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22001177 SOUTHEASTERN NATURALIST 1V6o(2l.) :1169,5 N–2o1. 42
Responses of an Endangered Songbird to an Extreme
Drought Event
Melanie R. Colón1,2,*, Ashley M. Long2, and Michael L. Morrison1
Abstract - Given natural variation in weather conditions and increased risk of drought associated
with climate change, understanding how birds respond to fluctuations in precipitation
is a necessary step toward development of more-effective, long-term management strategies
for species of conservation concern. We compared behaviors and reproductive output
of the federally endangered Vireo atricapilla (Black-capped Vireo, hereafter Vireo) during
an extreme drought event and a year with moderate rainfall. During the drought, Vireos had
lower pairing and territory success, delayed nest initiation, fewer re-nesting attempts, and
lower nest-success. Brood parasitism by Molothrus ater (Brown-headed Cowbirds), which
is one of the main threats to Vireo population persistence, was also greater during the drought
year. Nest placement varied between years, with Vireos using the evergreen Juniperus asheii
(Ashe Juniper) as a nest substrate more often when conditions were dry and the deciduous
Diospyros texana (Texas Persimmon) under moderate conditions. Removal of Ashe Juniper
and Brown-headed Cowbirds from Vireo habitat are common management practices used to
support Vireo conservation efforts. Our results suggest that regional weather patterns should
be considered when making decisions regarding Ashe Juniper removal. In addition, increased
Brown-headed Cowbird removal may be warranted in dry areas during drought years.
Introduction
Although definitions vary, drought is usually characterized by inadequate precipitation
over a time sufficient to impact vegetation and deplete soil moisture
(Kramer 1983). Depending on drought severity, this weather phenomenon can have
individual- and population-level consequences for birds. Heat waves associated
with summertime droughts can result in avian mortality (McKechnie and Wolf
2010, Saunders et al. 2011), but most birds experience the effects of drought indirectly
through changes in vegetation or other habitat features. For example, under
drought conditions, plants may exhibit delayed phenology, reduced leaf area, or
altered plant chemistry (Gutbrodt et al. 2011, Larsson and Ohmart 2008, Rathcke
and Lacey 1985). Such changes in vegetation can affect the timing and abundance
of available plant and insect foods (Greven et al. 2009, Morrison and Bolger 2002,
Ogaya and Peñulas 2007) and reduce vegetation cover at foraging and nesting sites,
thus increasing the risk of predation (Martin 1992, Sugden and Beyersbergen 1986)
and exposure to the elements (e.g., wind, rain, cold, heat; Walsberg 1981).
Birds can respond to drought by relocating to wetter sites (Strong et al. 1997,
Takekawa and Beissinger 2005) or by following shifting plant distributions
1Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station,
TX 77843-2258. 2Institute of Renewable Natural Resources, Texas A&M University, College
Station, TX 77843-2260. *Corresponding author - melaniec@tamu.edu.
Manuscript Editor: Roger Applegate
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(Mueller et al. 2005). Birds that remain in drought-impacted habitats may use
larger areas (van Zyl 1994) or alternative nest substrates (Martin 1993) in response
to reduced resource availability. Additionally, birds may delay (or forgo) breeding
during drought (Christman 2002, Preston and Rotenberry 2006, Visser et al. 2006)
or reduce their reproductive effort by laying smaller clutches, abandoning nests, or
engaging in fewer nesting attempts (Erikstad et al. 1998). Given natural variation
in weather conditions and increased risk of drought associated with climate change,
understanding how birds respond to fluctuations in precipitation is a necessary step
toward development of more-effective, long-term management strategies for species
of conservation concern (IPCC 2014, Jiang and Yang 2012).
Vireo atricapilla Woodhouse (Black-capped Vireo; hereafter, Vireo) is a small,
migratory songbird that breeds in early-successional, shrub-scrub vegetation in
arid and semi-arid regions of Oklahoma, Texas, and Mexico (González-Rojas et
al. 2014, Graber 1961, Grzybowski 1995). The US Fish and Wildlife Service listed
the Vireo as endangered in 1987, citing habitat loss and reduced reproductive success
resulting from brood parasitism as the primary threats to the species (USFWS
1987). Drought is a common occurrence across the Vireo’s breeding range that
helps maintain the vegetation structure needed for Vireo reproduction (Wilkins et
al. 2006). However, the severity of drought conditions that occur across the Vireo’s
breeding range can vary widely, and Graber (1961) suggested that the impacts of
drought on vegetation can cause previously occupied areas to become unsuitable
for Vireos. More recently, Smith et al. (2012) noted that Vireo productivity is
greatly influenced by precipitation in the dry, southwestern portion of the species’
breeding range in Texas.
In 2011, Texas experienced an extreme drought event with record high temperatures
and precipitation deficits (Hoerling et al. 2013). Drought persisted across
the state into 2012, but it was less intense, and rainfall in many locations was
comparable to long-term regional averages (NCEI 2016). The variability in precipitation
between years provided a unique opportunity to examine Vireo responses
to drought. Herein, we quantify differences in weather and vegetation greenness,
and compare Vireo behaviors and reproductive output during the 2011 (drought)
and 2012 (moderate) breeding seasons. Our results add to our understanding of
Vireo breeding ecology and may help inform management and conservation efforts
for this endangered species.
Field Site Description
We surveyed Vireos across an 1100-ha study site located at Dobbs Run Ranch
(~29°38'60"N, 100°24'36"W) from late March–late July in 2011 and 2012. Dobbs
Run Ranch is a privately owned property located in Edwards County, TX, on the
southwestern edge of the Edwards Plateau (Fig. 1). Soil within the study site is
predominantly limestone bedrock (99.6%; NRCS 2013), and common woody plants
include Juniper asheii J. Buchholz (Ashe Juniper), Quercus fusiformis Small (Plateau
Live Oak), Pinus remota Little (Texas Pinyon Pine), Diospyros texana Scheele
(Texas Persimmon), and Sophora secundiflorum Ortega (Texas Mountain Laurel).
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Average temperature in the region during the months of Vireo breeding (April–
July; Grzybowski 1995) is 31 °C, and average seasonal precipitation is ~25 cm;
however, the region experiences notable variation in temperature and precipitation
annually and seasonally (NCEI 2016).
Methods
Weather
To quantify differences in weather between years, we obtained daily maximum
temperature and daily precipitation data for 2010–2012 from the National Centers
for Environmental Information (NCEI 2016). We obtained most data from the
Brackettville 22 N station located at Kickapoo Caverns State Park (29°36'36"N,
100°27'07"W; Fig. 1), which is adjacent to Dobbs Run Ranch. A small number of
records were missing from this station during the study period. When necessary, we
substituted precipitation values from the Rocksprings 26 SSW station (29°41'16"N,
100°25'18"W; Fig. 1), which was located less than 15 km away. The Rocksprings 26 SSW
station did not record temperature information, so when temperature records were
not available from the Brackettville 22 N station, we substituted average values
Figure 1. Location of Dobbs Run Ranch in relation to nearby weather stations in Edwards
and Kinney counties, TX. Top inset shows the study site and nest locations (solid 2011,
open 2012) within Dobbs Run Ranch where we monitored Black-capped Vireos in 2011
and 2012. Bottom inset shows the location within the Black-capped Vireo’s breeding range
in Texas (gray shading).
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from the next 2 nearest stations (Carta Valley [29°47'24"N, 100°40'26"W] and
Brackettville [29°18'58"N, 100° 24'50"W]; Fig. 1), which were both located less than 30
km away. Substitutions accounted for less than 5% of weather data.
Greenness
To quantify vegetation greenness, we used ENVI software v. 5.1 and 5.2 (Exelis
Visual Information Solutions, Bouder, CO) to create normalized difference vegetation
index (NDVI) maps from 30-m resolution Landsat images taken in April and
May of each year. We then used the Spatial Analyst extension in ArcMap v. 10.2.2
(Environmental Research Systems Institute, Redlands, CA) to extract NDVI values
from each pixel for all periods. NDVI is a widely used vegetation index correlated
with vegetation cover (Wellens 1997), leaf-area index (Law and Waring 1994), and
plant productivity (Reed et al. 1994), as well as climate variables (e.g., rainfall,
temperature, evapotranspiration; Cihlar et al. 1991, Nicholson et al. 1990).
Territory and nest surveys
Each year from 20 March to 15 July, we conducted auditory and visual surveys
across the study site to locate male Vireos. We marked the locations of all males
with handheld Garmin RINO 120 GPS units (≤10 m accuracy). We returned to
marked locations every 5–10 d between the hours of sunrise and 1400 to define
territory boundaries and determine mating and reproductive status. Each time a
focal bird moved ≥20 m, we recorded its location with a GPS. To improve our
assignment of individuals to specific territories, we used standard target mistnetting
techniques with playback of recorded Vireo song to capture adult Vireos,
which we then banded with unique color-band combinations. We considered
males territorial if they occupied the same locations for ≥4 weeks, and we considered
territorial males paired if we consistently observed them with females or
they maintained active nests.
To locate nests, we observed the movements of Vireos engaged in behaviors
indicative of breeding (e.g., copulation, material or food carry, presence of fledglings).
We focused on females because they tend to spend more time near nests
(Grzybowski 1995, Pope et al. 2013b), but we also noted male behaviors and movement
patterns because this species shares parental duties (Grzybowski 1995, Pope
et al. 2013b). If we did not detect Vireos on arrival in a territory, we systematically
searched the area for nests (Bailey and Thompson 2007, Smith 2011). This method
often proved effective in the absence of behavioral cues—especially during the
egg-laying phase when nests were most difficult to find (e.g., Martin and Geupel
1993)—and accounted for differences in detection attributed to variation in vegetation.
We monitored Vireo nests every 2–3 days until they fledged young, failed, or
were abandoned, and recorded adult behaviors and nest contents on each visit. We
banded all Vireo nestlings aged 6–8 d with unique color -band combinations.
We did not remove (or addle) Molothrus ater Boddaert (Brown-headed Cowbird;
hereafter Cowbird) eggs from parasitized nests because their presence can
deter future parasitism (Ortega et al. 1994), but we removed all Cowbird nestlings
on discovery. Parasitized Vireo nests rarely fledge host young (Boves et al. 2014,
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Grzybowski 1995, Tazik 1991), and by dispatching Cowbird nestlings before they
fledged, Vireos did not engage in post-fledging care of non-host young, increasing
their opportunities to re-nest. We considered a parasitized nest as failed for the
purposes of our analyses (see below) if it contained Cowbird nestlings at any point.
We considered a nest successful if it fledged ≥1 Vireo young, provided we did not
previously dispatch any Cowbird nestlings. Young Vireos remain with their parents
for 2 or more weeks before independence (Grzybowski 1995); therefore, we surveyed
all territories in which we suspected fledging for a minimum of 2 weeks after
the expected fledging date. If we detected a fledgling (≤2 weeks of age) within the
territory, we recorded the territory and the nest as successful. We also considered
territories and nests successful if 2 or more observers independently identified a
banded fledgling, regardless of fledgling age or location within the study site.
We catalogued vegetation characteristics for each active (i.e., eggs or nestlings
tended by adults) Vireo nest after it fledged, failed, or was abandoned. Specifically,
we recorded the nest substrate to the nearest 0.1 m and measured the distance
to the nearest edge (i.e., nest rim to nearest leafy edge), nest height (from ground
to nest rim), nest substrate height, and canopy height. In addition, we positioned
a 2-m coverboard marked with 0.1-m2 squares immediately in front of each nest
and estimated the percent of each square obscured by vegetation from 7 m away
in each cardinal direction (Guthrey et al. 1981). We averaged these values to obtain
a single measurement of foliage cover. Lastly, we placed a 0.1-m2 board at
each nest and estimated the percent visual obstruction by vegetation from 1 m
away from nests in each cardinal direction as well as from 1 m above and 1 m below
(where possible). We averaged these values to get a single measurement of
nest concealment. All measurements were consistent with those collected during
other studies of nesting Vireos (e.g., Conkling et al. 2012; Pope et al. 2013a,
2013b; Smith et al. 2012).
Data analyses
We conducted all tests using the statistical program R v. 3.2.2 (R Core Team,
Vienna, Austria). We present all means described below with their associated standard
deviations. Our intent was to examine Vireo responses in relation to specific
weather characteristics. However, our analyses indicated clear differences in our
weather and greenness metrics between 2011 and 2012 (see below). As such, we
simplified our analyses by using temporal variables (i.e., day, year) as proxies to
examine Vireo responses to weather.
Weather. We calculated the mean maximum daily temperature for each year and
used a Welch’s 2-sample t-test (Crawley 2014:94–95, Ruxton 2006) with Cohen’s d
as a measure of effect size (Lakens 2013) to compare means between years. We also
used linear regression to examine temperature as a function of date within seasons
(Crawley 2014:114–140). We summed daily precipitation to determine cumulative
monthly precipitation totals for the 7 months leading up to and the 4 months of each
Vireo breeding season, and calculated the percent differences in seasonal rainfall
between years.
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Greenness. We calculated the mean NDVI of all pixels across the study site to
determine mean NDVI on the landscape for each year. We also calculated the mean
NDVI for each territory and used those values to determine the annual mean NDVI
for all territories. We compared NDVI on the landscape as well as mean NDVI within
territories between months and years using 2-way factorial analysis of variance tests
(ANOVA; Crawley 2014:170–173). If there was a significant interaction between
month and year, we used Tukey’s honest significant difference (HSD) tests to examine
pairwise differences (Crawley 2014:226) in months between (e.g., April 2011 vs.
April 2012) and within (e.g., April 2011 vs. May 2011) years. If there was no significant
interaction, we examined the main effects of month and year separately.
Territories and nests. We used Geospatial Modelling Environment v. 0.7.3.0
(Beyer 2009) to create minimum convex polygons (MCP) for all territorial males
with ≥15 location points, which we considered the minimum number required to
adequately represent territory boundaries (e.g., Morgan 2012, Smith 2011). We
defined territory size as the area within each MCP and compared territory size between
years using a Welch’s 2-sample t-test (Crawley 2014:94–95, Ruxton 2006)
with Cohen’s d as a measure of effect size (Lakens 2013). We calculated pairing
success as the number of paired males relative to the total number of territorial
males (Long et al. 2017, Stewart et al. 2014). We calculated territory success as the
number of successful territories relative to the total number of paired males (Long
et al. 2017, Stewart et al. 2014). We examined inter-annual differences in pairing
and territory success using Fisher’s exact tests (Crawley 2014:105–107) and calculated
the odds ratios (OR) as measures of ef fect size (McHugh 2009).
We used a chi-square test with Cramer’s V as a measure of effect size to determine
if nest substrate use differed between years (Crawley 2014:101–105),
and we used a 1-way, non-parametric, ANOVA-type multivariate test (reviewed
in Bathke et al. 2008) within the npmv package in program R (Burchett and Ellis
2015) to evaluate inter-annual differences in vegetation at nest sites and differences
in vegetation characteristics among the 4 most common nest substrates (i.e.,
global models). We subsequently used post hoc univariate tests to examine each
vegetation characteristic across years and substrates. We accounted for multiple
comparisons in post hoc tests using the Bonferroni correction and interpreted Pvalues
accordingly. We also examined the relative effects for each test. Relative
effects are measures of effect size that reflect the probability that a particular vegetation
characteristic measured at a randomly chosen nest in a given year (or substrate)
had a greater value than that from a randomly chosen nest from any year
(or substrate) (Burchett and Ellis 2015).
We estimated the laying date of the first egg (i.e., initiation date) of each nest
by backdating observations from nest checks with known nesting intervals. After
excluding nests for which nest initiation dates could not be determined, we calculated
the mean initiation date for each year and examined annual differences using
a Welch’s 2-sample t-test (Crawley 2014:94–95, Ruxton 2006) with Cohen’s d as a
measure of effect size (Lakens 2013). We then subtracted the mean initiation date
of the earliest 20% of nests from the mean initiation date of the latest 20% of nests
to characterize the length of each breeding season (e.g., Weatherhead 2005).
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We calculated mean clutch and brood sizes of nests for each year, excluding
nests from analyses for which these metrics could not be determined. We used a
1-way analysis of covariance (ANCOVA; Tabachnick and Fidel 2006:20) to examine
the effect of year on clutch size, while controlling for nest initiation date
because Vireo clutch size declines over the season (Campomizzi et al. 2013, Graber
1961, Locatelli et al. 2016). We used a chi-square test (Crawley 2014:101–105)
with phi (φ) as a measure of effect size (Hojat and Zu 2004) to compare hatching
success between years, then used ANCOVA (Tabachnick and Fidel 2006:20) to
examine the effect of year on brood size while controlling for clutch size. We excluded
parasitized nests from analyses of clutch and brood size because Cowbirds
may remove eggs or young from nests (Conkling et al. 2012, Peer and Bollinger
2012, Sealy 1992). We calculated eta-squared (ƞ2) as a measure of effect size for
both ANCOVA tests (Maher et al. 2013).
We used Fisher’s exact tests (Crawley 2014:105–107) with odds ratios
(McHugh 2009) to examine inter-annual differences in the frequency of nest
abandonment and brood parasitism. In addition, we developed a priori models
that included year and nest vegetation characteristics to examine their effects on
nest success. We used a generalized linear model approach to determine which
models best predicted nest success. Models included null, main effects, and additive
models for year and each vegetation characteristic. We also examined
additive models with nest substrate and each of the other vegetation characteristics
with year as a covariate. To test whether use of the dominant substrate in
either year contributed to nest success, we coded nest substrate as a binary variable
with 1 = the dominant substrate in a given year, and 0 = all other substrates.
Nest substrate was correlated with distance to edge (r = -0.16, P = 0.03) and nestsubstrate
height (r = 0.23, P ≤ 0.01). As such, we excluded additive models that
included nest substrate and these metrics from the final model set.
We also examined a priori models of daily nest survival that included year,
parasitism, nest stage, and linear and quadratic terms representing day of season
because these are known to impact daily nest survival in Vireos and other species
(e.g., Conkling et al. 2012, Skagen and Yackel Adams 2012). To account for differences
in season length between years, we considered the first day of each season
to coincide with the earliest nest initiation date in that year. We used the logisticexposure
method described by Shaffer (2004) to estimate daily nest survival. We
included abandoned nests—which we considered as failed during the interval that
abandonment was first suspected—as well as nests that contained Cowbird eggs,
which we considered failed during the interval in which any Cowbird eggs hatched.
As described above, we excluded nests that contained Cowbird nestlings when initially
located because we considered these failed on discovery. The final model set
included a null model, main effects models for each variable, and additive models
with combinations of these variables. We ranked models of nest success and daily
nest survival using Akaike’s information criterion adjusted for small sample sizes
(AICc; Burnham and Anderson 2002:49–97). We considered all models with ΔAICc
< 2.0 to be equally possible, but identified the most parsimonious of these models
as the most plausible.
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Results
Weather
Mean maximum daily temperature was 34 ± 4 °C (variation = 20–39 °C) in 2011
and 32 ± 4 °C (variation = 17–40 °C) in 2012. Maximum daily temperature varied
between years (t241.4 = 4.85, P ≤ 0.01, d = 0.62), and daily maximum temperature
increased over time within years (2011: F1, 120 = 59.66, P ≤ 0.01, r2 = 0.33; 2012:
F1, 120 = 80.78, P ≤ 0.01, r2 = 0.40). There was 54% less rainfall in the 7 months
leading up to the 2011 breeding season (13.1 cm) than during the corresponding
months the following year (28.4 cm). Similarly, 56% less rain fell during the 2011
breeding season (10.7 cm) than during the 2012 season (24.5 cm). Cumulative
rainfall during the 2012 breeding season was similar to the long-term seasonal
average for the region, while cumulative rainfall during the 2011 breeding season
was approximately half the long-term seasonal average (NCEI 2016). However,
cumulative precipitation totals belie the true conditions of the 2011 breeding season
during which 61% (6.48 cm) of the total rainfall occurred on a single day (12 May),
and mean precipitation of all other rainfall events (n = 7) was low (0.61 ± 0.44 cm).
Greenness
We found a significant interactive effect of month and year on NDVI across
the landscape (F1,52184 = 7,326, P ≤ 0.01). Post hoc Tukey’s HSD tests showed
that NDVI was significantly different across the study site for all combinations of
months and years (α ≤ 0.01). NDVI across the landscape was greater in May than
in April of both years (Table 1). We found no significant interactive effect of month
and year on mean NDVI within territories (F1, 556 = 0.70, P = 0.70), but mean NDVI
within territories varied both by month (F1, 558 = 5.83, P = 0.02) and year (F1, 558 =
1225.00, P ≤ 0.01). Mean NDVI within territories was greater in 2012 than in 2011
and greater during May compared to April (Table 1).
Territories and nests
We mapped and monitored 148 Vireo territories in 2011 and 132 Vireo territories
in 2012. Overall mean territory size was 1.69 ± 0.95 ha, with no significant
difference in territory size between years (t265.24 = -0.09, P = 0.93, d = 0.01). The
percentage of territorial males that successfully paired varied significantly between
years with 82% (n = 121) successfully pairing in 2011 and 99% (n = 130) in 2012
(Fisher’s exact test P ≤ 0.01, OR = 14.40). Similarly, the number of paired males
with successful territories also varied by year ,with 11% (n = 13) in 2011 and 78%
(n = 102) in 2012 (Fisher’s exact test P ≤ 0.01, OR = 29.66).
Table 1. Mean (and standard deviation) NDVI across the landscape and within Black-capped Vireo
territories at Dobbs Run Ranch, Edwards County, TX, in 2011 and 2012.
2011 2012
NDVI April May April May
Landscape 0.35 (0.06) 0.29 (0.03) 0.36 (0.04) 0.37 (0.05)
Territory 0.28 (0.03) 0.29 (0.02) 0.37 (0.03) 0.38 (0.04)
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We located and monitored 74 active nests in 2011 and 112 active nests in 2012
(Fig. 1). Vireos placed nests in 8 plant substrates including: Texas Persimmon (n =
69), Ashe Juniper (n = 63), Plateau Live Oak (n = 25), Forestiera reticualta Torr.
(Net-leaf Forestiera; n = 14), Quercus sinuata Walter var. breviloba (Torr.) C.H.
Mull (White Shin Oak; n = 6), Mahonia trifoliolata (Moric.) Fedde (Agarita; n = 4),
Texas Mountain Laurel (n = 3), and Karwinskia humboldtiana (Schult.) Zucc.
(Coyotillo; n = 1). We found a significant difference in nest substrate use between
years (χ2
7 = 75.41, P ≤ 0.01, V=
0.64). In 2011, Vireos placed 64% (n = 47) of
nests in Ashe Juniper compared with only 15% (n = 16) in 2012. Texas Persimmon
was the most common nest substrate in 2012, accounting for 58% (n = 65) of nests
compared to only 5% (n = 4) the previous year. Vireos did not place nests in Netleaf
Forestiera in 2011 or in Coyotillo or White Shin Oak in 2012. Vireos placed
nests in all other substrates similarly across years.
The global model comparing vegetation metrics at nest sites across years was
not significant (F4.97, 875.27 = 1.96, P = 0.08). The relative effects indicated a >50%
probability that overstory height, distance to edge, average cover, and average
concealment may have been greater at nests in 2012 compared with randomly selected
nests from either year; however, univariate post hoc tests showed no annual
differences in these or other characteristics. The global model comparing vegetation
characteristics among the 4 most-common nest substrates was significant
(F15.54, 555.71 = 4.20, P ≤ 0.0001). Univariate post hoc tests, however, suggested the
only difference was in nest substrate height (F3.00, 107.26 = 15.37, P ≤ 0.0001), wherein
there was a 65% probability that substrate height measured at a randomly chosen
nest placed in Ashe Juniper would have a greater value than that from a randomly
chosen nest from all possible nest substrates (Fig. 2).
We determined the earliest nest initiation dates were 18 April in 2011 and 1 April
in 2012. Mean nest initiation date overall was 9–10 May ± 19 days, but variation
in the timing of breeding was significantly different between years (t153.96 = 3.45,
P < 0.01, d = 0.56). Vireos laid clutches an average of 11 days later in 2011 than
in 2012 (2011: mean = 16 May ± 14 d, 2012: mean = 5 May ± 23 d). It should be
noted that later breeding in 2011 was not a function of later arrival on the breeding
grounds because Vireos arrived in similar numbers in both years starting in late
March (M.R. Colón, pers. observ.). The mean initiation dates of the earliest 20% of
nests were 25 April 2011 and 11 April 2012. The mean initiation dates of the latest
20% of nests were 4 June 2011 and 6 June 2012. Based on these values, season
length was 39 days in 2011 and 56 days in 2012, a difference of 17 days.
Vireos often re-nest after failed nesting attempts or lay a second clutch after
successful attempts (Grzybowski 1995); thus, mean nest initiation dates alone may
not accurately reflect differences in the timing of breeding between years. To better
demonstrate inter-annual differences, we graphed nest initiation dates by year
(Fig. 3). In 2012, nest initiation date had a bimodal distribution, with the second
peak likely corresponding with re-nesting or second brood attempts. However,
because many nests are not found (Mayfield 1975), it is not always possible to determine
the number of nesting attempts made per pair. That said, in some instances,
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we were able to confirm re-nesting attempts because males were banded or because
of male behavior and the location of nests within territories. We confirmed that 3
nests in 2011 and 19 nests in 2012 were re-nesting attempts following prior nest
failure, and 7 nests in 2012 were attempts to produce a second brood after an earlier
nest fledged.
Overall clutch size varied from 2 to 4 eggs (mean = 3.75 ± 0.47 eggs, n = 128
nests). Proportionally, there were more 3-egg clutches in 2011 than in 2012 (F1, 110
= 5.62, P = 0.02), but after controlling for nest initiation date, we found no effect
of year on clutch size (F1, 109 = 2.57, P = 0.11, ƞ2 = 0.02). Fifty-one percent (n = 30)
and 67% (n = 70) of non-parasitized Vireo nests survived to hatching in 2011 and
2012, respectively (χ2
1 = 3.14, P = 0.08, φ = 0.14). Overall brood size ranged from
Figure 2. Boxplot comparing nest substrate height at Black-capped Vireo nests within the
4 most commonly used nest substrates at Dobbs Run Ranch, Edwards County, TX, in 2011
and 2012. Boxes represent the middle (50%) range of substrate heights, with the thicker
black lines indicating median substrate heights. Lines extending above and below each box
identify the full range of substrate heights, with black dots representing outliers.
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1 to 4 young with a mean of 3.48 ± 0.79 young. After controlling for clutch size, we
found no effect of year on brood size (F1, 68 = 1.27, P = 0.26, η2 = 0.01), suggesting
no differences in egg hatchability between years.
Vireos abandoned 9% (n = 7) of nests in 2011 and 6% (n = 7) of nests in 2012
(Fisher’s exact test P = 0.57, OR = 1.56). Cowbirds parasitized 20% (n = 15) and 7%
(n = 8) of nests in 2011 and 2012, respectively (Fisher’s exact test P = 0.01, OR =
3.28). It was rarely possible to determine the exact dates that Cowbirds parasitized
nests, but we only found 2 nests that were parasitized before mid-May. Apparent
nest success was 15% in 2011 and 41% in 2012. The additive effects of year, nest
substrate, and average concealment best predicted overall nest success (Table 2).
The predicted probability of nest success was higher in 2012 and increased with
increasing nest concealment. In both years, Vireo nest success was lower for nests
placed in the most commonly used substrate; however, overlapping confidence intervals
suggest that differences associated with nest substrate were not statistically
Figure 3. Density plot showing initiation dates (Julian) of Black-capped Vireo nests within
the study site at Dobbs Run Ranch, Edwards County, TX, in 2011 and 2012.
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2017 Vol. 16, No. 2
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or biologically significant (Fig.4). The top 2 models that best predicted daily nest
survival included year and quadratic day trends, and one also included nest stage
(Table 2). Daily nest survival was lower in 2011 and decreased over time within seasons.
Survival was also lower during the nestling stage than during egg stage (i.e.,
egg laying and incubation). According to the most parsimonious model, mean predicted
daily nest survival was 93% (± 3%) in 2011 and 95% (± 4%) in 2012.
Discussion
Weather conditions at our study site were substantially different between
years. The 2011 Vireo breeding season was warmer and drier than the 2012
season. In the drier year, Vireos paired less frequently, used alternative nestsubstrates,
delayed nest initiation, and had lower territory and nest success. Our
results are similar to observations from the drier, western portion of the species’
breeding range in Texas (Graber 1961, Smith 2011, Smith et al. 2012); however,
reports from the wetter, eastern parts of the range suggest the impacts of drought
Table 2. Top 10 models for hypotheses of Black-capped Vireo nest success and daily nest survival
at Dobbs Run Ranch in Edwards County, TX, in 2011 and 2012. Model variables: nest substrate =
dominant species (yes or no); average concealment = average vegetation cover within 1 m; overstory
height = height of tallest woody vegetation above nest; nest height = height from ground to nest rim;
average cover = average vegetation cover within 7 m; substrate height = height of nest tree or shrub;
day = day of season; nest stage = egg or nestling; parasitism = nests parasitized by Brown-headed
Cowbirds. Statistics presented: K = number of parameters in the model; LL = log likelihood; AICc =
Akaike’s information criterion for small sample sizes; ΔAICc = difference in AICc; w = Akaike weight.
Response/model K LL AICc ΔAICc w
Nest success
Year + nest substrate + average concealment 4 -98.44 205.61 0.00 0.60
Year + nest substrate + overstory height 4 -99.49 207.71 2.10 0.21
Year + nest substrate 3 -101.50 209.42 3.81 0.09
Year + nest substrate + nest height 4 -101.02 210.77 5.16 0.05
Year + nest substrate + average cover 4 -101.41 211.55 5.94 0.03
Year + average concealment 3 -103.51 213.44 7.83 0.01
Year + overstory height 3 -103.57 213.57 7.96 0.01
Year 2 -106.08 216.38 10.77 0.00
Year + substrate height 3 -105.21 216.86 11.25 0.00
Year + nest height 3 -105.34 217.11 11.50 0.00
Daily nest survival
Year + day2 + nest stage 4 -349.72 708.18 0.00 0.46
Year + day 3 -351.83 710.09 1.92 0.18
Year + day + nest Stage 4 -350.86 710.46 2.28 0.15
Year + day 3 -352.33 711.09 2.92 0.11
Year + day2 + parasitism 4 -351.58 711.89 3.71 0.07
Year + day + parasitism 4 -352.16 713.04 4.87 0.04
Day 2 -358.76 721.72 13.55 0.00
Day2 2 -359.18 722.57 14.39 0.00
Year + parasitism + nest stage 4 -367.18 743.09 34.91 0.00
Year + nest stage 3 -368.44 743.31 35.13 0.00
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may vary regionally according to the precipitation gradient. For example, Cimprich
and Heimbuch (2011, 2012) monitored Vireos at Fort Hood during the same
years as our study. Although they observed significantly more re-nesting and
second brood attempts in 2012, they found that Vireo pairing, territory, and nest
success were relatively similar in both years.
Statewide, the period from October 2010 to September 2011 was the driest consecutive
12-mo period in recorded Texas history (Hoerling et al. 2013). Given that
precipitation is the main driver of aboveground primary productivity (Noy-Meir
1973, Sala et al. 1998), it is not surprising that we observed significantly lower
vegetation greenness in 2011 compared to 2012. Food availability is often directly
related to precipitation and vegetation greenness (Greven et al. 2009, Morrison and
Bolger 2002, Ogaya and Peñulas 2007), and birds may use vegetation as a cue for
future food availability (Marshall and Cooper 2004), defending larger or smaller
territories accordingly (Orians 1961, Pitelka et al. 1993, Smith and Shugart 1987).
We found no difference in Vireo territory size across years, perhaps because the
costs associated with defending larger territories were greater than the benefits of
securing additional resources or because Vireos compensated for any food limitation
in other ways (e.g., delayed nest initiation).
Nest-site characteristics varied little between years, with the notable exception
of nest substrate. There was pronounced variation in nest substrate use between
years, with a majority of Vireos selecting Ashe Juniper in 2011 and Texas Persimmon
in 2012. Bailey and Thompson (2007) previously suggested that Vireos were
considerably less likely to place nests in Ashe Juniper compared with deciduous
trees and shrubs. However, Ashe Juniper is a drought-tolerant evergreen species
Figure 4. Predicted probability of Black-capped Vireo nest success (with 95% confidence
intervals) as a function of nest concealment and use of common nest substrate at Dobbs
Run Ranch, Edwards County, TX, in 2011 and 2012. Nests placed in the most common nest
substrate (Ashe Juniper in 2011 and Texas Persimmon in 2012) are coded “yes”, and nests
in all others substrates are coded “no”. Gray shaded areas indi cate confidence intervals.
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(Gilman and Watson 1993) that can access deep water sources when surface soils
are dry (Jackson 1999). At our study site, Ashe Juniper was one of few species with
consistently green foliage in 2011 (M.R. Colón, pers. observ.), and it may have
provided cover at nest sites when deciduous species were bare. This hypothesis is
supported by our analyses of nest-site vegetation, which demonstrated that Vireos
were able to locate nest sites with similar characteristics (e.g., concealment) across
years despite the differences in vegetation greenness and nest substrate use.
Nonetheless, Vireos had lower reproductive success during the drought year,
some of which may have resulted from differences in reproductive investment between
years. Fewer Vireos paired during the dry conditions in 2011 compared to
the wetter 2012 season; those that did pair in 2011 delayed nesting until mid-May.
Birds often use environmental cues to predict future conditions (Bourgault et al.
2010, Farner and Follett 1979, Marshall and Cooper 2004), and timing reproductive
activities with rainfall is a common behavioral strategy for birds inhabiting arid
regions (e.g., Lloyd 1999, Ohmart 1969, Zann et al. 1995). The mean nest initiation
date for Vireos at our study site in 2011 (16 May) was within a few days of the
single greatest day of rainfall that season (12 May), suggesting that, as with other
species, rainfall may have stimulated breeding activity in Vireos that year.
Delayed nest initiation may be adaptive when resources are limited; however,
there are still consequences for annual fecundity. For example, clutch size declines
seasonally in many species (Drent and Daan 1980, Klomp 1970, Martin 1987). In our
study, we found no difference in clutch size between years after accounting for nest
initiation date, but birds that nested later in the season laid fewer eggs than those that
nested earlier. Similarly, annual fecundity may be determined by the number of nesting
attempts in a season. In 2011, later nest initiation at our study site corresponded to
a shortened breeding season that year, and we observed fewer re-nesting attempts and
no second brood attempts. Additionally, snakes and Cowbirds, common nest predators
at Vireo nests (Conkling et al. 2012, Stake and Cimprich ), are more active later
in the Vireo breeding season (e.g., Boves et al. 2014, Sperry et al. 2008). Cowbirds
present the added risk of nest failure from brood parasitism. Birds that delay nesting
increase their exposure to snakes and Cowbirds, which may explain the lower territory
and nest success and higher parasitism rates we observed in 2011.
Our results represent only a snapshot of the potential impacts of drought on Vireos,
and longer-term studies are needed to understand how population persistence
might be affected under prolonged or more frequent drought events. Drought has
been common throughout the Vireo’s breeding range for over 1000 years (Cleaveland
et al. 2011, Toomey et al. 1993, USDM 2016), but statewide climate models
predict that temperatures will steadily increase in Texas through the 21st century,
with warmer weather corresponding to drier conditions (Jiang and Yang 2012). Although
it is not possible to control such events, wildlife managers can plan for their
inevitability by understanding the responses of species of conservation concern and
identifying ways to minimize the consequences.
Current management recommendations for Vireos include the removal of Ashe
Juniper and Cowbirds from Vireo habitat (Campbell 1995). However, Grzybowski
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2017 Vol. 16, No. 2
et al. (1994) suggested that Ashe Juniper may provide important cover in areas
where deciduous vegetation is limited, especially in the drier, western portion of
the species’ breeding range in Texas. More frequent use of Ashe Juniper by Vireos
at our study site during the drought year suggests that Ashe Juniper may also be important
when deciduous vegetation is stressed. As such, regional weather patterns
as well as vegetation composition should be considered when making decisions
regarding Ashe Juniper removal in Vireo habitat. Additionally, 20% of Vireo nests
at our study site were parasitized by Cowbirds during the drought year. Managers
typically try to limit Cowbird parasitism of Vireo nests to less than 10% annually (e.g.,
Kostecke et al. 2005, USFWS 2000). Our results suggest that increased Cowbird removal
during drought years may be advisable. According to Summers et al. (2006),
Cowbird trapping is most effective in March and April before Cowbirds become
reproductively active and less effective in May when most nest parasitism occurs.
Locally breeding Cowbirds may be less attracted to grain-baited traps in May because
they switch to an insectivorous diet once they become reproductively active
(Ankney and Scott 1980). However, if insect abundance is lower during drought
years, continued trapping during May might be beneficial alone or in combination
with other management actions (S.G. Summers, US Army Natural Resources
Management, Fort Hood Military Reservation, Killeen, TX, pers. comm.), though
results are likely to vary with regional aridity.
Acknowledgments
E. and P. Smith provided access to Dobbs Run Ranch, and A. Beeler, D. Cormier, A.
Simnor, N. Vella-Geldart, M. Walters, K. Wolf-Roque, K. Brautigam, and K.N. Smith-Hicks
assisted in data collection. The Texas A&M Institute of Renewable Natural Resources
provided equipment and logistical and financial support. Additional financial support was
provided by Texas A&M University (i.e., Charles H. and Frances Fleming Scholarship,
J.H. Benedict Sr. Memorial Graduate Scholarship, Shirley Reynaud Duke Estate Scholarships,
W.B. Davis Scholarship, Association of Former Students Scholarship, and Tom Slick
Graduate Fellowship), the Texas Chapter of the Wildlife Society (i.e., Gary L. Waggerman
Memorial Scholarship), the Alfred P. Sloan Foundation, and Texas Ecolab. T.M. McFarland
provided helpful comments on an earlier version of this manuscript.
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