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Fine-Scale Spatial Genetic Structure in the Brown-Headed Nuthatch (Sitta pusilla)

Permanent Link: http://ufdc.ufl.edu/UFE0021198/00001

Material Information

Title: Fine-Scale Spatial Genetic Structure in the Brown-Headed Nuthatch (Sitta pusilla)
Physical Description: 1 online resource (46 p.)
Language: english
Creator: Haas, Sarah E
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: fragmentation, genetic, microsatellite, nuthatch, sittidae, structure
Zoology -- Dissertations, Academic -- UF
Genre: Zoology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Determining the spatial genetic structure of declining species is an important goal for many management and conservation programs. Cooperative breeding birds are expected to exhibit spatial genetic structure over small geographic distances due to restricted dispersal and natal philopatry. The brown-headed nuthatch (Sitta pusilla) is a cooperative breeding bird endemic to the pine forests of the southeastern United States. Increasing conservation awareness for this species is attributed to ongoing range-wide population declines resulting from habitat loss, degradation, and fragmentation. Prior to this study no molecular genetic work had been performed for the brown-headed nuthatch, but genetic information is needed in order to assist management recommendations regarding this imperiled species. Eight hypervariable microsatellite markers specific to the brown-headed nuthatch were used to examine patterns of fine-scale spatial genetic structure in this species. Analysis of 70 individuals from a single population revealed an average of 17 alleles per locus (range 11?24), an average observed heterozygosity of 0.69 (range 0.39?0.87), and an average polymorphic information content of 0.83 (range 0.66?0.94). Spatial genetic autocorrelation analysis using five of the microsatellite markers revealed that fine-scale spatial genetic structure exists in the brown-headed nuthatch. Significantly positive spatial autocorrelation was detected only in males when male auxiliary adults were included and was not found in females. This is most likely due to the majority of auxiliary adults in this species being second-year males that assist the nest of at least one parent and thus exhibit natal philopatry. However, the difference between the geographic distances separating pairs of related males versus females was not statistically different, suggesting that both sexes may be dispersing similar distances from the natal territory overall. It is anticipated that the microsatellite markers developed for this research will continue to be a useful tool for population genetic studies on the brown-headed nuthatch. In addition, it is hoped that the information pertaining to fine-scale spatial genetic structure in the brown-headed nuthatch will provide valuable baseline information for management agencies and others concerned with the conservation of this imperiled species.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Sarah E Haas.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Kimball, Rebecca T.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021198:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021198/00001

Material Information

Title: Fine-Scale Spatial Genetic Structure in the Brown-Headed Nuthatch (Sitta pusilla)
Physical Description: 1 online resource (46 p.)
Language: english
Creator: Haas, Sarah E
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: fragmentation, genetic, microsatellite, nuthatch, sittidae, structure
Zoology -- Dissertations, Academic -- UF
Genre: Zoology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Determining the spatial genetic structure of declining species is an important goal for many management and conservation programs. Cooperative breeding birds are expected to exhibit spatial genetic structure over small geographic distances due to restricted dispersal and natal philopatry. The brown-headed nuthatch (Sitta pusilla) is a cooperative breeding bird endemic to the pine forests of the southeastern United States. Increasing conservation awareness for this species is attributed to ongoing range-wide population declines resulting from habitat loss, degradation, and fragmentation. Prior to this study no molecular genetic work had been performed for the brown-headed nuthatch, but genetic information is needed in order to assist management recommendations regarding this imperiled species. Eight hypervariable microsatellite markers specific to the brown-headed nuthatch were used to examine patterns of fine-scale spatial genetic structure in this species. Analysis of 70 individuals from a single population revealed an average of 17 alleles per locus (range 11?24), an average observed heterozygosity of 0.69 (range 0.39?0.87), and an average polymorphic information content of 0.83 (range 0.66?0.94). Spatial genetic autocorrelation analysis using five of the microsatellite markers revealed that fine-scale spatial genetic structure exists in the brown-headed nuthatch. Significantly positive spatial autocorrelation was detected only in males when male auxiliary adults were included and was not found in females. This is most likely due to the majority of auxiliary adults in this species being second-year males that assist the nest of at least one parent and thus exhibit natal philopatry. However, the difference between the geographic distances separating pairs of related males versus females was not statistically different, suggesting that both sexes may be dispersing similar distances from the natal territory overall. It is anticipated that the microsatellite markers developed for this research will continue to be a useful tool for population genetic studies on the brown-headed nuthatch. In addition, it is hoped that the information pertaining to fine-scale spatial genetic structure in the brown-headed nuthatch will provide valuable baseline information for management agencies and others concerned with the conservation of this imperiled species.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Sarah E Haas.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Kimball, Rebecca T.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021198:00001


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FINE-SCALE SPATIAL GENETIC STRUCTURE IN THE BROWN-HEADED NUTHATCH
(Sitta pusilla)




















By

SARAH E. HAAS


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007





































O 2007 Sarah E. Haas


































To my parents and six beloved brothers and sisters









ACKNOWLEDGMENTS

I would like to thank my advisor, Dr. Rebecca T. Kimball for her patience, generous

assistance, and commitment to my success in graduate school. I thank my committee members,

Dr. Edward Braun and Dr. Scott Robinson, for helping me with my thesis research. I would like

to further thank Dr. Edward Braun for always making time to assist me with my research. I am

extremely thankful to my collaborator, Jim Cox at Tall Timbers Research Station (TTRS), for

providing help and support with my research. I also thank the staff at TTRS for their kindness

and assistance. I thank Lora Loke for helping me with my fieldwork at TTRS. I thank the

Department of Zoology at the University of Florida for providing me with a Grinter fellowship

and a Riewald-Olowo research grant. I would like to thank my undergraduate research

assistants, Sergio Gonzalez and Vanessa Schipani, who provided a great deal of assistance with

the field and laboratory portions of my thesis research, and also helped me learn how to become

a better mentor. I thank David Dorman and the other employees at Osceola National Forests

who provided assistance with fieldwork. I thank Julien Martin for continual support along the

way. Last of all, I would like to thank my family and friends who have encouraged me and

provided help in so many ways.












TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES .........__.. ..... .__. ...............6....


LIST OF FIGURES .............. ...............7.....


AB S TRAC T ......_ ................. ............_........8


CHAPTER


1 INTRODUCTION ................. ...............10.......... ......


2 ISOLATION AND CHARACTERIZATION OF EIGHT POLYMORPHIC
MICRO SATELLITE MARKERS FOR THE BROWN-HEADED NUTHATCH (Sitta
pusilla) ................. ...............14.......... .....

3 FINE-SCALE SPATIAL GENETIC STRUCTURE IN THE BROWN-HEADED
NUTHATCH (Sitta pusilla) .............. ...............19....

Introducti on ........._.___..... .___ ...............19.....
M ethods .............. ...............23....

Study Site............... ...............23..
Sample Collection .............. ...............23....
Microsatellite Genotyping ................. ...............24.......... .....
Genetic Variation............... ...............2

Spatial Autocorrelation............... ............2
Relatedness by Distance ................ ...............26........... ....
R e sults................... .......... ...............27.......
Genetic Variation............... ...............2

Spatial Autocorrelation............... ............2
Relatedness by Distance ................ ...............28........... ....
Discussion ................. ...............29.................


4 CONCLUSIONS .............. ...............39....


LIST OF REFERENCES ................. ...............41................


BIOGRAPHICAL SKETCH .............. ...............46....










LIST OF TABLES


Table page

2-1 PCR optimization conditions for the eight microsatellite loci developed for the
brown-headed nuthatch (Sitta pusilla) ............... ...............17....

2-2 Characterization of eight polymorphic microsatellite loci from the brown-headed
nuthatch (Sitta pusilla) collected in Leon County, Florida ................. ............ .........18

3-1 Characterization of five polymorphic microsatellite loci used in this study. These
data are from the 70 individuals sampled from TTRS during the spring of 2006............38









LIST OF FIGURES


Figure page

3-1 Maps showing the sampling site used in this study. A) Leon County, Florida, USA,
which is where Tall Timbers Research Station (TTRS) is located (30.66 N, 84.22..........34

3-2 Graph showing the influence of different class sizes on genetic autocorrelation. The
permuted 95% confidence interval (red lines) is shown. A) Alllndividuals (n= 70).......36

3-3 Graph showing the average geographic distance in meters separating pairs of males
and females (nfemales=31; nmales=19) from TTRS that exhibit maximum likelihood. .........37









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

FINE-SCALE SPATIAL GENETIC STRUCTURE OF THE BROWN-HEADED NUTHATCH
(Sitta pusilla)

By

Sarah E. Haas

August 2007

Chair: Rebecca T. Kimball
Major: Zoology

Determining the spatial genetic structure of declining species is an important goal for many

management and conservation programs. Cooperative breeding birds are expected to exhibit

spatial genetic structure over small geographic distances due to restricted dispersal and natal

philopatry. The brown-headed nuthatch (Sittapusilla) is a cooperative breeding bird endemic to

the pine forests of the southeastern United States. Increasing conservation awareness for this

species is attributed to ongoing range-wide population declines resulting from habitat loss,

degradation, and fragmentation. Prior to this study no molecular genetic work had been

performed for the brown-headed nuthatch, but genetic information is needed in order to assist

management recommendations regarding this imperiled species.

Eight hypervariable microsatellite markers specific to the brown-headed nuthatch were

used to examine patterns of Eine-scale spatial genetic structure in this species. Analysis of 70

individuals from a single population revealed an average of 17 alleles per locus (range 11-24), an

average observed heterozygosity of 0.69 (range 0.39-0.87), and an average polymorphic

information content of 0.83 (range 0.66-0.94). Spatial genetic autocorrelation analysis using fiye

of the microsatellite markers revealed that Eine-scale spatial genetic structure exists in the brown-

headed nuthatch. Significantly positive spatial autocorrelation was detected only in males when









male auxiliary adults were included and was not found in females. This is most likely due to the

maj ority of auxiliary adults in this species being second-year males that assist the nest of at least

one parent and thus exhibit natal philopatry. However, the difference between the geographic

distances separating pairs of related males versus females was not statistically different,

suggesting that both sexes may be dispersing similar distances from the natal territory overall. It

is anticipated that the microsatellite markers developed for this research will continue to be a

useful tool for population genetic studies on the brown-headed nuthatch. In addition, it is hoped

that the information pertaining to fine-scale spatial genetic structure in the brown-headed

nuthatch will provide valuable baseline information for management agencies and others

concerned with the conservation of this imperiled species.









CHAPTER 1
INTTRODUCTION

The brown-headed nuthatch (Sittapusilla) is a small, non-migratory cooperatively

breeding passerine endemic to the pine forests of the southeastern United States. This species

historically occurred throughout much of Florida; however, it is now largely absent from most

counties near and southeast of Lake Okeechobee (Withgott & Smith 1998 and references

therein). Increasing conservation awareness for this species arises from ongoing population

declines throughout their entire range (Sauer et al 2005). Based on these population trends, the

brown-headed nuthatch has been designated a species of management concern (Carter et al.

1998). Population declines have been attributed to habitat fragmentation, loss, and degradation

(Withgott & Smith 1998). Habitat alteration, including fire suppression and landscape

fragmentation, has caused a 97% decline in the area of longleaf pine ecosystems, making them

among the most imperiled ecosystems in the United States (Noss et al. 1995). Jackson (1988)

suggested that as these forests undergo further fragmentation, brown-headed nuthatch

populations will continue to decline.

Cooperative breeding is an unusual mating system in birds in which more than two

individuals of a species contribute to raising the young (Brown 1987). In brown-headed

nuthatches, territory groups consist of mature nonbreeders ("helpers-at-the-nest" or "auxiliaries")

that help protect and rear the young, but are presumably not parents of those offspring. In a

recent study of the brown-headed nuthatch, Cox & Slater (2007) reported the percentage of

territories with more than two adults averaged 10-32% among sites and years. The majority of

groups with > 2 adults consisted of a breeding pair and an auxiliary male which was presumably

related to at least one breeding adult. Auxiliary females were less common, but some were found

in their natal territories. Stacey & Ligon (1987) suggest that cooperative breeding in birds may









occur when species have a limited, unusual resource that selects for offspring that remain in the

natal territory near that resource. As such, these species may have limited dispersal and require

specialized habitats that make them particularly sensitive to habitat degradation (see also Walters

et al. 2004).

Typical of cooperatively breeding birds, long-distance dispersal in the brown-headed

nuthatch, if it occurs at all, is likely infrequent and/or limited in range (Withgott & Smith 1998).

Cox & Slater (2007) noted that breeding pairs maintain long-term pair bonds and frequently

excavated nests within 100m of nests used the previous year. In addition, mean dispersal

distance of first-year males was generally less than two territories (<300~m). Dispersal distances

of females remain unknown, though typically females disperse farther than males in birds. This

limited dispersal is likely to increase the susceptibility of this species to habitat fragmentation by

reducing gene flow between populations and making it unlikely that individuals will disperse to

recolonize distant fragments upon extirpation (Withgott & Smith 1998).

Brown-headed nuthatches have very specialized habitat requirements and rarely venture

from pine-dominated forests (Withgott & Smith 1998). Preferred habitat consists of mature pine

forests with open understory maintained by regular fires and retention of snags (i. e. standing

dead trees) suitable for the excavation of cavity nests. Fire suppression increases the invasion of

hardwoods and slows the creation of snags, degrading optimal habitat for this species (Withgott

& Smith 1998). Wilson & Watts (1999) found a negative correlation between nuthatch

abundance and canopy cover, hardwood density, and basal area of hardwoods. In addition, they

found that nuthatches were over three times as likely to be found in areas containing snags than

those without snags. The dependence of this species on pine forests with suitable understory and









fire regimes may make it an excellent indicator species for the health of the limited amount of

remaining southeastern pine forests (Withgott & Smith 1998).

An additional factor affecting the overall status of brown-headed nuthatch populations is

the reduction in effective population size due to the presence of non-breeding auxiliaries at nests,

especially in populations exhibiting high rates of cooperative breeding. Within small,

fragmented populations, the restricted number of breeding individuals can reduce the effective

population size below the level expected for a typical, non-cooperatively breeding species. A

reduction in effective population size may increase the loss of genetic variation due to deviations

from non-random mating (Sugg et al 1996). Empirical studies in other declining species, for

example the greater prairie chicken (Tympanuchus cupido), have demonstrated that loss of

genetic variation is correlated with reduced fitness, such as reduced hatching success

(Westemeier et al. 1998), which further threatens population health.

In cooperatively breeding birds where adult offspring remain in their natal territory, the

opportunity for inbreeding may be substantial (McRae & Amos 1999 and references therein),

which can further threaten the genetic health of populations. In one instance, a female brown-

headed nuthatch was documented assisting her parents during her first year, but was then

involved in an incestuous mating that followed the disappearance of her mother prior to the next

breeding season (J. Cox, unpublished data). Thus, cooperatively breeding birds may be

particularly dependent upon gene flow to overcome the negative genetic consequences of

inbreeding. Habitat fragmentation may inhibit dispersal among populations, especially for

species with limited dispersal and extreme habitat specialization (Boone & Rhodes 1996), as

seen in the brown-headed nuthatch. Fragmentation may prevent sufficient gene flow to rescue









populations from inbreeding depression and its associated affects on fitness (Daniels & Walters

2000).

An increasing number of studies are using molecular techniques to examine patterns of

genetic variation within and among populations of threatened species (Waser & Strobeck 1998).

These types of studies can reveal the degree of relatedness among individuals within populations

and the degree of genetic structure among populations, thereby facilitating the inference of

dispersal rates. Peterson (1992) concluded that social systems with high degrees of philopatry,

as seen in many cooperative breeding birds, facilitate rapid differentiation over short spatial

scales resulting in populations that have little within population genetic variation but are quite

genetically distinct from one another. Low genetic variation within populations in cooperatively

breeding birds may have long-term consequences for evolutionary processes, such as an inability

to adapt to environmental responses and the onset of inbreeding depression (McDonald et al.

1999). Despite the declining status of the brown-headed nuthatch, there is little research on this

species, including an absence of published molecular work, which is needed for proper

management and conservation of remaining fragmented populations.

My specific research objectives are: (1) To isolate and characterize polymorphic

microsatellite markers for the brown-headed nuthatch; and (2) To elucidate the fine-scale spatial

genetic structure within a population of brown-headed nuthatches. It is anticipated that this

research will greatly increase our knowledge of this poorly studied species of conservation

interest and will also provide preliminary information for conservation organizations and others

interested in management of this species.









CHAPTER 2
ISOLATION AND CHARACTERIZATION OF EIGHT POLYMORPHIC
MICRO SATELLITE MARKERS FOR THE BROWN-HEADED NUTHATCH (Sitta pusilla)

Eight highly polymorphic microsatellite loci were isolated and characterized for the

brown-headed nuthatch (Sitta pusilla). Analysis of individuals from a single population revealed

an average of 17 alleles per locus (range 1 1-24), an average observed heterozygosity of 0.69

(range 0.39-0.87) and an average polymorphic information content of 0.83 (range 0.66-0.94).

We anticipate that these microsatellite markers will be a useful tool for population genetic

studies on the brown-headed nuthatch.

The brown-headed nuthatch (Sittapusilla) is a small passerine bird endemic to pine forests

of the southeastern United States. This species has been undergoing significant range-wide

population declines resulting from habitat loss, degradation, and fragmentation (Withgott &

Smith 1998). The brown-headed nuthatch's cooperative-breeding mating system, restricted

dispersal, natal philopatry, and ecological specialization may increase susceptibility to habitat

alteration, which has also been suggested for other cooperative-breeding birds (Walters et al.

2004). Despite declining population trends, there has not been any molecular work published at

this time on the brown-headed nuthatch. We developed these microsatellite loci to analyze the

genetic mating system and population genetic structure of this species.

We constructed an enriched (CA)n microsatellite library using protocols from the

University of Florida Interdisciplinary Center for Biotechnology Research Molecular Markers

Workshop (Brazeau & Clark 2005), some of which were modified from Kandpal et al. (1994).

Genomic DNA was isolated using the PUREG;ENE DNA Purification Kit (Biozym, Hess.

Oldendorf, Germany) from two individuals sampled at Tall Timbers Research Station (TTRS) in

Leon County, Florida. Approximately 5Cpg of genomic DNA from each individual was

combined and digested with Sau3AI restriction enzyme and size selected for fragments greater









than 400bp using Chroma Spin" columns (Clonetech Laboratories). Size-fractionated genomic

DNA was ligated to Sau3AI linkers. Excess linkers were removed using Chroma Spin" columns

before amplification of the recombinant fragments by Polymerase Chain Reaction (PCR) using

the free linker oligonucleotide. Enrichment for (CA)n repeats was completed by hybridizing the

fragments to a biotinylated (CA)1STATAAGATA probe. The biotinylated products were bound

to an Avidin matrix (VECTREX" Avidin D, Vector Laboratories), allowing for the removal of

fragments that did not hybridize to the biotinylated probe. A second PCR amplification of

fragments enriched for (CA)n repeats was performed and the Phototope" -Star Chemiluminescent

Detection Kit (New England Biolabs) was used to test for successful selection of hybridized

DNA fragments by performing a dot blot.

PCR products of the enriched microsatellite library were directly ligated to a plasmid

vector (pCR~ 2. 1-TOPO~ vector; Invitrogen) used to transform Escherichia coli (One ShotTM

TOP 10 cells, Invitrogen). Colony lifts were screened using the (CA)n probe and the

chemiluminescent detection kit. Forty-five colonies with strong hybridization signals were

sequenced on an ABI 377 PRISM automated sequencer (Applied Biosystems) to confirm the

pre sence of mi cro satellite -c ontai ni ng rep eats.

Primer pairs complementary to the microsatellite-flanking sequence were designed for 24

of the 45 clones using the software package PRIMER 3 (Rozen & Skaletsky 1998). We optimized

primer pairs and tested for polymorphism using 10 individuals from TTRS. Among 24 primer

pairs designed, eight produced consistent amplification of polymorphic loci. Optimized PCR

conditions consisted of lX PCR buffer (10mM Tris-HC1, 50mM KC1, 1.5mM MgCl2), 0.2 mM

of each dNTP, 0.2 U Taq polymerase (New England BioLabs), 0.3 CLM of the forward and

reverse primer, and 8 ng of genomic DNA in a 10 CLL reaction. Locus-specific optimized PCR









conditions for the eight polymorphic loci can be found in Table 2-1. All PCRs began with 950C

(5 min); 35 cycles of 950 (60s), primer-specific annealing and elongation conditions (Table 2-1);

and a final extension at 720C (30 min). We added a GTTT sequence to the 5' end of three

primers and GT to a single primer to facilitate the non-templated addition of adenosine by Taxq

polymerase, commonly referred to as 'pigtailing' (Brown stein et al. 1996). Allele sizes were

determined using the MegaBACE 1000 DNA Sequencer (Amersham, Sunnyvale, CA) and raw

data was analyzed using GeneMarker@ v. 1.5 (SoftGenetics LLC, State College, PA).

We genotyped approximately 20-60 individuals from TTRS for each of the eight

polymorphic microsatellite loci using the PCR conditions previously described. Characteristics

of each primer pair are presented in Table 2. The average number of alleles per locus is 17

(range 11-24). Total exclusion probabilities for the first and second parent (0.999318 and

0.999982), expected and observed heterozygosities, polymorphic information content, and null

allele frequency estimates were calculated using CERVUS 2.0 (Marshall et al. 1998). Deviations

from Hardy-Weinberg equilibrium (HWE) and tests for linkage disequilibrium were tested using

a Markov chain method provided in GENEPOP version 3.4 (Raymond & Rousset 1995).

Three of the eight loci (Table 2-2) significantly deviated from HWE following sequential

Bonferroni correction (Rice 1989). The deviation from HWE for two of the loci, Spu36A and

SpuL4-30, may reflect the small sample sizes for these highly polymorphic loci, although further

testing is needed to confirm this. In addition, departures from HWE for the three loci may also

indicate heterozygote deficit consistent with the presence of null alleles. No evidence for linkage

disequilibrium (p< 0.05) was found between loci. Overall, these microsatellite loci are highly

variable and should be valuable tools for studying many biological aspects of the brown-headed

nuthatch.










Table 2-1. PCR optimization conditions for the eight microsatellite loci developed for the
brown-headed nuthatch (Sitta pusilla).
Locus Annealing Elongation Final Betaine
Mg" (mM) (1.25mM)
SpuL5-6 600/ 40s 720/ 60s 2.5

SpuA6 650/ 10s 720/ 10s 1.5

SpuE19 660/ 40s 720/ 60s 3

SpuL4-31 660/ 40s 720/ 60s 2.5

SpuL4-3 660/ 30s 720/ 45s 3 +

SpuL6-16 600/ 5s 720/ 25s 2.5 +

Spu36A 680/ 5s 720/ 45s 3 +

SpuL4-30 580/ 5s 720/ 25s 2.5 +











Table 2-2. Characterization of eight polymorphic microsatellite loci from the brown-headed nuthatch (Sittapusilla) collected in Leon


County, Florida.
Primer sequence (5'-3')


Locus


GenBank Fluorescent


Clonal Size n k Ho- HE PIC
repeat motif range


accession
number
EF474467

EF474468

EF474469

EF474470

EF474472

EF474473

EF474474

EF474475


dye

HEX

FAM

HEX

FAM

HEX

FAM

HEX

FAM


(bp)
229-295


SpuL5-6 F: CTTCCTTGTGCATGGTTGAA
R: TCTACTGTCCCACGGGTAAAA
SpuA6 F: ACCTCTAGCCTTGCTTGCAG
R: GCGAAGAATAGCAGGTTTGG
SpuE19 F: TCCTGTGAGAGCAGCAAGAA
R: CTGGCATCAAAGGAAAGCAT
SpuL4-31* F: CCCCAAACCCAACTCTGTTA
R: TGCATTGGTTCATTACTAGATGCT
SpuL4-3 F: AGTCAGCACATGGAACCACA
R: GTTTAAACCCAGCAAACATTCCAC
SpuL6-16 F: AGGCTCCCTGTGTAGGTGTG
R: GTTTATCCTTCAGGTGGGTGACTG
Spu36A* F: ACAGAGGAAGCCACCAGAGA
R: GTTTGAAGGGGCATCTCTTCTTCC
SpuL4-30* F: ATGCACTGGGTTCCTGTGTT
R: GTTTGTTCACATTGCTGGAAAGG


(GT),,

(AC)zz

(GThe

(GT),

(GT),,

(GT),,

(GT)33

(GT)29


24 0.852 0.908 0.894


190-232 51 13 0.627 0.682 0.655

234-328 60 15 0.683 0.733 0.704

271-319 52 11 0.654 0.813 0.778

360-406 56 19 0.786 0.869 0.850

304-356 39 20 0.872 0.922 0.904

332-412 23 22 0.391 0.962 0.938

262-306 27 17 0.630 0.926 0.902


Bolded bases indicate 'pigtail' addition; (n), number of individuals genotyped at each locus; (k), number of alleles; Ho, observed
heterozygosity; HE, expected heterozygosity; PIC, polymorphic information content. *Indicates locus with significant deviation from
Hardy-Weinberg equilibrium after Bonferroni correction.









CHAPTER 3
FINE-SCALE SPATIAL GENETIC STRUCTURE IN THE BROWN-HEADED NUTHATCH
(Sitta pusilla)

Understanding patterns of spatial genetic structure is important for the management and

conservation of many species. Fine-scale genetic structure may be found in species exhibiting

restricted dispersal and natal philopatry, as seen in many cooperative breeding birds. In this

study, spatial autocorrelation analysis using five microsatellite loci was performed to examine

patterns of fine-scale spatial genetic structure in the brown-headed nuthatch (Sitta pusilla). The

brown-headed nuthatch is a cooperative breeding bird that is currently experiencing population

declines attributed to habitat loss and fragmentation. Significantly positive autocorrelation was

only detected in males when auxiliary adults were included and was not found in females.

Contrary to expectations, the difference between the geographic distances separating pairs of

related males versus females was not statistically different, suggesting that both sexes may be

dispersing similar distances from the natal territory overall. This study is the first to describe the

fine-scale spatial genetic structure in the brown-headed nuthatch and is important to the

conservation and management of this declining species. Long-term management efforts of the

brown-headed nuthatch should consider maintaining adequate genetic variation within small,

potentially isolated populations, although additional studies are needed to further elucidate

spatial genetic patterns in this species.

Introduction

Determining the spatial genetic structure within and among populations is important for

the conservation and management of many declining species (Caizergues et al. 2003; Laikre et

al. 2005; Johnson & Dunn 2006). Information regarding the genetic structure can provide

important insights into behavioral and ecological processes including dispersal pattens, local

adaptation, and the effects of landscape features on gene flow (Piertney et al 1999; Bittner &









King 2003; Manel et al. 2003). Most studies to date that have analyzed population genetic

structure have focused on the landscape level, often sampling individuals from multiple

populations throughout the range of a species (Castric et al. 2001; Veit et al. 2005; Eggert et al.

2006; Sonstebo et al. 2007). However, there has recently been a substantial increase in the

number of studies focusing on fine-scale genetic structure (i.e. within populations) and the

underlying factors most likely generating these within-population spatial patterns (Brouat et al.

2003; Peakall et al. 2003; Hazlitt et al. 2004; Comer et al. 2005; Kitchen et al. 2005; Nussey et

al. 2005; Zamudio & Wieczorek 2007). Assessing microgeographic spatial genetic structure

within populations is useful for investigating limited and sex-biased dispersal, social behavior,

mating systems, and barriers to gene flow within populations (Peakall et al. 2003; Double et al.

2005).

Many cooperative breeding species are expected to exhibit microspatial genetic structuring

due to restricted dispersal and high levels of natal philopatry (Walters et al. 2004; Woxvold et al.

2006), yet relatively few studies have analyzed the presence of fine-scale genetic structure in

cooperative breeding birds (although see Painter et al. 2000; Double et al. 2005; Temple et al.

2006; Woxvold et al 2006). In addition to these characteristics, some cooperative breeding

birds also exhibit habitat specialization and have a large number of non-breeding adults that

function as helpers (Walters et al 2004). These traits may facilitate genetic structure over small

geographic distances (Peakall et al. 2003; Hazlitt et al. 2004; Double et al. 2005). In many

cooperative breeding birds, natal philopatry is sex-biased towards males while females typically

disperse over longer distances (Greenwood 1980; Koenig et al. 1992; Walters et al. 2004). Sex-

biased dispersal may result in demes of related individuals of the philopatric sex (Hazlitt et al.

2004; Sugg et al. 1996). The limited number of studies that have examined fine-scale genetic









structure in cooperative breeding birds all detected microgeographic genetic structure over small

distances (i. e. within a few territories), with more pronounced patterns of spatial genetic structure

in the philopatric males (Painter et al 2000; Double et al. 2005; Temple et al. 2006; Woxvold et

al. 2006).

In this study, I examined patterns of fine-scale spatial genetic structure in the cooperative

breeding brown-headed nuthatch (Sitta pusilla). The brown-headed nuthatch is a small (~10 g),

non-migratory, cavity-nesting passerine endemic to the longleaf pine ecosystems of the

southeastern United States (Withgott & Smith 1998). The percentage of breeding territories

containing one or more auxiliary adults has been documented to vary from 10-32% (Cox &

Slater 2007). Most groups containing more than two adults consist of a breeding pair and a

second-year auxiliary male who is related to at least one breeding adult (Cox & Slater 2007).

Breeding pairs maintain long-term pair bonds and are highly sedentary once a territory is

established-- frequently excavating nests within 100m of nests used the previous year (Cox &

Slater 2007). Natal philopatry appears to be heavily male-biased based on field observations,

although female helpers have been documented assisting at the natal territory (Cox & Slater

2007). Most dispersing second-year males establish territories within 300m of territories held by

their parents, which is generally the nearest neighbor to the natal territory (Cox & Slater 2007).

On the other hand, average dispersal distance from the limited number of recaptured females (n=

6) is 1240m (J. Cox, unpublished data).

Increasing conservation awareness for the brown-headed nuthatch has resulted from range-

wide population declines (Sauer et al. 2005), which have been attributed to habitat loss,

fragmentation, and degradation (Withgott & Smith 1998). This species possesses many of the

distinctive traits seen in other cooperative breeding birds that have been suggested to increase









susceptibility to habitat fragmentation (Walters et at. 2004) and generate fine-scale spatial

genetic structure (Woxvold et at. 2006). Especially relevant traits for the brown-headed nuthatch

include the presence of non-breeding adults that function as helpers, extreme philopatry, limited

dispersal, and ecological specialization (Withgott & Smith 1998). Despite ongoing population

declines in this species and the prediction that populations will continue to decline as pine forests

become further fragmented (Jackson 1988), there is little research on the brown-headed nuthatch,

including an absence of molecular work prior to this study. Furthermore, it is currently unknown

to what extent male-biased natal philopatry and limited dispersal promote spatial genetic

structure in this species.

This study combines spatial autocorrelation procedures and hypervariable microsatellite

markers to examine fine-scale patterns of genetic structure in the brown-headed nuthatch. The

use of spatial autocorrelation to elucidate microspatial genetic structure may be especially useful

for species that exhibit natal philopatry and restricted dispersal, both of which are characteristics

that may generate fine-scale nonrandom genetic patterns (Double et at 2005). My research

obj ectives were (1) to determine if genetic autocorrelation is affected by geographic distance, (2)

to compare genetic autocorrelation between males and females, and (3) to examine the influence

of auxiliary adults on genetic autocorrelation. I expected to find higher genetic autocorrelation at

small geographic distances versus large distances accompanied by a steady decrease in r due to

the overall sedentary behavior and restricted dispersal described for the brown-headed nuthatch.

I also predicted that males would exhibit stronger positive autocorrelation than females due to

male-biased natal philopatry in the brown-headed nuthatch. Lastly, I predicted that the inclusion

of auxiliary adults would strengthen genetic autocorrelation due to presumed relatedness

between breeding and auxiliary adults.









Methods


Study Site

Fieldwork for this study was conducted at Tall Timbers Research Station (TTRS) in Leon

County, Florida, USA (Fig. 3-1). TTRS encompasses approximately 1,630ha dominated by

upland pine habitats consisting primarily of loblolly (Pinus taeda) and shortleaf pines (P.

eichnata); although some of the area is not suitable habitat for brown-headed nuthatches (e.g.

water bodies, hardwood hammocks). The breeding activities of brown-headed nuthatch groups

within TTRS have been monitored by J. Cox since 2001, although genetic sampling was

sufficient to analyze population genetic structure only for 2006. Sampling of adult individuals

occurred from mid-February through May 2006, although sampling was not exhaustive over the

entire study area.

Sample Collection

A total of 70 adult individuals comprising 36 territories (~ 670 ha) were sampled during

the spring of 2006. For groups containing more than two adults, behavioral observations (e.g.

dominance, incubation, and copulation), and in some instances banding records from previous

years, were used to differentiate between breeding and auxiliary adults. Individuals were

captured using mist nets placed near nests, which has been found to disrupt <1% of nesting

attempts for this species (J. Cox, unpublished data). All nesting locations were geographically

referenced with Universal Transverse Mercator (UTM) coordinates using a hand-held global

positioning system; nest locations were assumed to represent the center of each territory. Birds

were fitted with color bands and an aluminum United States Fish and Wildlife Service (USFWS)

band. A blood sample (20-40 CIL) was taken from the brachial vein of each bird and stored in

1mL of lysis buffer (0. 1 M Tris-HC1, pH 8.0, 0. 1 M EDTA, 0.01 M NaC1, 1% SDS). Genomic

DNA was extracted using a PUREGENE" DNA Purification Kit (Biozym, Hess. Oldendorf,









Germany) and the sex of each individual was determined using the molecular sexing method

described by Fridolfsson & Ellegren (1999).

Microsatellite Genotyping

Five polymorphic microsatellite loci developed specifically for the brown-headed nuthatch

were used to obtain a multilocus genotype for each individual (Table 3-1). Briefly, microsatellite

loci were amplified via polymerase chain reaction (PCR) in 10CLL reaction volumes containing

the following: lX PCR buffer (10mM Tris-HC1, 50mM KC1, 1.5mM MgCl2), 0.2 mM of each

dNTP, 0.2 U Taq polymerase (New England BioLabs), 0.3 CLM of the reverse and fluorescently

labeled forward primer, and 8ng of genomic DNA (see Chapter 2 for further details).

Magnesium concentrations varied per locus (Table 3-1). The PCR additive betaine (1.25 mM)

was used for a single locus, SpuL4-3, to help mitigate the presence of microsatellite stutter. All

PCR amplifications began with 950C (5 min); 35 cycles of 950 (60s), primer-specific annealing

and elongation conditions; and a Einal extension at 720C (30 min). A MegaBACE 1000 DNA

Sequencer (Amersham, Sunnyvale, CA) produced raw data and alleles were sized using

GeneMarker" v. 1.5 (SoftGenetics LLC, State College, PA).

Genetic Variation

Exact tests for deviations from Hardy-Weinberg equilibrium (HWE) and tests for linkage

disequilibrium were tested using a Markov chain method with 5,000 iterations implemented in

GENEPOP version 3.4 (Raymond & Rousset 1995). When performing multiple comparisons,

sequential Bonferroni corrections were used to reduce global Type I error (Rice 1989). Average

number of alleles, observed and expected heterozygosity, mean proportion of individuals

genotyped, and tests for null alleles were calculated using CERVUS 2.0 (Marshall et al. 1998).









Spatial Autocorrelation

To examine Eine-scale genetic structure in the brown-headed nuthatch, spatial

autocorrelation analysis was performed using GenA1Ex, version 6 (Peakall & Smouse 2006) to

describe the genetic structure over the entire study area. Unlike classical spatial autocorrelation

analysis, which is implemented one locus at a time, GenA1Ex6 uses a multivariate approach that

strengthens the spatial signal by reducing random (locus to locus) noise (Smouse & Peakall

1999). The program generates an autocorrelation coefficient r, which provides a measurement of

the pairwise genetic similarity of individuals whose geographic separation falls within a

specified distance class. Individuals were classified into four categories: (1) All Individuals; (2)

All Males (includes auxiliary males); (3) Dominant Males (breeding males only); and (4)

Females.

Spatial autocorrelation was performed using automatically increasing geographic distance

classes for a given user-specified base distance class. This method uses a cumulative sampling

strategy so that each subsequent distance interval includes all pairwise comparisons from

previous intervals. I specified a base distance class size of 100m for 15 runs so that the first

distance interval would calculate r based on all pairwise comparisons within a distance of 0-

100m, the second analysis for 0-200m, and so on until the last run (i. e. 0-1500m) was completed.

This base distance class was chosen because 4 of the 36 (1 1%) territories used in this study had a

sampled nearest neighboring territory 100m. Analyses were also performed using a 200m base

distance class because previous research on the brown-headed nuthatch reported that the average

distance between nearest neighboring territories at TTRS was 198.5m (SD = 90.7) (Cox & Slater

2007).

Statistical significance was tested in GenA1Ex6 using random permutation ofr.

Permutation was repeated 1000 times to generate the 25th and 975th ValUeS used to define the









95% confidence intervals around the null hypothesis ofr = 0. Significant spatial genetic

structuring was declared when r exceeded the 95% confidence intervals. The autocorrelation

coefficients were plotted as a function of geographic distance and visualized graphically in

spatial genetic autocorrelograms.

Relatedness by Distance

In addition to spatial autocorrelation, I also used another approach to further investigate

Eine-scale spatial genetic structure of brown-headed nuthatches. This was performed because

sampling of territories at the study site was not exhaustive and spatial autocorrelation procedures,

which only analyze individuals falling within user-specified distance classes, may not capture the

true spatial genetic structure. I used the program ML-RELATE (Kalinowski et al. 2006) to

calculate maximum likelihood estimates of relatedness (r) (see Blouin 2003 for a review) for all

pairwise comparisons for Dominant Males and Females separately. Although autocorrelation

coefficients such as r are closely correlated with estimates of relatedness (Bank et al. 2005), they

are not a direct estimate of genealogical relationships among individuals (Temple et al. 2006).

Pairs of individuals within each sex exhibiting r-values greater than or equal to 0.50 were

selected and the geographic distances separating these individuals were recorded. The statistical

software R (R Development Core Team 2005) was used to perform a 1-tailed Wilcoxon rank

sum test between these distances to assess whether a statistically significant difference existed

between the average distance separating related males versus related females. In addition,

Microsoft Excel was used to perform an F-test to determine whether a statistically significant

difference existed between the variances in male and female distances.












Genetic Variation

I sampled individuals from 36 territories: a breeding male and female were obtained for 20

territories; a breeding pair and a single male helper were obtained for 5 territories; a breeding

pair and two male helpers were obtained for 1 territory; a single female was obtained for 7

territories; a single male was obtained for 3 territories; and both a dominant and auxiliary male

were obtained for a single territory. Molecular sexing confirmed that all 8 auxiliary adults were

males. There were prior field data for only three of the auxiliary adults, which revealed that all

three helpers were banded the previous year as nestlings at the nest of the male they were

currently helping when sampled. This suggests that these three individuals are offspring of the

breeding male in which they were assisting, although formal parentage analysis is needed to

confirm this.

Table 3-1 describes the Hyve microsatellite loci used in this study, all of which exhibited

high levels of polymorphism (average observed heterozygosity = 0.7146). A single locus

(SpuL4-3 1) significantly deviated from HWE, which may be due to the presence of null alleles

(null frequency estimate = 0.1033). None of the other loci showed evidence for null alleles.

Linkage disequilibrium was not detected for any of the loci (P>0.01). The number of alleles per

locus ranged from 11-24, with an average of 16 alleles per locus. The mean proportion of

individuals that were genotyped at all five loci was 0.929. Reasons for missing genotypes

include repeated PCR failure and ambiguous microsatellite products due to the presence of

stutter bands.

Spatial Autocorrelation

Spatial autocorrelation analysis detected the predicted pattern of higher genetic

autocorrelation at small geographic distances followed by a steady decrease in r for All2ales


Results










(Fig. 3-2 B), although no other sampling category revealed this pattern (Fig. 3-2). However, a

weaker, albeit non-significant, pattern was found in the All Individuals analysis (Fig. 3-2 A),

which also includes auxiliary adults. These results suggest that increasing geographic distance

does affect the spatial signal of fine-scale genetic structure in brown-headed nuthatches and that

the presence of auxiliary males increases the strength of positive genetic autocorrelation at small

distances. Contrary to expectations, the predicted pattern was not seen in Dominant Males (Fig.

3-2 C), despite male-biased natal philopatry in this species. Interestingly, Females exhibited

negative r-values at the two smallest distance intervals, whereas Dominant Males revealed

positive values. Although these results are not statistically significant, they suggest that females

may be less related at smaller distances than are males, which is supported once auxiliary males

are included in the analyses. The autocorrelation analysis for All2ales revealed significant

positive genetic autocorrelation until approximately 1300m. Similar results for all categories

were seen when analyses were performed using the 200m base distance class (results not shown).

Relatedness by Distance

A total of 19 pairwise comparisons for males and 31 pairwise comparisons for females

exhibited maximum likelihood estimates of relatedness greater than or equal to 0.50. The

average geographic distance between pairs of selected males was 1,585m (range = 193-2423m)

and for females was 1,780m (range = 192-3799m). The 1-tailed Wilcoxon rank sum test

returned a p-value of 0.393, suggesting that there is not a statistically significant difference in the

geographic distances separating related males and females provided the dataset used in this

study. In addition, there was substantial overlap in the 95% upper and lower confidence

intervals around the average for males and females, thereby revealing a weak effect size and

possible lack of biological significance (Fig. 3-3). The F-test reveled that the variances in the

distances separating pairs of related males and females were not statistically different (p=0.338).









Discussion

Prior field data for the brown-headed nuthatch show that males exhibit high rates of natal

philopatry and typically disperse over very short distances (Cox & Slater 2007). In contrast,

females have been documented less frequently as helpers and are thought to disperse much larger

distances than males (Cox & Slater 2007). This pattern of sex-biased dispersal would be

expected to generate microspatial genetic structure among males with little or no pattern in

females (Peakall et al. 2003). The spatial autocorrelation analyses presented in this study

revealed that all males exhibited significantly positive genetic autocorrelation at small distances,

whereas significance was not detected in females. However, significance in males was attributed

to the inclusion of helping individuals, which are rare in females (J. Cox, unpublished data) and

were not included in this study. Other studies on cooperative breeding birds also detected

stronger positive genetic autocorrelation when auxiliary adults were included in the analyses

(Double et al. 2005; Temple et al. 2006). Upon exclusion of auxiliary adults however, spatial

autocorrelation did not detect significance in males, which is in contrast to field observations

documenting shorter dispersal distances in males (Cox & Slater 2007).

In spatial autocorrelation, the distance class size at which r is no longer significantly

positive approximates the extent of detectable positive genetic structure (Peakall et al. 2003).

This distance is similar to the 'genetic neighborhood' size of a population (Wright 1943;

Golenberg 1987). In this study, autocorrelation revealed significantly positive genetic structure

among all males extending beyond six average territory widths (i.e. 1300m). Based on field

observations of the brown-headed nuthatch, Cox & Slater (2007) reported that the average

dispersal distance for second-year males dispersing equal to or greater than two territories away

from the natal territory was 1,358m. Interestingly, results from both spatial autocorrelation and









field observations suggest that the average distance of gene flow (i. e. genetic neighborhood size)

in male brown-headed nuthatches is approximately 1300m.

The analyses performed using maximum likelihood estimates of relatedness suggest that

the average distance separating related dominant males was approximately 1,600m, which is

only slightly higher (i. e. 300m) than the estimates obtained from mark-recapture data and spatial

autocorrelation for all males (i.e. helpers included). Although the autocorrelation procedure did

not detect significance in dominant males, this approach includes all individuals within a user-

specified distance class, which may or may not be related. On the other hand, the relatedness by

distance analysis disregards distance classes and only looks at those pairs of individuals

exhibiting high levels of relatedness and then determines the geographic distance separating that

particular pair. Despite the different approaches of these two procedures, both analyses suggest

that many male brown-headed nuthatches exhibit high leves of relatedness within a 1-2km

geographic distance interval, which closely approximates the previous estimate of Cox & Slater

(2007).

Contrary to expectations, the average distance separating related females was only about

200m greater than for dominant males. This finding contradicts the assumption that males

disperse significantly shorter distances than females; however, the range of dispersal distances in

the dataset for both sexes suggests that at least some females may be dispersing larger distances

than males (i.e. >1km). Interestingly, there was a greater number of pairwise comparisons of

females (n=31) than males (n=19) that showed a relatedness estimate greater than or equal to

0.50. Tenable biological conclusions cannot be made from this finding because territory

sampling was incomplete at the study site; however, this data suggest that females may not be









dispersing substantially larger distances than males as previously thought, although additional

studies are needed to validate the Eindings in this study.

Populations undergoing restricted gene flow and an absence of selection are expected to be

characterized by positive spatial genetic autocorrelation at small distances, subsequently

declining through zero and becoming negative (Peakall et al. 2003). I predicted that spatial

autocorrelation would be higher at small geographic distances accompanied by a steady decrease

in r due to the restricted dispersal and overall sedentary lifestyle described for the brown-headed

nuthatch (Withgott & Smith 1998). However, significance for this pattern was only found in All

Males, although it was also observed, albeit non-signifieant, in Alllndividuals. Both of these

sampling categories included male helpers, which further illustrates the impact that auxiliary

males have on generating positive genetic autocorrelation at small distances in the brown-headed

nuthatch. Other studies employing spatial autocorrelation on cooperative breeding birds did

however find the predicted pattern for all individuals (Double et al. 2005; Temple et al. 2006),

although these studies were based on larger sample sizes.

The information presented in this paper provides the first genetic study on brown-headed

nuthatches and indicates that genetics needs to be considered in conservation and management

decisions. The results suggest that cooperative breeding and the retention of putatively related

auxiliary adults on the natal territory may facilitate high levels of relatedness at small geographic

distances. However, a recent study reported that only 10-32% of groups exhibit cooperative

breeding in the brown-headed nuthatch (Cox & Slater 2007); thus, philopatric offspring may not

have a large overall effect on fine-scale spatial genetic structure in this species, as suggested by

the autocorrelation analyses performed on dominant males only (i. e. those without helpers).









The relatedness by distance analyses suggest that both sexes may be dispersing small

distances on average (i. e. <2km), although this study was limited to a single study site and is

therefore unable to assess long-distance dispersal. Nonetheless, if males are dispersing shorter

distances than females, then populations of the brown-headed nuthatch may be particularly

dependent upon female-mediated gene flow for the introduction of novel alleles and maintenance

of genetic variation within populations. If both sexes are dispersing only limited distances, as

has been suggested elsewhere (Withgott & Smith 1998), then populations of the brown-headed

nuthatch may require habitat corridors (e.g. pine plantations) to facilitate among-population

dispersal in fragmented landscapes. Limited dispersal combined with sociality and ecological

specialization, as seen in the brown-headed nuthatch, has been suggested to increase sensitivity

to habitat fragmentation (Henle et al. 2004). Moreover, habitat fragmentation has already been

documented to restrict dispersal in some other cooperative breeding species that also exhibit

limited dispersal (Breininger 1999; Cooper & Walters 2002).

Restricted dispersal can reduce gene flow both within and among populations and lead to

increased levels of relatedness within populations (Painter et al. 2000). Increased relatedness

among social groups may increase the occurrence of inbreeding, which may be a particular

concern in cooperative breeders where dispersal distances are usually short and relatedness is

typically high (Koenig & Haydock 2004). Although inbreeding has been shown to reduce fitness

in some cooperative breeding birds (Brown & Brown 1998; Daniels & Walters 2000), incest has

been documented only twice in the brown-headed nuthatch (Fleetwood 1946; J. Cox,

unpublished data). On the other hand, the analyses in this study revealed that many individuals

exhibited high pairwise relatedness with members of the same sex over small geographic

distances. In light of this finding, long-term management efforts of the brown-headed nuthatch









should consider maintaining sufficient genetic variation within small, potentially isolated

populations.

In conclusion, this study provided a preliminary assessment of spatial genetic structure in

the brown-headed nuthatch. Follow-up studies are needed that combine additional genetic and

demographic information to enable a better understanding of the complex interplay between

demography and spatial genetic structure in this declining species. In addition, further research

is needed to elucidate the genetic mating system of this cooperative breeding bird, and also

needed are studies that analyze the population genetic structure among populations to examine

dispersal patterns at the landscape level. The latter will be especially important for management

and conservation of the brown-headed nuthatch given the prediction that populations of this

species will continue to become further isolated and fragmented as habitat destruction continues

(Jackson 1988).


















Y"-i, il



,u'?









~

~*~d~$ c~~


Nesting Locations
SNo Samples
+ Blood Samples
SUpland Pines


sioo 600 Mveters


++
+. '*

'5

+
**'..~


+.


Figure 3-1. Maps showing the sampling site used in this study. A) Leon County, Florida, USA,
which is where Tall Timbers Research Station (TTRS) is located (30.66 N, 84.22 W).
B) + denotes individual territory locations (n= 36) at TTRS that were used in this
study .























a






















~- x



-1






100 00 40050607080901000 1100 20100 10010


Distance (m)


0 0040

0 020




.2 -0 020

S-0 040













B







0 200

0 150

S0 100

0 050

o 0000

Q)-0 050

-0 100

non15


L



































L


All Individuals


















0.300

0.200
0
0.100



S-0.2000


o a 0 0 0 0 0 0
Ditnc m


L


L`0.300

S0.200
O
a 0.100

= 0.000
O
o -0.100

-.0.200

e -0.300


O O O O O O O O
O O O O O O O O




Distance (m)


Figure 3-2. Graph showing the influence of different class sizes on genetic autocorrelation. The
permuted 95% confidence interval (red lines) is shown. A) All Individuals (n= 70).
B) All males (n= 37). C) Dominant Males (n= 29). D) Females (n= 33).


Dominant Males


Females












2500


2000













Males Females



Figure 3-3. Graph showing the average geographic distance in meters separating pairs of males
and females (nfemale=31; nmales=19) from TTRS that exhibit maximum likelihood
estimates of relatedness equal to or greater than 0.50. Bars represent the 95% upper
and lower confidence intervals around the mean.









Table 3-1. Characterization of five polymorphic microsatellite loci used in this study. These data are from the 70 individuals sampled
from TTRS during the spring of 2006.
Locus Repeat Size range GenB ank Final n k Ho HE
Motif (bp) accession number Mg2+(mM)
(primers)
SpuL5-6 (GT)27 229-295 EF474467 2.5 69 24 0.841 0.910
SpuL4-31 (GT)15 271-319 EF474470 2.5 60 11 0.667 0.825
SpuE 19 (GT)lo 234-328 EF474469 3.0 68 15 0.706 0.745
SpuA6 (AC)11 190-232 EF474468- 64 13 0.625 0.684
SpuL4-3 (GT)27 360-406 EF474472 3.0 64 20 0.734 0.877
(n), number of individuals genotyped at each locus; (k), number of alleles at each locus; Ho, observed heterozygosity; HE, expected
heterozygosity. Indicates locus with significant deviation from Hardy-Weinberg equilibrium after sequential Bonferroni correction.









CHAPTER 4
CONCLUSIONS

The brown-headed nuthatch exhibits distinctive traits typical of many cooperative breeding

birds including limited dispersal, natal philopatry, and habitat specialization (Walters et at.

2004). It has been suggested that these characteristics may render cooperative breeding species

unusually vulnerable to habitat loss, degradation, and fragmentation (Walters et at. 2004). In

addition, many cooperatively breeding species are expected to exhibit microspatial structuring

due to restricted dispersal and natal philopatry, yet relatively few studies to date have analyzed

fine-scale genetic structure in cooperative breeding birds (Double et at. 2005; Temple et at.

2006; Woxvold et at 2006). For my thesis research, I constructed species-specific polymorphic

microsatellite markers to examine patterns of fine-scale spatial genetic structure in the brown-

headed nuthatch.

There is no published genetic data for the brown-headed nuthatch prior to the research

presented in this thesis. The first portion of my thesis research consisted of developing eight

microsatellite loci specific to the brown-headed nuthatch in order to subsequently analyze

population genetic structure in this species (Chapter 2). All eight microsatellite markers

exhibited extremely high levels of polymorphism (Table 2-2), though only five could be scored

consistently enough to be used to examine fine-scale spatial genetic structuring.

For the second part of my thesis research, I used the microsatellite markers to examine

patterns of microspatial genetic structure in the brown-headed nuthatch (Chapter 3). As

predicted based on male-biased natal philopatry in this species, genetic autocorrelation was more

pronounced in males versus females, and became even stronger when male auxiliary individuals

were included. These results are similar to the few other studies that have used spatial

autocorrelation to examine fine-scale spatial genetic structure in cooperative breeding birds










(Double et al. 2005; Temple et al. 2006). Although formal kinship analyses using genetics have

not been conducted, the results in this study were attributed to putative relatedness between the

auxiliary males and the breeding males in which they were assisting. Overall, the spatial

autocorrelation results were not as strong as expected, but nonetheless revealed that fine-scale

spatial genetic structure exists in the brown-headed nuthatch.

Follow-up studies on the brown-headed nuthatch are needed to address many additional

aspects of this species biology. Included are further studies employing spatial autocorrelation,

but with larger sample sizes and all eight microsatellite markers. Ongoing collection of

demographic data on brown-headed nuthatches from the study site used in this research is needed

for additional spatial autocorrelation studies in order to allow a better understanding of the

complex interplay between demography and spatial genetic structure. In addition, future studies

are also needed to examine the genetic mating system of the brown-headed nuthatch. Knowing

whether breeding pairs are strictly monogamous or if extra-pair fertilizations are occurring will

help to further understand spatial genetic structure in this cooperative breeding species.









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BIOGRAPHICAL SKETCH

Sarah Haas was born and raised in Corpus Christi, Texas. In May of 2004, she received a

Bachelor of Science degree, magna cum laude, in biology with a minor in chemistry from Texas

State University in San Marcos, Texas. In August of 2004, Sarah began graduate school in the

Zoology Department at the University of Florida working under the supervision of Dr. Rebecca

Kimball and Dr. Edward Braun. Sarah' s thesis research was on the population genetics of the

cooperative breeding brown-headed nuthatch (Sitta pusilla). In addition, Sarah was the lead

investigator in a conservation genetics project on the Florida snail kite (R.s.plumbeus). After

graduation, Sarah moved to Washington D.C. to spend some time working in environmental

policy and other human-dimension aspects of conservation because of her desire to participate in

threatened and endangered species conservation while also being actively involved with public

outreach and education on environmental issues.





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1 FINE-SCALE SPATIAL GENETIC STRUCT URE IN THE BROWN-HEADED NUTHATCH ( Sitta pusilla ) By SARAH E. HAAS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

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2 2007 Sarah E. Haas

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3 To my parents and six bel oved brothers and sisters

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4 ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Reb ecca T. Kimball for her patience, generous assistance, and commitment to my success in gr aduate school. I thank my committee members, Dr. Edward Braun and Dr. Scott Robinson, for helpi ng me with my thesis research. I would like to further thank Dr. Edward Braun for always maki ng time to assist me with my research. I am extremely thankful to my colla borator, Jim Cox at Tall Timber s Research Station (TTRS), for providing help and support with my research. I also thank the staff at TTRS for their kindness and assistance. I thank Lora L oke for helping me with my fieldwork at TTRS. I thank the Department of Zoology at the University of Fl orida for providing me with a Grinter fellowship and a Riewald-Olowo research grant. I w ould like to thank my undergraduate research assistants, Sergio Gonzalez and Vanessa Schipani who provided a great deal of assistance with the field and laboratory portions of my thesis research, and also helped me learn how to become a better mentor. I thank David Dorman and th e other employees at Osceola National Forests who provided assistance with fieldwork. I tha nk Julien Martin for con tinual support along the way. Last of all, I would like to thank my fa mily and friends who have encouraged me and provided help in so many ways.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 ABSTRACT....................................................................................................................... ..............8 CHAPTER 1 INTRODUCTION..................................................................................................................10 2 ISOLATION AND CHARACTERIZAT ION OF EIGHT POLYMORPHIC MICROSATELLITE MARKERS FOR TH E BROWN-HEADED NUTHATCH ( Sitta pusilla ).............................................................................................................................. ......14 3 FINE-SCALE SPATIAL GENETIC ST RUCTURE IN THE BROWN-HEADED NUTHATCH ( Sitta pusilla )...................................................................................................19 Introduction................................................................................................................... ..........19 Methods........................................................................................................................ ..........23 Study Site..................................................................................................................... ....23 Sample Collection...........................................................................................................23 Microsatellite Genotyping...............................................................................................24 Genetic Variation.............................................................................................................24 Spatial Autocorrelation....................................................................................................25 Relatedness by Distance..................................................................................................26 Results........................................................................................................................ .............27 Genetic Variation.............................................................................................................27 Spatial Autocorrelation....................................................................................................27 Relatedness by Distance..................................................................................................28 Discussion..................................................................................................................... ..........29 4 CONCLUSIONS....................................................................................................................39 LIST OF REFERENCES............................................................................................................. ..41 BIOGRAPHICAL SKETCH.........................................................................................................46

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6 LIST OF TABLES Table page 2-1 PCR optimization conditions for the eight microsatellite loci developed for the brown-headed nuthatch ( Sitta pusilla )...............................................................................17 2-2 Characterization of eight polymorphic micr osatellite loci from the brown-headed nuthatch ( Sitta pusilla ) collected in Leon County, Florida................................................18 3-1 Characterization of five polymorphic microsatellite loci used in this study. These data are from the 70 individuals sample d from TTRS during the spring of 2006.............38

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7 LIST OF FIGURES Figure page 3-1 Maps showing the sampling site used in this study. A) Leon County, Florida, USA, which is where Tall Timbers Research Station (TTRS) is located (30.66 N, 84.22..........34 3-2 Graph showing the influence of different class sizes on genetic autocorrelation. The permuted 95% confidence interv al (red lines) is shown. A) All Individuals ( n = 70).......36 3-3 Graph showing the average geographic dist ance in meters separating pairs of males and females (nfemales=31; nmales=19) from TTRS that exhibit maximum likelihood..........37

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8 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science FINE-SCALE SPATIAL GENETIC STRUCT URE OF THE BROWN-HEADED NUTHATCH ( Sitta pusilla ) By Sarah E. Haas August 2007 Chair: Rebecca T. Kimball Major: Zoology Determining the spatial genetic structure of d eclining species is an important goal for many management and conservation programs. Coopera tive breeding birds are expected to exhibit spatial genetic structure over small geographic di stances due to restricted dispersal and natal philopatry. The brown-headed nuthatch ( Sitta pusilla ) is a cooperative breed ing bird endemic to the pine forests of the southeas tern United States. Increasing conservation awareness for this species is attributed to ongoing range-wide popul ation declines resul ting from habitat loss, degradation, and fragmentation. Prior to th is study no molecular genetic work had been performed for the brown-headed nuthatch, but gene tic information is needed in order to assist management recommendations regard ing this imperiled species. Eight hypervariable microsatellite markers sp ecific to the brown-headed nuthatch were used to examine patterns of fine-scale spatial genetic structure in this species. Analysis of 70 individuals from a single population revealed an average of 17 a lleles per locus (range 11-24), an average observed heteroz ygosity of 0.69 (range 0.39-0.87), a nd an average polymorphic information content of 0.83 (range 0.66-0.94). Spa tial genetic auto correlation analysis using five of the microsatellite markers rev ealed that fine-scale spatial geneti c structure exists in the brownheaded nuthatch. Significantly positive spatial au tocorrelation was detected only in males when

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9 male auxiliary adults were included and was not f ound in females. This is most likely due to the majority of auxiliary adults in this species being second-year males that assi st the nest of at least one parent and thus exhibit natal philopatry. However, the difference between the geographic distances separating pairs of related males ve rsus females was not statistically different, suggesting that both sexes may be dispersing similar distances from the natal territory overall. It is anticipated that the microsat ellite markers developed for this research will continue to be a useful tool for population geneti c studies on the brown-headed nut hatch. In addition, it is hoped that the information pertaining to fine-scale spatial genetic structure in the brown-headed nuthatch will provide valuable baseline info rmation for management agencies and others concerned with the conservation of this imperiled species.

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10 CHAPTER 1 INTRODUCTION The brown-headed nuthatch ( Sitta pusilla ) is a small, non-migratory cooperatively breeding passerine endemic to the pine forests of the southeastern United States. This species historically occurred throughout mu ch of Florida; however, it is now largely absent from most counties near and southeast of Lake Ok eechobee (Withgott & Smith 1998 and references therein). Increasing conserva tion awareness for this specie s arises from ongoing population declines throughout their entire range (Sauer et al. 2005). Based on these population trends, the brown-headed nuthatch has been designated a species of management concern (Carter et al. 1998). Population declines have been attributed to habitat fragmentation, loss, and degradation (Withgott & Smith 1998). Habitat alterati on, including fire suppr ession and landscape fragmentation, has caused a 97% de cline in the area of longleaf pine ecosystems, making them among the most imperiled ecosystems in the United States (Noss et al. 1995). Jackson (1988) suggested that as these forests undergo fu rther fragmentation, brown-headed nuthatch populations will continue to decline. Cooperative breeding is an unusual mating syst em in birds in which more than two individuals of a species cont ribute to raising the young (Bro wn 1987). In brown-headed nuthatches, territory groups cons ist of mature nonbreeders ("helper s-at-the-nest" or "auxiliaries") that help protect and rear th e young, but are presumably not pare nts of those offspring. In a recent study of the brown-headed nuthatch, Cox & Slater (2007) reported the percentage of territories with more than two adults averaged 10-32% among sites and y ears. The majority of groups with 2 adults consisted of a breeding pair a nd an auxiliary male which was presumably related to at least one breeding adult. Auxiliary females were less common, but some were found in their natal territories. Stacey & Ligon (1987) suggest that cooperative breeding in birds may

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11 occur when species have a limited, unusual resource that selects for offspring that remain in the natal territory near that resour ce. As such, these species may ha ve limited dispersal and require specialized habitats that make them particularly sensitive to habitat degradation (see also Walters et al. 2004). Typical of cooperatively breeding birds, l ong-distance dispersal in the brown-headed nuthatch, if it occurs at all, is likely infrequent and/or limited in range (Withgott & Smith 1998). Cox & Slater (2007) noted that breeding pairs maintain long-ter m pair bonds and frequently excavated nests within 100m of nests used th e previous year. In addition, mean dispersal distance of first-year males was generally less than two territories (<300m). Dispersal distances of females remain unknown, though typically females di sperse farther than males in birds. This limited dispersal is likely to increase the susceptib ility of this species to habitat fragmentation by reducing gene flow between populations and making it unlikely that individua ls will disperse to recolonize distant fragments upon ex tirpation (Withgott & Smith 1998). Brown-headed nuthatches have very specialized habitat requirements and rarely venture from pine-dominated forests (Withgott & Smith 1998). Preferred habitat consists of mature pine forests with open understory maintained by regular fires and retention of snags ( i.e standing dead trees) suitable for the excava tion of cavity nests. Fire suppr ession increases the invasion of hardwoods and slows the creation of snags, degr ading optimal habitat for this species (Withgott & Smith 1998). Wilson & Watts (1999) found a negative correlation between nuthatch abundance and canopy cover, hardwood density, and basal area of hardwoods. In addition, they found that nuthatches were over three times as li kely to be found in areas containing snags than those without snags. The dependence of this spec ies on pine forests with suitable understory and

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12 fire regimes may make it an excellent indicator species for the health of the limited amount of remaining southeastern pine forests (Withgott & Smith 1998). An additional factor affecting the overall status of brown-headed nuthatch populations is the reduction in effectiv e population size due to the presence of non-breeding auxiliaries at nests, especially in populations exhi biting high rates of cooperativ e breeding. Within small, fragmented populations, the restri cted number of breeding indivi duals can reduce the effective population size below the level e xpected for a typical, non-coopera tively breeding species. A reduction in effective population si ze may increase the loss of geneti c variation due to deviations from non-random mating (Sugg et al. 1996). Empirical studies in other declining species, for example the greater prairie chicken ( Tympanuchus cupido ), have demonstrated that loss of genetic variation is correlated with reduced fitness, such as reduced hatching success (Westemeier et al. 1998), which further th reatens population health. In cooperatively breeding birds where adult o ffspring remain in thei r natal territory, the opportunity for inbreeding may be substantial (McRae & Amos 1999 and references therein), which can further threaten the ge netic health of populations. In one instance, a female brownheaded nuthatch was documented assisting her parents during her first year, but was then involved in an incestuous mating th at followed the disappearance of her mother prior to the next breeding season (J. Cox, unpublished data). T hus, cooperatively breeding birds may be particularly dependent upon gene flow to ove rcome the negative genetic consequences of inbreeding. Habitat fragmenta tion may inhibit dispersal amo ng populations, especially for species with limited dispersal and extreme ha bitat specialization (Boone & Rhodes 1996), as seen in the brown-headed nuthatc h. Fragmentation may prevent su fficient gene flow to rescue

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13 populations from inbreeding depre ssion and its associated affects on fitness (Danie ls & Walters 2000). An increasing number of studies are using molecular techniques to examine patterns of genetic variation within and am ong populations of threatened sp ecies (Waser & Strobeck 1998). These types of studies can reveal the degree of relatedness among individu als within populations and the degree of genetic structure among populati ons, thereby facilitating the inference of dispersal rates. Peterson (1992) concluded that social systems with hi gh degrees of philopatry, as seen in many cooperative breeding birds, fac ilitate rapid differentia tion over short spatial scales resulting in populations th at have little within population genetic variation but are quite genetically distinct from one anot her. Low genetic variation with in populations in cooperatively breeding birds may have long-term consequences for evolutionary processes, such as an inability to adapt to environmental responses and th e onset of inbreeding depression (McDonald et al. 1999). Despite the declining status of the brown-headed nuthatch, th ere is little research on this species, including an absence of published mo lecular work, which is needed for proper management and conservation of re maining fragmented populations. My specific research objectives are: (1) To isolate and characterize polymorphic microsatellite markers for the brown-headed nuthatc h; and (2) To elucidate the fine-scale spatial genetic structure within a populati on of brown-headed nuthatches. It is anticipa ted that this research will greatly increase our knowledge of this poorly studied species of conservation interest and will also provide preliminary inform ation for conservation organizations and others interested in manageme nt of this species.

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14 CHAPTER 2 ISOLATION AND CHARACTERIZAT ION OF EIGHT POLYMORPHIC MICROSATELLITE MARKERS FOR TH E BROWN-HEADED NUTHATCH ( Sitta pusilla ) Eight highly polymorphic microsatellite loci were isolated and characterized for the brown-headed nuthatch ( Sitta pusilla ). Analysis of individuals from a single population revealed an average of 17 alleles per lo cus (range 11-24), an average observed heterozygosity of 0.69 (range 0.39-0.87) and an average polymorphic in formation content of 0.83 (range 0.66-0.94). We anticipate that these microsatellite marker s will be a useful tool for population genetic studies on the brown-headed nuthatch. The brown-headed nuthatch ( Sitta pusilla ) is a small passerine bird endemic to pine forests of the southeastern United States. This sp ecies has been undergoing significant range-wide population declines resulting fr om habitat loss, degradation, and fragmentation (Withgott & Smith 1998). The brown-headed nuthatchs c ooperative-breeding mating system, restricted dispersal, natal philopatry, and ecological specialization may incr ease susceptibility to habitat alteration, which has also been suggested fo r other cooperative-breeding birds (Walters et al 2004). Despite declining population trends, there has not been any molecular work published at this time on the brown-headed nuthatch. We deve loped these microsatellite loci to analyze the genetic mating system and population gene tic structure of this species. We constructed an enriched (CA)n microsatellite library using protocols from the University of Florida Interdisciplinary Center for Biotechnology Resear ch Molecular Markers Workshop (Brazeau & Clark 2005), some of which were modified from Kandpal et al. (1994). Genomic DNA was isolated using the PUREGENE DNA Purification Kit (Biozym, Hess. Oldendorf, Germany) from two individuals sample d at Tall Timbers Resear ch Station (TTRS) in Leon County, Florida. Approximately 5 g of genomic DNA from each individual was combined and digested with Sau 3AI restriction enzyme and size selected for fragments greater

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15 than 400bp using Chroma Spin columns (Clonetech Laboratories). Size-fractionated genomic DNA was ligated to Sau 3AI linkers. Excess linkers we re removed using Chroma Spin columns before amplification of the recombinant frag ments by Polymerase Chain Reaction (PCR) using the free linker oligonucleotide. Enrichment for (CA)n repeats was completed by hybridizing the fragments to a biotinylated (CA)15TATAAGATA probe. The biot inylated products were bound to an Avidin matrix (VECTREX Avidin D, Vector Laboratories ), allowing for the removal of fragments that did not hybridi ze to the biotinylated probe. A second PCR amplification of fragments enriched for (CA)n repeats was performed and the Phototope -Star Chemiluminescent Detection Kit (New England Biolabs) was used to test for successful selection of hybridized DNA fragments by performing a dot blot. PCR products of the enriched microsatellite library were directly ligated to a plasmid vector (pCR 2.1-TOPO vector; Invitrogen) used to transform Escherichia coli (One ShotTM TOP 10 cells, Invitrogen). Colony li fts were screened using the (CA)n probe and the chemiluminescent detection kit. Forty-five co lonies with strong hybridization signals were sequenced on an ABI 377 PRISM automated sequencer (Applied Biosystems) to confirm the presence of microsatellite -containing repeats. Primer pairs complementary to the microsat ellite-flanking sequence were designed for 24 of the 45 clones using the software package PRIMER 3 (Rozen & Skaletsky 1998). We optimized primer pairs and tested for polymorphism usi ng 10 individuals from TTRS. Among 24 primer pairs designed, eight produced consistent amplification of pol ymorphic loci. Optimized PCR conditions consisted of 1X PCR buffer (10mM Tris-HCl, 50mM KCl, 1.5mM MgCl2), 0.2 mM of each dNTP, 0.2 U Taq polymerase (New England BioLabs), 0.3 M of the forward and reverse primer, and 8 ng of genomic DNA in a 10 L reaction. Locus-specific optimized PCR

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16 conditions for the eight polymorphi c loci can be found in Table 2-1. All PCRs began with 95C (5 min); 35 cycles of 95 (60s), primer-specifi c annealing and elongation conditions (Table 2-1); and a final extension at 72C (30 min). We added a GTTT sequence to the 5 end of three primers and GT to a single primer to facili tate the non-templated addition of adenosine by Taq polymerase, commonly referred to as pigtailing (Brownstein et al. 1996). Allele sizes were determined using the MegaBACE 1000 DNA Se quencer (Amersham, Sunnyvale, CA) and raw data was analyzed using GeneMarker v.1.5 (S oftGenetics LLC, State College, PA). We genotyped approximately 20-60 indivi duals from TTRS for each of the eight polymorphic microsatellite loci using the PCR c onditions previously described. Characteristics of each primer pair are presented in Table 2. The average number of alleles per locus is 17 (range 11). Total exclusion probabilities for the first and second parent (0.999318 and 0.999982), expected and observed heterozygosities, polymorphic information content, and null allele frequency estimates were calculated using CERVUS 2.0 (Marshall et al. 1998). Deviations from Hardy-Weinberg equilibrium (HWE) and tests for linkage disequilibrium were tested using a Markov chain method provided in GENEPOP version 3.4 (Raymond & Rousset 1995). Three of the eight loci (Tab le 2-2) significantly deviated from HWE following sequential Bonferroni correction (Rice 1989). The de viation from HWE for two of the loci, Spu 36A and Spu L4-30, may reflect the small sample sizes for these highly polymorphic loci, although further testing is needed to confirm this. In addition, departures from HWE for the three loci may also indicate heterozygote deficit consis tent with the presence of null a lleles. No evidence for linkage disequilibrium (p< 0.05) was found be tween loci. Overall, these mi crosatellite loci are highly variable and should be valuable tools for studying many biological aspects of the brown-headed nuthatch.

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17 Table 2-1. PCR optimization conditions for the eight microsatellite loci developed for the brown-headed nuthatch ( Sitta pusilla ). Locus Annealing Elongation Final Mg2+ (mM) Betaine (1.25mM) Spu L5-6 60/ 40s 72/ 60s 2.5 Spu A6 65/ 10s 72/ 10s 1.5 Spu E19 66/ 40s 72/ 60s 3 Spu L4-31 66/ 40s 72/ 60s 2.5 Spu L4-3 66/ 30s 72/ 45s 3 + Spu L6-16 60/ 5s 72/ 25s 2.5 + Spu 36A 68/ 5s 72/ 45s 3 + Spu L4-30 58/ 5s 72/ 25s 2.5 +

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18Table 2-2. Characterization of eight polymorphic microsatel lite loci from the brown-headed nuthatch ( Sitta pusilla ) collected in Leon County, Florida. Locus Primer sequence (5-3) GenBank accession number Fluorescent dye Clonal repeat motif Size range (bp) n k HO HE PIC Spu L5-6 F: CTTCCTTGTGCATGGTTGAA R: TCTACTGTCCCACGGGTAAAA EF474467 HEX (GT)27 229-295 61 24 0.852 0.908 0.894 Spu A6 F: ACCTCTAGCCTTGCTTGCAG R: GCGAAGAATAGCAGGTTTGG EF474468 FAM (AC)11 190-232 51 13 0.627 0.682 0.655 Spu E19 F: TCCTGTGAGAGCAGCAAGAA R: CTGGCATCAAAGGAAAGCAT EF474469 HEX (GT)10 234-328 60 15 0.683 0.733 0.704 Spu L4-31* F: CCCCAAACCCAACTCTGTTA R: TGCATTGGTTCATTACTAGATGCT EF474470 FAM (GT)15 271-319 52 11 0.654 0.813 0.778 Spu L4-3 F: AGTCAG CACATGGAACCACA R: GTTT AAACCCAGCAAACATTCCAC EF474472 HEX (GT)27 360-406 56 19 0.786 0.869 0.850 Spu L6-16 F: AGGCTCCCTGTGTAGGTGTG R: GTTT ATCCTTCAGGTGGGTGACTG EF474473 FAM (GT)27 304-356 39 20 0.872 0.922 0.904 Spu 36A* F: ACAGAGGAAGCCACCAGAGA R: GTTT GAAGGGGCATCTCTTCTTCC EF474474 HEX (GT)33 332-412 23 22 0.391 0.962 0.938 Spu L4-30* F: ATGCACTGGGTTCCTGTGTT R: GT TTGTTCACATTGCTGGAAAGG EF474475 FAM (GT)29 262-306 27 17 0.630 0.926 0.902 Bolded bases indicate pigtail addition; ( n ), number of individuals ge notyped at each locus; ( k ), number of alleles; HO, observed heterozygosity; HE, expected heterozygosity; PIC, polymorphic information c ontent. *Indicates locus with significant deviation from Hardy-Weinberg equilibrium after Bonferroni correction.

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19 CHAPTER 3 FINE-SCALE SPATIAL GENETIC STRUCT URE IN THE BROWN-HEADED NUTHATCH ( Sitta pusilla ) Understanding patterns of spatia l genetic structure is importa nt for the management and conservation of many species. Fi ne-scale genetic structure may be found in species exhibiting restricted dispersal and natal ph ilopatry, as seen in many cooperative breeding birds. In this study, spatial autocorre lation analysis using five microsatel lite loci was performed to examine patterns of fine-scale spatial genetic st ructure in the brown-headed nuthatch ( Sitta pusilla ). The brown-headed nuthatch is a coopera tive breeding bird that is currently experi encing population declines attributed to habita t loss and fragmentation. Signifi cantly positive autocorrelation was only detected in males when auxiliary adults were included and was not found in females. Contrary to expectations, the difference between the geographic distances separating pairs of related males versus females was not statistica lly different, suggesting that both sexes may be dispersing similar distances from th e natal territory overall. This st udy is the first to describe the fine-scale spatial genetic structure in the br own-headed nuthatch and is important to the conservation and management of this declining species. Long-term mana gement efforts of the brown-headed nuthatch should consider maintaini ng adequate genetic vari ation within small, potentially isolated populations, although addition al studies are needed to further elucidate spatial genetic patterns in this species. Introduction Determining the spatial genetic structure w ithin and among populations is important for the conservation and management of many declining species (Caizergues et al. 2003; Laikre et al. 2005; Johnson & Dunn 2006). Information rega rding the genetic st ructure can provide important insights into behavior al and ecological processes including dispersal pattens, local adaptation, and the effects of landscape features on gene flow (Piertney et al. 1999; Bittner &

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20 King 2003; Manel et al. 2003). Most studies to date that have analyzed population genetic structure have focused on the landscape level, often sampling individuals from multiple populations throughout the range of a species (Castric et al. 2001; Veit et al. 2005; Eggert et al. 2006; Sonstebo et al. 2007). However, there has recently been a substantial increase in the number of studies focusing on fine-scale genetic structure ( i.e. within populations) and the underlying factors most likely generating thes e within-population spat ial patterns (Brouat et al. 2003; Peakall et al. 2003; Hazlitt et al. 2004; Comer et al 2005; Kitchen et al. 2005; Nussey et al. 2005; Zamudio & Wieczorek 2007). Assessing microgeographic spatial genetic structure within populations is useful for investigating lim ited and sex-biased disper sal, social behavior, mating systems, and barriers to gene flow within populations (Peakall et al. 2003; Double et al. 2005). Many cooperative breeding species are expected to exhibit micr ospatial genetic structuring due to restricted dispersal and high levels of natal philopatry (Walters et al. 2004; Woxvold et al. 2006), yet relatively few studies have analyzed the presence of fine-scal e genetic structure in cooperative breeding birds (although see Painter et al. 2000; Double et al. 2005; Temple et al. 2006; Woxvold et al. 2006). In addition to these charac teristics, some cooperative breeding birds also exhibit habitat speci alization and have a large numbe r of non-breeding adults that function as helpers (Walters et al. 2004). These traits may facil itate genetic structure over small geographic distances (Peakall et al. 2003; Hazlitt et al 2004; Double et al. 2005). In many cooperative breeding birds, natal philopatry is se x-biased towards males while females typically disperse over longer distances (Greenwood 1980; Koenig et al. 1992; Walters et al. 2004). Sexbiased dispersal may result in demes of relate d individuals of the phi lopatric sex (Hazlitt et al. 2004; Sugg et al. 1996). The limited number of studies th at have examined fine-scale genetic

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21 structure in cooperative breeding birds all detected microgeographi c genetic structure over small distances ( i.e. within a few territories), with more pronounc ed patterns of spatial genetic structure in the philopatric males (Painter et al. 2000; Double et al. 2005; Temple et al. 2006; Woxvold et al. 2006). In this study, I examined patterns of fine-scale spatial genetic struct ure in the cooperative breeding brown-headed nuthatch ( Sitta pusilla ). The brown-headed nuthatch is a small (~10 g), non-migratory, cavity-nesting passerine endemic to the longleaf pine ecosystems of the southeastern United States (Withgott & Smith 1998) The percentage of breeding territories containing one or more auxiliary adults has been documented to vary from 10-32% (Cox & Slater 2007). Most groups contai ning more than two adults c onsist of a breeding pair and a second-year auxiliary male who is related to at least one bree ding adult (Cox & Slater 2007). Breeding pairs maintain long-term pair bonds an d are highly sedentar y once a territory is established-frequently excavating nests within 100m of nests used the previous year (Cox & Slater 2007). Natal philopatry appears to be he avily male-biased based on field observations, although female helpers have been documented a ssisting at the natal te rritory (Cox & Slater 2007). Most dispersing second-year males establish territories with in 300m of territories held by their parents, which is generally the nearest ne ighbor to the natal terr itory (Cox & Slater 2007). On the other hand, average dispersal distance fr om the limited number of recaptured females ( n = 6) is 1240m (J. Cox, unpublished data). Increasing conservation awareness for the brow n-headed nuthatch has resulted from rangewide population declines (Sauer et al. 2005), which have been attributed to habitat loss, fragmentation, and degradation (Withgott & Smith 1998). This species possesses many of the distinctive traits seen in othe r cooperative breeding bi rds that have been suggested to increase

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22 susceptibility to habitat fragmentation (Walters et al. 2004) and generate fine-scale spatial genetic structure (Woxvold et al. 2006). Especially re levant traits for the brown-headed nuthatch include the presence of non-breedin g adults that function as help ers, extreme philopatry, limited dispersal, and ecological sp ecialization (Withgott & Smith 1998). Despite ongoing population declines in this species and the prediction that po pulations will continue to decline as pine forests become further fragmented (Jackson 1988), there is little research on the brown-headed nuthatch, including an absence of molecula r work prior to this study. Fu rthermore, it is currently unknown to what extent male-biased natal philopatry and limited dispersal promote spatial genetic structure in this species. This study combines spatial au tocorrelation procedures and hypervariable microsatellite markers to examine fine-scale patterns of genetic structure in the brow n-headed nuthatch. The use of spatial autocorrelation to elucidate microspatial ge netic structure may be especially useful for species that exhibit natal phil opatry and restricted dispersal, both of which are characteristics that may generate fine-scale non random genetic patterns (Double et al. 2005). My research objectives were (1) to determine if genetic auto correlation is affected by geographic distance, (2) to compare genetic autocorrelation between males and females, and (3) to examine the influence of auxiliary adults on genetic autocorrelation. I expected to find higher genetic autocorrelation at small geographic distances versus large di stances accompanied by a steady decrease in r due to the overall sedentary behavior and restricted dispersal described for the brown-headed nuthatch. I also predicted that males would exhibit strong er positive autocorrelation than females due to male-biased natal philopatry in the brown-headed nuthatch. Lastly, I predic ted that the inclusion of auxiliary adults would strengthen geneti c autocorrelation due to presumed relatedness between breeding and auxiliary adults.

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23 Methods Study Site Fieldwork for this study was conducted at Ta ll Timbers Research Station (TTRS) in Leon County, Florida, USA (Fig. 3-1). TTRS en compasses approximately 1,630ha dominated by upland pine habitats consisti ng primarily of loblolly ( Pinus taeda ) and shortleaf pines ( P. eichnata) ; although some of the area is not suitabl e habitat for brown-headed nuthatches ( e.g. water bodies, hardwood hammocks). The breeding activities of brown-h eaded nuthatch groups within TTRS have been monitored by J. Cox since 2001, although genetic sampling was sufficient to analyze population genetic struct ure only for 2006. Sampling of adult individuals occurred from mid-February through May 2006, although sampling was not exhaustive over the entire study area. Sample Collection A total of 70 adult individuals comprising 36 territories (~ 670 ha) were sampled during the spring of 2006. For groups containing more than two adults, behavioral observations ( e.g. dominance, incubation, and copulat ion), and in some instances banding records from previous years, were used to differentiate between br eeding and auxiliary adu lts. Individuals were captured using mist nets placed near nests, wh ich has been found to disrupt <1% of nesting attempts for this species (J. Cox, unpublished data ). All nesting locati ons were geographically referenced with Universal Tran sverse Mercator (UTM) coordi nates using a hand-held global positioning system; nest locations were assumed to represent the center of each territory. Birds were fitted with color bands and an aluminum United States Fish and Wildlife Service (USFWS) band. A blood sample (20-40 L) was taken from th e brachial vein of each bird and stored in 1mL of lysis buffer (0.1 M Tris-HCl, pH 8.0, 0.1 M EDTA, 0.01 M NaCl, 1% SDS). Genomic DNA was extracted using a PUREGENE DNA Purification Kit (B iozym, Hess. Oldendorf,

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24 Germany) and the sex of each individual was determined using the molecular sexing method described by Fridolfss on & Ellegren (1999). Microsatellite Genotyping Five polymorphic microsatellite loci developed specifically fo r the brown-headed nuthatch were used to obtain a multilocus genotype for each individual (Table 3-1). Briefly, microsatellite loci were amplified via polymerase chain reaction (PCR) in 10 L reaction volumes containing the following: 1X PCR buffer (10m M Tris-HCl, 50mM KCl, 1.5mM MgCl2), 0.2 mM of each dNTP, 0.2 U Taq polymerase (New England BioLabs), 0.3 M of the reverse and fluorescently labeled forward primer, and 8ng of genomic DNA (see Chapter 2 for further details). Magnesium concentrations varied per locus (Tab le 3-1). The PCR additive betaine (1.25 mM) was used for a single locus, Spu L4-3, to help mitigate the presence of microsatellite stutter. All PCR amplifications began with 95C (5 min); 35 cy cles of 95 (60s), pr imer-specific annealing and elongation conditions; and a final extens ion at 72C (30 min). A MegaBACE 1000 DNA Sequencer (Amersham, Sunnyvale, CA) produced raw data and allele s were sized using GeneMarker v.1.5 (SoftGenetics LLC, State College, PA). Genetic Variation Exact tests for deviations from Hardy-Weinbe rg equilibrium (HWE) and tests for linkage disequilibrium were tested using a Markov ch ain method with 5,000 iterations implemented in GENEPOP version 3.4 (Raymond & Rousset 1995) When performing multiple comparisons, sequential Bonferroni corrections were used to reduce global T ype I error (Rice 1989). Average number of alleles, observed and expected he terozygosity, mean proportion of individuals genotyped, and tests for null alleles were calculated us ing CERVUS 2.0 (Marshall et al. 1998).

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25 Spatial Autocorrelation To examine fine-scale genetic structur e in the brown-headed nuthatch, spatial autocorrelation analysis was performed using GenAlEx, version 6 (Peakall & Smouse 2006) to describe the genetic structure over the entire study area. Unlike classical spatial autocorrelation analysis, which is implemented one locus at a tim e, GenAlEx6 uses a multivariate approach that strengthens the spatial signal by reducing random (locus to lo cus) noise (Smouse & Peakall 1999). The program generates an autocorrelation coefficient r which provides a measurement of the pairwise genetic similarity of individua ls whose geographic separation falls within a specified distance class. Individu als were classified into four ca tegories: (1) All Individuals; (2) All Males (includes auxiliary males); (3) Do minant Males (breeding males only); and (4) Females. Spatial autocorrelation was pe rformed using automatically increasing geographic distance classes for a given user-specified base distance class. This method uses a cumulative sampling strategy so that each subsequent distance inte rval includes all pair wise comparisons from previous intervals. I specified a base distance class size of 100m for 15 runs so that the first distance interval would calculate r based on all pairwise comparis ons within a distance of 0100m, the second analysis for 0-200m, and so on until the last run ( i.e. 0-1500m) was completed. This base distance class was chosen because 4 of the 36 (11%) territories used in this study had a sampled nearest neighboring territory 100m. Anal yses were also performed using a 200m base distance class because previous research on the brown-headed nuthatch reported that the average distance between nearest neighbo ring territories at TTRS was 198.5m (SD = 90.7) (Cox & Slater 2007). Statistical significance was tested in GenAlEx6 using random permutation of r Permutation was repeated 1000 times to generate the 25th and 975th values used to define the

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26 95% confidence intervals around the null hypothesis of r = 0. Significant spatial genetic structuring was declared when r exceeded the 95% confidence intervals. The autocorrelation coefficients were plotted as a function of ge ographic distance and visu alized graphically in spatial genetic autocorrelograms. Relatedness by Distance In addition to spatial autocorrelation, I also used another approach to further investigate fine-scale spatial genetic struct ure of brown-headed nuthatches. This was performed because sampling of territories at the st udy site was not exhaustive and sp atial autocorrelation procedures, which only analyze individuals fall ing within user-specified distan ce classes, may not capture the true spatial genetic structure. I us ed the program ML-R ELATE (Kalinowski et al. 2006) to calculate maximum likelihood estimates of relatedness ( r ) (see Blouin 2003 for a review) for all pairwise comparisons for Dominant Males and Females separately. Although autocorrelation coefficients such as r are closely correlated with estimates of relatedness (Bank et al. 2005), they are not a direct estimate of genealogical relationships among individuals (Temple et al. 2006). Pairs of individuals within each sex exhibiting r -values greater than or equal to 0.50 were selected and the geographic distan ces separating these individuals we re recorded. The statistical software R (R Development Core Team 2005) was used to perform a 1-tailed Wilcoxon rank sum test between these distances to assess whet her a statistically significant difference existed between the average distance sepa rating related males versus related females. In addition, Microsoft Excel was used to perform an F-test to determine whether a statistically significant difference existed between the variances in male and female distances.

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27 Results Genetic Variation I sampled individuals from 36 territories: a br eeding male and female were obtained for 20 territories; a breeding pair and a single male he lper were obtained for 5 territories; a breeding pair and two male helpers were obtained for 1 territory; a single female was obtained for 7 territories; a single male was obtained for 3 territ ories; and both a dominant and auxiliary male were obtained for a single territo ry. Molecular sexing confirmed th at all 8 auxiliary adults were males. There were prior field da ta for only three of the auxiliary adults, which revealed that all three helpers were banded the previous year as nestlings at the nest of the male they were currently helping when sampled. This suggests th at these three individuals are offspring of the breeding male in which they were assisting, alth ough formal parentage analysis is needed to confirm this. Table 3-1 describes the five micr osatellite loci used in this study, all of which exhibited high levels of polymorphism (average obser ved heterozygosity = 0.7146). A single locus ( Spu L4-31) significantly deviated fr om HWE, which may be due to the presence of null alleles (null frequency estimate = 0.1033). None of the other loci showed evid ence for null alleles. Linkage disequilibrium was not dete cted for any of the loci (P> 0.01). The number of alleles per locus ranged from 11-24, with an average of 16 alleles per locus. The mean proportion of individuals that were genot yped at all five loci was 0.929. Reasons for missing genotypes include repeated PCR failure and ambiguous micr osatellite products due to the presence of stutter bands. Spatial Autocorrelation Spatial autocorrelation analysis detected the predicted pattern of higher genetic autocorrelation at small geographic dist ances followed by a steady decrease in r for All Males

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28 (Fig. 3-2 B), although no other sampling category re vealed this pattern (Fig. 3-2). However, a weaker, albeit non-significant, pattern was found in the All Individuals analysis (Fig. 3-2 A), which also includes auxiliary adults. These resu lts suggest that increas ing geographic distance does affect the spatial signal of fine-scale genetic structure in brown-headed nuthatches and that the presence of auxiliary males increases the strength of positive genetic autocorrelation at small distances. Contrary to expectations, the predicted pattern was not seen in Dominant Males (Fig. 3-2 C), despite male-biased natal philopatr y in this species. Interestingly, Females exhibited negative r -values at the two smallest distance intervals, whereas Dominant Males revealed positive values. Although these results are not stat istically significant, they suggest that females may be less related at smaller distances than ar e males, which is supported once auxiliary males are included in the analyses. The autocorrelation analysis for All Males revealed significant positive genetic autocorrelation until approximate ly 1300m. Similar results for all categories were seen when analyses were performed using the 200m base distance class (results not shown). Relatedness by Distance A total of 19 pairwise comparisons for ma les and 31 pairwise comparisons for females exhibited maximum likelihood estimates of rela tedness greater than or equal to 0.50. The average geographic distance between pairs of selected males was 1,585m (range = 193-2423m) and for females was 1,780m (range = 192-3799m). The 1-tailed Wilcoxon rank sum test returned a p-value of 0.393, suggesting that there is not a statistically signifi cant difference in the geographic distances separating re lated males and females provided the dataset used in this study. In addition, there was s ubstantial overlap in the 95% upper and lower confidence intervals around the average for males and female s, thereby revealing a weak effect size and possible lack of biological signif icance (Fig. 3-3). The F-test re veled that the variances in the distances separating pairs of related males and fe males were not statistica lly different (p=0.338).

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29 Discussion Prior field data for the brown-headed nuthatch show that males exhibit high rates of natal philopatry and typically disperse over very shor t distances (Cox & Slater 2007). In contrast, females have been documented less frequently as helpers and are thought to disperse much larger distances than males (Cox & Slat er 2007). This pattern of se x-biased dispersal would be expected to generate microspati al genetic structure among males with little or no pattern in females (Peakall et al. 2003). The spatial autocorrelation analyses presented in this study revealed that all males exhibited significantly positive genetic autocorrelation at small distances, whereas significance was not detected in females. However, significance in males was attributed to the inclusion of helping indi viduals, which are rare in fema les (J. Cox, unpublished data) and were not included in this st udy. Other studies on cooperative breeding birds also detected stronger positive genetic autocorrelation when aux iliary adults were included in the analyses (Double et al. 2005; Temple et al. 2006). Upon exclusion of auxi liary adults however, spatial autocorrelation did not detect significance in male s, which is in contrast to field observations documenting shorter dispersal distances in males (Cox & Slater 2007). In spatial autocorrelation, the distance class size at which r is no longer significantly positive approximates the extent of detectable positive genetic structure (Peakall et al. 2003). This distance is similar to the genetic neighborhood size of a population (Wright 1943; Golenberg 1987). In this study, autocorrelation revealed significa ntly positive genetic structure among all males extending beyond six average territory widths ( i.e. 1300m). Based on field observations of the brown-headed nuthatch, C ox & Slater (2007) reported that the average dispersal distance for second-year males dispersing equal to or gr eater than two te rritories away from the natal territory was 1,358m. Interestingl y, results from both spatial autocorrelation and

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30 field observations suggest that the average distance of gene flow ( i.e. genetic neighborhood size) in male brown-headed nuthatches is approximately 1300m. The analyses performed using maximum likelih ood estimates of relatedness suggest that the average distance separating related dominant males was approximately 1,600m, which is only slightly higher ( i.e. 300m) than the estimates obtained fr om mark-recapture data and spatial autocorrelation for all males ( i.e. helpers included). Although th e autocorrelation procedure did not detect significance in dominant males, this approach includes all individuals within a userspecified distance class, which may or may not be related. On the other hand, the relatedness by distance analysis disregards di stance classes and only looks at those pairs of individuals exhibiting high levels of relatedness and then de termines the geographic distance separating that particular pair. Despite the di fferent approaches of these two procedures, both analyses suggest that many male brown-headed nuthatches exhib it high leves of relatedness within a 1-2km geographic distance in terval, which closely approximates the previous estimate of Cox & Slater (2007). Contrary to expectations, the average dist ance separating related females was only about 200m greater than for dominant males. This finding contradicts the assumption that males disperse significantly shorter distances than females; however, the range of dispersal distances in the dataset for both sexes suggests that at least some females may be dispersing larger distances than males ( i.e >1km). Interestingly, there was a gr eater number of pairwise comparisons of females (n=31) than males (n=19) that showed a relatedness estimate greater than or equal to 0.50. Tenable biological conclusions cannot be made from this finding because territory sampling was incomplete at the study site; however this data suggest th at females may not be

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31 dispersing substantially larger distances than males as previously thought, although additional studies are needed to validate the findings in this study. Populations undergoing restricted gene flow and an absence of selection are expected to be characterized by positive spatia l genetic autocorrelation at small distances, subsequently declining through zero and b ecoming negative (Peakall et al. 2003). I predicted that spatial autocorrelation would be higher at small geogr aphic distances accompanied by a steady decrease in r due to the restricted dispersa l and overall sedentary lifestyle described for the brown-headed nuthatch (Withgott & Smith 1998). However, si gnificance for this pattern was only found in All Males although it was also observed, albeit non-significant, in All Individuals Both of these sampling categories included male helpers, which further illustrates the impact that auxiliary males have on generating positive genetic autocorrelation at small distances in the brown-headed nuthatch. Other studies employing spatial auto correlation on cooperative breeding birds did however find the predicted pattern for all individuals (Double et al. 2005; Temple et al. 2006), although these studies were based on larger sample sizes. The information presented in this paper provi des the first genetic study on brown-headed nuthatches and indicates that gene tics needs to be considered in conservation and management decisions. The results suggest that cooperative breeding and the retenti on of putatively related auxiliary adults on the natal territory may facilitat e high levels of relatedness at small geographic distances. However, a recent study reported th at only 10-32% of groups exhibit cooperative breeding in the brown-headed nut hatch (Cox & Slater 2007 ); thus, philopatric offspring may not have a large overall effect on fine -scale spatial genetic structure in this species, as suggested by the autocorrelation analyses pe rformed on dominant males only ( i.e. those without helpers).

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32 The relatedness by distance analyses suggest that both sexes may be dispersing small distances on average ( i.e <2km), although this study was limited to a single study site and is therefore unable to assess longdistance dispersal. Nonetheless, if males are dispersing shorter distances than females, then populations of th e brown-headed nuthatch may be particularly dependent upon female-mediated gene flow for the introduction of novel alleles and maintenance of genetic variation within popula tions. If both sexes are disper sing only limited distances, as has been suggested elsewhere (Withgott & Smith 1998), then populations of the brown-headed nuthatch may require habitat corridors ( e.g. pine plantations) to facilitate among-population dispersal in fragmented landscap es. Limited dispersal combined with sociality and ecological specialization, as seen in the brown-headed nutha tch, has been suggested to increase sensitivity to habitat fragmentation (Henle et al. 2004). Moreover, habitat frag mentation has already been documented to restrict dispersal in some other cooperative breeding spec ies that also exhibit limited dispersal (Bre ininger 1999; Cooper & Walters 2002). Restricted dispersal can reduce gene flow bot h within and among populations and lead to increased levels of relatedne ss within populations (Painter et al. 2000). Increased relatedness among social groups may increase the occurrence of inbreeding, which may be a particular concern in cooperative breeders where dispersal distances are usually short and relatedness is typically high (Koenig & Haydock 2004). Although inbreeding has been s hown to reduce fitness in some cooperative breeding birds (Brown & Brown 1998; Daniels & Walte rs 2000), incest has been documented only twice in the brown-headed nutha tch (Fleetwood 1946; J. Cox, unpublished data). On the other hand, the analyses in this study revealed that many individuals exhibited high pairwise relate dness with members of the same sex over small geographic distances. In light of this fi nding, long-term management effort s of the brown-headed nuthatch

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33 should consider maintaining sufficient genetic variation within small, potentially isolated populations. In conclusion, this study provided a preliminar y assessment of spatial genetic structure in the brown-headed nuthatch. Follow-up studies are needed that combine additional genetic and demographic information to enable a better understanding of the complex interplay between demography and spatial genetic structure in this declining species. In addition, further research is needed to elucidate the genetic mating syst em of this cooperative breeding bird, and also needed are studies that analy ze the population genetic structure among populations to examine dispersal patterns at the landscape level. The latter will be esp ecially important for management and conservation of the brown-headed nuthatch given the prediction that populations of this species will continue to become further isolated and fragmented as habita t destruction continues (Jackson 1988).

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34 A B Figure 3-1. Maps showing the sampling site used in this study. A) Leon County, Florida, USA, which is where Tall Timbers Research St ation (TTRS) is located (30.66 N, 84.22 W). B) + denotes individual territory locations ( n = 36) at TTRS that were used in this study.

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35 A All Individuals-0.060 -0.040 -0.020 0.000 0.020 0.040 0.0600 to 100 0 to 200 0 to 300 0 to 400 0 to 500 0 to 600 0 to 700 0 to 800 0 to 900 0 to 1000 0 to 1100 0 to 1200 0 to 1300 0 to 1400 0 to 1500Distance (m)Genetic correlation ( r ) r U L B All Males-0.150 -0.100 -0.050 0.000 0.050 0.100 0.150 0.200 0 to 100 0 to 200 0 to 300 0 to 400 0 to 500 0 to 600 0 to 700 0 to 800 0 to 900 0 to 1000 0 to 1100 0 to 1200 0 to 1300 0 to 1400 0 to 1500Distance (m)Genetic correlation ( r ) r U L

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36 C Dominant Males-0.300 -0.200 -0.100 0.000 0.100 0.200 0.3000 to 100 0 to 200 0 to 300 0 to 400 0 to 500 0 to 600 0 to 700 0 to 800 0 to 900 0 to 1000 0 to 1100 0 to 1200 0 to 1300 0 to 1400 0 to 1500Distance (m)Genetic correlation ( r ) r U L D Females-0.300 -0.200 -0.100 0.000 0.100 0.200 0.3000 to 100 0 to 200 0 to 300 0 to 400 0 to 500 0 to 600 0 to 700 0 to 800 0 to 900 0 to 1000 0 to 1100 0 to 1200 0 to 1300 0 to 1400 0 to 1500Distance (m)Genetic correlation ( r ) r U L Figure 3-2. Graph showing the influence of different class sizes on genetic autocorrelation. The permuted 95% confidence interv al (red lines) is shown. A) All Individuals ( n = 70). B) All males ( n = 37). C) Dominant Males ( n = 29). D) Females ( n = 33).

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37 Figure 3-3. Graph showing the av erage geographic distance in mete rs separating pairs of males and females (nfemales=31; nmales=19) from TTRS that exhibit maximum likelihood estimates of relatedness equal to or great er than 0.50. Bars represent the 95% upper and lower confidence intervals around the mean.

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38Table 3-1. Characterization of five polymorphic microsatellite lo ci used in this study. These data are from the 70 individual s sampled from TTRS during the spring of 2006. ( n ), number of individuals genotyped at each locus; ( k ), number of alleles at each locus; HO, observed heterozygosity; HE, expected heterozygosity. Indicates locus with signi ficant deviation from Hardy-Weinberg equilib rium after sequential Bonferroni correc tion. Locus Repeat Motif Size range (bp) GenBank accession number (primers) Final Mg2+(mM) n k HO HE Spu L5-6 (GT)27 229-295 EF474467 2.5 69 24 0.841 0.910 Spu L4-31* (GT)15 271-319 EF474470 2.5 60 11 0.667 0.825 Spu E19 (GT)10 234-328 EF474469 3.0 68 15 0.706 0.745 Spu A6 (AC)11 190-232 EF474468 64 13 0.625 0.684 Spu L4-3 (GT)27 360-406 EF474472 3.0 64 20 0.734 0.877

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39 CHAPTER 4 CONCLUSIONS The brown-headed nuthatch exhibits distinctiv e traits typical of ma ny cooperative breeding birds including limited dispersa l, natal philopatry, and habitat specialization (Walters et al. 2004). It has been suggested that these char acteristics may render cooperative breeding species unusually vulnerable to habitat loss, de gradation, and fragmentation (Walters et al. 2004). In addition, many cooperatively breedi ng species are expected to e xhibit microspatial structuring due to restricted dispersal and natal philopatry, ye t relatively few studies to date have analyzed fine-scale genetic structure in cooperative breedi ng birds (Double et al. 2005; Temple et al. 2006; Woxvold et al. 2006). For my thesis research, I c onstructed species-sp ecific polymorphic microsatellite markers to examine patterns of fi ne-scale spatial genetic structure in the brownheaded nuthatch. There is no published genetic data for the br own-headed nuthatch pr ior to the research presented in this thesis. The fi rst portion of my thesis research consisted of developing eight microsatellite loci specific to the brown-head ed nuthatch in order to subsequently analyze population genetic structure in th is species (Chapter 2). All eight microsatellite markers exhibited extremely high levels of polymorphism (Table 2-2), though only five could be scored consistently enough to be used to examine fine-scale spatial genetic structuring. For the second part of my thesis research, I used the microsatellite markers to examine patterns of microspatial genetic structure in the brown-headed nuthatch (Chapter 3). As predicted based on male-biased nata l philopatry in this species, genetic autocorrelation was more pronounced in males versus females, and became ev en stronger when male auxiliary individuals were included. These results are similar to the few other studies th at have used spatial autocorrelation to examine fine-scale spatial genetic structure in c ooperative breeding birds

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40 (Double et al. 2005; Temple et al. 2006). Although formal kinship analyses using genetics have not been conducted, the results in this study were attributed to putative relate dness between the auxiliary males and the breeding males in whic h they were assisting. Overall, the spatial autocorrelation results were not as strong as expe cted, but nonetheless revealed that fine-scale spatial genetic structure exists in the brown-headed nuthatch. Follow-up studies on the brown-headed nuthatc h are needed to address many additional aspects of this species biology. Included are further studies employing spatial autocorrelation, but with larger sample sizes and all eight mi crosatellite markers. Ongoing collection of demographic data on brown-headed nuthatches from th e study site used in this research is needed for additional spatial autocorrelation studies in order to allow a better understanding of the complex interplay between demography and spatial ge netic structure. In addition, future studies are also needed to examine the genetic mating sy stem of the brown-head ed nuthatch. Knowing whether breeding pairs are strictly monogamous or if extra-pair fertiliz ations are occurring will help to further understand spatial genetic stru cture in this cooperat ive breeding species.

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41 LIST OF REFERENCES Banks SC, Lindenmayer DB, Ward SJ, Taylor AC (2005) The effects of habitat fragmentation via forestry plantation establishment on spatia l genotypic structure in the small marsupial carnivore, Antechinus agilis Molecular Ecology 14 1667-1680. Bittner TD, King RB (2003) Gene flow and melanism in garter snak es revisited: a comparison of molecular markers and island vs. coalescent models. Biological Journal of the Linnean Society 79 389-399. Blouin MS (2003) DNA-based methods for pedigr ee reconstruction and kinship analysis in natural populations. Trends in Ecology and Evolution 18 503-511. Boone MD, Rhodes OEJ (1996) Genetic structur e among subpopulations of the Eastern Wild Turkey ( Meleagris gallopavo silverestris ). American Midland Naturalist 135 168-171. Brazeau D, Clark AM (2005) Molecular Markers: Tools for D eveloping Enriched Microsatellite Libraries ICBR, University of Florida, Gainesville, FL. Breininger DR (1999) Florida scru b-jab demography and dispersal in a fragmented landscape. Auk 116 520-527. Brouat C, Sennedot F, Audiot P, Leblois R, Rasplus J-Y (2003) Fi ne-scale genetic structure of two carabid species with contrasted levels of habi tat specialization. Molecular Ecology 12 1731-1745. Brown JL (1987) Helping and communal breeding in birds: ecology and evolution. Princeton University Press, Princeton, N.J Brown JL, Brown ER (1998) Are inbred offspring less fit? Survival in a natural population of Mexican jays. Behavioral Ecology 9 60-63. Brownstein MJ, Carpenter JD, Smith JR ( 1996) Modulation of nontemplated nucleotide addition by Taq polymerase: primer modifications that facilitate genotyping. Biotechniques 20 1004-1010. Caizergues A, Ratti O, Helle P, Rotelli L, El lison L, Rasplus J-Y (2003) Population genetic structure of male black grouse ( Tetrao tetrix L.) in fragmented vs. continuous landscapes. Molecular Ecology 12 2297-2305. Carter M, Hunter C, Pashley D, Petit D (1998) The watch list. Bird Conservation Summer 1998:10. Castric V, Bonney F, Bernatchez L (2001) Landscape structure and hierarchical genetic diversity in the brook char, Salvelinus fontinalis Evolution 55 1016-1028.

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46 BIOGRAPHICAL SKETCH Sarah Haas was born and raised in Corpus Chri sti, Texas. In May of 2004, she received a Bachelor of Science degree, magna cum laude in biology with a minor in chemistry from Texas State University in San Marcos, Texas. In A ugust of 2004, Sarah began graduate school in the Zoology Department at the University of Flor ida working under the supervision of Dr. Rebecca Kimball and Dr. Edward Braun. Sarahs thesis research was on the population genetics of the cooperative breeding brown-headed nuthatch ( Sitta pusilla ). In addition, Sarah was the lead investigator in a conservation genetics project on the Florida snail kite ( R.s.plumbeus ). After graduation, Sarah moved to Washington D.C. to spend some time working in environmental policy and other human-dimension aspects of conserva tion because of her desire to participate in threatened and endangered species conservation while also being actively involved with public outreach and education on environmental issues.