GEOGRAPHIC VARIATION IN THE YELLOW-THROATED WARBLER

(DENDROICA DOMINICA)

Except where reference is made to the work of others, the work described in this thesis is
my own or was done in collaboration with my advisory committee. This thesis does not
include proprietary or classified information.

___________________________
Bailey D. McKay

Certificate of Approval:

___________________________ ___________________________
Scott R. Santos Geoffrey E. Hill, Chair
Assistant Professor Professor
Biological Sciences Biological Sciences

___________________________ ___________________________
Craig Guyer George T. Flowers
Professor Interim Dean
Biological Sciences Graduate School
GEOGRAPHIC VARIATION IN THE YELLOW-THROATED WARBLER

(DENDROICA DOMINICA)

Bailey D. McKay

A Thesis
Submitted to
the Graduate Faculty of
Auburn University
in Partial Fulfillment of the
Requirements for the
Degree of
Master of Science

Auburn, Alabama
December 17, 2007

iii
GEOGRAPHIC VARIATION IN THE YELLOW-THROATED WARBLER

(DENDROICA DOMINICA)

Bailey D. McKay

Permission is granted to Auburn University to make copies of this thesis at its discretion,
upon request of individuals or institutions and at their expense. The author reserves all
publication rights.

___________________________
Signature of Author

___________________________
Date of Graduation

iv
THESIS ABSTRACT

GEOGRAPHIC VARIATION IN THE YELLOW-THROATED WARBLER

(DENDROICA DOMINICA)

Bailey D. McKay

Master of Science, December 17, 2007
(B.S., Samford University, 2004)

60 Typed Pages

Directed by Geoffrey E. Hill

I examined how variation within the yellow-throated warbler (Dendroica
dominica) relates to geography. The yellow-throated warbler is a common neotropical
migrant with a breeding range confined to the southeastern United States. It is divided
into three continental subspecies that differ in ecology, morphology, and migratory
behavior. In the first chapter, I used mitochondrial control region sequences to test
whether eastern and western yellow-throated warbler subspecies showed temporal
division consistent with a phylogeographic break, the Tombigbee River Discontinuity,
that is known to have affected the phylogeographic patterns of several vertebrates in the
southeast. Considerable genetic variation was uncovered in the yellow-throated warbler,
but most of this variation was found within rather than between populations or subspecies.
A shallow phylogenetic tree, star-like haplotype network, and unimodal mismatch
v
distribution all suggested a recent expansion. Coalescent modeling indicated that modern
yellow-throated warbler populations are derived from a single common ancestral
population and that differences between subspecies in morphology, ecology, and
migratory pathways are the result of recent evolution. Some avian subspecies were
described with insufficient evidence and do not reflect biological reality, so in the second
chapter I performed a range-wide reassessment of the phenotypic differences between
yellow-throated warbler subspecies to determine if there was a discrepancy between
mtDNA and morphology. Results indicated much overlap in the morphological
characters most important in diagnosing subspecies: bill length and proportion of yellow
in lore, and discriminant function analysis failed to correctly assign most individuals
especially those collected near the subspecies? border. There was a strong west to east
clinal change in bill length and proportion of yellow in lore and no evidence of discrete
morphological groups. I recommend eliminating the subspecies D. d. albilora and D. d.
stoddardi because they can not be reliably diagnosed by either morphology or mtDNA.
vi
Style manual or journal used: Molecular Ecology
Computer software used: Microsoft Word
vii
TABLE OF CONTENTS

LIST OF TABLES .. ??????????????????????????.viii

LIST OF FIGURES . ??????????????????????????..ix

CHAPTER 1. EVOLUTIONARY HISTORY AND RAPID DIFFERENTIATION
IN THE YELLOW-THROATED WARBLER (DENDROICA DOMINICA) ...????1

Abstract ..??????????????????????????????.2
Introduction ..????????????????????????????...3
Methods?..?????????????????????????????.6
Results? ..?????????????????????????????...9
Discussion? ..???????????????????????????...11
Acknowledgements? ..????????????????????????.15
Literature Cited? ..?????????????????????????...16
Figure Captions? ..?????????????????????????...25

CHAPTER 2. PHENOTYPIC VARIATION IN THE YELLOW-THROATED
WARBLER (DENDROICA DOMINICA) ?????????????????...29

Abstract ..?????????????????????????????...30
Introduction ..????????????????????????????.31
Methods..?????????????????????????????...33
Results ..??????????????????????????????.35
Discussion ..????????????????????????????...36
Acknowledgements ..?????????????????????????.38
Literature Cited ..??????????????????????????...40
Figure Captions ..??????????????????????????...46
viii
LIST OF TABLES

CHAPTER 1

Table 1. Morphological, ecological, and behavioral characteristics of distinct
yellow-throated warbler groups ............................................??????????22

Table 2. Population information and intrapopulation statistics for each yellow-
throated warbler populations separately, for each subspecies, and for all samples
combined (total) ????..?????????.??????????.???23

Table 3. Analysis of molecular variance (AMOVA) for yellow-throated warbler
mtDNA haplotype data .????????????????????????24

CHAPTER 2

Table 1. Numbers of male Yellow-throated Warblers examined in different parts
of the species? range. Map numbers refer to numbers plotted on the map in Fig. 1 .....43

Table 2. Morphological and plumage character measurements (mean ? SD)
and ANOVA results for ten populations of Yellow-throated Warbler. See
Table 1 for detailed population information .....???????????????44

Table 3. Predicted classification of Yellow-throated Warbler subspecies based
on stepwise discriminant function analysis of seven morphological characters ...??45

ix
LIST OF FIGURES

CHAPTER 1

Figure 1. Breeding range of the yellow-throated warbler (shaded area; adapted
from Dunn and Garrett 1997) and geographic locations of sampled population
in this study (black circles). Numbers correspond to populations in Table 1. The
light gray area represents the range of albilora. Light blue area represents the
range of dominica. Dark gray area represents the range of stoddardi ..........................26

Figure 2. Minimum-spanning network for the yellow-throated warbler mtDNA
control region haplotypes obtained in this study. Each circle represents a
haplotype, and the size of the circles is proportional to its frequency. Small
black circles represent unsampled haplotypes ..............................................................27

Figure 3. Mismatch distribution showing the significant correlation between
observed (solid line) and expected frequencies under a model of sudden expansion
(dotted line) for the number of pairwise differences in mitochondrial control region
sequences of yellow-throated warblers. The expected frequency distribution for a
model of constant population size is also shown (dashed line) ....................................28

CHAPTER 2

Figure 1. Breeding range of the Yellow-throated Warbler (shaded area; adapted
from Dunn and Garrett 1997) and geographic locations of sampled population in
this study (circles). The pie chart represents the average proportion of yellow in
lore for that population. The size of the circles is proportional to average bill size
for that population. Numbers correspond to populations in Table 1. The light gray
area represents the range of albilora. Light blue area represents the range of
dominica. Dark gray area represents the range of stoddardi. Numbers along the
x-axis are longitude, while numbers along the y-axis are latitude ................................47

Figure 2. Boxplots comparing significantly different (A) bill lengths and (B)
proportion of yellow in lore between ten populations of the Yellow-throated
Warbler. Horizontal lines in box plots show 10
th
, 25
th
, 50
th
, 75
th
, and 90
th

percentiles. See Table 1 for detailed population information .......................................48
x
Figure 3. Graph of the two most discriminating characters of Yellow-throated
Warbler subspecies: bill length and proportion of yellow in lore. Open circles
represent dominica, closed squares represent albilora, and stars represent
stoddardi subspecies .....................................................................................................49

Figure 4. Some significant correlations between morphological characters and
geography. Open circles represent dominica, closed squares represent albilora,
and stars represent stoddardi subspecies ......................................................................50

CHAPTER 1. EVOLUTIONARY HISTORY AND RAPID

DIFFERENTIATION IN THE YELLOW-THROATED WARBLER

(DENDROICA DOMINICA)
2
ABSTRACT
Molecular tools are reshaping many traditional paradigms concerning the
timeframe of avian diversification in North America. Phylogeographic studies of
unsurveyed taxa in little-studied regions are essential for guiding the emerging paradigms
regarding the geological events that shaped modern taxa. The southeastern United States
is one region where the tempo and mode of recent diversification is poorly understood.
One phylogeographic break in particular, the Tombigbee River Discontinuity, is
mysterious and requires further study. The distributions of morphological subspecies of
the yellow-throated warbler suggest that this bird was affected by the Tombigbee River
Discontinuity. To determine whether the phylogeographic patterns of the yellow-throated
warbler are consistent with this vicariant event, I analyzed control region sequences of
118 yellow-throated warblers from across the species? range. Considerable variation was
uncovered, but most of this variation was found within rather than between populations
or subspecies. A shallow phylogenetic tree, star-like haplotype network, and unimodal
mismatch distribution all suggested a recent expansion from a common ancestral
population. Coalescent modeling indicated that modern populations are derived from a
single common ancestral population and that differences between subspecies in
morphology, ecology, and migratory pathways are the result of recent evolution. The
implications of these results for understanding comparative phylogeography in the
southeastern United States and for defining taxonomic groups for conservation are
discussed.
3
INTRODUCTION
Climatic cycles in the late Pleistocene were long viewed as the major events
shaping songbird diversification in North America (Mengel 1964). However, when the
divergences of sister songbird taxa were dated with molecular tools, their level of
differentiation was found to be much larger than expected under a model of late
Pleistocene speciation and the Pliocene was implicated as a period of substantial avian
diversification (Klicka and Zink 1997; 1999; Zink et al. 2004). Subsequent studies using
different datasets and methods of comparing speciation patterns confirmed a non-trivial
role for the Pleistocene in driving avian diversification (Avise and Walker 1998; Johnson
and Cicero 2004; Weir and Schluter 2004), and a debate ensued over what period
produced exceptional diversity (given a background rate of speciation and extinction).
New paradigms, assimilating the best of both sides of the debate, are emerging (Lovette
2005), and molecular data are profoundly reshaping ideas concerning the timeframe for
songbird diversification in North America. For example, it is now evident that many of
the east-west splits, at least at lower latitudes, diverged earlier, whereas in some regions,
such as the boreal forests (Weir and Schluter 2004), diversification has occurred more
recently. Detailed phylogeographic studies of both unsurveyed species and poorly studied
regions are essential for correctly guiding the formation of new paradigms.
The timeframe for songbird diversification is especially poorly understood in the
eastern United States. A review of comparative phylogeography in North American birds
found little evidence for common phylogeographic divisions east of the Rocky Mountains
(Zink 1996). However, at least one vicariant event, the ?Tombigbee River Discontinuity,?
is an exception that involves at least one bird, the Carolina chickadee (Poecile
4
carolinensis; Gill et al. 1993; 1999). Along with the Carolina chickadee, a number of
other vertebrates including several fish species (Wiley and Mayden 1985; Bermingham
and Avise 1986), water snakes (Lawson 1987), and possibly swamp rabbits (Chapman
and Feldhamer 1981) show discreet eastern and western phylogroups divided roughly
along the Tombigbee River drainage in western Alabama (Soltis et al. 2006). Eastern and
western phylogroups are estimated to have diverged during the early to mid Pleistocene,
between 1.5 and 1 million years ago. Common phylogeographic patterns in such varied
taxa suggest that a vicariant episode is responsible, but exactly what caused this
vicariance is unclear. It is known, however, that range compression during glacial
maxima forced many taxa into refugia in the lowlands of the southeast (Pielou 1991) and
that current rivers were often much larger during periods of glacial maxima due in part to
glacial run-off. Given this, Gill et al. (1999) have advanced the leading hypothesis for
this vicariant event. They suggest that the Tombigbee River, which would have been
much larger during the glacial maxima, divided lowland refugia and served as a barrier to
gene flow. Genetic surveys of taxa likely affected by the Tombigbee River Discontinuity
will help gauge the timeframe of this vicariant event and determine whether the observed
pattern is consistent with the large river hypothesis advanced by Gill et al. (1999).
The yellow-throated warbler (Dendroica dominica) is another bird species that
appears to have been influenced by the Tombigbee River Discontinuity. This common
neotropical migrant has a breeding range confined to the southeastern United States
where it is divided into three continental subspecies differing in morphology, ecology,
and migratory behavior (Hall 1996). The two widespread subspecies represent eastern (D.
d. dominica) and western (D. d. albilora) forms separated roughly along the Tombigbee
5
River in Alabama (Fig. 1). The eastern dominica has a relatively long bill, has a yellow
lore, prefers small pockets of loblolly pine stands within deciduous forests, and migrates
southeast to its wintering grounds in peninsular Florida and the Caribbean (Hall 1996). In
contrast, albilora has a relatively shorter bill, has a white lore, prefers sycamore
bottomland forests, and migrates southwest to its wintering grounds in Central America
(Hall 1996). In addition, a third more restricted subspecies (D. d. stoddardi) is confined
to coastal Alabama and the Florida panhandle (Fig. 1). Stoddardi has a more slender bill
that averages longer than dominica, has a yellow lore, prefers habitats similar to
dominica, and is probably non-migratory (Hall 1996). There is also a distinct form
confined to the Delaware-Maryland-Virginia (Delmarva) peninsula (Ficken et al. 1968)
that is similar in appearance to stoddardi (Stevenson 1982). These differences suggest
significant and possibly long-standing differentiation between these forms, but a genetic
examination of this species is currently lacking.
In this paper, variation in mtDNA sequences was utilized to investigate the
evolutionary history of the yellow-throated warbler. The aim was to test the hypothesis
that eastern and western subspecies constitute phylogroups that show a pattern consistent
with the Tombigbee River Discontinuity, specifically, that these two subspecies began
diverging during the early to mid Pleistocene (approximately 1.5 to 1 million years ago).
Alternative hypotheses are that eastern and western populations are the product of earlier
diversification, such as during the Pliocene (Zink et al. 2004), or that the observed
morphological, ecological, and behavioral differences have arisen more recently (i.e. in
approximately the last 200,000 years ago). A secondary objective was to determine if two
distinct but geographically restricted populations of the yellow-throated warbler, namely
6
the subspecies stoddardi and the Delmarva population, constitute evolutionary significant
units (ESUs; Mortiz 1994), information critical to any future conservation plans
regarding this species.
METHODS
Sampling
Tissue samples from 98 individuals collected at 10 geographic localities across
the continental breeding range of the yellow-throated warbler were obtained during the
2006 breeding season (Fig. 1; Table 1). In addition, 20 tissue samples were obtained from
museums for a total of 118 samples. Tissue samples were preserved in 100% ethanol and
stored at -20?C. All recognized continental subspecies of the yellow-throated warbler as
well as a distinct population on the Delmarva peninsula are represented in this study.
Molecular lab techniques
Whole genomic DNA was extracted following a standard phenol-chloroform
protocol followed by ethanol wash (modified from Quinn and White 1987). DNA was re-
suspended in 1xTE (0.01M Tris, 0.001M EDTA, pH 8.0) and stored at -20?C. Domain I
of the mitochondrial control region was amplified in 10?l reactions on a MJ Research
PTC-100 thermocycler using the primers Dpdl-L5 and Dpdl-H4 (Milot et al. 2000) and a
thermal profile of 95?C for 30 s, 55?C for 30 s, and 70?C for 90 s. Extension time was
lengthened by 4 s each cycle for 35 cycles. Primers and excess dNTPs were removed
from the PCR product with ExoSAP-IT? (USB Corporation) following the
manufacturer?s instructions. The ExoSAP-IT? treated PCR products were then used as
templates in dideoxy-termination cycle sequencing reactions using the CEQ? DTCS
Quick Start Kit (Beckman Coulter) and the sequencing primers Passerine ContReg For
7
(5'-TAC CTA GGA GGT GGG CGA AT-3?; R. T. Brumfield, unpublished data) and
Passerine ContReg Rev (5'-CCC AAA CAT TAT CTC CAA AA-3?; R. T. Brumfield,
unpublished data). Sequencing reaction products were purified by ethanol precipitation
and sequenced on a Beckman CEQ? 8000 sequencer. All DNA sequences were
sequenced in both directions and complementary strands were unambiguously aligned
and edited using SEQUENCHER v. 4.6 (GeneCodes Corporation, Ann Arbor, Michigan).
Sequences were inspected individually using the raw spectrograph data and every point
mutation was checked for authenticity.
Genetic differentiation and population structure
Nucleotide diversity (?), haplotype diversity (h), and neutrality statistics
(Tajima?s D (Tajima 1989) and Fu?s Fs (Fu 1997)) were estimated at three levels: 1) for
each population separately, 2) for each subspecies, and 3) for all samples combined.
Neutrality statistics were computed in Arlequin v. 3.01 (Excoffier et al. 2005), whereas ?
and h were computed with DnaSP v. 4.0 (Rozas et al. 2003). Neutrality statistics are used
to test the assumption of selective neutrality, and they can also be informative about
demographic forces affecting populations with Fu?s Fs being particularly sensitive to
population demographic expansion (Fu 1997). The significance of the neutrality statistics
was tested with 10,000 coalescent simulations.
Overall genetic structure of populations was tested with an analysis of molecular
variance (AMOVA; Excoffier et al. 1992) as implemented in Arlequin. In the AMOVA,
?-statistics were used to examine the contribution of molecular variance at three levels:
(i) among the three subspecies (?
ct
); (ii) among populations within subspecies (?
sc
); and
(iii) among individuals within populations (?
st
). Mismatch distributions were compared
8
with expectations of a sudden-expansion model (Rogers 1995) and a model of constant
population size (Slatkin and Hudson 1991) as implemented in DnaSP. Populations that
have experienced a sudden demographic expansion are expected to show a unimodal
mismatch distribution, whereas populations that have been in equilibrium are expected to
show a bimodal or ragged distribution (Slatkin and Hudson 1991).
Coalescent-based analyses
To explicitly test whether eastern and western yellow-throated warbler subspecies
diverged in early to mid Pleistocene, a model was used that generates estimates of
divergence time independent of the gene-migration rates between two populations
(Nielson and Wakeley 2001). This was done using a web-based version of the program
MDIV (available at http://cbsuapps.tc.cornell.edu/; Nielson and Wakeley 2001), which
utilizes a Monte Carlo Markov chain (MCMC) method to estimate the time since two
populations diverged (T), the migration rate (M), and the population parameter theta (?;
twice the effective female population size (Nfe) times the mutation rate (?)). Three
independent runs were performed under the finite sites model using the same starting
conditions (Mmax = 50, Tmax = 10, chain length = 5 ? 106, burn-in = 5 ? 105) and
different random seeds. Based on the theoretical work of Lande et al. (2002), Mil? et al.
(2007) used a generation time of 1.8 years for another warbler species (Dendroica
coronata), so this estimate of generation time was used to convert number of generations
into years.
Phylogenetic analysis
Along with population level analyses, a maximum-likelihood (ML) phylogeny
was constructed using the program PAUP* v. 4.0b10 (Swofford 2001). Nucleotide
9
substitution model parameters were selected using a hierarchical likelihood ratio test
(hLRT) with the outgroup sequence removed as implemented in MODELTEST v. 3.7
(Posada and Crandall 1998). Published Dendroica coronata sequences (GenBank
ascensions DQ855191 and DQ855190) were used as an outgroup due to D. coronata?s
phylogenetic proximity to D. dominica (Lovette and Bermingham 1999). Because a
bifurcating tree may not accurately represent an intraspecific phylogeny (Templeton et al.
1992), a haplotype network (excluding outgroups) was also constructed under the
parsimony-based algorithm developed by Templeton et al. (1992) and implemented in the
program TCS 1.21 (Clement et al. 2000). To separate population history from population
structure (Templeton 1998), nested clade analysis (NCA; Templeton et al. 1995) was
performed. Prior to the NCA, reticulations in the haplotype spanning network were
resolved following the methods of Crandall et al. (1994), and the haplotypes were nested
according to the procedures of Crandall (1996). The NCA was conducted in GeoDis v.
2.5 (Posada et al. 2000).
RESULTS
Phylogenetic analysis
A total of 399 bp from Domain I of the control region was sequenced for all 118
individuals. These sequences yielded 40 variable and 20 parsimony-informative sites
resulting in 47 haplotypes (Fig. 3). The average uncorrected pairwise sequence distance
(p) between ingroup samples was 0.9%. The control region is located in an area of the
mitochondrial genome that is prone to produce nuclear copies of mitochondrial genes
(numts; Sorenson and Quinn 1998). However, several lines of evidence support a
mitochondrial origin for the sequences presented here. For example, no insertions or
10
deletions (indels) were observed. These sequences also aligned with the control region of
the chicken genome and aligned without indels with other published Dendroica control
region sequences. In addition, a large number of haplotypes, which is inconsistent with
numts, was uncovered (Zhang and Hewitt 1996).
The hLRT suggested the Hasegawa-Kishino-Yano model with a proportion of
invariable sites plus unequal rates among sites (HKY+I+G) as the model of molecular
evolution that best fit the data. Maximum likelihood analysis produced a phylogenetic
tree (-ln=1080.65; not shown) with short branch lengths and low overall bootstrap
support. The haplotype network (Fig. 2) also suggested little genetic structure and was
characterized by a large number of haplotypes nested within loops in the network. The
NCA resulted in no significant associations between clades and geography.
Genetic variability and population structure
Overall nucleotide diversity was low (0.00887) and was similar among all
populations (Table 2). Overall haplotype diversity was high (0.92) and ranged from 0.61
in the Maryland west coast population to 0.99 in the eastern Alabama population.
Neutrality statistics (Tajima?s D and Fu?s Fs) suggested no deviation from neutral
expectations in any single population (Table 2) but were significantly negative for the
dominica (D = -1.88, p < 0.007; Fs = -9.49, p < 0.007) and albilora (D = -1.60, p < 0.03;
Fs = -18.81, p < 0.001) subspecies and when all samples were combined (D = -1.94, p <
0.003; Fs = -25.65, p < 0.001). These patterns suggest either deviations from neutral
evolution in a population with a stable size or population growth.
AMOVA indicated that most of the genetic variation was found within
populations (96.9%; ?
st
= 0.03; p < 0.007). Small and non-significant amounts of
11
variation were partitioned among populations within subspecies (2.7%; ?
sc
= 0.03; p <
0.14) and among subspecies (0.4%; ?
ct
= 0.00; p < 0.26; see Table 3). The mismatch
distribution (Fig. 3) was distinctly unimodal with a low average number of differences
between haplotype pairs (4.42) and did not differ significantly from the expected model
of sudden expansion.
Coalescent-based analyses
Posterior probability distributions of time since divergence between eastern and
western subspecies produced by MDIV were almost uniform which suggests little
evolutionary difference between these subspecies. The estimated migration rate between
eastern and western subspecies was extremely high (M = 26.8) and converts to
approximately 14.9 migrant female individuals per year. The estimate of theta was low
(? = 9.91) which, given a high mutation rate in the control region, probably indicates a
relatively low long-term effective population size.
DISCUSSION
Genetic differentiation and population expansion
Although there are high levels of genetic variation within populations, the results
presented here demonstrate a complete lack of genetic differentiation between yellow-
throated warbler populations and subspecies. The shallow phylogenetic tree and star-like
haplotype network (Fig. 2) show no obvious correlates with geography, and nested clade
analysis did not report any significant associations between nested clades and their
geographical locations. AMOVA reported non-significant proportions of genetic
variation among subspecies and among populations within subspecies, indicating that
most (97%) genetic variation could be found within populations.
12
Several lines of evidence suggest a recent population expansion, which would be
one cause for the observed homogeneity across populations. For example, high haplotype
diversity and low nucleotide diversity are expected in population with a recent expansion
(Avise 2000). Neutrality statistics can indicate demographic expansion, and the
significantly negative Tajima?s D and Fu?s Fs reported here for the dominica and albilora
subspecies as well as for all samples combined are consistent with past population
expansion. Fu?s F
s
is more sensitive to departures from population equilibrium (Fu 1997)
and in every significant instance this figure was lower than Tajima?s D. Most populations
also have negative neutrality statistics, and some of these might be non-significant due to
small sample sizes. The distinctly unimodal mismatch distribution (Rogers and
Harpending 1992) did not differ significantly from a model of sudden expansion, and the
average number of pairwise differences was low for control region sequences indicating
the expansion was relatively recent. The observed homogeneity across populations and
lack of any association between genetic variation and geography suggests also that the
yellow-throated warbler expanded from a single refugium. A recent expansion is most
likely the result of the colonization of suitable habitat following glacial retreats from a
more limited yellow-throated warbler distribution during glacial maximums (Pielou
1991). It would be interesting to determine whether other southeastern birds exhibit
similar patterns.
Comparative phylogeography of the southeastern United States
In the yellow-throated warbler, there is little or no support for the kind of genetic
discontinuity reported in the Carolina chickadee (Gill et al. 1993, 1999) or other taxa
associated with the Tombigbee River Discontinuity (Soltis et al. 2006). Coalescent-based
13
analysis suggests that there has not been a genetic separation between eastern and
western yellow-throated warbler subspecies during the evolutionary history of the species
and that there has been substantial gene flow between these subspecies. Therefore, it
appears that there is a discrepancy between eastern and western morphological
subspecies, which spatially conform to the reciprocally monophyletic units uncovered in
the Carolina chickadee, and the genetic pattern of the yellow-throated warbler, in which
there is no evidence for the kind of temporal division reported in eastern and western
phylogroups of Carolina chickadees.
There are at least three ways to reconcile these observations. First, it is possible
that chickadees and yellow-throated warblers underwent the same vicariant event but,
following dissolution of the vicariant force, the resident chickadee maintained genetic
distinction but higher gene flow between populations of the migratory warbler expunged
evidence of a genetic break. If a large glacial river was the geographic boundary between
populations, then it makes sense that a neotropical migrant could more readily cross the
boundary than a small resident forest bird. Under this scenario, there would need to be
strong natural selection in order to preserve the differences found between eastern and
western warbler subspecies in the presence of such gene flow.
Second, if the vicariant episode was cyclic (as might be the case under the
scenario of a major river system proposed by Gill et al. 1999), then the warbler and
chickadee may have experienced the same vicariant event but at two different periods.
For example, chickadee populations may have been isolated during an earlier formation
of the vicariant event, and their isolation maintained (maybe in part due to their static
propensity) during weaker vicariant episodes. In contrast, the yellow-throated warbler
14
may have only been affected by a more recent vicariant maximum, such as during the
Wisconsinian glacial maximum (110 to 10 thousand years ago). In this case, eastern and
western warbler subspecies could be evolutionary lineages whose control region
haplotypes have not completely sorted. Bill shape has been shown to be highly heritable
in some songbirds (Schluter and Smith 1986), so morphology could have evolved faster
than mtDNA leaving a pattern of morphological differentiation without mtDNA
differentiation. This scenario might also explain why the phylogeographic patterns of
other organisms that show genetic discontinuity around the Tombigbee River differ
slightly in their spatial and temporal patterns.
A third possibility is that eastern and western yellow-throated warbler subspecies
are not evolutionary lineages, as has been demonstrated for many other avian subspecies
(Ball and Avise 1992; Zink 2004), and the apparent concordance of morphological
features of yellow-throated warblers with the Tombigbee River Discontinuity is
coincidental. It is well established that some characters used to delineate avian subspecies
can be influenced by the rearing environment (James 1983). If bill length and lore color
are phenotypically plastic traits in the yellow-throated warbler, these traits would be
expected to vary clinally rather than to form discreet clusters. In a companion study of
phenotypic variation within the yellow-throated warbler (Chapter 2), it was found that
bill length and the proportion of yellow coloration in the lore showed west to east clinal
change. The observation of clinal variation in morphology supports scenario three,
though more study is needed. Transplant experiments, such as those performed by James
(1983) with red-winged blackbirds (Agelaius phoeniceus), would help gauge the
heritability of bill length and lore color in the yellow-throated warbler.
15
Conservation genetics
While some workers maintain that evolutionary significant units should be based
on genetic differentiation or reciprocal monophyly (Moritz 1994; Zink 2004), others have
suggested that ESU designation should be based on ecologically important traits even if
neutral genetic markers show little or no differentiation (Crandall et al. 2000; Fraser and
Bernatchez 2001). The present study does not support the recognition of any of the three
continental yellow-throated warbler subspecies or the long-billed population on the
Delmarva peninsula as ESUs under genetic criteria alone. More study on the amount and
distribution of potentially ecologically important traits would be needed before ESU
assignment by any other criteria could be made. Based on these genetic data, however, it
seems that, at best, the conservation priority of any one yellow-throated warbler
population is low.
ACKNOWLEDGEMENTS
I would like to thank the Louisiana State University Museum of Natural History
and the University of Kansas Natural History Museum for providing tissue samples for
this study. This research was funded through grants from the Frank M. Chapman
Memorial Fund, AMNH and the Walter F. Coxe Research Fund, Birmingham Audubon
Society. G. Hill, S. Santos, C. Guyer, and the Hill lab made significant improvements to
the manuscript. Part of this work was carried out by using the resources of the
Computational Biology Service Unit from Cornell University which is partially funded
by Microsoft Corporation.
16
LITERATURE CITED
Avise JC, Walker D (1998) Pleistocene phylogeographic effects on avian populations and
the speciation process. Proceedings of the Royal Society of London. Series B,
Biological Sciences, 265, 457?463.
Ball RM, Avise JC (1992) Mitochondrial DNA phylogeographic differentiation among
avian populations and the evolutionary significance of subspecies. Auk, 109, 626-
636.
Bermingham E, Avise JC (1986) Molecular zoogeography of freshwater fishes in the
southeastern United States. Genetics, 113, 939?965.
Chapman JA, Feldhamer GA (1981) Sylvilagus aquaticus. In: Mammalian species, no.
151. The American Society of Mammalogists.
Clement M, Posada D, Crandall KA (2000) TCS: a computer program to estimate gene
genealogies. Molecular Ecology, 9, 1657?1660.
Crandall KA (1996) Multiple interspecies transmissions of human and simian T-cell
leukemia/lymphoma virus type I sequences. Molecular Biology and Evolution, 13,
115?131.
Crandall KA, Templeton AR, Sing CF (1994) Intraspecific phylogenetics: Problems and
solutions. In: Models in Phylogeny Reconstruction (eds Scotland RW, Siebert DJ,
Williams DM), pp. 273?297. Clarendon Press, Oxford, UK.
Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK (2000) Considering
evolutionary processes in conservation biology. Trends in Ecology & Evolution,
15, 290?295.

17
Dunn JL, Garrett, KL (1997) A field guide to warblers of North America. Houghton
Mifflin Co., Boston.
Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred
from metric distances among DNA haplotypes: application to human
mitochondrial DNA restriction data. Genetics, 131, 479?491.
Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: An integrated software
package for population genetics data analysis. Evolutionary Bioinformatics
Online, 1, 47-50.
Ficken RW, Ficken MS, Morse DH (1968) Competition and character displacement in
two sympatric pine-dwelling warblers (Dendroica, Parulidae). Evolution, 22, 307-
314.
Fraser DJ, Bernatchez L (2001) Adaptive evolutionary conservation: towards a unified
concept for defining conservation units. Molecular Ecology, 10, 2741?2751.
Fu YX (1997) Statistical neutrality of mutations against population growth, hitchhiking
and background selection. Genetics, 147, 915?925.
Gill FB, Mostrom AM (1993) Speciation in North American chickadees: I. patterns of
mtDNA genetic divergence. Evolution, 47, 195-212.
Gill FB, Slikas B, Agro D (1999) Speciation in North American chickadees: II.
Geography of mtDNA haplotypes in Poecile carolinensis. Auk, 116, 274-277.
Hall GA (1996) Yellow-throated Warbler (Dendroica dominica). In: The Birds of North
America (eds. Poole A, Gill F) The Academy of Natural Sciences, Philadelphia,
and The American Ornithologists? Union, Washington, D.C.

18
James FC (1983) Environmental component of morphological differentiation in birds.
Science, 221, 184-186.
Johnson NK, Cicero C (2004) New mitochondrial DNA data affirm the importance of
Pleistocene speciation in North American birds. Evolution, 58, 1122?1130.
Klicka J, Zink RM (1997) The importance of recent ice ages in speciation: a failed
paradigm. Science, 277, 1666?1669.
Klicka J, Zink RM (1999) Pleistocene effects on North American songbird evolution.
Proceedings of the Royal Society Biological Sciences Series B, 266, 695-700.
Lawson R (1987) Molecular studies of thamnophiline snakes: I. The phylogeny of the
genus Nerodia. Journal of Herpetology, 21, 140-157.
Lande R, Engen S, Saether B-E et al. (2002) Estimating density dependence from
population time series using demographic theory and life-history data. American
Naturalist, 159, 321?337.
Lovette IJ (2005) Glacial cycles and the tempo of avian speciation. Trends in Ecology &
Evolution, 20, 57?59.
Lovette IJ, Bermingham E (1999) Explosive speciation in the New World Dendroica
warbles. Proceedings of the Royal Society Biological Sciences Series B, 266,
1629?1636.
Mengel RM (1964) The probable history of species formation in some northern wood
warblers (Parulidae). Living Bird, 3, 9-43.
Mil? B, Smith TB, Wayne RK (2007) Speciation and rapid phenotypic differentiation in
the yellow-rumped warbler Dendroica coronata complex. Molecular Ecology, 16,
159-173.
19
Milot E, Gibbs HL, Hobson KA (2000) Phylogeography and genetic structure of northern
populations of the yellow warbler (Dendroica petechia). Molecular Ecology, 9,
667?681.
Moritz C (1994) Defining ?evolutionary significant units? for conservation. Trends in
Ecology & Evolution, 9, 373?375.
Nielsen R, Wakeley J (2001) Distinguishing migration from isolation: a Markov chain
Monte Carlo approach. Genetics, 158, 885?896.
Pielou EC (1991) After the Ice Age. University of Chicago Press, Chicago.
Posada D, Crandall KA, Templeton AR (2000) GeoDis: a program for the cladistic
nested analysis of the geographical distribution of genetic haplotypes. Molecular
Ecology, 9, 487?488.
Posada D, Crandall KA (1998) MODELTEST: Testing the model of DNA substitution.
Bioinformatics, 14, 817-818.
Quinn TW, White BN (1987) Analysis of DNA sequence variation. In: Avian Genetics
(eds. Cooke F, Buckley, PA), pp. 163-198. Academic Press, New York.
Rogers AR (1995) Genetic evidence for a Pleistocene population explosion. Evolution,
49, 608?615.
Rogers AR, Harpending H (1992) Population growth makes waves in the distribution of
pairwise genetic differences. Molecular Biology and Evolution, 9, 552?559.
Rozas J, Sanchez-DelBarrio JC, Messeguer X, Rozas R (2003) DnaSP, DNA
polymorphism analyses by the coalescent and other methods. Bioinformatics, 19,
2496-2497.
20
Slatkin M, Hudson RR (1991) Pairwise comparisons of mitochondrial DNA sequences in
stable and exponentially growing populations. Genetics, 129, 555?562.
Soltis DE, Morris AB, McLachlan JS, Manos PS, Soltis PS (2006) Comparative
phylogeography of unglaciated eastern North America. Molecular Ecology, 15,
4261-4293.
Sorenson MD, Quinn TW (1998) Numts: a challenge for avian systematics and
population biology. Auk, 115, 214?221.
Stevenson HM (1982) Comments on the identification of Stoddard's Yellow-throated
Warbler. Florida Field Naturalist, 9, 37-38.
Swofford DL (2001) PAUP*: Phylogenetic Analysis Using Parsimony (*and Other
Methods) 4.0b10. Sinauer Associates, Sunderland, Massachusetts.
Tajima F 1989 Statistical method for testing the neutral mutation hypothesis by DNA
polymorphism. Genetics, 123, 585-596.
Templeton AR (1998) Nested clade analyses of phylogeographic data: testing hypotheses
about gene flow and population history. Molecular Ecology, 7, 381?397.
Templeton AR, Crandall KA, Sing CF (1992) A cladistic analysis of phenotypic
associations with haplotypes inferred from restriction endonuclease mapping and
DNA sequence data. III. Cladogram estimation. Genetics, 132, 619?633.
Templeton AR, Routman E, Phillips CA (1995) Separating population structure from
population history: a cladistic analysis of the geographical distribution of
mitochondrial DNA haplotypes in the tiger salamander, Ambystoma tigrinum.
Genetics, 140, 767?782.
21
Weir J, Schluter D (2004) Ice sheets promote speciation in boreal birds. Proceedings of
the Royal Society Biological Sciences Series B, 271, 1881-1887.
Wiley EO, Mayden RL (1985) Species and speciation phylogenetic systematics with
examples from the North American fish fauna. Annals of the Missouri Botanical
Garden, 72, 596-635.
Zhang D-X, Hewitt GM (1996) Nuclear integrations: challenges for mitochondrial
DNA markers. Trends in Ecology & Evolution, 11, 247?251.
Zink RM (1996) Comparative phylogeography in North American birds. Evolution, 50,
308?317.
Zink RM (2004) The role of subspecies in obscuring avian biological diversity and
misleading conservation policy. Proceedings of the Royal Society of London.
Series B, Biological Sciences, 271, 561?564.
Zink RM, Klicka J, Barber BR (2004) The tempo of avian diversification during the
Quaternary. Philosophical Transactions of the Royal Society of London. Series B,
Biological Sciences, 359, 215?220.

22
Table 1.
Morphological, ecological, and behavioral char
acteristics of distinct yellow-throated
warbler groups.
Breeding
range
Migration behavior
Lore color
Bill length (
mm;
m
ean ? SD)*
Habitat
dominica

Eastern southeast
East
Yellow
9.55 ? 0.59
Predom
inately
m
i
xed forest
stands
albilora
Western southeast
West
White
9.22 ? 0.47
Predom
inately
Sycam
ore
bottom
l
and
stoddardi
Coastal Alabam
a
and the Flo
r
ida
panhandle
Resident?
Yellow
10.07 ? 0.44
Mixed forest or Loblolly pine stands
Delm
arva
population
Delm
arva
peninsula
East
Yellow
10.91 ? 0.49
Loblolly pine stands

*
m
easured from
nare to tip with digital calipers
and based on m
a
le specimens
used in this study:

dominica
(
n
= 45),
albilora
(
n
= 34),
stoddardi
(
n
= 9), Delm
arva population

(
n
= 8)
Table 2.
Population inform
ation and intrapopulation statistic
s for each y
e
llow-throated warbler p
opulations
separately, f
o
r each subs
pecies, and
for all sam
p
les com
b
ined (total).

Map

No
.

Population
State
Subspe
cies
n
n
h
h
?

D
F
s

1
AL-West

Alabam
a

al
bi
l
or
a

8
7
0
.
9
64
0
.
0
062
7
0
.
1
7
-
2.63*
2
AL-East
Alabam
a

do
mi
ni
c
a

1
4

1
3

0
.
9
89
0
.
0
083
2
-
0
.90
-
8
.14*
**
3

NC
No
rth

Car
o
lina

do
mi
ni
c
a

9
6
0
.
8
89
0
.
0
041
8
-
1.07
-
2.67*
4
MD-West
co
ast
Marylan
d

do
mi
ni
c
a

0.
60
7

0.
00
5
12

0.
08

1.
06

5
MD-Delm
arva
Maryland
do
mi
ni
c
a

1
0
7
0
.
8
67
0
.
0
121
6
-
1.21
2
.
9
0
6
FL-East

Flori
d
a

do
mi
ni
c
a

1
0

7
0
.
8
67
0
.
0
069
1
-
0
.98
-
2
.29
7
LA
Louisiana

al
bi
l
or
a

1
7

1
2

0
.
9
34
0
.
0
020
8
-
0
.72
-
5
.06*
*
8
MO

Misso
ur
i
al
bi
l
or
a

2
0

1
1

0
.
8
74
0
.
0
065
0
-
0
.84
-
4
.63*
*
9

Ohi
o

al
bi
l
or
a

1
3

9
0
.
9
36
0
.
0
080
2
-
1
.42
-
3
.12*
10

stoddardi

Flori
d
a

stoddardi

9
5
0
.
8
06
0
.
0
075
2
-
0.43
0
.
0
5

al
bi
l
or
a
(
poo
led
)

5
8
2
9
0
.
9
20
0
.
0
071
1
-
1.60*
-
18
.
81
***

do
mi
ni
c
a
(
poo
led
)

5
1
2
6
0
.
8
93
0
.
0
089
1
-
1.88*
*
-
9.49*
*

to
tal

1
18
4
7
0
.
9
22
0
.
0
088
7
-
1.94*
*
-
25
.
65
***
23
n
, s
a
m
p
le size;
nh
, n
u
m
b
er
o
f
hapl
ot
y
p
es;

h
, hapl
ot
y
p
e di
ve
rsi
t
y
;

?
, nucleotide dive
rsity.
* P<
0.
0
5
;
*
*

P
<
0.
01;

*
*
*
P<
0.
00
1

24
Table 3. Analysis of molecular variance (AMOVA) for yellow-throated warbler mtDNA
haplotype data.
Source of variation d.f. Sum of
squares
Variance
component
% variation ?-statistic
Among subspecies 2 6.435 0.01263 0.57 ?
ct
= 0.00
Among populations
within subspecies
7 19.804 0.05757 2.59 ?
sc
= 0.03
Within populations 108 232.278 2.15072 96.84 ?
st
= 0.03**
Total 117 258.517 2.22091
** P<0.01

25
FIGURE CAPTIONS

Figure 1. Breeding range of the yellow-throated warbler (shaded area; adapted from Dunn
and Garrett 1997) and geographic locations of sampled population in this study (black
circles). Numbers correspond to populations in Table 1. The light gray area represents the
range of albilora. Light blue area represents the range of dominica. Dark gray area represents
the range of stoddardi.

Figure 2. Minimum-spanning network for the yellow-throated warbler mtDNA control
region haplotypes obtained in this study. Each circle represents a haplotype, and the size of
the circles is proportional to its frequency. Small black circles represent unsampled
haplotypes.

Figure 3. Mismatch distribution showing the significant correlation between observed (solid
line) and expected frequencies under a model of sudden expansion (dotted line) for the
number of pairwise differences in mitochondrial control region sequences of yellow-throated
warblers. The expected frequency distribution for a model of constant population size is also
shown (dashed line).

Figure 1.
26

Figure 2.
27

0.00
0.05
0.10
0.15
0.20
0.25
0.30
0 5 10 15 20
Number of Pairwise Differences
Fr
e
que
nc
y

Figure 3.
28
29

CHAPTER 2. PHENOTYPIC VARIATION IN THE YELLOW-THROATED

WARBLER (DENDROICA DOMINICA)

30
ABSTRACT
Subspecies are assumed to have unique evolutionary histories, but molecular data
sometimes contradict morphological avian subspecies. A recent genetic survey of the
Yellow-throated warbler (Dendroica dominica) found that none of its three continental
subspecies qualified as evolutionary significant units. Therefore, these subspecies either do
not correspond to biological entities or the morphological differences between them have
evolved rapidly. Since there has been no range-wide quantitative assessment of Yellow-
throated warbler subspecies, it has been impossible to gauge the amount of rapid evolution
that has occurred if these subspecies are products of recent differentiation or to test whether
morphological differences are clinal, which might suggest phenotypes are influenced by the
rearing environmental. Here I perform a range-wide morphological reassessment of the
continental Yellow-throated warbler subspecies in an effort to quantify their differences and
examine if and how differences relate to geography. Results indicate much overlap in the
morphological characters most important in diagnosing subspecies: bill length and proportion
of yellow in lore, and discriminant function analysis fails to correctly assign most individuals
especially those collected near the subspecies? border. There is a strong west to east clinal
change in bill length and proportion of yellow in lore and no evidence of discrete
morphological groups. I recommend eliminating the subspecies D. d. albilora and D. d.
stoddardi because they can not be reliably diagnosed by morphology or mtDNA.
31
INTRODUCTION
The rise of the biological species concept during the mid-twentieth century fostered
an explosion in the number of described avian subspecies, and, though the utility of the
subspecies rank was questioned (Wilson and Brown 1953), it was believed that variation
within species represented local adaptations of evolutionary significance (Mayr 1982). The
assumption that subspecies have unique evolutionary histories has subsequently led to the use
of subspecies in roles that require their evolutionary independence, such as taxonomy,
evolution studies, and conservation plans (Zink 2004). Many of the morphological traits used
to designate subspecies, however, can be directly affected by the rearing environment (James
1983), and when morphological subspecies are subjected to independent tests of evolutionary
isolation (i.e. neutral molecular markers) they often fail to meet the requirements of
evolutionary significant units (Ball and Avise 1992; Zink 2004).
The above situation is exemplified by the Yellow-throated Warbler (Dendroica
dominica). The Yellow-throated Warbler is mid-sized warbler with a black face, white
supercilium, and bold yellow throat patch. It is a neotropical migrant that breeds in the
southeastern United States and is divided into three continental subspecies (a fourth
subspecies is confined to the Bahamas and will not be considered here)(Hall 1996). These
subspecies were not named following any rule, and their description is based on
approximately 15 to 20 individuals per subspecies (Ridgway 1902; Sutton 1951). Also, the
specimens used to describe dominica and albilora were take from the extreme eastern or
western portion of their ranges (Ridgway 1902). The subspecies differ in morphology,
ecology, and plumage. The eastern D. d. dominica is reported to have a long bill (12.4-15.0
mm, sexes combined; Curson et al. 1994), have a yellow lore, breed in mixed forests or
32
cypress swamps, and winter mainly in the Caribbean (Curson et al. 1994; Hall 1996). The
western D. d. albilora is reported to be larger than dominica (Ridgway 1902), have a short
bill (10.9-12.7mm, sexes combined; Curson et al. 1994), have a white lore, breed in
sycamore bottomlands or cypress swamps, and to winter mainly in Central America (Hall
1996). D. d. stoddardi is confined to coastal Alabama and the panhandle of Florida where it
may be resident (Hall 1996). It is reported as being indistinguishable from dominica (Curson
et al. 1994) except in having a longer and more slender bill (14.0-17.0 mm, sexes combined;
Sutton 1951). There is also a migratory long-billed form on the Delaware-Maryland-Virginia
(Delmarva) peninsula (Ficken et al. 1968) that is reported to be indistinguishable from
stoddardi in appearance (Stevenson and Anderson 1994) from which it is separated by over
1400 km.
Distributions of eastern and western morphological subspecies of the Yellow-throated
Warbler correspond spatially to a phylogeographic break reported for several vertebrate
species including the Carolina Chickadee (Poecile carolinensis)(Chapter 1). Thus, in a recent
evolutionary study of the Yellow-throated Warbler, a genetic partition was assumed a priori
to correspond to the observed morphological partition, and it was hypothesized that the
Yellow-throated Warbler fit temporally into this comparative phylogeographic framework
(Chapter 1). Surprisingly, however, mitochondrial DNA (mtDNA) control region sequences
indicated a pronounced lack of differentiation between Yellow-throated Warbler subspecies
(Chapter 1). Potential causes for this discrepancy are that morphological traits have evolved
faster than mtDNA or that morphological subspecies in the Yellow-throated Warbler do not
correspond to evolutionary lineages. As there has been no range-wide quantitative
assessment of phenotypic variation in the Yellow-throated Warbler, it is unknown whether
33
variation in extent of yellow coloration in the face and variation in bill properties vary
discretely or gradually across the species? range. Here I reassess the morphological
subspecies of the Yellow-throated Warbler in an effort to quantify their differences and
examine if and how differences relate to geography.
METHODS
Samples and measurements
A total of 89 specimens from 10 populations located across the Yellow-throated
Warbler?s breeding range were collected during the breeding season (April and May) of 2006
(Table 1; Fig. 1). All of these specimens were also included in the phylogeographic study of
this species (Chapter 1). Seven morphological characters (6 body and 1 plumage), including
all of those used to differentiate subspecies (i.e. bill length, bill width, and proportion of
yellow in lore), were measured. These characters were: bill length, bill width, bill depth (all
at the anterior edge of the nare), tarsus length, wing cord, tail length (at center rectrix), and
proportion of yellow area of lore, hereafter ?proportion of yellow in lore? (see below). Bill
measurements and tarsus length were measured to the nearest 0.01 mm using a digital caliper
and wing cord and tail length were measured to the nearest 0.5 mm using a wing rule.
Proportion of yellow in lore was quantified as follows. Close-up photographs of the lore of
each Yellow-throated Warbler specimen were loaded into the program ImageJ for
Windows
TM
(available at http://rsb.info.nih.gov/ij/) and the area of the total lore, considered
the white or yellow area from the posterior end of the bill to the most anterior point of the
eye, was measured. Using the same procedure, I then measured the area of the yellow within
the lore. The yellow area of the lore was divided by the total lore area to estimate the
proportion of yellow within the lore. Due to damage sustained during collection, 14% of the
34
specimens had some missing data, but this accounted for no more than 6% of missing data
for any variable. In addition, bill measurements (length, width, and depth) from 52 male
museum specimens collected between 15 March and 30 June were included in subspecies?
level analyses, but were not assigned a population. In all analyses, only males were used. All
measurements were made by myself; for tarsus length and all bill characters, the mean of
three measurements was used.
Statistical analyses
SPSS 12.0 for Windows
TM
(SPSS Inc. 2003) was used for all statistical analyses, and
a p-value ? 0.05 was considered statistically significant. I tested each morphological
character for departures from normality. I then determined two-tailed Pearson correlation
coefficients for all pairwise comparisons between body characters. Next, I compared the
means of each character using an analysis of variance (ANOVA). Two ANOVAs were run:
the first with the samples grouped by population and the second with the samples grouped by
subspecies (dominica, albilora, or stoddardi). A Tukey HSD post hoc test was used to
determine maximum homogeneous groupings of populations and of subspecies for each
character. The two characters most diagnostic of subspecies, bill length and proportion of
yellow in lore, were plotted to determine whether they formed discrete clusters.
To further evaluate the distinctiveness of each subspecies, I grouped specimens by
subspecies and applied a stepwise discriminant function analysis (DFA) using all seven
morphological characters. Prior probabilities were computed from group sizes, and missing
values were replaced with the mean for that character. The leave-one-out method was used to
cross-validate the accuracy of the group assignments. Finally, to check for patterns between
characters and geography, I computed two-tailed Pearson correlation coefficients for all
35
pairwise comparisons between both latitude and longitude for all characters.
RESULTS
All data conformed to normality. Two sets of size measurements, among the six size
variables measured, were significantly correlated: bill width and depth (r = -0.60; n = 133; p
< 0.001) and wing cord and tail length (r = 0.36; n = 83; p < 0.001). ANOVA indicated the
following five characters differed significantly between populations (Table 2): bill length (F
= 16.8; df = 85; p < 0.001), bill width (F = 12.9; df = 85; p < 0.001), bill depth (F = 8.1; df =
80; p < 0.001), tail length (F = 2.1; df = 87; p < 0.041), and proportion of yellow in lore (F =
18.5; df = 87; p < 0.001), and the following four characters differed significantly between
subspecies: bill length (F = 12.9; df = 137; p < 0.001), bill width (F = 7.0; df = 137; p <
0.001), wing cord (F = 3.4; df = 82; p < 0.04) and proportion of yellow in lore (F = 25.7; df =
87; p < 0.001). The Tukey HSD test revealed overlap between all homogeneous groups in all
characters differing significantly between both populations and subspecies, and, thus, no
exclusive groups were identified. Bill length plotted against proportion of yellow in lore
resulted in overlap between all subspecies (Fig. 3).
Discriminant function analysis produced a final model with one function (eigenvalue
= 0.64) and, of the seven characters, included only proportion of yellow in lore. The overall
Wilk?s lambda was significant (? = 0.61, ?
2
= 31.0, n = 89, p < 0.001). Classification and
cross-validation both indicated that 66% of all individuals were assigned to the correct
subspecies (Table 3). Removing stoddardi did not affect the classification results of dominica
or albilora. The majority (73%) of incorrectly assigned individuals were collected near the
dominica-albilora border in Alabama, Ohio, and North Carolina.
Four characters were significantly correlated with geography. Bill length (r = -0.41; n
36
= 138; p < 0.001; Fig. 4a) and proportion of yellow in lore (r = -0.57; n = 87; p < 0.001; Fig.
4b) were both negatively correlated with longitude. Tail length (r = 0.37; n = 88; p < 0.001;
Fig. 4c) and bill depth (r = 0.22; n = 133; p < 0.01; Fig. 4d) were both positively correlated
with latitude, and proportion of yellow in lore (r = -0.32; n = 87; p < 0.005) was negatively
correlated with latitude.
DISCUSSION
Results from ANOVA indicate that there are significant differences in bill length, bill
width, wing cord, and proportion of yellow in lore when samples are grouped by subspecies.
There are also significant differences in several characters when samples are grouped by
population. Post hoc tests, however, do not place populations into exclusive groups that
correspond to subspecies and, instead, indicate that populations are more similar to their
nearest geographical neighbor than they are to their subspecies. A most common, albeit
arbitrary, cutoff point used to define subspecies in ornithology is 75% diagnosablity
(Amadon 1949), and discriminant function analysis fails to assign at least 75% of either
albilora or stoddardi individuals to the correct subspecies, suggesting there is only one
continental Yellow-throated Warbler subspecies. The DFA correctly groups individuals from
extreme eastern or western populations into subspecies but fails to correctly assign most
albilora individuals from the more central Ohio and western Alabama populations or some
dominica individuals from the more central North Carolina and eastern Alabama populations.
Bill length and proportion of yellow in lore both gradually increase from west to east and do
not show a sharp break, which would be indicative of discrete groups. Plotting bill length and
proportion of yellow in lore together results in an undifferentiated cluster of points.
Though stoddardi birds have longer bills on average than dominica birds, DFA fails
37
to distinguish stoddardi and assigns all of its individuals to dominica. The longer-billed birds
on the Delmarva peninsula do not differ significantly from the nearby population on the
western shore of Maryland. Thus, the three longest billed populations that I sampled were
also the three populations within 30 km of the coast. This supports a previous study that
suggested shorter-billed Yellow-throated Warbler populations were more prevalent inland
where they may be more associated with deciduous forests and longer-billed forms are
prevalent in coastal areas with long-coned pine forests (Ficken et al. 1968). This suggests
stoddardi may be an isolated example of what is a common form along the Atlantic coast.
This may be, as suggested by Ficken et al. (1968), an adaptive response to more specific
coastal habitat perhaps in part due to competition with pine Warblers (Dendroica pinus).
Bill shape differences between avian subspecies can be highly heritable (e.g. Schluter
and Smith 1986) or greatly influenced by the rearing environment (e.g. James 1983).
Transplant experiments with the Yellow-throated Warbler, such as those performed by James
(1983) with Red-winged Blackbirds (Agelaius phoeniceus), could detect phenotypic
plasticity in Yellow-throated Warbler bill shape. Lore color might also be heavily influenced
by the environment. Carotenoids are probably responsible for the Yellow-throated Warbler?s
yellow throat and lore, and increased carotenoid consumption can cause yellows and reds to
bleed into other parts of a bird?s plumage (Hill 2002). Because eastern and western Yellow-
throated Warblers differ in their primary breeding habitat, it is likely they ingest different
levels of carotenoids. A higher carotenoid diet in dominica may make it more likely to
allocate carotenoids to the lore. Blue tits (Cyanistes caeruleus) obtain more carotenoids in a
deciduous versus a coniferous forest, which is the opposite of what would be expected in the
Yellow-throated Warbler (Partali et al. 1987). Because it is unknown exactly how the
38
Yellow-throated Warbler?s diet differs between eastern and western subspecies, it remains
possible that the observed variation in lore color results from different diets.
Overall, my observations indicate that there is much overlap in the morphological
characters used to distinguish Yellow-throated Warbler subspecies. Average differences can
distinguish subspecies when individuals from across the subspecies? range are included, but
average differences have been argued to be insufficient for diagnosing subspecies (Patten and
Unitt 2002). The clinal change in both bill length and proportion of yellow in lore is
consistent with an environmental component to these characters though more study is
needed. The failure of these analyses in identifying discrete groups within the Yellow-
throated Warbler corroborates earlier mtDNA surveys that indicated Yellow-throated
Warbler subspecies were not evolutionary significant units (sensu Moritz 1994). While there
is an interesting pattern of phenotypic variation within the Yellow-throated Warbler, there is
probably little value in subdividing clinal continuums into different subspecies (Rising 2007).
Therefore, I recommend eliminating the albilora subspecies. It is also clear that some avian
subspecies were described with insufficient evidence and do not correspond to evolutionary
lineages (e.g. Pruett et al. 2004). This seems to be the case with stoddardi as it can not be
reliably diagnosed and there is no evidence that it is different from other long-billed forms
common along the Atlantic coast. Therefore, I also recommend eliminating the subspecies
stoddardi.
ACKNOWLEDGEMENTS
I would like to thank the Louisiana State University Museum of Natural History for
access to their collection. This research was funded through grants from the Frank M.
Chapman Memorial Fund, AMNH and the Walter F. Coxe Research Fund, Birmingham
39
Audubon Society. G. Hill, S. Santos, C. Guyer, and the Hill lab made significant
improvements to the manuscript.
40
LITERATURE CITED
Amadon, D. 1949. The seventy-five per cent rule for subspecies. Condor 51:250-258.
Ball, Jr., R. M. and J. C. Avise. 1992. Mitochondrial DNA phylogeographic
differentiation among avian populations and the evolutionary significance of
subspecies. Auk 109:626?636.
Curson, J., D. Quinn, and D. Beadle. 1994. Warblers of the Americas: an identification
guide. Houghton Mifflin Company, New York.
Dunn, J. L., K. L. Garrett 1997. A field guide to warblers of North America. Houghton
Mifflin Co., Boston.
Ficken, R. W., M. S. Ficken, and D. H. Morse 1968. Competition and character displacement
in two sympatric pine-dwelling Warblers (Dendroica, Parulidae). Evolution 22:307-
314.
Hall, G. A. 1996. Yellow-throated Warbler (Dendroica dominica). In: The Birds of North
America (eds. Poole A, Gill F) The Academy of Natural Sciences, Philadelphia, and
The American Ornithologists? Union, Washington, D.C.
Hill, G. E. 2002. A red bird in brown bag: the function and evolution of colorful plumage
in the house finch. Oxford University Press, New York.
James, F. C. 1983. Environmental component of morphological differentiation in birds.
Science 221:184-186.
Mayr, E. 1982. Of what use are subspecies? Auk 99:593-595.
Moritz, C. 1994. Defining ?evolutionary significant units? for conservation. Trends in
Ecology and Evolution 9:373?375.

41
Partali, V., S. Liaaen-Jensen, T. Slagsvold, and J. T. Lifjeld. 1987. Carotenoids in food
chain studies. II. The food chain of Parus spp. monitored by carotenoid analysis.
Comparative Biochemistry and Physiology B 87:885-888.
Patten, M. A., and P. Unitt. 2002. Diagnosability versus mean differences of Sage Sparrow
subspecies. Auk 119:26-35.
Pruett, C. L., D. D. Gibson, and K. Winker. 2004. Amak Island Song Sparrows (Melospiza
melodia amaka) are not evolutionarily significant. Ornithological Science 3:133-
138.
Ridgway, R. 1902. The birds of North and Middle American: a descriptive catalog of the
higher groups, genera, species, and subspecies known to occur in North America.
United States National Museum Bulletin 50:578-584.
Rising, J. D. 2007. Named subspecies and their significance in contemporary ornithology.
Ornithological Monographs 63:45-54.
Schluter, D., and J. N. M. Smith 1986. Natural selection on beak and body size in the
song sparrow. Evolution 40:221-231.
Stevenson, H. M., and B. H. Anderson. 1994. The birdlife of Florida. University Presses of
Florida, Tallahassee.
Sutton, G. M. 1953. A new race of Yellow-throated Warbler from northwestern Florida. Auk
68:27-29.
Wilson, E. O., and W. L. Brown, Jr. 1953. The subspecies concept and its taxonomic
application. Systematic Zoology 2:97?111.

42
Zink, R. M. 2004. The role of subspecies in obscuring avian biological diversity and
misleading conservation policy. Proceedings of the Royal Society of London.
Series B, Biological Sciences 271:561?564.
43
Table 1. Numbers of male Yellow-throated Warblers examined in different parts of the
species? range. Map numbers refer to numbers plotted on the map in Fig. 1.
Map
No.
Population State Subspecies n Locality
1 LA Louisiana albilora 4 Pointe Coupee Parish
2 MO Missouri albilora 11 Oregon, Ripley Co.
3 AL-West Alabama albilora 8 Lawrence Co.
4 AL-East Alabama dominica 12 Conecuh, Macon, Talladega Co.
5 FL-West Florida stoddardi 9 Wakulla Co.
6 OH Ohio albilora 12 Lawrence Co.
7 NC North
Carolina
dominica 9 Graham Co.
8 FL-East Florida dominica 9 Marion Co.
9 MD-West
Coast
Maryland dominica 7 Charles, Prince George, St.
Mary?s Co.
10 MD-
Delmarva
Maryland dominica 8 Worcester Co.
Table 2.
Morphological and plum
ag
e character m
easure
m
en
ts (m
ean ? SD) and ANOVA results for ten populations of
Yellow-thro
ated W
arbler. See
Table 1 for detailed population inform
ation.

Character
LA

AL-
W
est

AL-
E
ast

FL-West

FL-East

MD
-W
est

MD
-
Delm
arva

A
NOV
A
F-value

Bill len
g
th

(m
m
)

9.
16
?
0.
40

9.
04
?
0.
56

9.
57
?
0.
31

9.
35
?
0.
35

10
.0
7
?
0
.
4
4

9
.
1
7?0
.4
1
9
.
2
6?0
.3
0
9
.
4
5?0
.3
2
1
0.45?
0.68
1
0.91?
0.4
9
1
6
.8**
Bill wid
t
h

(m
m
)

2
.
8
2
?0
.1
3
3
.
4
7
?0
.1
2
2
.
8
6
?0
.1
3
3
.
4
4
?0
.5
4
3
.
3
5
?0
.2
7
2
.
8
4
?0
.1
4
2
.
8
6
?0
.1
1
2
.
7
8
?0
.2
2
2
.
8
2
?0
.1
5
2
.
8
2
?0
.0
1
1
2
.9**
Bill d
e
p
th

(m
m
)

3.
15
?
0.
09

3.
57
?
0.
16

3.
23
?
0.
11

3.
36
?
0.
19

3.
39
?
0.
14

3.
18
?
0.
15

3.
20
?
0.
01

3.
16
?
0.
11

3.
24
?
0.
08

3.
27
?
0.
15

8.
1*
*

Tars
us
l
e
ngt
h

(m
m
)

17
.3
?
0
.
4

16
.7
?
0
.
6

16
.8
?
0
.
3

16
.9
?
0
.
8

16
.7
?
0
.
3

16
.6
?
0
.
3

16
.6
?
0
.
5

16
.8
?
0
.
4

16
.9
?
0
.
6

17
.2
?
0
.
4

1.
7

Wi
n
g
c
o
r
d

(m
m
)

67
.4
?
2
.
3

67
.8
?
2
.
1

67
.1
?
1
.
2

68
.2
?
0
.
6

66
.2
?
1
.
4

67
.0
?
1
.
8

67
.4
?
1
.
5

66
.8
?
1
.
2

67
.7
?
0
.
8

67
.8
?
1
.
9

1.
4

Tail l
e
ngt
h

(m
m
)

48
.4
?
1
.
8

49
.9
?
1
.
5

50
.0
?
1
.
9

48
.9
?
1
.
1

48
.4
?
1
.
7

49
.8
?
1
.
5

49
.1
?
0
.
8

48
.8
?
1
.
1

49
.7
?
0
.
5

50
.4
?
1
.
3

2.
1*

Pr
opo
r
tion
o
f
yello
w
in
lore
0
.
2
6
?0
.4
5
0
.
1
1
?0
.0
5
0
.
6
5
?0
.1
2
0
.
6
5
?0
.1
8
0
.
7
1
?0
.0
7
0
.
3
8
?0
.2
7
0
.
5
5
?0
.1
0
0
.
8
4
?0
.0
9
0
.
7
2
?0
.1
0
0
.
7
6
?0
.1
2
1
8
.5**
44
* P<
0.
0
5;
*
*
P
<
0.
00
1

45
Table 3. Predicted classification of Yellow-throated Warbler subspecies based on stepwise
discriminant function analysis of seven morphological characters.
Predicted:
dominica
Predicted:
albilora
Predicted:
stoddardi
Correct
classification (%)
dominica 40 5 0 89
albilora 16 19 0 54
stoddardi 9 0 0 0

46
FIGURE CAPTIONS

Figure 1. Breeding range of the Yellow-throated Warbler (shaded area; adapted from Dunn
and Garrett 1997) and geographic locations of sampled population in this study (circles). The
pie chart represents the average proportion of yellow in lore for that population. The size of
the circles is proportional to average bill size for that population. Numbers correspond to
populations in Table 1. The light gray area represents the range of albilora. Light blue area
represents the range of dominica. Dark gray area represents the range of stoddardi. Numbers
along the x-axis are longitude; numbers along the y-axis are latitude.

Figure 2. Boxplots comparing significantly different (A) bill lengths and (B) proportion of
yellow in lore between ten populations of the Yellow-throated Warbler. Horizontal lines in
box plots show 10
th
, 25
th
, 50
th
, 75
th
, and 90
th
percentiles. See Table 1 for detailed population
information.

Figure 3. Graph of the two most discriminating characters of Yellow-throated Warbler
subspecies: bill length and proportion of yellow in lore. Open circles represent dominica,
closed squares represent albilora, and stars represent stoddardi subspecies.

Figure 4. Some significant correlations between morphological characters of the Yellow-
throated Warbler and geography. Open circles represent dominica, closed squares represent
albilora, and stars represent stoddardi subspecies.

Figure 1.
47
Bill len
g
th (mm)
12
11
10
9
8
7
A.
M
D
-D
e
lmarva
MD
-W
e
s
t
C
o
a
s
t
FL-
E
a
st
NCOHFL-
We
s
t
A
L
-
E
ast
AL
-
We
st
MOLA
Proportion of ye
llow in
lore
1.0
.8
.6
.4
.2
0.0
B.

Figure 2.
48

Yellow proportion of lore
1.21.0.8.6.4.20.0-.2
Bill le
n
g
th (mm)
12.0
11.5
11.0
10.5
10.0
9.5
9.0
8.5
8.0

Figure 3.
49

50
Ta il length (mm )
54 52 50 48 46 44
Yellow proport i o n of lore
1.
2
1.
0
.8 .6 .4 .2
0.
0
-.2
Longitude
100
90
80
70
Bill len g th (mm)
12 11 10
9 8 7
La
titude
40
38
36
34
32
30
28
Bill depth (mm)
4.
0
3.
8
3.
6
3.
4
3.
2
3.
0
2.
8
A.
C.
B.
D.
Figure 4.