DOI: 10.5061/dryad.4j0zpc8qx
title: Climatic niche variation in genetically distinct populations throughout the annual cycle for a migratory parulid bird, <em>Cardellina pusilla</em>

description: 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. 
description: # Climatic niche variation in genetically distinct populations throughout
 the annual cycle for a migratory parulid bird, *Cardellina pusilla*
 Dataset DOI: [10.5061/dryad.4j0zpc8qx](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
 &gt; 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 &gt; 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 &gt; 0.8, the breeding group is noted, and if it was &lt; 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: *
 [https://github.com/eriqande/wiwa-popgen](https://github.com/eriqande/wiwa-popgen) * doi:**[10.5061/dryad.j5d33](https://doi.org/10.5061/dryad.j5d33 "Link to external resource: 10.5061/dryad.j5d33")**