DOI: 10.5061/dryad.1jwstqk3t
title: Data from: Feather macrostructure corresponds to increased temperature not urbanization across California

description: Urban environments are often associated with resource and environmental
 differences, providing potential novel selection pressures compared to
 adjacent unmodified landscapes. While these characteristics (e.g., heat
 islands, reduced vegetation) can contribute to differences in certain
 behaviors, morphology, or physiological traits, there is mixed evidence on
 how and to what extent populations are responding. In this study, we
 compared the feather morphology of Dark-eyed Junco (Junco hyemalis)
 populations established across an urbanization gradient. We examined
 whether differential temperature regimes, related to urbanization,
 correspond with significant variations in the proportion of down. We
 sampled ventral and dorsal feathers from 256 individuals throughout
 central and southern California at varying degrees of urbanization. Dorsal
 feathers had a higher proportion of down compared to ventral feathers, but
 did not differ between populations. Urbanization did not significantly
 correlate with feather morphology. Ventral feathers had a greater
 proportion of down as the range of temperature increased, but this
 correlation was marginal. Our results show that despite urbanization
 altering fine-scale habitat conditions, these did not correspond with
 rapid feather morphological variations. Whether this is the case for other
 feather types or across species is still unknown, but it would provide
 insight into the complex effects of urbanization on wildlife biology.
description: We captured 256 Dark-eyed Juncos across central and southern
 California during the 2022 (n = 47) and 2023 (n = 209) breeding season
 (February–August) between 07:00 and 12:00. We mist netted at six locations
 on average per day, and at each location, the net was open for 30 min
 during which playbacks were used to attract juncos in the area. Playbacks
 consisted of singing juncos from Los Angeles. We color-banded each junco
 with a unique three-color band and one USGS aluminum band combination and
 recorded various metrics as part of a long-term study. Metrics included
 bill dimensions (width, depth, and length), body weight, wing chord
 length, tail length, and tarsus length. We quantified sex differences
 based on the presence of brood patch or cloacal protuberance, as well as
 plumage characteristics. The juncos were aged as after second year (ASY),
 second year (SY), after hatch year (AHY), or hatch year (HY) based on
 known plumage and molt limit. Data from HYs and recaptured juncos were
 excluded from this study. We collected 2–6 contour
 feathers from male and female adult juncos in definitive basic plumage. To
 sample feathers, banders removed 1–3 feathers from the anterior region of
 the mantle (dorsal) and 1–3 feathers from the anterior region of the
 breast (ventral) of each bird. Feathers were stored dry in envelopes until
 processing. Our sites consist of the University of California, Los Angeles
 (UCLA, n = 121), the University of California, San Diego (UCSD, n = 22),
 the University of California, Santa Barbara (UCSB, n = 18), Occidental
 College (Occ, n = 22), San Francisco State University (SFSU, n = 6), Santa
 Monica Parks (SM Parks, n = 9), Los Angeles Parks (LA Parks, n = 10), as
 well as nearby mountain regions in the Santa Monica Mountains (SMM,
 n = 9), and the Angeles National Forest (ANF, n = 35; Fig. 1). The minimum
 distance between our sampling sites was 4700 m (between UCLA and SM
 Parks). This distance is further than the expected maximum distance of 174
 m that a junco will fly during the breeding season, reducing the
 possibility of the same individual moving between sites. Coordinates of
 each banding site were recorded and used to obtain corresponding
 environmental and climatic conditions. All methods were
 carried out by the relevant ARRIVE methods required for observational
 animal research and by institutional guidelines and regulations. Animal
 handling in this study adhered to protocols approved by the Institutional
 Animal Care and Use Committee (IACUC) of UCLA (ARC-2018-007-AM 004).
 Banding efforts were conducted in compliance with the Ethics and
 Responsibilities of Bird Banders published by the US Geological Survey
 Federal Bird Banding Laboratory (Permit #23809) and as outlined by the
 State of California Department of Fish and Wildlife Scientific Collecting
 Permit—Specific Use (S-191300002-20288-001-02) for taking/possession of
 wildlife for scientific purposes. We calculated the
 proportion of the feather surface area that consists of plumulaceous barbs
 (henceforth “proportion of down”) and then averaged these values for each
 bird. To determine the proportion of down, we scanned each feather using a
 CanoScan LiDE 400 Color Image Scanner at a resolution of 600 dots per inch
 (dpi). When scanning the images, we placed the feathers on a transparency
 sheet labeled with a 10 mm scale and weighed each feather down with a
 0.13–0.19 mm-thick coverslip. A colored sheet of cardstock laid on top
 maximized the contrast between the desired region and the
 background. To measure the relative proportion of down,
 we developed color thresholds using a hue-saturation-brightness color
 space in ImageJ for the ventral and dorsal feathers in order to increase
 repeatability and reduce potential observer bias. For dorsal feathers, a
 yellow (#ebd798) background and a white (#e8e7e5) background provided the
 best contrast to measure the pennaceous region and total surface area,
 respectively (Fig. 2a, b). To analyze ventral feathers, we measured the
 proportion of down and total surface area against a red (#c71934)
 background (Fig. 2c). We then selected and measured the area above the set
 color threshold. To calculate the area of down in dorsal feathers, we
 subtracted the area of pennaceous barbs from the total area. We then
 calculated the proportion of down for dorsal and ventral feathers by
 dividing the area of down by the total surface area.
 Using a subset of feathers, our values correlated with previously
 published metrics used to measure the proportion of down and pennaceous
 feathers based on a Kendall’s rank correlation tau, where the color
 difference measures of surface area were strongly correlated with the
 length of down/pennaceous regions along the shaft of the feathers
 (τ = 0.388, p &lt; 0.001, n = 100)[23343545]. We selected our metric
 to reduce potential observer bias when quantifying feather barbs. We
 assessed repeatability of our measurements with feathers from museum
 specimens to reduce stress on living birds. Repeatability of our
 measurements was included to account for sampling bias. Museum specimens
 provided by the Occidental College Moore Laboratory of Zoology were all
 collected within five years of our study from Los Angeles (Specimen
 numbers: MLZ: Bird:70290; MLZ: Bird:70291; MLZ: Bird:70222; MLZ:
 Bird:70246; MLZ: Bird:70221; MLZ: Bird:70292). We randomly sampled a
 different number of feathers from each specimen (n = 5, 6, 8, 9, 12, 15)
 and calculated the proportion of down using the methods previously
 described. We then ran a linear model for the variance of the proportion
 of down of dorsal feathers against sample size, defined as the number of
 feathers sampled from a given specimen. We repeated this model for ventral
 feathers. Temperature data from the PRISM Climate Group
 was available using the prism 0.2.0 package in R[48]. Our climatic
 variables include mean temperature (Tmean: μ = 17.3 ºC, SD = 1.1,
 range = 13.4 to 18.9, CV = 6.28%) and the temperature range, based on the
 difference between the maximum and minimum temperatures (ΔTemp: μ = 9.9
 ºC, SD = 1.7, range = 6.1 to 13.6, CV = 16.90%; Fig. 1). For each
 variable, we extracted averages over 30 years (1991–2020) at a resolution
 of 800 m using the terra 1.7, sp 2.0, and sf 1.0 packages. Selected values
 capture the broadest conditions but may not accurately represent the
 strongest selective pressures. Temperature extremes, for instance, could
 be more impactful, but were not available for our study. Measurements of
 urbanization are based on the Built-Up index (BU) calculated using raster
 images from Collection 2 Level 2 Landsat 8 data available from the U.S.
 Geological Survey Earth Resources Observation and Science (EROS) Center
 Science Processing Architecture (ESPA). These raster images are at a 30 m
 resolution within one month of the sampling date, where cloud cover was
 less than 8%. We used QGIS[52] to calculate the BU index.
 At each sampling coordinate, we then averaged the BU index within
 a 50 m radius (μ = −0.236, SD = 0.095, range = −0.531 to −0.041,
 CV = 40.33%), which represents the average territory size of Dark-eyed
 Juncos recorded by previous literature as well as our observations. This
 method of averaging the BU index is most accurately able to capture the
 degree of urbanization of our study sites. Detailed information on the BU,
 Tmean, and ΔTemp for different sites is provided (Supplemental Table
 S1).
description: # Feather macrostructure corresponds to increased temperature, not
 urbanization, across California
 [https://doi.org/10.5061/dryad.1jwstqk3t.](https://doi.org/10.5061/dryad.1jwstqk3t) Comparison of feather macrostructures (plumulaceous barbs and pennaceous barbs) found in dark-eyed juncos. Temperature values include the mean, minimum, maximum, and range from 1991 to 2020, as well as from 2021 to 2022. Built-up Index (BU) values were presented based on average values within a 50m radius around the banding site and calculated as the difference between NDBI and NDVI.  Relevant morphometrics per individual are also included, and the federal band number is listed. ## Description of the data and file structure The dataset consists of data files: dorsalfeather.csv and ventralfeather.csv. Standard morphometric values are provided and measured in (mm), except weight, measured in (g). Federal band numbers and band colors are included, as well as site metrics. "Eumelanin Proportion" refers to plumulaceous barbs, while pheomelanin refers to pennaceous barbs. * X = Row number - Reference.Number = Sample Number * Scan.. = Scan Number - USGS.Band = Federal band number * Location: ANF = Angeles National Forest, UCLA = UC Los Angeles, UCSD = UC San Diego, UCSB = UC Santa Barbara, SFSU = San Francisco State University, Proper names of parks: Barnsdall; Paramount ; Occidental; Stunt Ranch; Tongva; Clover; Douglas;Mem orial; La Brea Tar Pits; UCLA William Clark Memorial Library - Band.Color: L = Lavendar, Al = Feberal Aluminum Band, DB = Dark Blue, DG = Dark Green, LB = Light Blue, LG = Light Green, R = Red, LW = Lavendar/White, Y = Yellow, O = Orange, B = Black, W = White, HPDB = Hot Pink/Dark Blue, DBR = Dark Blue/Red, LGL = Light Green/Lavendar, RY = Red/Yellow, BW = Black/White, RW = Red/White * Age: AHY = After Hatch Year, ASY = After Second Year, SY = Second Year - Sex: M = Male, F = Female, U = Unknown * lat = Latitude - lon = Longitude * Name = Researcher-selected name for monitoring - Total.A. rea..mm.. 2 = Total Surface Area of Feathers (mm) * Pheomelaninated.Area..mm.. 2.. = Surface Area of Pennaceous barbs (mm) - Eumelaninated.Area..mm.. 2 = Surface Area of Plumulaceous barbs (mm) * All.Eumelanin.Proportion = Relative proportion of Plumulaceous barbs (%) - New_Recap: N = Newly captured/banded bird, R = Recaptured bird/previously banded * Urban = Habitat type - Sites: ANF = Angeles National Forest, UCLA = UC Los Angeles, UCSD = UC San Diego, UCSB = UC Santa Barbara, SFSU = San Francisco State University, LA Parks = Barnsdall; Tongva; Clover; Douglas; Memorial; La Brea Tar Pits; UCLA William Clark Memorial Library, SMM = Stunt Ranch; Paramount, Occidental = Occidental College * Weight = Bird mass (g) - Tarsus = Tarsus length (mm) * Wing = Wing length  (mm) - Tail = Tail length (mm) * Culmen = Nares to tip of bill (mm) - Bill_Depth = Height at top of nares to bottom of bill (mm) * Bill_Width =Length across bill at nares (mm) - Measurer: WAM = Wilmer Amaya-Mejia, ES = Ellis Song, SF = Sara Freimuth, MW = Mars Walters, ED = Ellie Diamant, SZ = Suu Zhou * Condition = Body Condition (residuals of mass vs tarsus length) - tmean_30yrnorm = Mean temperature (C) averaged across 30 years * tmean_2021 = Mean temperature (C) of 2021 - tmean_2022 = Mean temperature (C) of 2022 * tmean_annual = Mean annual temperatures (C) - NDVI_50m = Built-Up Index value averaged within 50m of lat/long coordinates * Elevation = Elevation at lat/long coordinates (m) - tmax_(30yrnorm/2021/2022) = Maximum temperatures (C) across 30 years, in 2021, and i022 * tmin_(30yrnorm/2021/2022) = Minimum temperature (C) across 30 years, in 2021, and 2022 - range_30yrnorm = Max temp - Min temp across 30 years at each lat/long coordinate * range_annual = Annual Max temp - Min temp per year at each lat/long coordinate #### Sharing/Accessing information Data can be assessed upon request.  Data was derived from the following sources: * Temperature Data * [https://prism.oregonstate.edu/](https://prism.oregonstate.edu/)  * Urbanization Data * [https://www.usgs.gov/earth-resources-observation-and-science-eros-center](https://www.usgs.gov/earth-resources-observation-and-science-eros-center)