Climate and density influence annual survival and
movement in a migratory songbird
Ann E. McKellar1, Matthew W. Reudink2, Peter P. Marra3, Laurene M. Ratcliffe4 & Scott Wilson5
1

Canadian Wildlife Service, Environment Canada, 115 Perimeter Road, Saskatoon, Saskatchewan S7N 0X4, Canada
Department of Biological Sciences, Thompson Rivers University, Kamloops, British Columbia V2C 0C8, Canada
3
Migratory Bird Center, Smithsonian Conservation Biology Institute, Washington, District of Columbia 20013-7012
4
Department of Biology, Queen’s University, Kingston, Ontario K7L 3N6, Canada
5
Wildlife Research Division, Environment Canada, National Wildlife Research Centre, 1125 Colonel by Drive, Ottawa, Ontario K1A 0H3, Canada
2

Keywords
American redstart, annual survival, breeding
~o Southern
dispersal, density, El Nin
Oscillation, multistate mark–recapture,
Normalized Difference Vegetation Index,
Setophaga ruticilla.
Correspondence
Ann E. McKellar, Canadian Wildlife Service,
Environment Canada, 115 Perimeter Road,
Saskatoon, SK S7N 0X4, Canada.
Tel: 306-975-4799;
Fax: 306-975-4089;
E-mail: ann.mckellar@canada.ca
Funding Information
National Science Foundation, Natural
Sciences and Engineering Research Council
of Canada, and Environment Canada.
Received: 12 June 2015; Revised: 23 October
2015; Accepted: 28 October 2015

doi: 10.1002/ece3.1854

Abstract
Assessing the drivers of survival across the annual cycle is important for understanding when and how population limitation occurs in migratory animals.
Density-dependent population regulation can occur during breeding and nonbreeding periods, and large-scale climate cycles can also affect survival throughout the annual cycle via their effects on local weather and vegetation
productivity. Most studies of survival use mark–recapture techniques to estimate apparent survival, but true survival rates remain obscured due to
unknown rates of permanent emigration. This is especially problematic when
assessing annual survival of migratory birds, whose movement between breeding attempts, or breeding dispersal, can be substantial. We used a multistate
approach to examine drivers of annual survival and one component of breeding
dispersal (habitat-specific movements) in a population of American redstarts
(Setophaga ruticilla) over 11 years in two adjacent habitat types. Annual survival
displayed a curvilinear relation to the Southern Oscillation Index, with lower
survival during La Ni~
na and El Ni~
no conditions. Although redstart density had
no impact on survival, habitat-specific density influenced local movements
between habitat types, with redstarts being less likely to disperse from their previous year’s breeding habitat as density within that habitat increased. This finding was strongest in males and may be explained by conspecific attraction
influencing settlement decisions. Survival was lowest in young males, but movement was highest in this group, indicating that apparent survival rates were
likely biased low due to permanent emigration. Our findings demonstrate the
utility of examining breeding dispersal in mark–recapture studies and complement recent work using spatially explicit models of dispersal probability to
obtain greater accuracy in survival estimates.

Introduction
Given conservation concerns over recent and ongoing
declines in many migratory bird populations (Sauer and
Link 2011), a key research need is to determine the causes
of population limitation and when they occur (Faaborg
et al. 2010). Migratory birds are vulnerable to stressors
during different times of year and across often vastly different geographic regions. Thus, limitation can be caused
by conditions experienced during breeding, nonbreeding,
or migratory phases of the annual cycle (Newton 2004),
and events experienced during one phase can carry over

to influence performance during subsequent phases
(Marra et al. 1998; Reudink et al. 2009). In particular, the
importance of weather as a driver of bird demographic
rates has long been recognized (Lack 1954; Newton
1998).
Local weather patterns influence primary productivity
(Lieth 1973) and insect abundance (Janzen and Schoener
1968), which in turn can affect the body condition of
birds (Brown and Sherry 2006; Studds and Marra 2007)
and ultimately their survival (Robinson et al. 2007). Local
weather conditions are driven in large part by global
climate cycles (Rogers 1988; Holmgren et al. 2001), which

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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Survival and Movement in a Migratory Bird

A. E. McKellar et al.

are often better predictors of ecological processes than are
small-scale weather indices (Hallett et al. 2004). In the
Caribbean region where many Neotropical migrants overwinter, high values of the Southern Oscillation Index
(SOI) are indicative of La Ni~
na conditions and generally
result in wetter winters, whereas low values are indicative
of El Ni~
no conditions and are associated with milder and
drier winters (Ropelewski and Halpert 1987). Previous
work on Neotropical migrants in Jamaica found lower
survival following El Ni~
no winters (Sillett et al. 2000).
The NDVI (Normalized Difference Vegetation Index) has
also been used to describe weather conditions experienced
by migratory birds. Higher NDVI values are indicative of
greater primary production and are generally associated
with wetter conditions that are favorable to birds across
breeding (Pillar et al. 2015) and nonbreeding periods
(Saino et al. 2004).
Intrinsic factors such as population density can also
influence survival rates, potentially contributing to negative density-dependent population regulation (Newton
1998). Multiple mechanisms, such as site dependence or
crowding, can contribute to such density dependence
(Rodenhouse et al. 1997), and these mechanisms can act
on fecundity, survival, or both (Sutherland 1996). The
relative strengths of stochastic climatic effects versus density dependence in contributing to demographic variation
and population dynamics remain a key focus of research
in population ecology (Leirs et al. 1997; Grosbois et al.
2008).
To assess the effects of climate, density, and other factors on bird survival, researchers generally rely on mark–
recapture studies of color-banded birds. However, most
studies estimate apparent survival, which is the product
of both true mortality and fidelity to the study area
(Lebreton et al. 1992). For migratory birds, patterns of
annual survival on the breeding grounds may be obscured
if there is temporal variation in breeding dispersal (Marshall et al. 2004), defined as the movement of adults
between breeding attempts. Existing methods that quantify rates of emigration generally rely on live recapture
and dead recovery data that allow for the separation of
true survival and permanent emigration (Burnham 1993),
but these data are rarely available for nonharvested species. More recent spatially explicit mark–recapture
approaches make use of the locations of individual
encounters to model dispersal probabilities (Gilroy et al.
2012; Ergon and Gardner 2014; Schaub and Royle 2014).
However, these methods require the precise locations of
capture for each individual in each year and specific
assumptions (e.g., individuals have unique centers of
activity where capture is most likely to occur; movement
direction is unrelated to location). An alternative
approach which may be more feasible with limited data is

to quantify dispersal rates within a study area to infer
patterns of dispersal more generally (Lebreton et al. 2009;
Schaub and von Hirschheydt 2009).
As with survival, dispersal can be influenced by climate
and population density. Natal dispersal in American redstarts (Setophaga ruticilla) is influenced by nonbreeding
habitat quality (Studds et al. 2008), and both natal and
breeding dispersal may be related to annual variation in
breeding season phenology (Rushing et al. 2015a). Greater
population densities can lead to higher dispersal if competition and resource depletion encourage individuals to
disperse (Paradis et al. 1998), or lower dispersal through
mechanisms such as conspecific attraction (Fretwell and
Lucas 1970; Muller et al. 1997). Public information can
also influence patterns of breeding dispersal based on a
site’s reproductive output (Doligez et al. 2002; Parejo
et al. 2007).
The relative influence of factors such as climate and
density might vary among sex and age classes. In Eurasian
spoonbills (Platalea leucorodia leucorodia), a positive effect
of density on annual survival was apparent at low population sizes in younger but not in older birds, whereas
younger birds showed a stronger decrease in survival with
increasing population size (Lok et al. 2013). In American
redstarts, females and young birds are often excluded
from high-quality nonbreeding habitat by dominant older
males (Marra 2000) and thus may suffer greater effects on
their annual survival in years of unfavorable nonbreeding
season weather (Studds and Marra 2007). Unfortunately,
such age- and sex-specific interaction effects with annual
covariates are often difficult to discern in mark–recapture
studies due to large sample size requirements.
In this study, we used multistate mark–recapture models to examine potential drivers of age- and sex-specific
annual survival in a population of American redstarts
over 11 years. We further made use of the existence of
two spatially separate deciduous habitat types within our
study area that differed in age structure and landscape
continuity to examine factors influencing one component
of breeding dispersal: habitat-specific movements across
years. We first asked how apparent survival and movement varied among age and sex classes. We then tested
the effects of potential drivers of annual variation in survival and movement. For the second objective, we made
the following predictions: (1) more favorable nonbreeding
season weather (high SOI, high NDVI) would be associated with higher survival, with less of an influence of local
breeding season weather (Hallett et al. 2004) and that
(1a) these effects would be strongest in females and young
birds (Studds and Marra 2007); (2) survival would be
lower following years of higher density (Newton 1998);
(3) movements would be lower with increasing habitatspecific density the current year, due to conspecific

2

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A. E. McKellar et al.

attraction (Hahn and Silverman 2006), and following
higher reproductive success the previous year (Doligez
et al. 2002).

Materials and Methods
Field methods
American redstarts are small (7–8 g), Nearctic–Neotropical migrant songbirds that breed across the northern United States and Canada and spend the boreal winter across
Mexico, the Caribbean, and parts of Central and South
America (Sherry and Holmes 1997). Based on feather
stable isotope analysis, redstarts overwintering in the Caribbean appear to breed primarily in the northeastern United States and southeastern Canada, including our study
site (Norris et al. 2006).
Field work for this project was conducted from May–
July 2001–2011 at the QUBS (Queen’s University Biological Station), Chaffey’s Lock, Ontario, Canada (44°340 N,
76°190 W). The study area includes two major habitat
types: “undisturbed forest” (hereafter forest; 75 ha) and
“campground” (25 ha), divided by a two-lane country
road. Both habitats are mixed-deciduous forest, dominated by sugar maple (Acer saccharum) and Eastern hop
hornbeam (Ostrya virginiana). Although the habitats are
adjacent, they differ markedly in terms of landscape continuity, edge habitat, and human presence. The forest is
largely contiguous, disrupted only by walking trails and
several small wetlands. In contrast, the campground to
the south of the country road is composed of a mix of
cottages, recreational vehicle campsites, and tent campsites connected by a network of roads and trails. Due to
these light disturbances, the campground contains a
greater proportion of early-successional components than
the mature forest. In addition, the campground area borders on Lake Opinicon with ~1 km of shoreline on its
south boundary.
Male redstarts arrive on the breeding grounds several
days prior to females and begin singing immediately upon
arrival to demarcate territory boundaries and attract
females. During the arrival period (May 1–31), we surveyed the entire study area each day from 0600 to 1200,
detecting males through singing, mapping territory
boundaries, and identifying returning individuals by the
presence of leg bands. Birds on each territory were followed for at least 20–30 min/day and locations where
birds were observed were noted on paper maps with the
help of landmarks, trails, and camp numbers in the
campground, and a grid of flagged trees in the forest. For
birds mapped over multiple years, we determined approximate movement distances from 1 year to the next based
on the mapped territories. Due to the inexact nature of

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Survival and Movement in a Migratory Bird

the mapping, we grouped movement distances into
100 m categories (<100, 100–200, 200–300 m, etc.). We
recorded pairing date and the location of the nest. Once
nest-building commenced, we recorded the number of
eggs laid, hatching success, and fledging success (see Reudink et al. 2009).
Males, and occasionally females, were captured shortly
after arrival, using mist nets with song playback and a
decoy to simulate a territorial intrusion. Females were primarily captured during feeding trips to the nest or using
fledgling distress calls to lure them into the net. Upon capture, all individuals were given a single USGS aluminum
band and 2–3 color bands for individual identification.
Male American redstarts exhibit delayed plumage maturation and were aged based on plumage coloration; after second year (ASY), males are black with orange patches on the
tails, wings, and flanks, whereas second year (SY) males
exhibit the same patterning but resemble females with gray
and yellow plumage. Females were identified by plumage
coloration and the presence of a brood patch and aged
based on the degree of wear and coloring of the rectrices
and molt limits, following Pyle (1997).
We considered annual territory density for each habitat
type as the total number of pairs and unmated territorial
males each year (Table 1; see McKellar et al. 2014). We calculated annual mean fledging success for each habitat type
by dividing the total number of offspring successfully
fledged by the number of females monitored throughout
the entire season each year. We considered a habitat-specific movement event to occur when an individual that previously held a territory in one habitat type was found to hold
a territory in the other habitat type in a subsequent year.

Climate and vegetation indices
We obtained mean monthly values for the SOI from the
NOAA (National Oceanic and Atmospheric Administration) Climate Prediction Centre (http://www.cpc.ncep.
noaa.gov/data/indices/). We used the mean SOI during the
dry season from December through March as a proxy to
reflect the conditions experienced by American redstarts
during the nonbreeding period. Weather during this time
period in the Caribbean is associated with food availability
(Studds and Marra 2007), departure dates from the nonbreeding grounds (Studds and Marra 2011), arrival to the
breeding grounds (McKellar et al. 2013), and subsequent
breeding season abundance (Wilson et al. 2011).
We obtained NDVI values from the NASA Land
Processes Distributed Active Archive Center (LP DAAC;
https://lpdaac.usgs.gov/data_access). The NDVI is calculated
as (NIR  Red)/(NIR + Red) with NIR (near-infrared) and
Red being equal to the amount of near-infrared and red
light, respectively, reflected by a surface and recorded by

3

Survival and Movement in a Migratory Bird

A. E. McKellar et al.

Table 1. Annual territory density (number of territories), mean fledging success (fledglings per female), and habitat-specific movement for American redstarts in forest (F) or campground (C) type habitats. Movement events are indicated for the year in which movement into the new habitat
type occurred.

Year

F. territories

C. territories

F. fledging
success

C. fledging
success

2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

9
15
21
26
34
33
30
32
22
23
18

19
25
23
17
23
8
17
15
17
19
22

2.44
1.08
1.88
2.13
0.86
1.77
2.00
1.64
2.93
1.46
0.08

3.40
2.81
1.44
2.20
1.00
0.60
0.67
1.10
1.80
2.17
1.00

remote sensing (Jensen 2007). The NDVI is positively correlated with measures of plant productivity such as leaf area
index and canopy extent (Hicke et al. 2002; Wang et al.
2005). Data were provided as monthly 1 km resolution
products from the MODIS (Moderate Resolution Imaging
Spectroradiometer) Terra dataset. From these, we calculated annual mean NDVI from December through March
for islands in the Greater Antilles. Due to high correlations
between NDVI from Cuba and Jamaica (r = 0.70), and
from Hispaniola and Puerto Rico (r = 0.69), we computed
area-weighted means for the two regions and used separate
western (Cuba/Jamaica) and eastern (Hispaniola/Puerto
Rico) NDVI covariates in our models.
Local breeding season temperature and rainfall data were
obtained from a weather station at QUBS. The station provided mean daily temperature and daily total rainfall, and
we used these to calculate mean temperature and total rainfall for the breeding season (June–July) each year.

Multistate capture–recapture model
To examine survival and breeding dispersal, we used the
spatial configuration of the habitat types in a multistate
mark–recapture approach (Nichols et al. 1994; Lebreton
et al. 2009), which provides estimation of state-specific
probabilities of apparent survival and recapture as well as
the transition probabilities between states. While a multistate approach cannot separate true survival and permanent emigration, it can provide an indication of breeding
dispersal between habitat types and the extent to which it
varies with sex and age and in relation to our predictions.
Multistate analyses were conducted in program MARK
(White et al. 2006).
Each individual’s encounter history contained an “F” or
a “C” as the two states dependent on whether the individual held a territory in forest (F) or campground (C),
respectively, in year t1. As an example, we illustrate the

4

Movement
F–C

Movement
C–F

3
1
2
1
2
1

3
1
1

associated probabilities for an individual in state F at time
t1 (i.e., establishes in forest habitat). This individual will
either survive (/F) or die (1  /F) during the interval t1
to t as a partial function of having been established in forest
at time t1. If the individual survives the interval and
returns to the study area, it can remain in state F at time t
with probability wFF (i.e., establishes again in forest) or
move to state C with probability wFC = 1  wFF (i.e.,
establishes in campground). Thus, as defined here, the individual survives the interval prior to the movement event.
This is a reasonable assumption for Neotropical migrants
as we expect they return to their former territory during
the prebreeding period in year t and subsequently disperse
as opposed to dispersing between habitats prior to fall
migration in year t1. Regardless, this assumption pertains
to the influence of an individual’s state in year t1 on survival from t1 to t. Even if they prospect in the new habitat
during the postbreeding period, we expect that survival is
influenced by their habitat choice in year t1 and our
models were structured to represent survival followed by
dispersal. Conditional on the individual surviving the interval and returning to the study area, it can then be recaptured at time t with probability pF in forest or pC in
campground. An individual that has permanently emigrated from the study area cannot be recaptured and thus
multistate models as used here can only provide a minimum estimate of breeding dispersal.

Estimating apparent survival, recapture, and
movement
Model support was evaluated using AIC (Akaike’s information criterion, Burnham and Anderson 2002), and
model fit was examined using the median ^c test on the
most general model. Our model set did not contain a
fully time-dependent model, and therefore, a goodnessof-fit test was only possible with median ^c (Cooch and

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

A. E. McKellar et al.

Survival and Movement in a Migratory Bird

White 2013). If there was lack of fit, we used ^c to adjust
standard errors, and the DQAIC values and Akaike
weights (wi) were used to infer support for each of the
candidate models.
Our analyses included two objectives: (1) estimation of
how survival and movement rates varied between sex and
age classes, and (2) tests of predictions on the mechanisms that influenced survival and movement. Our modeling approach began with objective 1, and we used a
model that included additive effects of sex and age on
survival and state transition (i.e., movement) probabilities
to identify the recapture structure with the greatest support. To examine recapture, we included sex, age, and
habitat as additive effects along with reduced models that
excluded age and/or habitat. Due to larger sample sizes of
males (n = 445) than females (n = 211), we always
included sex in the models. We also included interactions
of sex by habitat and sex by age on recapture probability.
After evaluating support for recapture, we considered
additional survival and transition model structures with
habitat, interactions of sex and age, as well as reduced
models without age effects. We obtained the real parameter estimates for survival and movement by age and sex
using model averaging across the candidate set.
For objective 2, we used the most well-supported model
from objective 1 that also allowed us to test all predictions.
For apparent survival from year t1 to t, we considered
SOI and NDVI in year t1(December) to year t (January–
March), breeding season weather in year t1 (June–July
temperature and precipitation), and habitat-specific density
in year t1. The three nonbreeding season variables were
included individually because the El Ni~
no Southern Oscillation affects rainfall in the Caribbean (Ropelewski and Halpert 1987) and may influence plant productivity at larger
scales measured by the NDVI (Poveda et al. 2001). For SOI
and the two breeding season weather variables, we considered both linear and quadratic relationships because it is
possible that survival is lower at the extremes (e.g., El Ni~
no
and La Ni~
na events). All annual variables were standardized
prior to analysis with mean 0 and standard deviation 1.
Because models included interactions, we did not model
average the beta coefficients and instead report coefficients
for annual covariate effects from the top model containing
the respective variable.
To evaluate the influence of annual covariates, we
added each covariate individually to the best model without covariates and evaluated support in terms of change
in QAICc (including interactions of these variables with
age and sex). Covariates whose inclusion led to a drop in
QAICc were then included together in the top model.
We also examined support for reduced versions of this
model because correlated variables may explain the same
variance in the response. Finally, we added each of the

The estimate of ^c for the most general model was 1.18,
indicating a reasonable fit of the model to the data. We
fit 56 models in total, with 16 for objective 1 and 40
for objective 2. The recapture model with the greatest

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

5

previously excluded annual covariates back into the top
model and evaluated their support again because it is
possible that influential variables must be in the model to
identify weaker effects of other covariates. This latter step
will result in models that differ in only one parameter
and are within 2 QAICc units of the top models but
appear competitive only because of the variables in the
top model. Therefore, if the addition of these variables
did not lead to a reduction in QAICc, the model was
removed (see Devries et al. 2008).
For habitat-specific movement, we included the effects
of (1) mean fledging success in an individual’s habitat in
year t1 and (2) density in year t of the habitat in which
an individual occurred in year t1. Due to low sample
sizes, we only tested these variables as a uniform response
across sex and age classes, and as a uniform response
among age classes in males only.

Results
Between 2001 and 2010, we marked 211 females (117 ASY,
94 SY) and 445 males (261 ASY, 184 SY). Of these, 127
individuals were observed in at least one year subsequent
to marking and several were observed in two or more years
(mean  SD = 2.4  0.7 years). These 127 individuals
included 20 ASY females, 20 SY females, 65 ASY males and
22 SY males. Total movements between habitats were few;
of 178 cases where an individual had a known habitat in
year t1 and was observed in year t, 163 returned to the
same habitat while 15 switched habitats (three females, 12
males). The majority of habitat-specific movements were
from forest to campground (Table 1).
Of the 178 cases when an individual returned in a subsequent year, we were able to determine the approximate
distance moved for 152 cases, including all 15 movements
between habitat types and 137 movements within a habitat type (Fig. 1). For the remaining cases, mapping details
were not sufficient to categorize the movement distances.
For movements within habitat types, birds were often
found to return to the same or very nearby territories. In
contrast, movements that occurred between habitat types
often featured longer distances. At the same time, it was
possible for individuals to switch between habitat types
and yet move shorter distances than individuals that
remained within the same habitat type (Fig. 1).

Objective 1: survival, recapture, and
movement probabilities

Survival and Movement in a Migratory Bird

A. E. McKellar et al.

female apparent survival. There was little support for an
effect of habitat on apparent survival.
Movement probabilities between habitats were lowest
for ASY females, similar for SY females and ASY males,
and highest for SY males (Table 3). A model with sex*age
interactions had lower support than a sex+age model,
with males showing a higher probability of moving
between habitats than females but similar differences with
age for each sex. Our models did not support a difference
in the direction of movement between habitats although
this may have been a sampling limitation. Of 12 male
movements, 10 were from forest to campground, while 2
were the reverse. For females, all 3 movements were from
campground to forest.

Objective 2: influence of annual covariates
on apparent survival and movement
Figure 1. Frequency histogram of distances moved for American
redstarts that moved between habitat types (n = 15) or remained
within the same habitat type (n = 137) across years.

support included habitat and sex; recapture rates were
higher for males and in campground (male campground:
0.91  0.04, male forest: 0.70  0.10, female campground: 0.53  0.13, female forest: 0.21  0.07, Table 2).
Model-averaged estimates of apparent survival showed
similar values for the two age classes among females but a
strong difference among males, with SY birds displaying
far lower apparent survival compared to ASYs (Table 3).
Apparent survival of both male age classes was lower than

Apparent annual survival displayed a curvilinear relationship with the SOI and was highest at intermediate values
(b^SOI = 0.22, [95% CI: 0.14, 0.57], b^SOI:sq = 0.37,
[0.60, 0.15], Table 2, Fig. 2). There was no evidence
for males and females to differ in this relationship, and
while there was some support for a model with a quadratic SOI (SOIsq) by age interaction, the predictions from
that model showed similar patterns for the two age
classes. There was no evidence for an influence of NDVI
from Cuba/Jamaica on apparent annual survival as a uniform response (b^WestNDVI = 0.03 [0.15, 0.21]) or as an
interaction with age or sex. The addition of NDVI from
Hispaniola/Puerto Rico led to a drop in QAICc = 3.54
with a negative response of survival to NDVI
(b^eastNDVI = 0.23 [0.43, 0.04]). The response was

Table 2. Model selection results of factors influencing apparent survival (/), recapture (p), and movement rates (w) in American redstarts. The
change in Akaike’s information criterion based on quasi-likelihood with small sample correction bias (DQAICc), QAICc weights (wi), number of
model parameters (k), and model deviance (Qdev) are shown. We examined 56 candidate models and present the top 10 with Σwi > 0.99 as well
as the top model containing variation in /, p and w by sex, age and habitat prior to adding annual covariates (bolded).
Model1

DQAICc

wi

k

Qdev

/sex*age+SOIsq+rain psex*age+habitat wsex+age+ density (t1).male*
/sex*age+SOIsq*age+rain psex*age+habitat wsex+age+ density (t1).male
/sex*age+SOIsq+rain psex*age+habitat wsex+age
/sex*age+SOIsq+rain psex*age+habitat wsex+age+rep.succ
/sex*age+SOIsq*sex+rain psex*age+habitat wsex+age
/sex*age+SOI*age+rain psex*age+habitat wsex+age
/sex*age+SOIsq*age*sex+rain psex*age+habitat wsex+age
/sex*age+SOIsq psex*age+habitat wsex+age
/sex*age+SOI+rain psex*age+habitat wsex+age
/sex*age+rain psex*age+habitat wsex+age
/sex*age psex*age+habitat wsex+age

0
0.39
1.07
2.19
5.02
7.92
8.06
9.27
10.33
14.42
19.26

0.35
0.28
0.20
0.12
0.03
0.01
0.01
0.00
0.00
0.00
0.00

16
18
15
16
17
15
21
16
14
13
12

266.84
263.06
266.99
269.03
269.78
276.84
264.43
276.11
281.32
287.48
294.39

1

Subscripts include sex (gender), age (second year-after second year), habitat (campground-forest), rain (breeding season rainfall), SOI (linear relationship with Southern Oscillation Index [SOI]), SOIsq (quadratic relationship with SOI), density (t1), .male (male response to density in prior year),
rep.succ (habitat-specific reproductive success in prior year).

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ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

A. E. McKellar et al.

Survival and Movement in a Migratory Bird

Table 3. Apparent annual survival and habitat-specific movement
rates by age and sex for American redstarts. Values shown are the
model-averaged estimates and 95% confidence intervals from models
prior to including annual covariates.

Class
After second year
(ASY) female
Second year
(SY) female
ASY male
SY male

Apparent
annual survival

Breeding dispersal1

n

0.39 (0.26–0.53)

0.03 (0.01–0.14)

117

0.35 (0.20–0.55)

0.09 (0.03–0.28)

94

0.33 (0.27–0.39)
0.15 (0.09–0.23)

0.07 (0.03–0.13)
0.18 (0.06–0.40)

261
184

1

Shown for transition from forest to campground.

stronger for ASYs (b^eastNDVI ASY = 0.35, [0.58,
0.12]) than SYs (b^eastNDVI SY = 0.10, [0.27, 0.47]),
but showed no difference by sex.
We found a negative linear relationship between breeding ground rainfall and apparent survival (b^rain = 0.23,
(0.44, 0.02), R2dev = 0.199), with no variation by age
or sex. However, this negative effect appeared to be largely due to a single year of high survival from 2002 to
2003 when conditions were unusually dry during the
2002 breeding season (standardized rainfall = 2.18). A
re-analysis of the data with rainfall for that year set to the
average resulted in a higher QAICc than a model without
rainfall. Breeding ground temperature led to a drop in
QAICc when included individually (b^temp = 0.14, [0.06,
0.34], R2dev = 0.077, Table 2), but dropped out of top
models that included rainfall and SOI, perhaps because
wetter years are cooler on average. Addition of breeding
season density in year t  1 did not improve model
support, either as a uniform effect (b^density;sury = 0.13,
[0.09, 0.36], R2dev = 0.038) or as an interaction by age
or sex (Table 2).
Male movement between habitats was negatively density
dependent: individuals were less likely to move as the density
at their former habitat increased (b^density;maledisp = 0.63,
[1.31, 0.03], Fig. 3, Table 2). With both males and females
included, the coefficient was still negative but weaker and
the confidence intervals overlapped zero to a greater extent
(b^density;disp = 0.33, [0.92, 0.24], Fig. 3, Table 2). There
was no evidence that the average fledging success for a habitat in year t  1 had an effect on movement between habitats in year t (both sexes: b^success = 0.35, [1.14, 0.45],
males only: b^success;maledisp = 0.30, [1.16, 0.56], Table 2).

Figure 2. Relationship between the SOI (Southern Oscillation Index)
and apparent annual survival of female American redstarts in
southeastern Ontario, 2001–2011. Annual survival estimates
(mean  SE) were derived by model averaging across the candidate
set and are plotted against the winter SOI. Solid lines are the
predicted estimates from the second best model in Table 2 with an
SOIsq by age interaction. There was no evidence for different
responses of males and females and we only plot results for females
to illustrate the relationship.

Mark–recapture studies of avian survival typically assess
apparent survival, but often less attention is paid to
temporally varying factors that could influence dispersal

rates. We examined age- and sex-specific apparent survival rates in a population of American redstarts over
11 years. To examine one component of breeding dispersal, we made use of two distinct but adjacent habitat
types within our study area to examine movements
between habitat types. Finally, we assessed the influence
of potential drivers on rates of survival and movement to
test various predictions. Apparent annual survival was
generally low for all age and sex classes (<0.4), and particularly for SY males (0.15), but this group also showed the
highest movement rates between habitat types. We found

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

7

Discussion

Survival and Movement in a Migratory Bird

A. E. McKellar et al.

Apparent annual survival of American redstarts breeding
in Ontario (Table 3) was generally lower than previous
estimates from elsewhere across the breeding and nonbreeding range, particularly for SY males. In New Hampshire, USA, and Saskatchewan, Canada, annual survival
for all age and sex classes combined was 0.67 and 0.55,
respectively (Nichols et al. 1981; Bayne and Hobson
2002). In Jamaica, annual survival ranged from 0.28 to
0.58 across different age and sex classes and habitat
types, but was generally >0.4 (Johnson et al. 2006; Marra
et al. 2015). We suspect that substantial movement of
birds, rather than strictly lower survival, could have

played a role in the below-average survival rates on our
study site.
Despite a low overall number of movement events
between forest and campground habitat types on our
study site, we were able to estimated movement rates that
ranged from 0.03 for ASY females to 0.18 for SY males.
These values could be interpreted as minimum estimates
of true breeding dispersal. In other words, the movement
rates that we calculated represent small-scale local movements (<1400 m; Fig. 1) that are only one component of
true breeding dispersal. We were not able to account for
long-distance dispersal events that could have resulted in
permanent emigration when birds moved out of our
study site. For example, recent work using stable isotope
techniques has shown that long-distance dispersal distances can be substantial (i.e., hundreds of km) and can
be influenced by conditions experienced by birds on the
nonbreeding grounds – although these dispersal events
are most common during natal dispersal (i.e., from hatch
year to SY; Studds et al. 2008; Rushing et al. 2015a). Similarly, we could not account for small-scale movement
that could have occurred if birds moved to nearby territories just outside of our study site boundaries, but within
the same habitat type. Indeed, we observed a number of
small-scale movements (<500 m) of birds which remained
within the same habitat type on our study site from year
to year. Interestingly, the semi-fragmented nature of our
study region could have influenced the dispersal behavior
of birds. For example, our estimates of apparent survival
were most similar to another highly fragmented landscape
in central Alberta where survival rates were 0.40 for ASY
males and 0.23 for SY males (S. Hannon, unpubl. data).
Thus, although we have suggestive evidence for breeding
dispersal influencing apparent survival rates, particularly
for SY males which showed a strong negative correlation
between apparent survival and movement rates, a full
consideration of movement at multiple scales would be
needed to fully understand this relationship.
Comparison of our results with other studies where
movement may be more limited can provide a sense of
the proportion of individuals leaving our study area
between breeding seasons. Studies on Neotropical
migrants have found that the vast majority of annual
mortality occurs during the nonbreeding period (Sillett
and Holmes 2002; Sillett & Marra, unpubl. data). For
American redstarts, individuals that breed in eastern
North America are thought to overwinter primarily in the
Greater Antilles (Norris et al. 2006). Thus, long-term field
studies of American redstarts in Jamaica likely sample the
same overall population as our study population in
Ontario, and they likely experience similar sources of
mortality throughout the annual cycle. Estimates of
apparent annual survival in high-quality mangrove habitat

8

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Figure 3. Predicted movement of after second year male American
redstarts in relation to habitat-specific density in southeastern Ontario,
2001–2011. Values are the model-averaged estimates (95% CI) and
show the predicted movement from forest to campground in relation
to the density in a male’s habitat from the previous year. Note that
seven rather than ten data points are shown due to density in forest
being the same for some years.

support for the hypothesis that global climate cycles influence survival. However, while we predicted that survival
would be higher during La Ni~
na events, we found lower
survival during El Ni~
no and La Ni~
na conditions with
higher survival in average years. We found support for
the hypothesis that breeding density influences movement
rates between contiguous forest and more disturbed
campground habitat types, but no evidence that movement was affected by habitat-specific reproductive success.

Apparent annual survival and movement
rates

A. E. McKellar et al.

in Jamaica were 0.50 for SY males and 0.59 for ASY
males, and while some interannual movement may occur,
it is likely low (Marra et al. 2015). If annual survival is
similar between redstarts that breed on our study site and
those that overwinter in Jamaica, this would suggest that
only 15% of SY breeders in year t survive and return to
the study area in year t + 1, while about twice as many
would survive and return, but breed outside of the study
area. Of those that did return to the study area, we found
that 18% on average switched habitats. If this approach is
applied to the other age classes, it suggests that roughly
one quarter of ASY males and <10% of females would
return but breed elsewhere. We acknowledge that these
are only coarse estimates dependent on several assumptions but they provide an approximate extent of breeding
dispersal beyond what we were able to measure in this
study.

Influence of annual covariates on apparent
survival
Survival of American redstarts was highest at intermediate
values of the SOI and declined under La Ni~
na and El Ni~
no
conditions. This is in contrast to previous work showing
positive effects of an increasing SOI (La Ni~
na conditions)
on survival in other Neotropical migrants (Sillett et al.
2000; Mazerolle et al. 2005). It should be noted, however,
that no strong El Ni~
no events occurred during the course
of our study, in contrast to several strong El Ni~
no events
and no strong La Ni~
na events in the 1990s that were
reported in previous work (Sillett et al. 2000; Mazerolle
et al. 2005). In our study, apparent survival was particularly
low during the La Ni~
na event of 2010–2011, the strongest
La Ni~
na episode in the past century, when only two of 51
individuals known to be alive in 2010 were observed in the
study area. While El Ni~
no events have been associated with
lower winter rainfall (Ropelewski and Halpert 1987) which
may contribute to reduced body condition of redstarts
(Studds and Marra 2007), La Ni~
na events generally result in
higher winter rainfall, and thus it is not clear why this
would contribute to lower survival. A recent study of a
nonbreeding population of American redstarts in Jamaica
also reported a negative influence of increasing rainfall on
apparent survival (Marra et al. 2015). Taken together, these
results suggest that both weather extremes may have negative effects on American redstart survival. While El Ni~
no
conditions have been linked to survival through effects on
rainfall, perhaps larger scale effects of La Ni~
na conditions
influence individuals throughout the annual cycle. For
instance, La Ni~
na conditions are associated with tropical
storm frequency in the Caribbean (Vitart and Anderson
2001), which could negatively affect individuals during
migration or winter. Another intriguing possibility is that a

ª 2015 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Survival and Movement in a Migratory Bird

joint influence of the El Ni~
no Southern Oscillation on
departure decisions from the wintering grounds and
weather on the breeding grounds constrains survival in redstarts. Higher rainfall in Jamaica is associated with earlier
departure from Jamaica (Studds and Marra 2011) and earlier arrival in Ontario (McKellar et al. 2013), and birds
arriving too early may face unfavorable conditions such as
cold weather in April and May that is typical of La Ni~
na
events in eastern Canada and the northeastern United
States (Shabbar 2006). We did not find strong evidence for
an age or sex difference in the influence of the SOI on survival.
Overall, winter NDVI from the larger of the nonbreeding
areas (Cuba and Jamaica) did not appear to have any influence on survival, while there was some evidence of a negative effect on survival of NDVI in Hispaniola and Puerto
Rico, which was stronger in ASY males. This was contrary
to our predictions and may have been driven by correlations between the NDVI and SOI, and the generally more
negative association between SOI and survival (Fig. 2).
Density-dependent population regulation has been
observed across a wide range of taxa (Newton 1998; Coulson et al. 2001). In American redstarts, annual survival
decreases with increasing density in high-quality habitat on
the Jamaican nonbreeding grounds (Marra et al. 2015),
and fecundity decreases with increasing density on the
Ontario breeding grounds (McKellar et al. 2014), but we
did not observe density-dependent survival on the breeding
grounds. Similarly, density-dependent fecundity, but not
annual survival, was observed in a breeding population
of black-throated blue warblers (Setophaga caerulescens)
(Sillett and Holmes 2005). The lack of density-dependent
survival on the breeding grounds could be a reflection of
generally high oversummer survival of migratory birds
(Sillett and Holmes 2002), indicating that negative effects
of density such as crowding do not influence annual
survival on the breeding grounds. In contrast, on the
nonbreeding grounds, crowding results in a decrease in
body condition and likely later departure in American
redstarts, possibly increasing mortality risk during subsequent phases of the annual cycle (Marra et al. 2015). The
contrasting patterns of density dependence in breeding and
nonbreeding areas could have implications for management and conservation of migratory populations across the
annual cycle (Sheehy et al. 2010).

Influence of annual covariates on
movement
Both positive and negative density-dependent dispersal
have been observed in a variety of bird and mammal
species (Matthysen 2005). In a playback experiment,
Hahn and Silverman (2006) found evidence for negative

9

Survival and Movement in a Migratory Bird

density-dependent dispersal caused by conspecific attraction in American redstarts breeding in Michigan, USA.
Our results provide further evidence for conspecific
attraction in redstarts, because returning birds were less
likely to disperse between habitat types when the density
at their previously occupied habitat was greater (Fig. 3).
This pattern was strongest in males, although sample sizes
were much lower for females. While the results of Hahn
and Silverman (2006) were driven primarily by new ASY
males recruiting into the population (see also Rushing
et al. 2015b), our results demonstrate that returning
males may also respond to local density in their settlement decisions. Male redstarts may benefit from settling
in dense areas due to increased opportunities for extrapair paternity, although they may face a trade-off due to
greater paternity losses in these areas (McKellar et al.
2014). Interestingly, our results and those of Studds et al.
(2008) and Rushing et al. (2015a) suggest that different
mechanisms may operate at different scales to influence
large and small-scale movement patterns of redstarts (i.e.,
habitat quality on the nonbreeding grounds vs. density on
the breeding grounds), which may have implications for
optimal conservation strategies in the face of habitat loss
and climate change (Knowlton and Graham 2010).
In contrast to our second dispersal prediction, we found
no effect of habitat-specific fledging success on movement
patterns. Previous work has shown that greater numbers of
fledglings can attract more adults to that habitat the subsequent season (Doligez et al. 2002; Parejo et al. 2007). We
used mean fledging success, which may not have adequately
reflected the reproductive output of a habitat. We were not
able to use total number of fledglings due to incomplete
reproductive data for all pairs. However, recent work with
American redstarts breeding in Maryland, USA, also failed
to find evidence for the use of public information on breeding habitat selection: experimental plots treated during one
breeding season with adult and fledgling calls were no more
likely to be settled the subsequent season than were control
plots (Rushing et al. 2015b).

A. E. McKellar et al.

events as movements between two distinct habitat types
within our study area. This method proved especially useful
in our study system because it both aided in the interpretation of unusually low apparent survival and provided
insights into proximate causes of breeding dispersal
between habitat types. Future work should take into
account other forms of dispersal, both large-scale and
small-scale, in order to adequately distinguish mortality
from permanent emigration, which will no doubt be critical
to accurately parameterizing population models needed for
setting conservation goals (Fletcher et al. 2006).

Acknowledgments
We thank the many field assistants, technicians, and students who worked on this project over the years. Funding
was provided by the National Science Foundation
(P.P.M), Natural Sciences and Engineering Research
Council of Canada (L.M.R. and students), and Environment Canada.

Conflict of Interest
None declared.
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