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© 2014
TARA B. BUK
ALL RIGHTS RESERVED
1
GENE FLOW PATTERNS OF THE FIVE LINED SKINK
EUMECES FASCIATUS IN THE FRAGMENTED
LANDSCAPE OF NORTHEAST OHIO
A Thesis Presentation Presented
to the Graduate Faculty
at the University of Akron.
In Partial Fulfillment of the Requirements
for the degree of Master of Science
By: Tara B. Buk
May 2014
2
GENE FLOW PATTERNS OF THE FIVE LINED SKINK (EUMECES FASCIATUS) IN THE
FRAGMENTED LANDSCAPE OF NORTHEAST
Tara B. Buk
Thesis
Approved:
Accepted:
Advisor
Dr. Francisco Moore
Dean of the College
Dr. Chand Midha
Co-Advisor or Faculty Reader
Dr. Randall Mitchell
Dean of the Graduate School
Dr. George Newkome
Department Chair
Dr. Rich Londraville
Date
ii
TABLE OF CONTENTS
Page
LIST OF FIGURES………………………………………………………………….v
LIST OF TABLES…………………………………………………………………..vi
ABSTRACT…………………………………………………………………………1
CHAPTERS
I.
INTRODUCTION……………………………………………………….2
II.
METHODS………………………………………………………………7
Study System………………………………………………………...7
Population Sampling…………………………………………………7
Genotyping…………………………………………………………..9
Statistical Analysis…………………………………………………..9
III.
RESULTS……………………………………………………………….11
Fit…………………………………………………………………….11
Fis…………………………………………………………………….11
Fst…………………………………………………………………….11
Isolation by Distance………………………………………………...11
IV.
DISCUSSION…………………………………………………………...16
Regional Population Structure……………………………………….16
Local Population Structure…………………………………………..17
Broader Implications…………………………………………………18
iii
LIST OF FIGURES
Figure
1
2
3
Page
Distribution Map ............................................................................................................. 6
Isolation by Distance......................................................................................................15
Isolation by Distance Independent ................................................................................ 15
iv
LIST OF TABLES
TABLE
1
2
3
4
Page
Populations name, county, sample size, GPS coordinates, and FIS values.............5
Locus name, number of alleles, FIT, FIS, and FST values ......................................13
Matrix of pairwise geographical distances and FST values .................................. 14
Matrix of pairwise Nm values…………………………………………………....14
v
ABSTRACT
A major obstacle to the preservation of animal populations is habitat fragmentation.
Fragmentation often results in the isolation and subsequent loss of subpopulations.
Gene flow determines the extent to which populations remain separated as independent
evolutionary units, and thus affects the evolution of a species. Gene flow between small
fragmented subpopulations can often have great effects on the species stability. If small
populations are lost and there is no migration between subpopulations, recolonization
of suitable habitat does not occur and the overall population declines. The loss of
naturally occurring populations reduces gene flow, which may lead to genetic
differentiation. This study investigated the population structure of the five-lined skink,
Eumeces fasciatus, occupying what appear to be isolated sites in the fragmented
landscape of Northeast Ohio. Populations in Akron were of particular interest because
they exist in highly urbanized locales, and these lizards have rarely been recorded in
Summit County. Additionally, there is a large gap in distribution record of the species
statewide. Five polymorphic microsatellite markers were used to evaluate the gene flow
between 5 different locations in Northeast Ohio. The gene flow estimates indicated that
there is a significant pattern of isolation by distance (IBD). However, even across very
broad geographical scales (170km), the IBD did not lead to a consequential divergence
of populations. This data offers information on the genetic divergence of this species
and contributes to our understanding of the larger problem of animal conservation in
urban areas, as well as its relation to anthropogenic habitat fragmentation and
degradation.
1
CHAPTER I
INTRODUCTION
Population connectivity plays a crucial role in species survivability, particularly in areas
affected by habitat degradation and fragmentation. Considering the continual rise in
anthropogenic fragmentation, it is not surprising that understanding population
connectivity has become primary goal of conservation ecology. In particular, studies that
investigate gene flow between subpopulations are needed to determine whether
populations are isolated, or part of the connected metapopulation that is capable of
recolonization.
Previous research indicates that reptiles frequently exist in a matrix of connected
subpopulations, or metapopulations (Joyal 2001, Pianka 1996, Sarre 1995, Templeton
2011). Dispersal between subpopulations is needed for the persistence of the regional
metapopulation and thus plays a fundamental role in population dynamics. However,
directly measuring dispersal of individuals has proven to be fairly difficult and fails to
reflect the reproductive success of migrants that determines their influence on a
population’s persistence. Measurement of the gene flow between populations is a simpler
and more useful way to infer dispersal rates, probability of recolonization, and thus
regional connectivity within the metapopulation (Howes 2006). Gene flow is directly
2
relevant to population connectivity because gene flow data can be used to interpret
reproductive success of migrants between populations rather than just movement of
individuals.
Understanding rates of gene flow between fragmented populations can help
recognize populations under threat, and clarify the degree to which loss of local
populations reduce overall genetic diversity within the taxon. Management of endangered
groups therefore needs to treat most populations separately because of their genetic
distinctiveness and low rates of genetic exchange (Dubey 2010). Differences in dispersal
among subpopulations contribute to genetic differentiation; genetic patterns can then
serve as a signal of disruptions in regional population connectivity due to the effect of
demographic alterations. Isolated subpopulations may be subject to increased risk of local
extinction (Frankham 2005).
Landscape-level processes on the population biology of reptiles are critical,
especially for species inhabiting anthropogenically modified landscapes (Purrenhage
2009). Many studies have clearly shown that gene flow between populations is often
affected by anthropogenic habitat change causing patch isolation. This type of
relationship is referred to as Isolation By Distance (IBD). IBD focuses on the genetic
effect of geographic isolation among patches, that is to say, it focuses on the general
landscape rather than the state of the habitat patches directly. Other factors can combine
with IBD to determine the ultimate genetic structure of a population (Hoffman 2004).
The focus this study is on urbanization effects rather than glacial advance and retreat as
in previous studies. Geologic changes such as glacial advance may alter the population
structure of animals but they are a relatively slow process. This study focuses on
3
anthropogenic habitat change that has occurred over a short period of time. A previous
study using mtDNA showed that phylogeographic patterns for E. fasciatus were related to
divergence that predates the Pleistocene (Howes, 2006). There are no studies on this
species that explore the impacts of urbanization in the last century.
Little is known about the population dynamics of Eumeces fasciatus in the
fragmented landscape of Northeast Ohio. Although the species had not been recorded in
Summit County in the last 5 decades, a seemingly robust population of this species has
recently been located in the city of Akron. Consequently, this species offers us an
opportunity to investigate the current gene flow between populations that may have been
isolated due to habitat fragmentation. In order to better understand the viability of the
species in this region we must understand the dispersal between subpopulations. Here we
run a genetic analysis on five E. fasciatus subpopulations in Northern Ohio using nuclear
DNA microsatellite data to determine gene flow. Because gene flow is an indicator of
connectivity between subpopulations, it allows us to infer the probability of
recolonization. This study helps determine if the Akron populations are connected both
within the city and across the region.
4
Table 1: Populations name, county, sample size (N), GPS coordinates, and FIS values.
FIS was significantly greater than zero in every population, using a randomization test
with 25,000 randomizations for each of the sampled Eumeces fasciatus breeding
populations. (P-value for FIS within samples. based on: 25000 randomizations. Indicative
adjusted nominal level (5%) for one table is: 0.002)
Population Name
Ashtabula
PineBrook
Sandusky
Tow Path
Stairs
TP&S combined
County
Ashtabula
Geauga
Erie
Summit
Summit
Summit
N
13
15
17
20
18
38
Coordinates
FIS
41.748987,-80.8434678
41.54003,-81.09692
41.40332,-82.81686
41.0912309,-81.5183279
41.085054,-81.52481
0.174
0.201
0.209
0.283
0.286
0.299
5
P-value
0.005
0.001
0.001
0.000
0.000
0.000
Figure 1: Distribution Map of E.fasciatus populations samples for this study
6
CHAPTER II
METHODS
Study system
Five-lined skinks are small to medium size lizards growing to about 12.5 cm to
21.5 cm total in length. Young five-lined Skinks are dark brown to black with five
distinctive white to yellow stripes running along the body and a bright blue tail. In
females, the blue color fades to a light blue with age, and the stripes may also slowly
disappear. As they age, both sexes become uniformly brown, with the exception of a
red throat and cheeks in males. Eggs are laid between May and July. Females exhibit
a high level of maternal care during gestation which typically lasts between 25 and55
days.
Population sampling
In order to study patterns of movement in this reptile species, capture, marking
and sampling is necessary. Tissue samples are required for this genetic study. In order
to cause as little harm to the animal as possible toe clipping is the preferred method.
Toe clipping is recommended because it is minimally invasive, marks the animal,
provides a tissue sample, and because normal toe loss is high enough in these lizard
populations to suggest that little or no permanent harm is caused to the animal
(Clemann et al. 2007, Beaupre et al. 2004). This method is preferable to a blood draw
because a blood draw requires equal trauma and the individual to be taken back to lab
rather than being done directly on site.
7
A local anesthesia was used since the relatively unpredictable and potentially
delayed response to immobilants or anesthetics contra indicate their use under this type
of field use (Beaupre et al. 2004). Specifically, inability to behavioral thermoregulation
and risk of predation would create a high mortality risk. Overnight holding needed for
general anesthesia presents additional risks because it causes unnecessary stress and
increased mortality (Beaupre et al. 2004).
This study was conducted in an area spanning 4500 km² in northeastern Ohio.
The sampling areas are located in a landscape fragmented by roads, agriculture, urban
areas, and private residences. We investigated 5 study populations located in four
counties (Table 1). Ashtabula habitat is an open field used by locals for four wheeling
and dirt biking that runs parallel to the Western Reserve Greenway, a 43 mile bike trail.
It was a dry area with little to no tree cover. The Geauga habitat is a pristine reservation
containing established upland woods, lowland woods, marsh habitats, and several ponds.
The Sandusky habitat is a public wetland wildlife area with ponds totaling more than
400 acres of water as well as large remnant prairie. The Towpath is part of an 84 mile
trail that runs parallel to the little Cuyahoga River and follows a historic trail from the
1800’s. The Stairs habitat is highly urbanized area on a historic set of steps built in the
early 1900’s surrounded by roadways on all sides of the patch.
Sampling was conducted from late spring to late summer. Sites were first
surveyed and identified in the first hours after sunrise. Lizards are easier to find when
they are basking, however more difficult to capture. After population locations were
established sampling was initiated. Individuals were hand-captured, generally on warm
8
days with high precipitation. Collection did not occur unless at least 10 tissue samples
could be taken since we considered five animals to be the minimum required for
analysis. No more than 20 samples were taken from any site, as previous work indicated
that thissample size is adequate to provide statistical detection of even low levels of
gene flow (Purrenhage et al. 2009).
Genotyping
We genotyped 83 individuals at five microsatellite loci: EuFa1, EuFa7, Eufa15,
Eufa21, Eufa27 (Howes 2004). Total DNA was extracted using the E.Z.N.A Tissue
DNA extraction kit (Omega Bio-tech) following manufacturer’s instructions, and stored
at 20°C. DNA extracts (diluted to 100 ng/μL) were used for the amplification of the
microsatellite markers (Purrenhage 2009). We used combined hot start and touchdown
polymerase chain reaction (PCR) conditions for all loci , as follows: 94°C, 2 minutes
followed by 10 cycles of +94°C, 30 minutes; annealing temperature step-downs every
cycle of 1°C (from 65°C to +55°C); +72°C, 1 minute. The annealing temperature for the
final 25 cycles was +55°C with denaturation and extension phases as previously stated.
Alleles were then scored using Peak Scanner Software (Applied Biosystems) with a size
standard of GS500LIZ-3130.
Statistical analysis
F-statistics were generated with the computer program Fstat version 2.9.3.
(Goudet 2001). F-statistics are used to investigate different levels of population
structure. Bootstrapping generated 95% confidence limits for all F-statistics. We were
particularly interested in FIT, FIS, and FST. FIT is the inbreeding coefficient of an
individual relative to the total. FIS is the inbreeding coefficient of an individual relative
9
to the subpopulation.FIS is used as a measure of inbreeding within populations. A FIS of 0
indicates the populations are in hardy-weinburg equilibrium. Theoretically the closer FIS
is to 1 the more inbreeding is occurring. FST is the effect of subpopulations compared to
the total population. We quantified genetic differentiation between populations by using
pairwise FST based on allele frequencies. We then used FST to calculate gene flow (Nm).
Measuring dispersal of individuals directly is difficult with such an elusive species. For
this reason we used Nm estimates rather than inferring individual migration rates. Nm
was calculated from the level of genetic differentiation, FST, with the equation Nm=((1Fst)-1)÷4. We used Nei's estimation of heterozygosity to determine heterozygosity at
each loci.
Microsatellite markers must be polymorphic in order to determine diversity
between populations. Allelic Richness per locus and population was quantified and the
markers were indeed polymorphic, the number of alleles present at each locus ranged
from five to 15. To evaluate isolation-by-distance over populations, the correlation
between the linear FST estimates, which is measured as FST / (1 – FST), and the natural log
of geographic distances was tested by using Mantel’s test (10,000 permutations) with
Passage2.
10
CHAPTER III
RESULTS
FIT
Combining data across all loci, a significant deviation (Bootstrap p<.05) from
Hardy Weinberg equilibrium was found across the populations with an FIT = 0.317
(Table 2).
FIS
Inbreeding (FIS values significantly greater than zero) was found in all 5
populations. FIS values per population ranged from ranged from 0.174 to 0.286 with
an average of 0.237 (Table 1). The two highest FIS values are seen in the two Summit
county. When Summit Stairs population was combined with the Summit Towpath
population FIS increased to 0.299. This maybe expected due location of the two
Summit county populations.
FST
Significant differentiation of demes were found between all pairwise
comparisons between demes (Table 3). FST estimates ranged from 0.025 to 0.1655 with a
significant overall FST of 0.097 (Table 2).
Isolation by distance:
The lowest Nm estimate calculated from pairwise FST estimates was 1.26 between
11
the Ashtabula and Summit Stairs Populations these two populations are 92,878 meters
apart (Table3&4). The Highest Nm estimate was 9.75 between the two summit county
populations which are only 274 meters apart.
Overall geographic distance was related to genetic differentiation. A Mantel
tests based on pairwise differentiation measures indicated a significant pattern of
isolation by distance when the two summit county populations were combined (r =
0.2538, P=0.0093)(graph1). When Summit subpopulations were considered separately,
a significant pattern of isolation by distance was also detected (r = 0.5469,
P=0.0005)(graph 2). This indicates significant IBD . The two Akron populations fit the
larger scale trend such that more of the variation (r2=0.5469 vs. r2 = 0.2538) is
explained when the local structure is included than when it is left out.
12
Table 2: Locus name, number of alleles, FIT, FIS,and FST values for each locus and over
all loci. Bootstrapping was performed over all loci to determine 95% confidence interval.
All values are significant p<.05
Locus Name
EuFa1
EuFa7
EuFa15
EuFa21
EuFa27
# of
alleles
13
15
11
11
11
FIT
0.251
0.519
0.29
0.343
0.188
FIS
0.171
0.464
0.19
0.275
0.093
FST
0.097
0.102
0.123
0.094
0.105
Over All Loci
0.317
0.237
0.104
95% Confidence
Interval.
Upper Bound
Lower Bound
0.232
0.423
0.144
0.351
0.097
0.115
13
Table 3: Matrix of geographical distances (km) between the populations studied, above
the diagonal, and FST values between pairs of populations of E. fasciatus below the
diagonal. All FST values were significantly greater than 0 (p<.005) 200 permutations).
Populations*
A
G
S
SS
TP
A
0
0.0825
0.132
0.1655
0.118
G
31.22
0
0.0826
0.1172
0.0959
S
168.49
144.12
0
0.1414
0.1008
SS
92.88
61.73
113.81
0
0.025
TP
92.52
61.52
114.09
0.27
0
*Populations: A-Ashtabula; G-Geauga; S-Sandusky; SS- Stairs; TP- TowPath
Table 4: Matrix of Nm values between pairs of populations of E. fasciatus below the
diagonal. All Nm values were significant (p <.005)
Populations
A
G
S
SS
TP
A
G
S
0
2.780303
1.643939
1.260574
1.868644
0
2.776634
1.883106
2.356882
0
1.518034
2.230159
14
S
S
0
9.75
T
P
0
0.16
LinFst = 0.023*ln(M) - 0.1411
R² = 0.2538
0.15
0.14
Mantel test Righttailed p=.00938
Linear FST
0.13
0.12
Lin Fst
0.11
Linear (Lin Fst)
0.1
0.09
0.08
10
10.5
11
11.5
12
12.5
Natural Log Distance (m)
Figure 2: The Mantel tests based on pairwise differentiation values indicated a significant
pattern of isolation by distance when the two summit county populations were treated as one
subpopulation rather than two
0.2
LinFst = 0.0187*ln(M) - 0.0812
R² = 0.5469
0.18
0.16
Mantel test Righttailed p=.00057
Linear FST
0.14
0.12
linFST
0.1
Linear (linFST)
0.08
0.06
0.04
0.02
4
6
8
10
12
Figure 3: The Mantel tests based on pairwise differentiation values indicated a significant
pattern of isolation by distance when the two summit county populations were treated separately
15
CHAPTER IV
DISCUSSION
E.Fasciatus has not been reported in Summit county in recent decades. This in
conjunction with the fact that the Summit Stairs population is found in a highly
urbanized area lead us to hypothesize it may have been an isolated relic population
rather than connected to the larger metapopulation. We expected to see these subpopulations in summit have drifted in their gene frequencies from surrounding
populations. However this data indicated that there is functional connectivity (gene
flow) between all northeast Ohio subpopulations. We found that the populations are not
isolated which is counter intuitive based on the information known of anthropogenic
fragmentations effect on reptile population connectivity. One reason this may have
occurred is that historic areas and paths such as the Glendale steps and Metroparks
towpath acting as refuges and connecting corridors in locals that would have otherwise
been isolated by anthropogenic fragmentation.
Regional population structure
We found a significant pattern of genetic isolation by distance. This relationship
between distance and genetic differentiation was significant when looked at across
regional populations with distance explaining just over 25% of the genetic variation.
When we included our two local Summit county populations separately, the pattern for
distance became an even better predictor explaining almost 55% of the genetic
variation between demes. This consistency indicates that large scale isolation may
16
mirror the buildup of smaller scale pattern. The pattern is one of highly significant
genetic isolation by distance in E.fasciatus. Yet this isolation by distance was not so
high that it indicates isolation of populations within this geographic scale.In terms of
genetic variation it is clear that these populations are acting as one large population and
that there is gene flow occurring between populations. Levels of gene flow among our
populations were high (Nm ranging from 1.52-9.75). This in combination with low
pair-wise FST values indicates significant connectivity between populations. The levels
of gene flow indicate that these populations are part of the regional metapopulation and
if one of these populations were lost they would be capable of recolonization.
Therefore extirpation from any of these counties is unlikely. The highest amount of
gene flow was seen between the two summit populations, which is expected given their
proximity. Furthermore even populations that were furthest apart demonstrated enough
gene flow to be considered connected. Clearly individuals from Sandusky are not
directly migrating to Ashtabula. However these high levels of gene flow may indicate
there are many other undiscovered populations of E.fasciatus throughout Northeast
Ohio.
Local population structure
Although we see that there is not meaningful divergence between populations we
did observe substructure within populations. Considerable inbreeding was observed
within each population due to non-random mating. This is reflected by the FIS values
that were significantly greater than zero. The highest FIS values indicated that
inbreeding is most prevalent in the habitats that are fragmented by urbanization. This
may be because the surrounding habitat is more variable and has more physical barriers
17
to individual movement. This high FIS in the PineBrook and Sandusky populations may
be because samples were collected from individuals from several different sites on the
reservations that may actually be sites of different subpopulations. The Ashtabula
population demonstrated the lowest amount of inbreeding which may be explained by
the homogeneous habitat of the Ashtabula field. In Ashtabula individuals were found in
a uniformly flat 17 acre field hence there were not many physical impediment to
dispersal within the population.
Broader Implications
Now more than ever, conservation biologists need to be concerned with the
difficult task of managing fragmented landscapes. As expansion of urban areas and
thus anthropogenic habitat fragmentation continue to rise, it is expected that
populations will have reduced survivability and connectivity. Therefore, studying
functional connectivity is particularly valuable in evaluating population viability. If
sub-populations exhibit gene flow after a fragmentation event, the population will be
more likely to persist than one that has been functionally isolated. Given our
unexpected results it is clear that making generalizations about particular
fragmentation effects on gene flow can be difficult.
The level of connectivity between subpopulations has a massive influence on
survival and persistence of the regional metapopulation. Connectivity is particularly
critical in urban landscapes since urban patches are often of lower quality and smaller
size they are less likely to maintain a species in isolation. The degree to which a patch
is isolated often depends on the quality of landscape between patches, thus by
18
increasing quality of land between patches the subpopulation may experience higher
connectivity. One way that management can achieve this is by reinforcing the use of
corridors for maintaining metapopulation connectivity. The corridors allow organisms
to bypass urban habitats such as roads and buildings that would normally be
impassible. This will result in increased gene flow between subpopulations and
consequently increased survivability. The data has shown that although the towpath
and stairs population are found within highly anthropogenically modified environments
they still exhibit a high amount of geneflow with all populations. Both of these
populations are near the Metroparks Towpath, an 84 mile corridor that starts in Akron
and heads north into Cleveland. It is our assumption that this historical trail may be
acting as a connecting corridor for Eumeces fasciatus and possibly numerous other
native species. Consequently, this data reinforces that by creating and maintaining
connecting corridors between populations gene flow can be maintained between
populations that would have otherwise been isolated by human development.
19
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