis. Samples with missing genotypes at > 10 % of SNP assays were removed from the analyses. Each nonbreeding individual sampled was assigned to the known C. pusilla’s genetically distinct populations recovered by Ruegg et al. (2014) using the R package rubias (Moran & Anderson, 2018). This is a Bayesian hierarchical genetic identification approach that accounts for population structure and differences in the number of populations grouped as genetically differentiated. We consider a robust assignment as > 0.8 posterior probability of assignment to the inferred collection. The six genetically distinct populations were Coastal California (CC), California Sierra (CS), Pacific Northwest (PNW), Western Boreal (WB), Basin Rockies (BR) and Eastern Boreal (EB), following Ruegg et al. (2020).
Files and variables
File: WIWA.Genaro_samples107.Master_meta.txt
Description: This file contains the metadata for the newly SNP genotyped individuals
Variables
- BGP_ID: This is the sample name
- Collection_Number: The museum ID corresponding to sample name
- Collection_Date: The date a genetic sample was collected in the field
- Country: The country the sample was collected from
- Sample_Type: The genetic material DNA was extracted from (feather, toe-pad, blood, etc)
- Species: 4 code abbreviation for Wilson's Warbler (WIWA)
- State: The State/Province the nonbreeding bird was sampled in
- NearTown: The name of near town the nonbreeding bird was sampled in
- Latitude
- Longitude
- Sex: if known, sex of the bird in indicated (M=male, F=female, U= Undetermined,
- DAY: The day sample was collected (duplicate information in Collection_Date)
- MONTH: The month sample was collected (duplicate information in Collection_Date)
- YEAR: The year the sample was collected (duplicate information in Collection_Date)
- Stage: All samples were collected during the nonbreeding months (W=winter)
- Popassignment: Genetic assignment of nonbreeding birds to one of 6 Wilson's warblers distinct genetic breeding groups. If posterior probability of assignment was > 0.8, the breeding group is noted, and if it was < 0.8, assignment was denoted as uncertain and that individual was not used in subsequent analyses.
File: WIWA107.FinalPanel.GP1_3.fixed.rubias_input.txt
Description: The file includes the SNP genotypes for 107 nonbreeding birds for 96 SNP-type Fluidigm assays designed by Ruegg et al. (2014) and genotyped in this study. The format is specific for the R software package, rubias (Moran & Anderson, 2018).
Variables
- sample_type: In rubias formatting, all unknown samples, or in this case, nonbreeding birds, are mixture sample type (not reference sample type).
- repunit: Designated as NA, because as nonbreeding birds, we do not know the breeding origin (e.g. reporting unit or repunit), and want to assign them back to breeding origin
- collection: While nonbreeding birds were sampled from many locations , the collection can simply be designated as mixture as we want to determine mixture proportion from distinct genetic clusters without any prior
- indiv: Sample name associated with genotypes
- Columns AB_AK_02.1-SW_PRBO_4.2: The remaining columns are the genotypes, 2 columns per named assay ("$assay_name".1 = first allele, and "$assay_name".2 = second allele). The numbers in the columns refer to nucleotides (1 = A, 2 = C, 3 = G, 4 = T, and NA is missing data).
File: WIWA.env_vals.breed_nonbreeding.combined.csv
Description: For niche calculations, we extracted WorldClim historic climate data from the monthly time series of precipitation and temperature that spans from 1960 to 2018 with a spatial resolution of 2.5 arc minutes using R software.
Variables
- species: Scientific name of Wilson's warbler
- lon: Longitude
- lat: Latitude
- GeneticCluster: This is identical to the Popassignment column in the meta data. However this file includes breeding and nonbreeding genetic samples
- Stage: Breeding and nonbreeding
- precip: Average mean precipitation extracted in R from the Latitude/Longitude during breeding season months (June, July) or nonbreeding season months (November, December, January and February).
- tmin: Average temperature minimum extracted in R from the Latitude/Longitude during breeding season months (June, July) or nonbreeding season months (November, December, January and February).
- tmax: Average temperature max extracted in R from the Latitude/Longitude during breeding season months (June, July) or nonbreeding season months (November, December, January and February).
File: wiwa-96snp-genotypes.breeding.rubias_input.txt
Description: The file includes the SNP genotypes for 407 breeding birds for 96 SNP-type Fluidigm assays designed by Ruegg et al. (2014) and genotyped in the 2014 study. The format is specific for the R software package, rubias (Moran & Anderson, 2018). This data is provided with dryad submission and Github page associated with Ruegg et al. 2014, but included here as well.
Variables
- sample_type: Breeding birds are defined as reference birds in sample_type
- repunit: refers to one of the six distinct breeding units delineated in Ruegg et al. 2020 (Coastal California: CoastalCA, BasinRockies: RockyMtn, Eastern Boreal: Eastern, California Sierras: Sierra, Pacific Northwest: PacNorthwest, and Western Boreal).
- collection: The NearTown the sample was collected at
- indiv: Sample name associated with genotypes
- Columns AB_AK_02.1-SW_PRBO_4.2: The remaining columns are the genotypes, 2 columns per named assay ("$assay_name".1 = first allele, and "$assay_name".2 = second allele). The numbers in the columns refer to nucleotides (1 = A, 2 = C, 3 = G, 4 = T, and NA is missing data).
Code/software
Rubias is an R software program that probabilistically assigns individuals to specific reporting units (i.e. genetic clusters diagnosed in the breeding region). Originally used for fish stock identification, we've co-opted it for bird genoscapes.
Access information
Other publicly accessible locations of the data:
