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Genetic structure as a response to anthropogenic and extreme weather disturbances of a coastal dune dwelling spider, Arctosa sanctaerosae



The continued increase in the number of tourists visiting the Northern Gulf Coast (NGC), USA, in the last century, and the resulting sprawl of large cities along the coast, has degraded and fragmented the available habitat of Arctosa sanctaerosae, a wolf spider endemic to the secondary dunes of the white sandy beaches of the NGC. In addition to anthropogenic disturbance to this coastal region, hurricanes are an additional and natural perturbation to the ecosystem. The data presented here explore the status of populations of this species spanning the entire known range and the factors influencing population demography including anthropogenic disturbance and severe tropical storms. Using microsatellite markers, we were able to document the genetic structure of A. sanctaerosae, including current and historic patterns of migration. These results combined with ecological and census data reveal the characteristics that have influenced population persistence: ecological variables affecting the recovery of the population clusters after severe tropical storms, genetic fragmentation due to anthropogenic disturbance, and their interaction. These findings demonstrate the significance that the high traffic beach communities of the NGC and their impact on the once intact contiguous dune ecosystem have on recovery after severe tropical storms. Contemporary modeling methods that compare current and historic levels of gene flow suggest A. sanctaerosae has experienced a single, contiguous population subdivision, and the isolates reduced in size since the onset of commercial development of the NGC. These results point to the need for monitoring of the species and increased protection for this endangered habitat.
Ecology and Evolution. 2021;11:743–752.
Received: 26 June 2019 
  Revised: 23 Se ptember 2020 
  Accepted: 28 September 2020
DOI: 10.1002/ece3.6919
Genetic structure as a response to anthropogenic and extreme
weather disturbances of a coastal dune dwelling spider, Arctosa
Robert A. Hataway | David H. Reed
This is an op en access arti cle under the ter ms of the Creative Commons Attribution L icense, which pe rmits use, dis tribu tion and reprod uction in any med ium,
provide d the original wor k is properly cited.
© 2020 The Authors. Ecolog y and Evolution published by John Wiley & S ons Ltd
Sadly D avid pass ed away prior to sub mission of this wo rk, I dedicate t he work to his
memor y
Samford U niversity, Birmingham , AL, US A
Rober t A. Hat away, Samford Univer sity, 80 0
Lakesh ore Dri ve, Birmingham , AL 35229,
The continued increase in the number of tourists visiting the Northern Gulf Coast
(NGC), USA, in the last century, and the resulting sprawl of large cities along the
coast, has degraded and fragmented the available habitat of Arctosa sanctaerosae,
a wolf spider endemic to the secondary dunes of the white sandy beaches of the
NGC. In addition to anthropogenic disturbance to this coastal region, hurricanes are
an additional and natural perturbation to the ecosystem. The data presented here
explore the status of populations of this species spanning the entire known range and
the factors influencing population demography including anthropogenic disturbance
and severe tropical storms. Using microsatellite markers, we were able to document
the genetic structure of A. sanctaerosae, including current and historic patterns of
migration. These results combined with ecological and census data reveal the char-
acteristics that have influenced population persistence: ecological variables affecting
the recovery of the population clusters after severe tropical storms, genetic frag-
mentation due to anthropogenic disturbance, and their interaction. These findings
demonstrate the significance that the high traffic beach communities of the NGC
and their impact on the once intact contiguous dune ecosystem have on recovery
after severe tropical storms. Contemporary modeling methods that compare current
and historic levels of gene flow suggest A. sanctaerosae has experienced a single,
contiguous population subdivision, and the isolates reduced in size since the onset of
commercial development of the NGC. These results point to the need for monitoring
of the species and increased protection for this endangered habitat.
coastal conservation, dune habitat, ef fective population size, hurricane
Human degradation of habitat is known to interrupt migration
between subpopulations through fragmentation and can influ-
ence population viability (Reed, 2004; Reed, Lowe, et al., 2003;
Reed, O'Grady, Ballou, et al., 20 03; Reed, O'Grady, Brook, et al.,
2003). This human degradation represents a novel disturbance
to species that evolved in the absence of anthropogenic fac tors
(Pickett & White, 1985). The high rate at which human encroach-
ment occurs may prevent the evolution of behaviors of life history
traits to avoid extinction or extirpation (Boulding & Hay, 2001;
Stockwell et al., 2003). In addition to human pressures, naturally
occurring extreme environmental perturbations (catastrophes)
have a profound effect on the persistence time of populations
and species (Brooks & Smith, 2001; Lande, 1993; Mangel &
Tier, 1993; Reed, 2007; Reed, Lowe, et al., 2003; Reed, O'Grady,
Ballou, et al., 2003; Reed, O'Grady, Brook, et al., 2003; Schoener
et al., 2001; Spiller et al., 1998; Young, 1994). There have been
few studies that look at the role of hurricanes as a form of distur-
bance regime and their effects on population dynamics (Askins &
Ew er t , 1991; Land e, 1993 ; Lync h, 19 91 ; Re agan , 1991; Re e d , Lowe ,
et al., 2003; Reed, O'Grady, Ballou, et al., 2003; Reed, O'Grady,
Broo k, et al ., 20 03; Tray lor-Ho lz er et al., 20 05 ; Wa id e, 1991; Will ig
& Camilo, 1991; Woolbright, 1991; Wunderle et al., 1992).
The interaction of the hurricanes and human-induced pressures
on coastal taxa has not been extensively studied. Human modifica-
tions are known to severely limit the dynamic ability of an ecosys-
tem for vary naturally (Nordstrom, 2000) or can amplify the impacts
of naturally occurring stochastic disturbances (Jonzen et al., 2004;
Schrott et al., 2005). These modifications include alteration to the
supply and transport of the sand as well as climate change-induced
sea level and surface temperature rise which is predicted to increase
the severity of tropical storms (Komar, 1998; Slott et al., 2006).
The ecosystem along the Northern Gulf of Mexico Coast (NGC)
is experiencing growth in both of these classes of disturbance. The
NGC including Northern Florida, Alabama, Mississippi, and Louisiana
has had 35 hurricanes of category 3 or higher make landfall in the last
100 years and in that same period, the human population of the major
cities along NGC has increased approximately 15-fold from 10,0 00
individuals to 150,0 00 (U. S. Census Bureau, 1990). This increased
habitat fragmentation due to human encroachment is hypothesized
to have reduced population size of flora and fauna through the cre-
ation of barriers to migration and subsequent subdivision of larger
populations into a series of smaller populations. Small populations
experience reduced population viability and persistence (Palstra &
Ruzzante, 2008; Reed, 2010; Reed, Lowe, et al., 2003; Reed, O'Grady,
Ballou, et al., 2003; Reed, O'Grady, Brook, et al., 2003; Saccheri
et al., 1998). Small populations are also more susceptible to loss of
genetic diversity due to random genetic drift, they maintain lower
levels of fitness (Reed, 2005; Reed & Frankham, 2003), and have
reduced adaptive potential (Blows & Hoffman, 2005; Reed, 2005;
Reed, Lowe, et al., 2003; Reed, O'Grady, Ballou, et al., 2003; Reed,
O'Grady, Brook, et al., 2003) when compared to larger populations.
The spatial heterogeneity in hurricane impacts suggests that
spatial autocorrelations in population fluctuations (Burgman
et al., 1993; McCarthy & Lindenmayer, 2000; Reed, 2004) might be
especially important to metapopulation persistence in this system.
Because hurricanes reduce population size via the direct destruction
of habitat, results from one habit at-specific species with similarities
in vulnerability to storm-driven mor tality should be relevant to the
persistence of all species limited to that habitat.
Using the nocturnal burrow-dwelling wolf spider, Arctosa sanc-
taerosae, Gertsch and Wallace, 1935 (Araneae: Lycosidae) (Figure 1),
we are able to investigate the effects of habitat fragmentation
(human encroachment) and a catastrophe regime (severe tropical
storms) as well as the interaction of these natural and anthropogenic
disturbances. This species is an ideal subject to explore these ques-
tions, as it is entirely restricted to the secondary dunes in the coastal
dune system of the NGC (McNatt et al., 2000). Given the general
lack of invertebrate conservation work (Skerl & Gillespie, 1999) and
the discrete generation length that spiders have, this taxon will pro-
vide insight into threats faced by other invertebrates and small ver-
tebrate species of interest in the region (e.g., several species of the
beach mouse Peromyscus polionotus, Osgood, 1907).
The purpose of this study was threefold: (a) explore the effects
of severe tropical storms on spider density, and relate these to the
physical attributes of the dune system, extent of disturbance, and
the distance from the point of landfall of the tropical storm; (b) de-
scribe the genetic diversity and structure of these population clus-
ters; and finally (c) to investigate gene flow, past and present, among
these. The comparison of historic versus recent gene flow can po-
tentially be used to differentiate isolation of populations caused
by hurricanes and other forms of prehuman isolation (historically
constant) versus contemporary causes of reduced connectivity in-
cluding those caused by conversion of habitat by humans within the
last 100 years. Assuming that hurricanes have occurred since the
evolution of this species and that human disturbance on a large scale
in the region star ted only a hundred years ago, the dominant force
that is shaping the current st atus of the species and its populations
should emerge. Gaining insight into the effects of environmental
FIGURE 1 Arctosa sanctaerosae, Gertsch and Wallace, 1935
(Araneae: Lycosidae)
perturbations, anthropogenic encroachment, and their interaction
would be invaluable informing the long-term conservation goals
species who share the same endangered coastal dune habitat along
the NGC.
2.1 | Population densities and growth rates
Densities were measured by hand collecting individuals inside three
in depe n den t 12 m by 12 m quad r ats (14 4 m2) randomly placed within
the secondary dunes of ten sites across the NGC during the summer
months between 2003 and 2007 (Figure 2). Counts were made of
spiders at or near their burrows one hour after night fall on three
consecutive clear nights. The quadrat s were located each year using
GPS data and resampled. Growth rate (R) was calculated as R = ln
(N1/N0) for each site. All density estimates of zero were adjusted to
0.5 to ease statistical analysis based on the assumption that these
population numbers were most likely not zero but too small to be
These rates were compared before and after landfall of major
hurricanes, Hurricane Ivan in 2004 and Hurricane Katrina in 2005.
These hurricanes led to severe erosion of the dunes of the NGC.
Hurricane Ivan made landfall at Gulf Shores, Alabama, on 16
September 2004 as a category three hurricane. Then, on 25 August
2005, Hurricane Katrina made its original landfall in southeast
Louisiana as a category three hurricane. Densities were measured
one month af ter landfall of the storms.
Physical measures, dune height (dh) and the density of veg-
etation, were also quantified within the quadrats. These two
measures were included due to their provision and maintenance
of habitat for A. sanctaerosae as well as prey. Vegetation cover
of dunes was quantified by counting the number of stems of sea
oats, Uniola paniculata L. (Liliopsida:Poaceae) and similar vegeta-
tion within three independent, randomly chosen one square meter
quadrat s within the larger quadrats on each of the three sampling
nights per site. Dune height was measured from the height of the
apparent high tide mark on the active beach to the highest point
on the secondary due. Model selection for explaining population
growth rates was accomplished using an infor mation-theoretic ap-
proach. Stepwise multiple regression was subsequently used to ex-
plore the relationships among these ecological factors and changes
in them, as a func tion of hurricane landfall, associated with each
site in order to identify those that best explained the variation in
population decline and recovery observed after each of these two
2.2 | Census population size
Census population sizes were calculated for each of the five clusters
(recovered by genetic clustering algorithms detailed below) by mul-
tiplying population densities across the clusters by the total habitat
area. The total extent of habitat was estimated by calculating the
area of secondary dunes within each cluster. This was done using
GOOGLE EARTH by creating polygons and using the area tool to
calculate the total area. The density per quadrat was then multiplied
against total area to estimate census population size.
2.3 | Genetic sampling
Tissu e samples from 20 ind iv iduals collected f rom ea ch of th e si te s
wer e co ll ec te d bet ween 1st June and 11th June 20 07 to be used in
gene ti c ana lyses . A ll indi vi dua ls were sto red at −8 0°C in 10 0% et h-
anol, and approximately 1 mg of tissue acquired from the legs was
used for subsequent DNA extraction (Qiagen DNeasy kit). Target
microsatellite sequences were amplified using 11 microsatellite
primers, ten developed for the study sp ec ie s (H at away et al ., 2011)
and an addition developed for a sister taxa. Fluorescence-labeled
fragments were visualized on an ABI 3130, and allele sizes
were determined through comparison with a known size stand-
ard (GeneScan -500 ROX) using GENEMAPPER version 3.7. All
scores were checked manually, and ambiguous fragments were
FIGURE 2 The five population clusters
recovered from genetic data using
with major human development s labeled:
(a) Gulf Shores, AL, (b) Pensacola Beach,
FL, (c and d) Destin, FL
2.4 | Population structure
Population dif ferentiation was accomplished using the Bayesian
clustering algorithms in the programs STRUCTURE (Pritchard
et al., 20 00) and GENEL AND ver. 3. 2.4 (Guillot et al., 2005; Guillot
& Santos, 2009). Both of these programs have idiosyncrasies and
can be used in concert to not only suggest a current number of clus-
ters and assign individuals to them, but also to find support for a
suggested model. GENEL AND was run and included the correlated
model, which assigns individuals to geographic clusters without
prior knowledge of the site where that individual was sampled. This
accounts for several factors relevant to this system. Spatially, we
expect areas of intense human impact to create a barrier between
populations and so we add into the model the set of georeferenced
coordinates, in this case the location of our collection sites (Guillot
& Santos, 2009). GENEL AND and STRUCTURE both recovered five
clusters and these assignments were used for all subsequent demo-
graphic analyses.
2.5 | Genetic diversity
FSTAT ver. (Goudet, 2002) was used: (a) to test for Hardy–
Weinberg equilibrium within populations (b) to estimate Fis (c)
to calculate allelic richness (Ar) and (d) to calculate gene diversity
(Hs). GENEPOP (Raymond & Rousset, 1995; Rousset, 20 08) was
used to test population differentiation and to estimate the number
of null alleles. ARELEQUIN ver. (Excoffier, 2010; Excoffier
et al., 2005) was used to calculate expected (He) and observed (Ho)
heterozygosities and pairwise Fst values between populations. Other
statistics have been suggested for estimating gene flow in micros-
atellites (Goldstein & Pollock, 1997; Goldstein et al., 1995; Weir &
Cockerham, 1984; Zhivotovsky, 1999), but Fst is the most commonly
used metric and was employed here. Expected heterozygosity was
computed among and within populations using Levene's method
(1949) in the software package POPGEN (Yeh et al., 1999). Isolation
by distance was tested using a Mantel test of log transformed lin-
earized Fst and geographic distance values was conducted among
the clusters.
2.6 | Historic and recent geneflow estimation
Historic mutation scaled migration rates (M) were calculated using
MIGRATE ver. 3.2.1 (Beerli, 2010). The estimates given are long-
term averages heavily influenced by the recent past and are calcu-
lated over the las t 4Ne ge ne rations. The rate of recent ge ne flow was
calculated using BAYESASS ver. 1.3 (Wilson & Rannala, 2003), which
estimates migration rates within the last two to three generations
using a Bayesian inference framework and gametic disequilibrium
among immigrants and their descendant s. Individuals from each of
the five clusters were grouped suggested by GENELAND for both
2.7 | Historic and recent bottleneck detection
To test for evidence of bottlenecks, M ratios were calculated (Garza
& Williamson, 2001) in ARLEQUIN version 3.1 (Excoffier, 2010;
Excoffier et al., 2005). The effectiveness of this method has been
shown to be maximized when the bottleneck is older and lasted sev-
eral generations before recovery (Williamson-Natesan, 20 05).
BOTTLENECK (Cornuet and Luikart 1996; Luikart &
Cornuet, 1998; Piry et al., 1999) was used for estimations of bot-
tlenecks within the previous 4Ne generations, for this species ap-
proximately the last 100–500 years. The method employed in this
program has been shown to have the ability to detect less severe and
more recent reductions in population size.
2.8 | Historic and recent effective population
size estimation
Historic effective populations sizes were measured using three
methods. First, using the equation Ө = 4 N eμ where Ө is th e mut ati o n
scaled ef fective population size and μ is th e mut ation rate (Gaggiotti
& Excoffier, 2000). Mutation rate was held constant and at a rate of
5x10-4, and a coalescent approach was used to estimate of Ө over
the last 4Ne generations in the program MIGRATE (Beerli, 2010;
Beerli & Felsenstein, 1999).
Historic effective population size was also calculated using the
methods of Hartl and Clark (1989) and Ohta and Kimura (1973).
These methods assume an infinite allele model (IAM) and a step-
wise mutational model (SMM), respectively. Both methods hold
Ne as a func tion of He. The mutational models estimate the upper
and lower extremes of mutation, and so the true Ne is likely to be
found between the two estimates (Busch et al., 2007). A paired
t test was then carried out between the historic and recent esti-
mates of Ne.
Recent effective population sizes were estimated using
ONeSamp (Tallmon et al., 2008) as well as LDNe (Waples &
Do, 2008). LDNe uses linkage disequilibrium to estimate Ne. The
major issue affecting its usefulness for this study is that linkage
disequilibrium can be caused by inbreeding, substructure, or im-
migration. The first is known to be an issue in this species, and
so the results of these test s bear careful scrutiny. ONeSAMP on
the other hand uses eight different genetic parameters includ-
ing: “the number of alleles divided by allele length range (Garza
& Williamson, 2001), the difference of the natural logarithms of
variance in allele length and heterozygosity (King et al., 2000),
expected heterozygosity (Nei, 1987), number of alleles per locus,
Wright 's FIS (Nei, 1987), the mean and variance of multilocus ho-
mozygosit y, and the sq uar e of th e cor rel ati on of alle le s at dif fer ent
loci (Hill 1981)” ( Tallmon et al., 2008). This is expected to provide
more accurate results, although high inbreeding levels (FIS) may
confound results. The results for both methodologies including es-
timates using both 0.01 and 0.02 for the lowest allele frequencies
for the analysis in LDNe are reported.
3.1 | Population densities and growth rates
The mean population growth rate (R) across sites during the period
between 2003 and 2004, which included the effects of Hurric ane
Ivan, was −2.703 (SE = 0.517). In the following one-year period
(2004–2005), the growth rate across sites was 1.738 (SE of 0.416).
This demonstrates a pattern of reduction and recovery of densities,
assuming that the sites had been stable for some time before this.
This assumption is based on the extended period of time prior to
Hurricane Ivan (8 years) since the last major tropical storm made
landfall and the protected status of the sites used. There was an in-
crease in density at all sites in the period following Ivan's landfall
between 200 4 and 2005. However, population densities had not re-
turned to the levels they were found at in 2003 prior to the landfall
of Katrina.
The average distance of study sites from the landfall of
Hurricane Ivan was 106 km, while for Hurricane Katrina it was
288 km. The furthest sites from Katrina were over 400 km away
and experienced little or no population reduction and, in most
cases, had positive population growth rates despite the landfall
of the hurricane. When the density of A. sanctaerosae prior to
Hurricane Ivan is regressed against the proportional reductions
of density of A. sanctaerosae at each site (density before storm
divided by den sity after stor m), the res ults are foun d to be nonsig-
nificant (p = .67, R2 = .0 31). The same is t rue for Hur ricane Katrina
(p = .7127, R2 = .018). This confirms what had long been assumed,
the effects of major hurricanes are density-independent which in
this case means the density of spiders prior to landfall of a major
hurricane has no apparent impact on the magnitude of the loss of
density after the landfall of the storm.
Multiple regression models were created to explore what eco-
logical factors varied with population reductions for each of the
two storms independently. The factors included were as follows:
distance from landfall, dune height and vegetation before landfall,
and proportional loss of dune height and vegetation after landfall.
The model that best described the effects seen from the storms only
included the distance from the point of landfall in both the case of
Hurricane Ivan (R2 adjusted = .638, p = .002, AIC adjusted = 5.046,
w = 0.880) (Table 1) and Katrina (R2 adjusted = . 0 3 69, p = .014, AIC
adjusted = 39.561, w = 0.922) (Table 2).
Similar multiple regression models for the recovery of density
included the possible explanatory variables: distance from landfall,
dune height and vegetation minimums after storms, and propor-
tional recover y of dune height and veget ation in the year following
the storms landfall. The model that best predicted the recover y of
population density of A. sanctaerosae after Hurricane Ivan suggest s
that variation in the recovery of dune height in the year following
the storm event best explains the variation in the recovery of the
population (R2 adjusted = .416 , p = 012, AIC adjusted = 36 .261,
w = 0.887) (Table 3). In the recover y from Hurricane Katrina, the
best model incorporated both the recover y of dune height and the distance from the place of landfall (R2 adjusted = .595, p = .009, AIC
TABLE 1 Comparison of models describing the proposed fac tors
contributing to proportional population reduction as a result of
Hurricane Ivan
Model AICc w
Distance from L andfall of
5.406 0.880
+ Dune Height before 9.4 25 0 .118
+ Vegetation b efore 17. 4 4 3 0.002
+ loss of Vegetation 32.005 1. 474 E−06
+ loss of Dune Height 59.7 7 0 1.379E−1 2
TABLE 2 Comparison of models describing the proposed fac tors
contributing to proportional population reduction as a result of
Hurricane Katrina
Model AICc w
Distance from L andfall of
39. 5 611 0.922
+Loss of Dune Height 44. 5507 0.076
+Loss of veg 52.2326 0.002
+2005–2006 veg 63.7523 5.150E−06
+2005 Dh 93 .7519 1. 576E−1 2
TABLE 3 Comparison of models describing the proposed fac tors
contributing to population growth rate in the year immediately
following Hurricane Ivan
Model AICc w
Recovery of Dune Height 36.261 0.887
+ Distance from L andfall Ivan 40.6 49 0.099
+Dune Height minimum after
44 .474 0.015
+Vegetation minimum after
58.645 1.222E−05
+Recovery of Vegetation 88.460 4.099E−12
TABLE 4 Comparison of models describing the proposed fac tors
contributing to population growth rate in the year immediately
following Hurricane Katrina
Model AICc w
Recovery of Dune Height 25.510 0.155
+ Distance from L andfall
22.214 0.806
+Vegetation minimum after
28.269 0.039
+Dune Height minimum after
41.97 9 4.115E−05
+ Recovery of vegetation 71.957 1.272E−11
adjusted = 22.214, w = 0.8 06) (Table 4).
The recovery of the sites after Hurricane Ivan did appear to dis-
play a level of density dependent growth. The proportional reduc-
tion explained 45% of the rate of growth in the year following the
storm (R2 = .452, p = .0332): The larger the propor tion of reduction,
the faster the rate of recovery. This result is logical considering the
increased habitat availabilit y at sites whose densities were impacted
more severely leaving open habitat patches.
There was spectrum of effects on the density of A. sanctaerosae
after the storms from zero in the most distal sites to severe at sites
such as Fort Pickens, FL . The densit y of individuals at Fort Pickens
experienced the most severe effects from Hurricane Ivan. Extensive
flooding and overwashing of the western portion of Santa Rosa
Island occurred where this collection site is located. It was sampled
in 200 5–2007 (it was not sa mp led in 20 0 4. Acc es s to the sit e wa s re -
stricted) with zero individuals being located in the first 3 years after
Ivan. It was not until 2007 that individuals were found at this site.
This suggests either a loc al extinction or such a severe reduction
that individuals were not detectable with our sample sizes. Other
sites saw depressions in po pulation density but not as severe or sus-
tained as what was seen at Ft. Pickens, FL.
3.2 | Census population size
Census population sizes were large and range from 71,000 to
315,000 individuals spread across the available habitat per cluster
(Table 5). There was a significant difference between recent Ne and
estimates of Nc for each of the clusters.
3.3 | Population structure
GENELAND and STRUCTURE identified five population clusters
that were consistent across all independent runs. The three sites
of western Alabama were clustered as a single population (Cluster
1) despite Dauphin Island, AL and For t Morgan, AL being sepa-
rated by a 5 km stretch of open water. The sites combined to form
both Clusters 2 and 3 are also separated by stretches of water. A
single site, geographically isolated by human development com-
posed Cluster 4. Finally, the three most easterly sites formed Cluster
5 (Figure 1).
3.4 | Genetic diversity
The number of alleles per locus varied from 3 to 11, and null alleles
were estimated to be <0.16% across all loci. Each of the eleven loci
tested were found to be in gametic equilibrium. Tests of linkage dis-
equilibrium, within and across populations, were all insignificant,
satisf ying the assumption that all loci are unlinked. The measures
of diversity (allelic richness and gene diversity) decreased longitu-
dinally, with the lowest levels of obser ved diversity in the western-
most populations. Heterozygosity, gene diversity, and allelic richness
all followed this east – west pattern ( Table 6). Fis scores for each of
the clusters loosely followed this pattern and ranged from 0.18 to
0.06. Pairwise Fst scores ranged from 0.05 to 0.30, and all were sig-
nificant (Table 7). The Mantel test showed Pearson's r of .6 8 that wa s
highly significant (p = .001) meaning that individuals are more likely
to find mates from populations geographically close to themselves
rather than at random across all populations.
3.5 | Historic and recent geneflow estimation
Using MIGRATE, a mean historic migration rate was calculated as
the number of effective migrants (Table 8). BAYESASS estimates of
recent migration were significantly lower, suggesting these clusters
showed higher levels of isolation in the recent past. A paired t test
of the means found the dif ference between historic and recent mi-
gration rates of A. sanctaerosae to be statistically significant (df = 4,
p < .002).
3.6 | Historic and recent bottleneck detection
Tests of heterozygosity using the statistical package BOTTLENECK
showed no significant excess in the five clusters. However, the M
TABLE 5 Estimates of historic and recent effective population size (Ne) and census population size (Nc) for each of the five population
clusters recovered from genetic data using GENEL AND and STRUCTURE
Population cluster
Historic NeRecent Ne
Census Population
Mean of three methods used (SMM, IAM, and
Lower C. I. Mean Upper C .I. Lower C. I. Ne Upper C .I.
188.7 94.0 160.4 53.7 68.4 81.4 128,350.0
2115. 5 160.2 204.9 18.6 32.7 43.7 87,597.9
3103. 3 193.6 283.9 34.5 50.2 68.4 71,066.7
428 7. 6 351 . 0 614. 3 31.1 46.8 56.3 196,48.6
5544.4 773.0 1,501. 5 101.7 153.9 24 3.6 315,8 42.2
ratios (generated by ARLEQUIN) ranged from 0.17 to 0.72. The
three western clusters all had upper 95% C.I. estimates below the
critical value of 0.68. These results support recent and severe bot-
tleneck events in clusters one, two, and three. Cluster four has an
M ratio below the critical value, but its confidence intervals over-
lap it suggesting an older or less severe event. Cluster five has an
M ratio above the critical value and does not appear to have been
3.7 | Historic and recent effective population
size estimation
Historic estimates of Ne (Table 5) across methods varied. The mean
of the three methods was used for subsequent analyses and was
significantly higher than the estimate of recent effective population
size and the lower C.I. did not cross the upper C.I. of the estimates
of recent Ne.
Estimates of recent effective population size from LDNe var-
ied widely and included negative values as well as upper estimates
that reached infinity. Varying the lowest allele frequency from
0.01 to 0.02 did not narrow the 95% confidence intervals (Table 5).
ONeSAMP gave results that appeared to be more biologically sig-
nificant. Each of the clusters has a Ne of less than one hundred indi-
viduals with the exception of cluster 5. Mean estimates range from
32 to 153 individuals with less variation around the estimates using
this method compared to LDNe. Only the ONeSAMP estimates were
used for comparisons against historic Ne.
The impact of hurricanes on the density of A. sanctaerosae was di-
rect, density-independent, and the best predictor of the magnitude
of population reduction was the distance from the point of landfall.
The effect s of Hur ri ca ne Kat ri na showed a gradient of severity ra ng-
ing from the most severe in the western sites to no measurable ef-
fect in sites beyond 283 km from the site of landfall. Hurric ane Ivan,
by contrast, was centered directly over the western sites and was of
sufficient severity to affect every site.
More specifically, population clusters 2 and 4 are receiving
more effective migrants than the other three clusters. The rate of
emigration into Cluster 4 is best explained by it s geographic isola-
tion and small size in relation to the other populations, suggesting
this locality may serve as a sink population that requires immigra-
tion to persist. The severity of effects experienced by Cluster 2
due to hurric anes in t he recent past could explain the high number
of migrants from Cluster 1. Additionally, the spatial heterogeneity
of hurricane effects is not limited to the distance from landfall.
The hurricane's leading edge has higher wind speeds relative to
the trailing edge and is formed on the eastern side of the storm
in the northern hemisphere. This frequently leads to an increased
number of tornadoes spawned by the storm and more destructive
TABLE 6 Number of individuals (N), mean allelic richness (Ar), gene diversity (Hs), observed heterozygosity (Ho), expected heterozygosity
(He), and the inbreeding coefficient (Fis) for Arctosa sanctaerosae in five population clusters along the Northern Gulf of Mexico Coast
Population Cluster N Ar±95% C.I. Hs±95% C.I. HoSD HeSD Fis
192 1.84 0.73 0.14 0.14 0.13 0.21 0.14 0.21 0.06
246 2.09 0.86 0.23 0.16 0.21 0.21 0.23 0.23 0.07
348 2.11 0.60 0. 28 0.17 0.24 0.23 0.27 0.26 0.11
427 2.73 0.80 0.37 0.14 0.33 0.18 0.36 0.21 0.09
560 3.56 1.26 0.54 0.11 0.43 0.18 0.53 0.20 0.18
Population cluster 1. 2. 3. 4. 5.
1. *40.56 8 7.9 3 149.79 2 3 7. 07
2. 0.0773 *25.40 87. 62 178.71
3. 0.1459 0.0464 *23.18 119. 3 5
4. 0.1577 0.0421 0.0179 *98.08
5. 0.2891 0.1696 0.1250 0.0530 *
* are blank values.
TABLE 7 Pairwise Fst Scores below
diagonal and pairwise geographic
distances (km) above the line
TABLE 8 Comparison of the mean number of effective
immigrants per generation reaching a population recently (as
estimated by BAYESASS) versus the mean number of immigrants
reaching a site historically (as estimated by MIGR ATE)
Population cluster Nm recent
10.01 1.23
20.57 2.68
30.14 2.75
40.69 3.34
50.09 1.28
power to the east of the storms point of landfall (Williams &
Sheets, 2001). Hurricane Ivan made landfall due west of Cluster
2, and thus, the severity of effect s may have been higher than that
at Cluster 1, which with its high migration rate, provided a rescue
effect. This migration appears to be elevated after major storm
The model that best explained population recovery in the year
following a storm included both distance from landfall of the hurri-
cane and the recovery of dune height. This dune habitat that is re-
quired for population recovery is often removed or highly partitioned
by commercial development along the NGC. Five genetically distinct
population clusters were recovered, and the barriers separating
them were the high traffic beach communities of the NGC including
the following: Gulf Shores, AL; Orange Beach, AL; Pensacola Beach,
FL; Destin, FL; and Panama City Beach, FL; (Figure 1). This suggests
that the commercial development of the NGC and the storm-related
population reductions work in concert to reduce the size of popula-
tion clusters, reduce the cluster's ability to recover from storms, and
reduce the population cluster's connectivity.
This type of habitat fragmentation shapes population genetic
structure by reducing population cluster connectivity. In addition to
low rates of gene flow, reductions in population size and loss of avail-
able high-quality habitat can lead to genetic isolation and eventual
extinction of populations (Reed 200 8). Previous studies of spider
population demography in fragmented habitats have found levels of
structure and inbreeding similar to those found in the current study
suggesting a decreased role of ballooning (Reed et al., 2011). The
genetic isolation seen in the population clusters of Arctosa sanctaero-
saeis is likely due to a decline in effective population size and effec-
tive migration in the recent past with Fis scores ranging from 0.18
to 0.06, which suggests low amounts of dispersal across available
Historically, these population clusters experience severe reduc-
tion in size due to hurricanes or other catastrophic events; however,
they had the ability to recover within one to two generations through
migration to recently vacated habitat patches. This migration erased
enough of the genetic signature of the reduction that it is undetect-
able using the current methodology. The genetic data suggest that
there has been a significant decrease in the amount of migration
between the five clusters within the last 100 years. However, this
lack of migration in the recent past combined with the correlation
of the patterns of genetic structure and the timing of the develop-
ment of high traffic beach communities supports placing the timing
of the subdivision to within the last 100 years. Once subdivided, the
migration between clusters was reduced, and genetic drift, direct
removal of diversity due to severe tropical storms, and commercial
develo pment led to declining po pulat ion sizes an d reduced dive rsit y.
The observed genetic variation decreases along a geographic
gradient from east to west with the alleles found in western pop-
ulations as subset s of the alleles found in the eastern populations.
Allelic richness and gene diversity are highest in the east and de-
crease as you move west ward. The best three possible explanations
for the higher genetic diversity seen in the eastern clusters are (a)
the relatively few numbers of hurricanes to make landfall in the east
in recent years, (b) significantly fewer high traffic beach communi-
ties, or (c) the possibility that A. sanctaerosae has expanded its dis-
tribution westward over time from the site of its divergence from
its sister taxa. Hurricane Michael made landfall in October of 2018
in the eastern most cluster, which exhibits the highest richness and
diversit y, at Mexico Beach, Florida, and directly on several collection
sites. The effects this will have on the species’ persistence would not
be known for decades.
All of this dat a combined paints a picture of a metapopulation
that has evolved in the presence of severe tropical storms and has
been recently impacted through commercial development that has
created barriers to repopulation, gene flow, and directly lowered
Ne. With the severity of tropical storms predicted to increase over
time due to elevations in surface temperature of the Gulf of Mexico
caused by climate change (Goldenberg et al., 2001; Slott et al., 2006;
Webster et al., 20 05), population connectivity will become increas-
ingly important for population and even species persistence.
Moving forward, conservation measures must recognize the
need for a contiguous dune system, not only for the physical pres-
ervation of the coastal dune ecosystem, but also for maintaining
population structure and connectivity of this and presumably other
species. Importantly, increased continuity and protec tion of these
dunes will also lead to a healthier dune system that prevents erosion
and inland destruction in the face of tropical storms. It must be rec-
ognized that a contiguous dune system, while beneficial to the focal
species, also ser ves the broader goals of ecological and commercial
interests along the NGC. By removing the dunes for commercial de-
velopment, we have increased erosion and must reclaim the beach
sands regularly as well as replace structures damaged during major
tropical storms at great cost. It makes ecological as well as financial
sense to restore these dune systems to their original st ate and allow
natural processes to maintain them. Only the halting and/or reversal
of the current developmental trends, including the complete removal
of barriers interrupting the corridors for inter-population migration,
will result in the long-term persistence of A. sanctaerosae.
I would like to thank all the colleagues who graciously reviewed the
manuscript as well as Brice Noonan for laboratory assistance.
There are no sources or any potential sources of conflict of interest.
There is no interest or relationship, financial or otherwise, that might
be perceived as influencing the objectivity of this work.
Rober t A Hataway: Conceptualization (equal); Data curation (equal);
Formal analysis (equal); Investigation (equal); Methodology (equal);
Project administration (equal); Visualization (equal); Writing-original
draft (equal); Writing-review & editing (equal). David H Reed:
Conceptualization (equal); Formal analysis (equal); Methodology
(equal); Supervision (equal); Writing-original draft (equal).
Microsatellite genotypes: pp1z.
Sampling locations and microsatellite genotypes available Dryad.
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How to cite this article: Hataway RA, Reed DH. Genetic
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