EDITED Karmacharya Draft Five_SDT FINAL

Population Dynamics of Northern Cardinal and Carolina Wren in an Urban Forest Fragment:
Safe Refuge or Ecological Trap?
A Thesis
Presented to the
Graduate Faculty of the
University of Louisiana at Lafayette
In Partial Fulfillment of the
Requirements for the Degree
Master of Science
Binab Karmacharya
Fall 2015

© Binab Karmacharya
2015
All Rights Reserved

Population Dynamics of Northern Cardinal and Carolina Wren in an Urban Forest Fragment:
Safe Refuge or Ecological Trap?
Binab Karmacharya
APPROVED:
Scott M. Duke-Sylvester, Chair Joseph E. Neigel
Assistant Professor of Biology Professor of Biology
Paul L. Klerks Mary Farmer-Kaiser
Professor of Biology Dean of the Graduate School

ACKNOWLEDGMENTS
I thank my adviser, Dr. Scott M. Duke-Sylvester, for his guidance throughout my
graduate study and for his patience, critical suggestions, and encouragement during the
preparation of this manuscript. I also thank my committee members, Drs. Joseph E. Neigel
and Paul L. Klerks, for their help in improving this manuscript.
I am very grateful to three individuals: Jeff Hostetler, Erik Johnson, and Jared Wolfe.
Jeff helped me with data analysis and Erik and Jared taught me important aspects of field
ornithology, avian ecology, and bird banding. I cannot imagine completing this work without
their help.
I am grateful to many people and agencies for supporting my graduate degree and this
project. Thanks to all the volunteers at the Louisiana Bird Observatory, who worked hard
under tough conditions to collect the data. The Department of Biology, University of
Louisiana at Lafayette, and the Louisiana Board of Reagent supported my graduate program,
and the Graduate Student Organization at the University of Louisiana provided funding for
field equipment.
I am grateful to my wife, Janabi, daughter, Ojaswi, and my parents for support and
encouragement throughout the graduate program.

TABLE OF CONTENTS
ACKNOWLEDGMENTS ................................................................................................. iv
LIST OF TABLES............................................................................................................. vi
LIST OF FIGURES .......................................................................................................... vii
INTRODUCTION ...............................................................................................................1
METHODS ..........................................................................................................................5
RESULTS ..........................................................................................................................10
DISCUSSION....................................................................................................................13
TABLES ............................................................................................................................18
FIGURES...........................................................................................................................21
LITERATURE CITED ......................................................................................................25
ABSTRACT.......................................................................................................................34
BIOGRAPHICAL SKETCH .............................................................................................36

LIST OF TABLES
Table 1: Model comparison table for Cormack–Jolly–Seber capture–mark–
recapture analysis to investigate the best base model for capture probability (p)
and survival (φ) for Northern Cardinals at the Bluebonnet Swamp Nature Center,
Baton Rouge, Louisiana, from 2010 to 2014. The table includes the number of
parameters (K), difference in AICc (∆AICc), and model weights (relative
likelihood of models in the set). Only the ten best-supported models are presented...............18
Table 2: Model comparison table for Cormack–Jolly–Seber capture–mark–
recapture analysis to investigate the best base model for capture probability (p)
and survival (φ) for Carolina Wrens at the Bluebonnet Swamp Nature Center,
Baton Rouge, Louisiana, from 2010 to 2014. The table includes the number of
likelihood of models in the set). For this analysis capture probability (p), was
modeled as p ((season) + effort; Table S2). Only the ten best-supported models
are presented ............................................................................................................................19
Table 3: Model comparison table for reverse-time capture-recapture Pradel model
to investigate the best model for realized population growth rate (λ) for Northern
Cardinals and Carolina Wrens at the Bluebonnet Swamp Nature Center, Baton
Rouge, Louisiana, from 2010 to 2014. The table includes the number of
likelihood of models in the set). For this analysis capture probability (p) was
modeled as p (season + effort + sex) and survival rate (φ) was modeled as φ (year
+ season + sex) for Northern Cardinals, and p (season + effort) and φ (year) for
Carolina Wrens. .......................................................................................................................20

LIST OF FIGURES
Figure 1: Annual, seasonal and sex-specific variation in monthly apparent
survival estimates (± SE) of resident Northern Cardinals in the Bluebonnet
Swamp Nature Center, Baton Rouge, Louisiana, from 2010 to 2014. Open circles
represent females and solid triangles represent males.............................................................21
Figure 2: Effect of size apparent survival estimates (± SE) of Northern Cardinals
and Carolina Wrens in the Bluebonnet Swamp Nature Center, Baton Rouge,
Louisiana, from 2010 to 2014..................................................................................................22
Figure 3: Seasonal variation in monthly realized population growth rate (± SE) of
Northern Cardinals and Carolina Wrens in the Bluebonnet Swamp Nature Center,
Baton Rouge, Louisiana, from 2010 to 2014. Open circles represent Carolina
Wrens and solid triangles represent Northern Cardinals .........................................................23
Figure 4: Annual variation in monthly apparent survival estimates (± SE) of
Carolina Wrens in the Bluebonnet Swamp Nature Center, Baton Rouge,
Louisiana, from 2010 to 2014. ................................................................................................24

INTRODUCTION
Habitat loss and fragmentation has been a primary cause of the global biodiversity
crisis (Wilson 1992). The fragmentation of native landscape often results in networks of
small and isolated habitat patches that offer varying degrees of ecological value to resident
and migrant bird communities (Stephens et al. 2004). Although the creation of small nature
preserves embedded within urban matrixes is often perceived as a possible mitigation
strategy to anthropogenic development, these isolated habitat patches may actually serve as
ecological traps where bird species prefer to settle, but experience reduced survival and
reproduction (Gates and Gysel 1978, Robertson and Hutto 2006). Ecological traps can
manifest in small nature preserves for several reasons: edge effects may support populations
of native and exotic predators, increase contact with emerging diseases and environmental
contaminates, and resulting structural changes in vegetation can reduce or alter food and
shelter resources (Batten 1973, Dunn and Tessaglia 1994, Franklin et al. 2000, Rolstad
1991). In general, birds adapted to habitat heterogeneity, such as edge-specialists, tend to fare
better in small nature preserves as opposed to bird species which are more reliant on pristine
habitats (Temple and Cary 1988, Villard 1988, Whitcomb et al. 1981). As urban centers
continue to expand into wild and rural areas, researchers have begun to focus on ways to
improve the quality of urban areas for birds sensitive to human development (Rosenzweig
2003). Clearly, to prevent causing more harm than good, land managers need to understand
how small nature preserves within urban matrices influence bird populations (Donnelly and
Marzluff 2004, Wolfe et al. 2013).
To precisely determine the ecological value of nature preserves to birds, we must
move beyond measures of abundance and focus on species-specific vital rates, such as

2
survival, recruitment, and population growth, to better understand processes that determine
population-level persistence (Van Horne 1983). Additionally, by examining demographic
processes that influence avian persistence within small nature preserves, we can begin to
identify those behavioral and physiological attributes that make certain bird species more
successful than others within a fragmented landscape.
As such, capture-mark-recapture (CMR) methodologies have been used extensively
to generate survival, recruitment and population growth estimates for a diversity of bird
species (Pradel 1996). CMR frameworks are particularly useful for disentangling
mechanisms responsible for variation in vital rates by modeling survival, recruitment, and
population growth as a function of habitat and physiological attributes of individual birds
(Johnson and Omland 2004). For example, a study carried out in the boreal forest of Canada
revealed that Ovenbirds (Seiurus aurocapilla) suffered lower survival in habitat patches
surrounded by a ‘harder’ agricultural-edge than birds in fragments with a ‘softer’ forestry-
edge (Bayne and Hobson 2002). The asymmetrical response to edge effects suggest that birds
residing in nature preserves within urban matrices must be well-adapted for ecotones, or,
conversely, birds in small nature preserves suffer from high mortality rates and populations
are subsequently replenished by immigrants from more salubrious habitats.
Birds are adapted to predictable and seasonal changes in climate, length of day, and
availability of food resources resulting in periods of opportunity and stress. In this context,
non-migratory birds have evolutionarily streamlined three energetically intensive annual
cycle events to maximize individual and population level success throughout the year: spring
and summer reproduction, molting in the late summer and fall, and increased
thermoregulatory needs during the winter season. Non-migratory birds presumably structure

3
the two most energetically taxing phases of the annual cycle, breeding and molt, around the
availability of seasonal food resources (Jacobs and Wingfield 2000). Additional energetic
expenditure during periods of breeding and molt may negatively affect survival despite
increased food availability. Conversely, reduced or unpredictable food resources coupled
with cold weather during the winter periods can have a strong negative influence on survival
(Desrochers et al. 1988, Jansson et al. 1981). Measuring differences in survival across the
annual cycle represents a critical step towards identifying the phase of the life cycle where
non-migratory bird populations are most vulnerable to perturbation and would benefit most
from protection.
In addition to variation throughout the annual life cycle, variation in individual traits
like age, sex, and body size may also influence vital rates (Lomnicki 1988, DeAngelis and
Gross 1992, Lebreton 1992). Overall, body size is an important indicator of individual fitness
and wing length is one of the best proxy-measurements of body size in birds (James 1970,
Hamilton 1961). Clearly, the physiological condition of individual birds influences survival
probability as exemplified by studies of blackbird demography, where a positive correlation
between body size (based on wing length) and survival rate was detected (Searcy and
Yasukawa 1981). Both age and sex can also play a role in determining individual
survivorship. Birds in their first year of life are often less likely to survive than adults
(Woolfenden 1984); differences in survival between age classes may be attributed to superior
competitive ability and a wider range of learned skills amongst adults (Siriwardena et al.
1998, Armstrong et al. 2002). In addition to differences in survival between age classes,
differences in survival between sexes could arise from the cost of sexually selected traits and
asymmetric costs of reproduction (Promislow 1992, Promislow et al. 1992). For example,

4
some blackbird species exhibit sexual skew in survival where dichromatism may result in
higher mortality amongst males with brightly colored plumage (Searcy and Yasukawa 1981).
Mortality amongst males was higher than females during an outbreak of Mycoplasma
infection amongst House Finches (Carpodacus mexicanus) (Nolan et al. 1998).
In this study, we sampled Northern Cardinal (Cardinalis cardinalis) and Carolina
Wren (Thryothorus ludovicianus) populations in a 41.7-ha nature preserve embedded in an
urban matrix to ascertain the influence of sex, age, body size, and seasonal and annual
variation in survivorship, recruitment, and population growth. Specifically we explored if or
how these two species persist in a small habitat fragment, and which vital rate characteristics
are most limiting to their persistence. Our results represent the first published full annual
cycle estimates of survival and population growth relative to age, sex, and body size for non-
migratory passerines.

METHODS
Study Sites –- Our study was carried out at Bluebonnet Swamp Nature Center located
within the city of Baton Rouge, Louisiana (lat: 30.369 and long: -91.107). The swamp is a
41.7-ha reserve containing lowland hardwood forest and forest residential edges dominated
by bald cypress (Taxodium distichum L) and water tupelo (Nyssa aquatica L). The
understory is composed of emergent wetland species in areas that are perennially flooded,
and of dense stands of understory shrubs dominated by Chinese privet (Ligustrum sinense).
Once part of a larger bottomland hardwood system, much of the watershed was converted to
agriculture by the 1940s, followed by a rapid conversion of agricultural to residential use in
the 1960s continuing through today (BREC 2013). To protect the remnant swamp from
continuing urban expansion, the study site was designated as conservation area in 1997 after
being purchased by The Nature Conservancy and donated to the Parks and Recreation
Commission of East Baton Rouge Parish. The park remains an isolated patch of protected
forest and swamp embedded in the dense urban habitat (Wolfe et al. 2013).
Study species – Northern Cardinals are a non-migratory passerine distributed
throughout eastern and central North America from southern Canada into Mexico (Halkin
and Linville 1999). They are found in a variety of habitats with shrubs and/or small trees,
including forest edges and interior, shrubby areas in logged and second-growth forests, marsh
edges, grasslands with shrubs, successional fields, hedgerows in agricultural fields, and
plantings around buildings (Dow 1969, Halkin and Linville 1999). Carolina Wrens are also a
non-migratory passerine distributed throughout the eastern United States and into Mexico
and they inhabit a wide range of habitats including brushy clearcuts, lowland cypress
(Taxodium sp.) swamps, forests, and ravines densely populated by hemlock (Tsuga sp.) and

6
rhododendron (Rhododendron sp.) (Dickson et al. 1984, Horn 1984). In spite of their similar
geographic distribution and habitat preference, Northern Cardinals and Carolina Wrens have
distinctly different life history strategies. Northern Cardinals are sexually dimorphic with
males being bright red and larger relative to the browner-colored females. Northern Cardinals
form pair bonds and defend their territory only during the breeding season, whereas during
the non-breeding season they live in non-cohesive nomadic flocks (Filliater and Breitwisch
1997). Male and female Carolina Wrens are indistinguishable in appearance, with males
being only slightly larger than females (Pyle 1997, Twedt 2004). Also in contrast to Northern
Cardinals, Carolina Wrens maintain a year-round pair bond and home territory, maintained
by calls and songs rather than plumage ornaments (Haggerty et al. 2014).
Field Methods – We sampled bird populations twice a month year-round from April
2010 to March 2014. Each sampling period started at sunrise and lasted for five hours. Birds
were captured using 12 m x 2.6 m mist-nets with a 36-mm mesh size. Nets were deployed at
a set of permanent net runs located within the nature center and positioned in areas with
varying plant densities. From April 2010 to February 2013, we used an initial set of 15 net
locations, which was sampled twice a month. In March of 2013, we added a second set of 15
net location and alternated between the original set of 15 and the new set of 15 net, with each
set being sampled once per month. On a few occasions we ran as few as 10 nets (due to
damaged nets) or as many as 30 nets during a sampling period, and adjusted for variation in
sampling effort in our data analysis as necessary (see below). Nets were checked
approximately every 30 minutes, but during cold weather they were checked as often as
every 15 minutes. All birds extracted from nets were placed individually into clean cotton

7
bags with drawstrings with the time and net number of each capture noted on the bag. Birds
were returned to a central station for processing.
Newly caught individuals were marked with uniquely numbered USFWS metal bands
and released near the capture site. For all captured individuals, we recorded date, net ID,
band number (if previously captured), sex, age, molt limit, molt cycle, reproductive
condition, mass, and wing length. Birds were aged using molt limit criteria described by Pyle
(1997). For this study, we categorized individuals into one of two age groups, immature or
adult. Individuals in their pre-formative molt or earlier in life were categorized as "immature"
(approximately < 5 months old), whereas individuals in their formative and definitive basic
plumages were categorized as "adult" (approximately > 5 months old).
We conducted 104 capture occasions over the four-year period. To analyze the data,
we divided each year into three seasons: breeding, molting, and winter. The study period was
divided into annual cycles spanning between April of one year and March of the subsequent
year. This meant that each study year started with the breeding season and ended with the
winter season. Observed breeding and molting records of birds captured at our study site
were used to determine the onset and termination of those seasons. Based upon these
observations, we categorized April 1 to July 15 as the breeding season, July 16 to October 31
as the molting season, and November 1 to March 31 as the non-breeding season. This was
consistent with the breeding and molting cycle reported in the previous studies (Halkin et al.
1999, Haggerty et. al. 2014). Standardized right wing length (standardized to have a mean of
0 and a standard deviation of 1) was used as an index of body size.
Statistical Methods – We analyzed our data using the program MARK (White and
Burnham 1999) with the R package RMark (R Development Core Team 2013, Laake and

8
Rexstad 2008). We performed a goodness-of-fit test using the median ĉ approach (White and
Burnham 1999) and found no evidence of over-dispersion or lack of fit (ĉ = 1.00). Model
selection was accomplished with Akaike’s Information Criterion corrected for small sample
size (AICc) (Burnham and Anderson, 2002). The model with the lowest AICc value is
considered the best supported model, although models with a difference in AICc (∆AICc) of
< 2 are considered to have similar support with no evidence for difference among models
being compared; 2 ≤ ∆AICc ≤ 4 suggests evidence for considerable difference, 4 ≤ ∆AICc ≤
7 suggests substantial evidence for difference, and ∆AICc > 7 is generally indicative of
overwhelming evidence for difference in support received by the models being compared
(Burnham and Anderson 2002). If no single model received overwhelming support,
suggesting model selection uncertainty, we averaged parameter estimates weighed by model
certainty (Burnham and Anderson 2002). We investigated various aspects of demography
using three classes of CMR models: Cormack Jolly Seber (CJS), multi-state, and reverse-
time Pradel models.
Apparent survival rate (φ) and recapture probability (p) were modeled and estimated
with CJS models (Lebreton et al. 1992). Model selection was carried out in a sequential
approach. First we investigated the influence of sex, season, year, capture effort (the number
of nets used during each capture occasion), and capture occasion on p. The best model of p
was used to test for effects of sex, transient individuals, season, size, year, and their additive
and two-way interactive effects on φ. Time-since-marking (TSM) models that accounted for
transients were used to account for survival deflation due to presence of transient individuals
moving thorough the study area (Pradel 1996, Pradel et al. 1997). Finally, multi-state models

9
were used to test for variation in age-specific (immature and adult) apparent survival rate
(Brownie et al. 1993).
A reverse-time Pradel model was used to model and estimate realized population
growth rate (λ) (Hines and Nichols 2002, Pradel 1996). We tested for the effect of season,
year and their additive effect on λ. Even though reverse time models cannot account for the
negative bias in survival rate introduced by transient individuals, the estimates of λ will be
unbiased, as underestimation of survival rates is balanced by overestimation of recruitment
rate (Saracco and DeSante 2008). Recruitment rates (f) and seniority parameters (γ) were
derived from λ and φ (estimated with CJS model accounting for transients) using the formula
f = λ - φ and γ = φ/ λ (Saracco et al. 2008). Proportional contribution of φ and f to λ was
explored by using seniority parameter (γ), the probability that an individual in the population
was also present in the population previous period (Nichols et al. 2000).
The time intervals between capture occasions were adjusted in the program MARK
such that monthly (30-day) estimates of population parameters were provided. We report
estimates of parameters and confidence intervals as monthly rates and report annual estimates
as monthly rates raised to the 12th
power. Unless indicated otherwise, all means were
presented as ± 1 standard error (SE).

RESULTS
Northern Cardinal – During our four-year study period, we captured 362 (189 males and
173 females) individual cardinals a total of 843 times. Our initial model analysis using CJS
models revealed that the capture probability (p) was best described by an additive effect of
sex, season, and capture effort (Table 1). The best-supported model for monthly apparent
survival, φ, included an interactive effect of sex and body size, and an additive effect of year,
season, and transients (Table 1). Because the top ten models differed by ΔAICc < 7,
indicating model selection uncertainty, we averaged the top ten models to obtain model-
averaged parameter estimates. The latter estimates were similar to the estimates from the
best-supported model.
Overall average monthly survival (φ) was 0.947 ± 0.006 during the study period.
Estimates from the best-supported CJS model suggested that average monthly φ was highest
for females during the winter season of year 2011-12 (0.977 ± SE 0.009) and lowest for
males during the breeding season of year 2010-11 (0.811 ± 0.057) (Figure 1). Average
monthly φ was 0.954 ± 0.007 for females and 0.938 ± 0.009 for males. Average monthly φ
was lowest in the year 2010-11 compared to rest of the study period (Figure 1). Average
monthly φ was 0.913 ± 0.020 for the breeding season, 0.952 ± 0.014 for the molting season,
and 0.963 ± 0.012 for the winter season. The top CJS models included body size as an
explanatory variable, with bigger birds exhibiting higher survival (Figure 2). The overall
average monthly survival rate of adults (0.940 ± 0.006) was higher than that of immatures
(0.870 ± 0.060).
The best-supported Pradel model indicated that seasonal variation was an important
factor for the population growth rate (λ) (Table 3). Average monthly population growth rate

11
(λ) was highest during the breeding season (1.116 ± 0.035) and lowest during the winter
season (0.957 ± 0.019) (Figure 3). Overall average monthly λ was 1.007 ± 0.004 and average
annual λ was 1.092 ± 0.051. Average monthly recruitment rate (f) and seniority rate (γ)
during the breeding season were 0.203 and 0.818.
Carolina Wren – During our four-year study period, we caught 149 individual wrens
a total of 432 times. Due to the absence of obvious sexual dimorphism, we did not categorize
individuals as male or female. Our initial model analysis with the CJS method revealed that
capture probability (p) was best described by an additive effect of season and capture effort
(Table 2). The best supported model for monthly apparent survival (φ) included an additive
effect of year, body size, and transients (Table 2); however, the top ten models differed by
ΔAICc < 7, indicating model selection uncertainty. We employed model averaging to obtain
model-averaged parameter estimates. Model averaged parameter estimates were similar to
the best-supported model and there was no indication of seasonal variation. Survival
estimates are provided only for the resident birds with transients excluded.
Overall monthly survival rate φ was 0.919 ± 0.011. The best-supported model showed
that average monthly apparent survival rate (φ) was highest in year 2010-11 (0.955 ± 0.015)
and lowest in the year 2012-13 (0.897 ± 0.020) (Figure 4). The top CJS models included
body size as an explanatory variable, with bigger birds exhibiting higher survival (Figure 2).
Monthly survival rate for immatures (0.656 ± 0.053) were significantly lower than that of
adults (0.938 ± 0.010).
The most parsimonious model for population growth rate (λ) included a model with
seasonal variation (Table 3). Average monthly λ was highest during the breeding season
(1.246 ± 0.058) and lowest during the molting season (0.883 ± 0.038) (Figure3). Overall

12
average monthly λ was 1.010 ± 0.002 and average annual λ was 1.133 ± 0.075. Average
monthly recruitment rate (f) and seniority rate (γ) during the breeding season were 0.304 and
0.756, respectively.

DISCUSSION
Annual life cycle estimates of survival, recruitment and population growth rates for non-
migratory birds are surprisingly rare as studies often focus on breeding or winter ecology
exclusively. Despite a growing interest in measuring vital rates for migratory birds during
breeding, migratory, and winter periods (Hostetler et al. 2015, Taylor and Norris 2010), we
are unaware of studies that report annual life cycle estimates of multiple vital rates for non-
migratory passerines. In this vein, we used 4 years of year-round mark-recapture data to
examine variation in survival and population growth of Northern Cardinals and Carolina
Wrens within a nature preserve throughout their annual cycles. The overall annual survival
rate (0.520 ± 0.050) of the Northern Cardinal was similar to the regional baseline estimate of
0.537 ± 0.008 (DeSante and Kaschube 2009) and overall annual survival rate (0.349 ± 0.050)
of Carolina Wren was similar to the regional baseline estimate of 0.358 ± 0.022 (DeSante
and Kaschube 2009). In spite of their contrasting life history strategies, both species had
stable or even slightly growing populations (annual growth rate >1) suggesting that the 41.7-
ha refuge served as a source, not an ecological trap, for these two resident bird species.
Our study did not find support for a proposed facet of life history tradeoff theory,
which predicts lower survival during cold winter months when food resources become scarce
(Desrochers et al. 1988, Jansson et al. 1981). The paucity of winter food resources has been
elicited as a selective pressure that led to the long-distance movements of Nearctic-Neotropic
migrant birds (Cox 1968, Levey and Stiles 1992). Five non-mutually exclusive processes
may explain the lack of evidence for a demographic tradeoff between the breeding and winter
seasons at our study site. First, the subtropical environment of central Louisiana provides the
winter resources necessary to maintain relatively high survival for both species. Second, the

14
availability of supplemental food at bird feeders may mitigate the paucity of natural food
resources during winter months for cardinals (wrens do not feed at feeders). Third, some
dominant nonnative plants, such as Chinese privet (Ligustrum sinense), may provide the food
and structural resources necessary to sustain relatively high survival through the cold winter
months. More specifically, Chinese privet is not deciduous thereby potentially providing the
structural resources for insectivorous understory birds, like Carolina Wren, to acquire the
food necessary to persist through the winter. Furthermore, Chinese privet provides an
abundant winter crop of fruit that Northern Cardinals commonly consume (J. D. Wolfe,
personal observations). Fourth, an absence of some migrant birds may provide an
intraspecific competitive release for both species. Fifth, these species have evolved to adjust
metabolic needs in winter and adjust their diet in concordance with seasonally shifting food
resources. Expanding this study across latitudes and habitats would provide valuable tests of
these hypotheses.
Seasonal variation in survival was detected only for the Northern Cardinal, where
survival was lowest during the breeding season in both sexes, suggesting a cost associated
with breeding in the study area. The cost of reproduction on survival is an important tradeoff
around which life histories are thought to evolve (Williams 1966, Stearns 1992); tradeoffs
affecting survival during the breeding season include metabolic drain or increased
susceptibility to pathogens, such as West Nile virus and avian malaria, and increased
vulnerability to predators (Bennett and Cameron 1974, Harshman and Zera 2007,
Magnhagen 1991, Post and Gotmark 2006, Reisen et al. 2006). Northern Cardinal and
Carolina Wren have different life history strategies, which may help explain interspecific
differences in seasonal survival. For example, Northern Cardinals live in large non-cohesive

15
nomadic flocks during non-breeding seasons, and pair bond and defend their territory during
breeding season (Filliater and Breitwisch 1997). Thus, during the breeding season, Northern
Cardinals lose anti-predator benefits of living in large flocks, which may partly explain their
lower survival during this period (Lima 2009). In contrast, the Carolina Wren maintains a
year-round pair bond and home territory such that they don't make drastic changes in
territorial behavior during breeding and non-breeding seasons (Haggerty et al. 2014).
Maintaining a single year-round territory and liberty from demands of finding a mate for pair
bonding may make breeding a less costly endeavor for Carolina Wrens relative to Cardinals.
We suggest that lower survival in male Northern Cardinals may be due to costs
associated with bright-red plumage, larger size and generally elevated exposure to predators.
Sexually selected traits in males, like carotenoid pigmentation, are not only costly to produce,
but also may increase predation risk (McGraw et al. 2005). Unfortunately, we could not
ascertain sex for many captured Carolina Wrens to examine sexually mediated differences in
survival where males do not invest in sexually selected traits, but are generally larger than
females.
Immature birds of both species had significantly lower survival than adults; however,
this difference was more pronounced in Carolina Wrens than Northern Cardinals. Due to
year-round territory defense, young Carolina Wrens may be subjected to intraspecific
competition with their adult counterparts once they are fledged. Conversely, Northern
Cardinals live in non-territorial flocks, thereby potentially releasing young cardinals from the
negative effects of intraspecific competition.
Body size (wing length) in both Northern Cardinal and Carolina Wren was found to
positively vary with survival. This effect was present even after accounting for potential

16
biases due to sex (female Northern Cardinals are smaller than males) and age specific
differences in body size (immatures are generally smaller than adults). We also tested
quadratic models for size effect to see if an intermediate size is optimal for either species, but
found no support for these alternatives. Although larger birds tended to exhibit higher
survival, presumably a threshold exists where larger birds incur a cost for their size or,
conversely, food provisioned to nestlings, has cascading effects on adult body size, thereby
allowing large birds to acquire and defend better territories later in life. Disentangling the
processes responsible for differences in survival relative to body size represents an
interesting avenue for further research.
To our knowledge, our population growth rate estimates are the first for these two
species in an urban nature reserve. Population growth rate is a critical parameter of interest in
the study of wildlife population because it provides information regarding the long-term
viability of focal populations (Nichols et al. 2000). Average annual growth rate estimates
were greater than 1.0 for both species, indicating stable and perhaps slightly increasing
populations. Despite lower survival relative to Northern Cardinals, Carolina Wrens were able
to maintain a stable population through higher recruitment. During the breeding season,
monthly population growth was estimated to be about 24% and 11% for Carolina Wrens and
Northern Cardinals, respectively. The proportional contribution of survival and recruitment
towards population growth as measured with seniority rate, indicated that recruitment yielded
a higher contribution for Carolina Wrens than it did for Northern Cardinals. The lower
survival rate of Carolina Wrens relative to Northern Cardinal appears to be offset by its
higher reproductive rate, as Carolina Wrens tend to have larger average clutch size and

17
higher reproductive success (Haggerty et al. 2014, Halkin et al. 1999, Crowell and Rothstein
1981).
This study provided detailed vital rate estimates for two birds population in an urban
nature preserve and provided a realistic demographic target for conservation efforts of more-
sensitive species in human-modified landscapes. Unfortunately, the statistical techniques
necessary to provide robust estimates of survival and recruitment are data intensive and this
fact precludes doing such analysis for many species of conservation concern because they are
inherently rare. Thus, estimating the demographic response of model bird species to habitat
degradation may provide insight into those factors that limit the recovery of more-sensitive
species.

TABLES
TABLE 1 —Model comparison table for Cormack–Jolly–Seber capture–mark–
recapture analysis to investigate the best base model for capture probability (p) and survival
(φ) for Northern Cardinals at the Bluebonnet Swamp Nature Center, Baton Rouge, Louisiana,
from 2010 to 2014. The table includes the number of parameters (K), difference in AICc
(∆AICc), and model weights (relative likelihood of models in the set). Only the ten best-
supported models are presented.
Model K ∆AICc a
Model weight
Capture probability
p (sex + season + effort) 13 0.000 0.415
p ((sex * season) + effort) 15 0.420 0.336
p (season + effort) 12 1.600 0.186
p (year + season + effort) 15 4.142 0.052
p ((year * season) + effort) 21 7.337 0.011
p (effort) 10 16.916 0.000
p (sex + year + effort) 14 17.749 0.000
p ((sex * year) + effort) 17 18.574 0.000
p (year + effort) 13 19.039 0.000
Survival rate
φ ((sex * size) + year + season + transients) 20 0.000 0.208
φ (sex + year + season + size + transients) 19 0.454 0.166
φ ((sex * size) + transients) 15 0.674 0.149
φ (year + season + transients + size) 18 1.336 0.107
φ (season + size + transients) 15 1.440 0.101
φ (sex + transients + size) 14 1.640 0.092
φ (size + transients) 13 1.780 0.085
φ (year + size + transients) 16 3.162 0.043
φ (season + transients) 14 5.301 0.015
φ (year + transients + season) 17 6.403 0.000
a
Values of AIC for the top-ranked models for capture probability and survival rate were
3727.516 and 3694.173, respectively.

19
TABLE 2 —Model comparison table for Cormack–Jolly–Seber capture–mark–
recapture analysis to investigate the best base model for capture probability (p) and survival
(φ) for Carolina Wrens at the Bluebonnet Swamp Nature Center, Baton Rouge, Louisiana,
from 2010 to 2014. The table includes the number of parameters (K), difference in AICc
(∆AICc), and model weights (relative likelihood of models in the set). For this analysis
capture probability (p), was modeled as p ((season) + effort; Table S2). Only the ten best-
supported models are presented.
Model K ∆AICc a
Model weight
Capture Probability
p (season + effort) 12 0.000 0.727
p (year + season + effort) 15 2.084 0.257
p (season) 6 8.546 0.010
p ((year + season) + effort) 21 10.521 0.004
p (year + season) 9 12.285 0.002
p (year * season) 15 13.451 0.001
p (effort) 10 30.808 0.000
p (year + effort) 13 34.581 0.000
p (constant) 4 51.037 0.000
p (year) 7 53.238 0.000
Survival rates
φ (year + transients + size) 15 0.000 0.332
φ (size + transients) 12 0.603 0.246
φ (year + transients) 14 2.045 0.119
φ (transients) 11 2.060 0.119
φ (year + season + size + transients) 17 3.718 0.052
φ (season + size + transients) 14 3.849 0.048
φ (season + transients) 13 5.584 0.020
φ (year + season + transients) 16 5.888 0.017
φ (size) 11 6.237 0.015
φ (year + size) 14 6.556 0.013
a
Values of AICc for the top-ranked models for capture probability and survival rate were

20
TABLE 3 —Model comparison table for reverse-time capture-recapture Pradel model
to investigate the best model for realized population growth rate (λ) for Northern Cardinals
and Carolina Wrens at the Bluebonnet Swamp Nature Center, Baton Rouge, Louisiana, from
2010 to 2014. The table includes the number of parameters (K), difference in AICc (∆AICc),
and model weights (relative likelihood of models in the set). For this analysis capture
probability (p) was modeled as p (season + effort + sex) and survival rate (φ) was modeled as
φ (year + season + sex) for Northern Cardinal, and p (season + effort) and φ (year) for
Carolina Wren.
Model K ∆AICc a
Model weight
Northern Cardinal
λ (season) 19 0.000 0.827
λ (year + season) 22 3.254 0.163
λ (constant) 17 9.491 0.007
λ (year) 20 11.433 0.003
Carolina Wren
λ (season) 18 0.000 0.854
λ (year + season) 21 6.124 0.106
λ (constant) 16 18.517 0.040
λ (year) 19 24.020 0.000
a
Values of AICc for the top-ranked models for Northern Cardinals and Carolina Wrens were

FIGURES
FIGURE 1 —Annual, seasonal and sex-specific variation in monthly apparent survival
estimates (± SE) of resident Northern Cardinals in the Bluebonnet Swamp Nature Center,
Baton Rouge, Louisiana, from 2010 to 2014. Open circles represent females and solid
triangles represent males

22
FIGURE 2 —Effect of size on apparent survival estimates (± SE) of Northern Cardinals and
Carolina Wrens in the Bluebonnet Swamp Nature Center, Baton Rouge, Louisiana, from
2010 to 2014.

23
FIGURE 3 —Seasonal variation in monthly realized population growth rate (± SE) of
Northern Cardinals and Carolina Wrens in the Bluebonnet Swamp Nature Center, Baton
Rouge, Louisiana, from 2010 to 2014. Open circles represent Carolina Wrens and solid
triangles represent Northern Cardinals.

24
FIGURE 4 — Annual variation in monthly apparent survival estimates (± SE) of Carolina
Wrens in the Bluebonnet Swamp Nature Center, Baton Rouge, Louisiana, from 2010 to
2014.

LITERATURE CITED
Armstrong, D. P., R. S. Davidson, J. W. Dimond, J. K. Perrott, I. Castro, J. G. Ewen, R.
Griffiths, and J. Taylor (2002). Population dynamics of reintroduced forest birds on
New Zealand islands. Journal of Biogeography 29: 609-621.
Batten, L. A. (1973). Population dynamics of suburban blackbirds. Bird Study 20: 251-258.
Bayne, E. M., and K. A. Hobson (2002). Apparent survival of male Ovenbirds in fragmented
and forested boreal landscapes. Ecology 83(5): 1307-1316
Bennett, G. F., and M. Cameron (1974). Seasonal prevalence of avian hematozoa in
passeriform birds of Atlantic Canada. Canadian Journal of Zoology 52(10): 1259-
1264.
BREC 2013. Natural Resources Management Plan. BREC Conservation Department, East
Baton Rouge Parish Recreation and Park Commission, Baton Rouge, LA.
Brownie, C., J. E. Hines, J. D. Nichols, K. H. Pollock and J. B. Hestbeck (1993). Capture-
recapture studies for multiple strata including non-Markovian transitions. Biometrics
49: 1173-1187
Burnham, K. P., and D. R. Anderson (2002). Model Selection and Multimodel Inference: A
Practical Information-Theoretic Approach, second edition. Springer, New York, NY,
USA.
Cox, G. W. (1968). The role of competition in the evolution of migration. Evolution
22:180-192.
Crowell, K. L., and S. I. Rothstein (1981). Clutch sizes and breeding strategies among
Bermudan and north-American passerines. Ibis 123:42-50.

26
DeAngelis, D. L., and L. J. Gross (1992). Individual-based models and approaches in
ecology: populations, communities and ecosystems. Chapman & Hall.
Desrochers, A., S. J. Hannon, and K. E. Nordin (1988). Winter survival and territory
acquisition in a northern population of Black-capped Chickadees. The Auk 105: 727-
736.
DeSante, D. F., and D. R. Kaschube (2009). The monitoring avian productivity and
survivorship (MAPS) Program 2004, 2005, and 2006 report. Bird Populations 9:86-
169.
Dickson, J. G., R. N. Conner, and J. H. Williamson. 1984. Bird community changes in a
young pine plantation in east Texas. Southern Journal of Applied Forestry 8:47-51.
Donnelly, R., and J. M. Marzluff (2004). Importance of reserve size and landscape context
to urban bird conservation. Conservation Biology 18:733-745.
Dow, D. D. (1969). Habitat utilization by Cardinal in central and peripheral breeding
populations. Canadian Journal of Zoology 47: 409-417.
Dunn, E. H., and D. L. Tessaglia (1994). Predation of birds at feeders in winter. Journal of
Field Ornithology 65:8–16.
Filliater, T. S., and R. Breitwisch (1997). Nestling provisioning by the extremely
dichromatic Northern Cardinal. Wilson Bulletin 109:145-153.
Franklin, A.B., D. R. Anderson, R. J. Guitierrez and K. P. Burnham (2000). Climate, habitat
quality, and fitness in northern spotted owl populations in northwestern California.
Ecological Monographs 70: 539–590.
Gates, J. E., and L. W. Gysel (1978). Avian nest dispersion and fledging success in field-
forest ecotones. Ecology 59:871-883.

27
Haggerty, T M., and E S. Morton (2014). Carolina Wren (Thryothorus ludovicianus), The
Birds of North America Online (A. Poole, Ed.). Ithaca: Cornell Lab of Ornithology;
Retrieved from the Birds of North America Online:
http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/188 doi:
10.2173/bna.188
Halkin, S. L., and S. U. Linville (1999). Northern Cardinal (Cardinalis cardinalis), The
Birds of North America Online (A. Poole, Ed.). Ithaca: Cornell Lab of Ornithology;
Retrieved from the Birds of North America Online:
http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/440
doi:10.2173/bna.440
Hamilton, T. H. (1961). The adaptive significances of intraspecific trends of variation in
wing length and body size among bird species. Evolution 15:180-195.
Harshman, L. G., and A. J. Zera (2007). The cost of reproduction: the devil in the details.
Trends in Ecology & Evolution 22:80-86.
Hines, J. E., and J. D. Nichols (2002). Investigations of potential bias in the estimation of
lambda using Pradel's (1996) model for capture-recapture data. Journal of Applied
Statistics 29:573-587.
Horn, J. C. (1984). Short-term changes in bird communities after clear-cutting in western
North Carolina. Wilson Bulletin 96: 684-689.
Hostetler, J. A., T.S. Sillett, and P.P. Marra (2015). Full-annual-cycle population models for
migratory birds. The Auk, 132: 433-449.
Jacobs, J. D., and J.C. Wingfield (2000). Endocrine control of life-cycle stages: a constraint
on response to the environment? The Condor 102: 35-51.

28
James, F. C. (1970). Geographic size variation in birds and its relationship to climate.
Ecology 51:365-390.
Jansson, C., J. Eckman, and A. von Bromssen (1981). Winter mortality and food supply in
tits, Parus spp. Oikos 37:313–322.
Johnson, J. B., and K. S. Omland (2004). Model selection in ecology and evolution. Trends
in Ecology & Evolution 19:101-108.
Laake, J., and E. Rextad. 2008. RMark: an alternative approach to building linear models in
MARK. Pages Pp C1-C115 in G. C. W. E. Cooch, editor. Program MARK: a gentle
introduction. http://www.phidot.org/software/mark/docs/book.
Lebreton, J. D., K. P. Burnham, J. Clobert, and D. R. Anderson (1992). Modeling survival
and testing biological hypotheses using marked animals - a unified approach with
case studies. Ecological Monographs 62:67-118.
Levey, D. J., and F. G. Stiles (1992). Evolutionary precursors of long-distance migration:
resource availability and movement patterns in Neotropical landbirds. American
Naturalist 140:447-476.
Lima, S. L. (2009). Predators and the breeding bird: behavioral and reproductive flexibility
under the risk of predation. Biological reviews, 84: 485-513.
Lomnicki, A. (1988). Population ecology of individuals. Princeton University Press, City.
Magnhagen, C. (1991). Predation risk as a cost of reproduction. Trends in Ecology &
Evolution 6:183-185.
McGraw, K. J., G. E. Hill, and R. S. Parker (2005). The physiological costs of being
colourful: nutritional control of carotenoid utilization in the American Goldfinch,
Carduelis tristis. Animal Behaviour 69:653-660.

29
Nichols, J. D., J. E. Hines, J. D. Lebreton, and R. Pradel (2000). Estimation of contributions
to population growth: A reverse-time capture-recapture approach. Ecology 81:3362-
3376.
Nolan, P. M., G. E. Hill, and A. M. Stoehr (1998). Sex, size, and plumage redness predict
house finch survival in an epidemic. Proceedings of the Royal Society of London.
Series B: Biological Sciences 265: 961-965.
Post, P., and F. Götmark (2006). Foraging behavior and predation risk in male and female
Eurasian Blackbirds (Turdus merula) during the breeding season. The Auk 123:162-
170.
Pradel, R. (1996). Utilization of capture-mark-recapture for the study of recruitment and
population growth rate. Biometrics: 703-709.
Pradel, R., A. R. Johnson, A. Viallefont, R. G. Nager, and F. Cezilly (1997). Local
recruitment in the Greater Flamingo: A new approach using capture-mark-recapture
data. Ecology 78:1431-1445.
Promislow, D. E. (1992). Costs of sexual selection in natural populations of mammals.
Proceedings of the Royal Society of London. Series B: Biological Sciences 247:203-
210.
Promislow, D. E., R. Montgomerie, and T. E. Martin (1992). Mortality costs of sexual
dimorphism in birds. Proceedings of the Royal Society of London. Series B:
Biological Sciences 250:143-150.
Pyle, P. (1997). Identification Guide to North American Birds, Part I. Slate Creek Press,
Bolinas, CA.

30
R Core Team (2013). R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL
http://www.R-project.org/.
Reisen, W. K., Y. Fang and V. M. Martinez (2006). Effects of temperature on the
transmission of West Nile virus by Culex tarsalis (Diptera: Culicidae). Journal of
Medical Entomology 43:309-317.
Robertson, B. A., and R. L. Hutto (2006). A framework for understanding ecological traps
and an evaluation of existing evidence. Ecology 87:1075-1085.
Rolstad, J. (1991). Consequences of forest fragmentation for the dynamics of bird
populations: conceptual issues and the evidence. Biological Journal of the Linnean
Society 42: 149–163.
Rosenzweig, M. L. (2003). Win-win ecology: how the earth's species can survive in the
midst of human enterprise. Oxford University Press.
Saracco, J. F., D. F. Desante, and D. R. Kaschube (2008). Assessing landbird monitoring
programs and demographic causes of population trends. Journal of Wildlife
Management 72:1665-1673.
Saracco, J. F., and D. F DeSante (2008). Identifying proximate causes of population trends
in migratory birds. The Institute for Bird Populations, Point Reyes Station, CA.
Searcy, W. A., and K. Yasukawa (1981). Sexual size dimorphism and survival of male and
female blackbirds (Icteridae). Auk 98:457–465.
Siriwardena, G. M., S. R. Baillie, and J. D. Wilson (1998). Variation in the survival rates of
some British passerines with respect to their population trends on farmland. Bird
Study 45:276-292.

31
Stearns, S. C. (1992). The evolution of life histories. Oxford University Press Oxford.
Stephens, S. E., D.N. Koons, J. J. Rotella, and D. W. Willey (2004). Effects of habitat
fragmentation on avian nesting success: a review of the evidence at multiple spatial
scales. Biological Conservation, 115:101-110.
Taylor, C. M., and D. R. Norris (2010). Population dynamics in migratory networks.
Theoretical Ecology 3:65–73.
Temple, S. A., and J. R. Cary (1988). Modeling dynamics of habitat interior bird
populations in fragmented landscapes. Conservation Biology 2: 340-347.
Twedt, D. J. (2004). Sex determination of Carolina Wrens in the Mississippi Alluvial
Valley. North American Bird Bander 29: 171-174.
Van Horne, B. (1983). Density as a misleading indicator of habitat quality. The Journal of
Wildlife Management 47:893–901.
Villard, M. A. (1998). On forest-interior species, edge avoidance, area sensitivity, and
dogmas in avian conservation. Auk 115:801–805
Williams, G. C. (1966). Natural selection, the costs of reproduction, and a refinement of
Lack's principal. American Naturalist 100:687-690.
Wilson, D. S. (1992). Complex interactions in metacommunities, with implications for
biodiversity and higher levels of selection. Ecology 73:1984-2000.
White G. C., and K. P. Burnham (1999). Program MARK: survival estimation from
populations of marked animals. Bird Study 46 (Supplement):120–138.
Whitcomb, R.F., C. S. Robbins, J. F. Lynch, B. L. Whitcomb, M. K. Klimkiewicz and D.
Bystrak (1981). Effects of forest fragmentation on avifauna of the eastern deciduous

32
forest. In: Burgess, R. L. and Sharpe, D. M. (eds), Forest island dynamics in man-
dominated landscapes. Springer, New York, pp. 125-205
Wolfe, J. D., E. I. Johnson, P. C. Stouffer, F. Owens, E. Deleon, E. Liffmann, K. Brzeski, S.
Utley, D. Mooney, C. Coco, and G. Grandy (2013). Annual survival of birds
captured in a habitat island bordered by the urban matrix of Baton Rouge, LA.
Southeastern Naturalist 12: 492-499.
Woolfenden, G. E. and J. W. Fitzpatrick. 1984. The Florida Scrub Jay: demography of a
cooperative-breeding bird. Monographs in Population Biology No. 20. Princeton
University Press, Princeton, NJ.

Karmacharya, B. Bachelor of Science, Tribhuvan University, 2003; Master of Science,
University of Florida, Fall 201, Master of Science
Major: Biology
Title of Thesis: Population Dynamics of Northern Cardinal and Carolina Wren in an Urban
Forest Fragment: Safe Refuge or Ecological Trap?
Thesis Director: Dr. Scott M. Duke-Sylvester
Pages in Thesis: 36, Words in Abstract: 298
ABSTRACT
Conserving bird populations in urban landscapes often depends on interactions
between extinction, recolonization, and survival in remnant habitat patches such as small
nature preserves. Thus, determining the ecological value of small nature preserves to birds is
a necessary step towards an informed conservation strategy. As such, I conducted a year
round capture-mark-recapture study from April 2010 to March 2014 to examine population
dynamics of Northern Cardinals (Cardinalis cardinalis) and Carolina Wrens (Thryothorus
ludovicianus) in a 41.7-ha nature preserve embedded in an urban matrix. More specifically,
we examined variation in survival, recruitment, and realized population growth rates relative
to year, season, sex, age, and wing length (as a proxy for body size) to investigate attributes
that affect individual survival and to assess whether the reserve served as a population source
or sink. The overall annual apparent survival rate of Northern Cardinals (0.520 ± SE 0.050)
was higher than that of the Carolina Wrens (0.349 ± 0.050), and estimates in both species
were similar to regional baseline estimates. The survival rates for adults were significantly
higher than for immatures in both species, with body size having a positive influence on
survival. Seasonal variation in survivorship was evident only in Northern Cardinals, being
highest in the winter and lowest during the breeding season. Average annual population
growth rate was slightly greater than 1.0 for both species, indicating stable or perhaps

34
modestly increasing populations. These results represent the first published full annual cycle
estimates of survival and population growth relative to age, sex, and body size for non-
migratory passerines. Our results suggest that urban forests can provide the necessary
resources to sustain growing populations of locally common birds. Furthermore, our
demographic estimates derived from two healthy bird populations can serve as target values
for other species of conservation concern within human-modified landscapes.

BIOGRAPHICAL SKETCH
Binab Karmacharya is a native of Nepal. Binab completed his masters in Wildlife
Ecology and Conservation from the University of Florida, Gainesville, Florida. He studied
the effect of longleaf pine management practices on the population dynamics of small
mammals in southeastern United States. After his masters, he worked as a wildlife biologist
for environmental consultancy Normandeau Associates in Gainesville, Florida, studying
potential impacts of windmills on different avian species. This got him interested in avian
ecology and he joined the graduate school at the University of Louisiana at Lafayette to study
population dynamics of passerine birds in an urban forest. He completed his masters in Fall
2015.

EDITED Karmacharya Draft Five_SDT FINAL

More Related Content

What's hot

Viewers also liked

Similar to EDITED Karmacharya Draft Five_SDT FINAL

EDITED Karmacharya Draft Five_SDT FINAL