DOI: 10.5061/dryad.5dv41nsh0
title: Data from: Appalachian-breeding Vermivora chrysoptera (Golden-winged Warbler) occur at very low densities in mid-elevation forests and agroforestry systems throughout the Andes and isolated massifs of northern Colombia

description: Vermivora chrysoptera (Golden-winged Warbler) is one of the most striking
 but also one of the most vulnerable migratory warblers on Earth. To
 understand its non-breeding ecology in northern South America, where the
 steeply declining Appalachian breeding population is known to spend the
 non-breeding season, we conducted 2,534 surveys between 2018 and 2023 in
 isolated massifs and the Andes of Colombia. Our goal was to evaluate the
 distribution, detection rates, elevational range, habitat preferences and
 microhabitat associations of the species. We obtained 54 detections, with
 a very low detection rate (2.13%) compared to rates reported from Central
 America (~10%). Detections covered a wide range of elevations (634 – 2,551
 m a.s.l.), with support for a mid-elevation peak at around 1,750 m a.s.l.
 Importantly, detection elevation was negatively correlated with latitude
 such that peak abundances occurred at higher elevations closer to the
 equator. Most detections were in mature or secondary forests (72%), but
 birds also occurred along forest edges (17%) and in agroforestry systems
 (11%), such as shade-grown coffee. We found weak evidence for a female
 preference for lower elevations, as well as more frequent use of
 agroforestry systems relative to males. Logistic regressions provided some
 support for a preference for forest over agriculture in both sexes, as
 well as a higher detection probability at points with intermediate canopy
 height and canopy cover. Our results highlight the low density at which
 the species occurs across the northern Andes of Colombia and other
 isolated massifs. The association with forested habitats and the
 relatively narrow elevation range occupied by most birds, implies that
 focusing conservation efforts on protecting or restoring forests at
 elevations where detection rates peaked would likely be an effective
 strategy for ensuring that non-breeding habitat remains for
 Appalachian-breeding Vermivora chrysoptera.
description: <em>Distribution and timing of surveys
 </em> We conducted surveys for
 <em>Vermivora chrysoptera</em> in Colombia during five
 nonbreeding seasons in 2018 – 2023 across a broad elevation gradient (350
 – 2,650 m a.s.l.). Survey locations were established in six biogeographic
 regions: Magdalena Valley – departments of Santander and Tolima; Cauca
 Valley – departments of Caldas, Quindío, Antioquia, Valle del Cauca and
 Risaralda; Sierra Nevada de Santa Marta – department of Magdalena; Pacific
 slope – Antioquia, Chocó, Risaralda and Valle del Cauca; Serranía de
 Perijá – Cesar; and Orinoco-Amazonas – Boyacá (Figure 1). Locations within
 biogeographic regions were selected to maximize coverage of likely
 nonbreeding areas, however, certain regions could not be surveyed due
 Colombia´s internal conflict, including parts of northern Antioquia and
 eastern Norte de Santander. In any given season, surveys were conducted
 between November 10 and March 20 in order to avoid the main post-breeding
 and pre-breeding migration periods. Not all regions were surveyed in each
 year. At each of 101 locations, 8 – 12 point count
 stations were established, resulting in 1,324 unique points (Table 1),
 with each point separated by at least 250 m from all the other points
 (except in 2020, when intermediate points were placed at locations with no
 detections to ensure that birds had not been missed between points).
 Within a season, individual points were surveyed once (647 points) or on
 at least two separate occasions (677 points). Points surveyed in more than
 one season (105 points), were treated as unique data points for each
 season, as they represented independent habitat selection processes by
 birds. Surveys were distributed among six different landcovers: mature
 forest, secondary forest, riparian forest, forest edge, agroforestry
 systems and live fences typically bordering cattle pastures (for detailed
 descriptions see Habitat Type below; see Table 3 for sample size by
 habitat). These were the most representative landcovers within our study
 region, however, points were not established in open, treeless, cattle
 pastures (the most extensive landcover), given that <em>V.
 chrysoptera</em> does not occur where there is a near or complete
 absence of trees, vines, hanging dead leaves and epiphytes (Bennett et al.
 2016). In two regions, a stratified survey design was
 implemented over two nonbreeding seasons in order to examine variation in
 elevation and habitat use: 1) in Santander, including the municipalities
 of Tona and Bucaramanga and 2) in Caldas, primarily Manizales
 municipality. In each region, points were divided nearly equally across
 six 250 m-wide elevation bands, spanning elevations from 1,000 to 2,500 m
 a.s.l., and also among landcover types. Each point was surveyed on three
 occasions during a given nonbreeding season.
 <em>Point-count protocol</em>
 Point counts had a duration of 10 minutes and followed the
 protocol tested and adopted by Bennett et al. (2019a) to maximize the
 detectability of <em>V. chrysoptera</em>. During each point,
 we broadcast a five-minute recording of <em>V.
 chrysoptera</em> songs and calls (periods A: 0 – 2.5 min and B: 2.5
 – 5 min), immediately followed by a five-minute reproduction of an owl
 mobbing sequence including the vocalizations of <em>Glaucidium
 brasilianum</em> (Ferruginous Pygmy-Owl), <em>Megascops
 asio</em> (Eastern Screech-Owl) and alarm calls of several migratory
 landbirds (period C: 5 – 10 min). To broadcast recordings, a portable
 speaker (Xiaomi Compact Bluetooth Speaker 2) was placed at head height in
 a tree and speaker volume was set to one level less than the maximum. When
 a <em>V. chrysoptera</em> was detected during a survey, we
 recorded the period (A, B or C) of the initial detection, sex (e.g., the
 face mask and throat of males is black, while in females it is gray and
 indistinct), and signs of hybridization (e.g., yellow coloration in the
 breast or clear phenotypes of <em>V. chrysoptera x
 cyanoptera</em> [Brewster’s or Lawerence’s Warblers]), where they
 could be reliably determined. Points were surveyed primarily in the
 morning (82% of points; mean time = 09:47 local time).
 At each point count station, we recorded geographic coordinates
 using a handheld GPS unit, elevation above sea level in meters, and time
 of day (24-hour format). We also recorded the following vegetation
 variables: <strong>Habitat type</strong> – Observers selected
 the habitat classification that best described the landscape within a 50-m
 radius around a point: mature forest (canopy &gt; 15 m); secondary
 forest (canopy &lt; 15 m); forest edge (clear boundaries between
 forest and other landcovers); agroforestry system (typically shade-grown
 coffee with canopy cover &gt; 30%); riparian forest (narrow strips of
 forest bordering watercourses &lt; 50 m wide); live fence (boundaries
 formed by trees and native vegetation); other (heterogenous agricultural
 areas that did not fall into the above categories). <strong>Canopy
 cover</strong> – estimated to the nearest 10% at four cardinal
 points 5 m from the center of the point, by looking directly up through an
 inverted binocular and estimating the percentage of the field of view
 covered by vegetation; <strong>Canopy height</strong> – Four
 trees within 25 m of the point and representative of the average canopy
 height (i.e., not the tallest tree) were selected and measured using the
 Measure Height application for smart phones; <strong>Hanging dead
 leaf index -</strong> was recorded on a four point scale: 1. No dead
 leaves; 2. 1-50 dead leaves; 3. 50-500 dead leaves; 4. &gt;500 dead
 leaves; <strong>Epiphyte index</strong> - (including
 bromeliads, lichens and mosses) 1. No epiphytes; 2. 1-30% of trees covered
 with epiphytes; 3. 30-70%; 4. &gt;70%; <strong>Vine
 index</strong> - included only vines in the midstory and upper
 forest levels: 1. No vines; 2. Few vines, thin, not forming tangles or
 clusters; 3. Medium vines, thicker, 1-2 vine tangles; 4. Many vines of all
 sizes, 3+ vine tangles. Values for the hanging dead leaf index, epiphyte
 index and vine index correspond to an estimate of all dead leaves,
 epiphytes and vines within a 50-m radius of a point.
description: # Appalachian-breeding Vermivora chrysoptera (Golden-winged Warbler) occur
 at very low densities in mid-elevation forests and agroforestry systems
 throughout the Andes and isolated massifs of northern Colombia
 [https://doi.org/10.5061/dryad.5dv41nsh0](https://doi.org/10.5061/dryad.5dv41nsh0) ## Description of the data and file structure The data contained in these files are the result of 2534 surveys being carried out across 1324 unique points located in the Andes and isolated massifs of Colombia. The surveys were carried out to understand the distribution, elevation use, habitat preferences and microhabitat associations of the Golden-winged Warbler (Vermivora chrysoptera). During surveys all migratory birds were recorded and are therefore included in the file entitled "León et al. 2025 - Raw point count data". ### Files and variables #### File: León\_et\_al.*2025*-\_Raw\_point\_count\_data.xlsx **Description:** Raw point count data based on 2534 surveys carried out at 1324 unique points across Colombia. All migratory birds observed at included in the dataset, along with vegetation variables collected at each point (see methods). #### File: León\_et\_al.*2025*-\_Processed\_point\_count\_data.xlsx **Description:** Processed point count data based on 2534 surveys carried out at 1324 unique points across Colombia. Individual datasets within the file were used to generate summary statistics of detection probabilities by region, by landcover and for each of the main vegetation variables recorded (see methods). #### File: GWWA\_SanCal.csv **Description:** Reduced dataset for two focal regions where point counts were distributed evenly across an elevation gradient spanning 1250 to 2500 m.a.s.l. and also across the main landcover types. ##### Variables * **Point_ID**: Region: Site: Habitat: **CanopyHeight**: In meters based on the average of four measurements taken at each point. **CanopyCover**: Percent cover based on the average of four measurements taken at each point; **Dead_leaves**: see methods; **Epiphytes**: see methods; **Lianas**: see methods; **Elevation**: **Present**: if a V. chrysoptera was recorded at a point or not; **Elevation_S**: standardized variable for logistic regression; **CanopyH**: standardized variable for logistic regression; **CanopyC**: standardized variable for logistic regression; **Forest**: 2 level categorical variable, forest or no-forest; **Forest_E**: **Habitatx3**: 3 level categorical variable, forest, forest edge and agriculture; **Site2**: **LeavesB**: binomial variable for presence of dead leaves; **EpiphytesB**: binomial variable for presence of epiphytes; **LianasB**: binomial variable for presence of lianas. #### File: GWWA\_Elev\_x\_Lat.csv **Description:** Dataset used to examine the relationship between the elevation at which Golden-winged Warblers were detected and latitude. ##### Variables * Ele: Elevation in meters at which individual Golden-winged Warblers were detected in Colombia. * Lat: Latitude at which individual Golden-winged Warblers were detected in Colombia (reduced to 3 decimal degrees of precision). #### File: GWWA\_eBird\_precipitation.csv **Description:** Dataset for examining the relationship between the detection probability of Golden-winged Warblers and precipitation across 101 unique sites in Colombia, as well as exploring if the eBird Status and Trends abundance surfaces predicted the presence of warblers. ##### Variables * Site: Unique site (n = 101) * Transect: Point count ID * Lon1: Longitude of point (reduced to 3 decimal degrees of precision) * Lat1: Latitude of point (reduced to 3 decimal degrees of precision) * eBird: Abundance value generated from eBird Status and Trends models * Detection: A binomial variable describing if a Golden-winged Warbler was detected or not. * ANRain: Annual rainfall in mm at each site based on values extracted from the WorldClim database. * NBRain: Nonbreeding season rainfall in mm at each site based on values for the months November through March extracted from the WorldClim database. ## Code/software The script is for use in R. ## Access information Other publicly accessible locations of the data: * The majority of the point count data were uploaded to [www.ebird.org](http://www.ebird.org)