DOI: 10.5061/dryad.rr4xgxdm9
title: Data from: Sex- and age-related differences in post-breeding molt phenology are phylogenetically and ecologically widespread in passerines

description: Assessment of within-population variation in the timing and duration of
 molt is crucial to understanding how molt overlaps and interacts with
 other important phases of the avian annual cycle, including breeding and
 migration. We investigated the effects of sex and adult age on phenology
 of the post-breeding prebasic molt in an assemblage of migratory songbird
 species captured during banding operations at Powdermill Avian Research
 Center in southwestern Pennsylvania, USA. Across all species examined,
 males consistently initiated molt earlier than females (14 of 15 species),
 and young adults hatched the previous year consistently initiated molt
 earlier than experienced older adults (13 of 13 species). Sex also had a
 weaker but significant effect on molt duration, with females completing
 molt more rapidly than males in 67% of the species examined. Adult age, in
 contrast, had no significant effect on molt duration. A review of the
 literature indicates that similar patterns are observed in the
 post-breeding molt of passerines worldwide, with females showing delayed
 but more rapid molt in diverse geographic, phylogenetic, and ecological
 contexts. The delayed onset of post-breeding molt in female passerines
 probably reflects either (1) their generally greater reproductive effort
 in egg-laying, incubation, and brooding of young, or (2) sex-specific
 physiological constraints imposed by the shared neuroendocrine mechanisms
 that regulate both avian reproduction and molt. The shorter duration of
 post-breeding molt in females may partially reflect their smaller body
 size and shorter flight feathers. Earlier onset of molt in young adults
 probably reflects their worn retained juvenile plumage, lower probability
 of successful nesting, and early termination of their initial breeding
 season. Regardless of the causes, strong sex- and age-based differences in
 the phenology of post-breeding molt are likely to produce cascading
 trade-offs with other aspects of the songbird annual cycle, including the
 timing of breeding, late-season parental care, and migration.
description: <strong>Collection of Molt Data</strong>
 Molt data analyzed for this study were collected from 1986–2004
 in conjunction with year-round mist-netting and bird-banding operations at
 Powdermill Avian Research Center (40.1637°N, 79.2674°W), the field station
 of Carnegie Museum of Natural History, in southwestern Pennsylvania, USA.
 After identifying each captured individual to species and banding it with
 a uniquely numbered U. S. Bird Banding Laboratory band, we determined its
 sex using either plumage characteristics (for sexually dimorphic species)
 or the presence of a brood patch or cloacal protuberance. Adults were
 age-classified as either SY (second-year birds hatched the previous
 calendar year) or ASY (after-second-year birds hatched two or more
 calendar years ago), based on wing molt limits (Mulvihill 1993) and other
 plumage criteria that have since become standard in passerine aging (Pyle
 2022). Each individual was then assigned a total flight-feather molt score
 (0–90) based on the molt stage of the 18 remiges (9 primaries and 9
 secondaries) on the right wing. We used the 0–5 molt scoring system of
 Ginn and Melville (1983): 0 = old feather, 1 = old feather missing or new
 pin feather, 2 = new feather emerging from sheath up to one-third grown, 3
 = new feather between one-third and two-thirds grown, 4 = new feather more
 than two-thirds grown but still sheathed at base, and 5 = fully grown new
 feather with no trace of the sheath at its base. All assignments of sex,
 age, and molt score were performed by a single individual. In the present
 study we focused on species that undergo a complete post-breeding prebasic
 molt on their breeding grounds and excluded individuals that showed
 evidence of partial or suspended molts. Our analysis of
 sex differences was limited to species with at least 25 records of
 known-sex individuals in active molt—i.e., with molt scores 1–89. In
 addition, we selected species with at least some data from birds
 recaptured and re-scored during the same molt cycle, as data from
 recaptured individuals greatly improves estimation of molt phenology
 (Boersch-Supan et al. 2024, Mumme et al. 2025). A total of 15 species
 representing 5 families, all passerines that are either completely (13
 species) or partially migratory (2 species), met these criteria for
 inclusion. Total sample size available for analysis of sex differences was
 2468 molt records—1253 from males and 1215 from females.
 Similarly, the dataset for our analysis of age differences was
 based on species for which there was at least some recapture data and at
 least 25 records of actively molting known-age adults classified as SY or
 ASY. Thirteen species representing 5 families, all passerines that at
 Powdermill are completely migratory, met these criteria for inclusion, and
 the final dataset comprised 1552 molt records—749 from SY birds and 803
 from ASY individuals. <strong>Statistical
 Analysis</strong> Flight-feather molt in most
 temperate-zone passerines is a nonlinear sigmoidal process; it progresses
 gradually at the beginning and end of molt, when only a few flight
 feathers are being replaced, but more rapidly during intermediate stages,
 when multiple flight feathers are being replaced simultaneously (Dawson
 and Newton 2004, Newton 2009, Mumme et al. 2021, Guallar and Quesada
 2023). To help linearize the molt process and make it more amenable to
 statistical modeling, we followed Mumme et al. (2025) by transforming
 total molt scores as arcsine (square root[molt score/90]), and then
 rescaling the resulting transformed values as a proportion between 0 and
 1. Using this transformed molt index, we then estimated molt start and
 molt duration separately for the four sex and age categories—males,
 females, SY birds, and ASY birds—using the mixed-model extension of Pimm
 regression (Pimm 1976) developed by Mumme et al. (2025). In this approach,
 ordinal capture date (the dependent <em>y</em> variable) is
 regressed on the transformed molt index (the independent
 <em>x</em> variable), and bird-year—the unique band number
 coupled with the year captured—is included as a random effect to account
 for the non-independence arising from multiple measures of molt obtained
 from the same individual during a single molt cycle. This mixed-model
 extension of Pimm regression, which allows molt duration and start date to
 be estimated directly from the slope and intercept of the resulting
 regression equation, is the most appropriate method for analyzing the
 Powdermill data; it is unaffected by molt-dependent sampling bias, which
 is pronounced in the Powdermill data, and produces accurate and unbiased
 estimates of molt phenology whenever molt data are collected across a
 broad range of dates (Mumme et al. 2025). We examined
 the statistical effects of sex on molt phenology by additional Pimm mixed
 models in which sex, and the interaction between sex and transformed molt
 index, were included as fixed effects. We interpreted significant main
 effects of sex on ordinal date as evidence of sex-based differences in the
 onset of molt, and significant interactions between sex and transformed
 molt index as evidence of sex-based differences in molt duration. We used
 comparable mixed models that included age, and its interaction with
 transformed molt index, to test the effects of adult age on molt
 phenology. All mixed models were built using JMP Pro 17.2 (SAS
 Corporation, Cary, NC USA). To control for phylogenetic
 effects in across-species comparisons, we used R version 4.4.2 (R core
 team 2024) and the R packages <em>ape</em> 5.8.1 (Paradis and
 Schliep 2019) and <em>phytools</em> 2.4-4 (Revell 2024) to
 incorporate appropriate evolutionary trees and calculate phylogenetic
 correlation coefficients and phylogenetic matched-pairs
 <em>t</em>-tests. Trees were based on data drawn from
 birdtree.org (Jetz et al. 2012) and a multilocus phylogeny of the
 Parulidae (Lovette et al. 2010), and branch lengths were estimated using
 the modified Grafen method (Revell 2024).
description: # Data from: Sex- and age-related differences in post-breeding molt
 phenology are phylogenetically and ecologically widespread in passerines
 Dataset DOI: [10.5061/dryad.rr4xgxdm9](10.5061/dryad.rr4xgxdm9) ##
 Description of the data and file structure Molt data collected at
 Powdermill Avian Research Center (40.1637°N, 79.2674°W), the field station
 of Carnegie Museum of Natural History, in southwestern Pennsylvania, USA,
 1986-2004. After identifying each captured individual to species and
 banding it with a uniquely numbered U. S. Bird Banding Laboratory band, we
 determined its sex using either plumage characteristics (for sexually
 dimorphic species) or the presence of a brood patch or cloacal
 protuberance. Adults were age-classified as either SY (second-year birds
 hatched the previous calendar year) or ASY (after-second-year birds
 hatched two or more calendar years ago), based on wing molt limits
 (Mulvihill 1993) and other plumage criteria that have since become
 standard in passerine aging (Pyle 2022). Each individual was then assigned
 a total flight-feather molt score (0–90) based on the molt stage of the 18
 remiges (9 primaries and 9 secondaries) on the right wing. We used the 0–5
 molt scoring system of Ginn and Melville (1983): 0 = old feather, 1 = old
 feather missing or new pin feather, 2 = new feather emerging from sheath
 up to one-third grown, 3 = new feather between one-third and two-thirds
 grown, 4 = new feather more than two-thirds grown but still sheathed at
 base, and 5 = fully grown new feather with no trace of the sheath at its
 base. All assignments of sex, age, and molt score were performed by a
 single individual. In the present study we focused on species that undergo
 a complete post-breeding prebasic molt on their breeding grounds and
 excluded individuals that showed evidence of partial or suspended molts.
 ### Files and variables #### File: MasterAgeFile.xlsx
 **Description:** Complete data for analyzing effects of adult age on molt
 phenology. ##### Variables 1. **Species**. Four-letter code for the 13
 species examined. Scientific names, English names, and four-letter codes
 are shown below and in Table 2 of the associated published paper.  *Vireo
 griseus* White-eyed Vireo (WEVI) *Dumatella carolinensis* Gray Catbird
 (GRCA) *Catharus fuscescens* Veery (VEER) *Seiurus aurocapilla* Ovenbird
 (OVEN) *Vermivora chrysoptera* Golden-winged Warbler (GWWA) *Mniotilta
 varia* Black-and-white Warbler (BAWW) *Geothlypis formosa* Kentucky
 Warbler (KEWA) *Geothlypis trichas* Common Yellowthroat (COYE) *Setophaga
 citrina* Hooded Warbler (HOWA) *Setophaga ruticilla* American Redstart
 (AMRE) *Setophaga petechia* Yellow Warbler (YEWA) *Pheucticus
 ludovicianus* Rose-breasted Grosbeak (RBGR) *Passerina cyanea* Indigo
 Bunting (INBU) 2. **BandPrefix**. First four numbers of the Banding Office
 band. 3. **BandSuffix**. Final five numbers of the Banding Office band. 
 4. **age**. Bird age, with SY = second year, ASY = after second year. 5.
 **sex**. Bird sex, with F = female, M = male, U = unknown sex. 6.
 **month**. Numerical month of capture. 7. **day**. Numerical day of the
 month of capture. 8. **year**. Year of capture. 9. **OrdinalDate**.
 Ordinal day of the year (1 = January 1) of capture 10. **Date**. Date of
 capture. 11. **MoltScore**. Molt score of the remiges. For birds in active
 molt, this number varies between 1 and 89. 12. **bird_id**. A
 concatenation of year of capture and the bird's BandSuffix. The
 resulting concatenation provides a unique identifier so that cases where
 an individual has multiple records from the same molt cycle can be
 identified. 13. **MoltProp**. Proportion of remige molt completed,
 calculated as MoltScore/90. 14. **sasMoltProp**. The arcsine transformed
 value of MoltProp, scaled as a proportion between 0 and 1.  #### **File:
 MasterSexFile.xlsx** **Description:** Complete data for analyzing effects
 of sex on molt phenology. ##### Variables 1. **Species**. Four-letter code
 for the 15 species examined. Scientific names, English names, and
 four-letter codes are shown below and in Table 1 of the associated
 published paper.  *Vireo griseus* White-eyed Vireo (WEVI) *Catharus
 fuscescens* Veery (VEER) *Haemorhous purpureus* Purple Finch (PUFI)
 *Spinus tristis* American Goldfinch (AMGO) *Seiurus aurocapilla* Ovenbird
 (OVEN) *Parkesia motacilla* Louisiana Waterthrush (LOWA) *Vermivora
 chrysoptera* Golden-winged Warbler (GWWA) *Mniotilta varia*
 Black-and-white Warbler (BAWW) *Geothlypis formosa* Kentucky Warbler
 (KEWA) *Geothlypis trichas* Common Yellowthroat (COYE) *Setophaga citrina*
 Hooded Warbler (HOWA) *Setophaga ruticilla* American Redstart (AMRE)
 *Setophaga petechia* Yellow Warbler (YEWA) *Pheucticus ludovicianus*
 Rose-breasted Grosbeak (RBGR) *Passerina cyanea* Indigo Bunting (INBU) 2.
 **BandPrefix**. First four numbers of the Banding Office band. 3.
 **BandSuffix**. Final five numbers of the Banding Office band.  4.
 **age**. Bird age, with SY = second year, ASY = after second year, AHY =
 after hatching year. 5. **sex**. Bird sex, with F = female, M = male. 6.
 **month**. Numerical month of capture. 7. **day**. Numerical day of the
 month of capture. 8. **year**. Year of capture. 9. **OrdinalDate**.
 Ordinal day of the year (1 = January 1) of capture 10. **Date**. Date of
 capture. 11. **MoltScore**. Molt score of the remiges. For birds in active
 molt, this number varies between 1 and 89. 12. **bird_id**. A
 concatenation of year of capture and the bird's BandSuffix. The
 resulting concatenation provides a unique identifier so that cases where
 an individual has multiple records from the same molt cycle can be
 identified. 13. **MoltProp**. Proportion of remige molt completed,
 calculated as MoltScore/90. 14. **sasMoltProp**. The arcsine transformed
 value of MoltProp, scaled as a proportion between 0 and 1.  ##
 Code/software Data files are in Microsoft Excel .xlsx format, and can be
 opened via a variety of freely available software packages, including R,
 LibreOffice Calc, Google Sheets, etc.