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\begin{document}

\title{Real-time geographic settling of a hybrid zone between the invasive
winter moth (Operophtera brumata L.) and the native Bruce spanworm (O.
bruceata Hulst)}



\author[1]{Jeremy Andersen}%
\author[2]{Nathan Havill}%
\author[1]{George Boettner}%
\author[1]{Jennifer Chandler}%
\author[3]{Adalgisa Caccone}%
\author[1]{Joseph Elkinton}%
\affil[1]{University of Massachusetts Amherst}%
\affil[2]{USDA Forest Service Northern Research Station}%
\affil[3]{Yale University}%


\vspace{-1em}



  
  \date{May 18, 2024}


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\selectlanguage{english}
\begin{abstract}
Hybridization plays an important and underappreciated role in shaping
the evolutionary trajectories of species. Following the introduction of
a non-native organism to a novel habitat, hybridization with a native
congener may affect the probability of establishment of the introduced
species. In most documented cases of hybridization between a native and
a non-native species, a mosaic hybrid zone is formed, with hybridization
occurring heterogeneously across the landscape. In contrast, most
naturally occurring hybrid zones are clinal in structure. Here we report
on a long-term microsatellite dataset that monitored hybridization
between the invasive winter moth, Operophtera brumata (Lepidoptera:
Geometridae), and the native Bruce spanworm, O. bruceata, over a 12-year
period. Our results document one of the first examples of the real-time
formation and geographic settling of a clinal hybrid zone. In addition,
by comparing one transect in Massachusetts where extreme winter cold
temperatures have been hypothesized to restrict the distribution of
winter moth, and one in coastal Connecticut, where winter temperatures
are moderated by Long Island Sound, we find that the location of the
hybrid zone appears to be independent of environmental variables and
maintained under a tension model wherein the stability of the hybrid
zone is constrained by population density, reduced hybrid fitness, and
low dispersal rates. Documenting the formation of a contemporary clinal
hybrid zone may provide important insights into the factors that shaped
other well-established hybrid zones.%
\end{abstract}%



\sloppy


\textbf{Title:} Real-time geographic settling of a hybrid zone between
the invasive winter moth (\emph{Operophtera brumata} L.) and the native
Bruce spanworm (\emph{O. bruceata} Hulst)

\textbf{Short Title:} Winter moth hybrid zone formation

\textbf{Authors:} Jeremy C. Andersen\textsuperscript{1,*}, Nathan P.
Havill\textsuperscript{2}, George H. Boettner\textsuperscript{1},
Jennifer L. Chandler\textsuperscript{1}, Adalgisa
Caccone\textsuperscript{3}, Joseph S. Elkinton\textsuperscript{1}

\textbf{Affiliations:}

\textsuperscript{1}Department of Environmental Conservation, University
of Massachusetts, Amherst

\textsuperscript{2}Northern Research Station, USDA Forest Service,
Hamden, Connecticut

\textsuperscript{3}Department of Ecology \& Evolutionary Biology, Yale
University, New Haven, Connecticut

\textsuperscript{*} Corresponding Author email: jcandersen@umass.edu

\textbf{Abstract:}

Hybridization plays an important and underappreciated role in shaping
the evolutionary trajectories of species. Following the introduction of
a non-native organism to a novel habitat, hybridization with a native
congener may affect the probability of establishment of the introduced
species. In most documented cases of hybridization between a native and
a non-native species, a mosaic hybrid zone is formed, with hybridization
occurring heterogeneously across the landscape. In contrast, most
naturally occurring hybrid zones are clinal in structure. Here we report
on a long-term microsatellite dataset that monitored hybridization
between the invasive winter moth, \emph{Operophtera
brumata}(Lepidoptera: Geometridae), and the native Bruce spanworm,
\emph{O. bruceata,} over a 12-year period. Our results document one of
the first examples of the real-time formation and geographic settling of
a clinal hybrid zone. In addition, by comparing one transect in
Massachusetts where extreme winter cold temperatures have been
hypothesized to restrict the distribution of winter moth, and one in
coastal Connecticut, where winter temperatures are moderated by Long
Island Sound, we find that the location of the hybrid zone appears to be
independent of environmental variables and maintained under a tension
model wherein the stability of the hybrid zone is constrained by
population density, reduced hybrid fitness, and low dispersal rates.
Documenting the formation of a contemporary clinal hybrid zone may
provide important insights into the factors that shaped other
well-established hybrid zones.

\textbf{Keywords:} Tension zone, hybrid fitness, introgression,
Lepidoptera, forest pest.



\textbf{Introduction:}

Hybridization is a driver of speciation and evolutionary trajectories
across the tree of life (Allendorf, Leary, Spruell, \& Wenburg, 2001;
Costedoat, Pech, Chappaz, \& Gilles, 2007; Harrison \& Larson, 2014;
Mallet, 2005). While numerous pre- and post-zygotic barriers exist in
most natural ecosystems to reduce genetic exchanges between species,
human-mediated disturbance and climate change have led to increased
hybridization rates across a diversity of taxonomic groups (Gomez,
Gonzalez-Megias, Lorite, Abdelaziz, \& Perfectti, 2015; Hegarty, 2012;
Larson, Tinghitella, \& Taylor, 2019). The accidental introduction of
non-native organisms to novel habitats has further increased these rates
by uniting previously disjunct species or genetically distinct
populations (Chown et al., 2015; Havill et al., 2012; Havill et al.,
2021; Michaelides, While, Bell, \& Uller, 2013). In addition to
illuminating factors that may be important in invasion ecology, studying
the real-time formation of hybrid zones between native and non-native
species may provide a type of natural laboratory, providing important
insights into how other well-established hybrid zones may have formed
and settled over evolutionary timescales. As such, recent work has
highlighted the importance of studying newly-formed hybrid zones for
understanding speciation and the preservation of species boundaries
(Johannesson, Le Moan, Perini, \& Andre, 2020; Larson et al., 2019).

These natural laboratories are particularly important because most
documented hybrid zones have likely existed for thousands of years and
formed following the movement of species in response to long-term
processes such as changing climates during the Quaternary climatic
oscillations (e.g., Ryan et al., 2018; Ryan et al., 2017; Scriber, 2011;
Taylor, Larson, \& Harrison, 2015). Natural hybrid zones frequently have
a clinal structure, with a narrow, linear geographic zone of admixture
where phenotypic and genetic states change across a gradient between
parent species (Barton \& Hewitt, 1985; Endler, 1977). In contrast, most
documented hybrid zones created in contemporary settings between
introduced and native species have a mosaic structure (see Harrison \&
Rand, 1989), with zones of genetic exchange spread across the landscape
in a patchy and non-linear fashion (e.g. Cordeiro et al., 2020; Havill
et al., 2012). Therefore, additional examples of newly formed clinal
hybrid zones are needed to better understand the evolutionary and
ecological processes that shape these temporally and spatially dynamic
regions of secondary contact.

Species of moths and butterflies (Insecta: Lepidoptera) have provided
some of the most stunning examples of the diversity of interactions
resulting from hybridization (e.g., Ipekdal, Burban, Saune, Battisti, \&
Kerdelhue, 2020; Lucek, Butlin, \& Patsiou, 2020; Ryan et al., 2018;
Ryan et al., 2017; Scriber, 2011). Here we explore the formation of a
hybrid zone in northeastern North America between the introduced
European winter moth, \emph{Operophtera brumata} L. (Lepidoptera:
Geometridae) and the native Bruce spanworm, \emph{O. bruceata} Hulst.
Winter moth is native to western Eurasia and North Africa (Ferguson,
1978) and originally became established in North America in Nova Scotia
in the 1930s, where it was identified as a major pest in apple orchards
and oak-dominated hardwood forests (Embree, 1966, 1967). Subsequently,
populations were identified in Oregon as a pest in hazelnut (filbert)
orchards in the 1950s (Kimberling, Miller, \& Penrose, 1986), British
Columbia as a pest in apple orchards and of urban trees in the 1970s
(Gillespie, Wratten, Cruickshank, Wiseman, \& Gibbs, 1978), and most
recently in the northeastern United States (hereafter, the
``Northeast'') as a pest of blueberries, cranberries, and many native
deciduous trees in the 1990's (Elkinton et al., 2010; Elkinton,
Liebhold, Boettner, \& Sremac, 2014). Each of these regions were likely
the result of independent invasions from Europe (Andersen, Havill,
Caccone, \& Elkinton, 2021), and while successful biological control
programs have reduced the abundance and economic impacts of this
important pest in each invaded region (Elkinton, Boettner, Liebhold, \&
Gwiazdowski, 2015; Elkinton, Boettner, \& Broadley, 2021; Kimberling et
al., 1986; Roland \& Embree, 1995), populations of winter moth continue
to persist at low densities in each location. Previous work in this
system has shown that winter moth and Bruce spanworm hybridize readily
in the field (Andersen et al., 2019; Elkinton et al., 2010, 2014; Havill
et al., 2017). Additionally, in the Northeast it has been documented
that the proportions of individuals of winter moth versus Bruce spanworm
can be modeled using logistic regression, with populations proximate to
Boston, Massachusetts being nearly 100\% winter moth, and populations in
western Massachusetts being nearly 100\% Bruce spanworm (Elkinton et
al., 2014). This gradient in winter moth and Bruce spanworm population
densities in the Northeast therefore raises the possibility that a
clinal hybrid zone may exist in this region, making it one of the first
documented cases of this type of hybrid zone between an introduced and a
native species.

We explored the spatial and temporal dynamics of the hybrid zone between
the invasive winter moth and native Bruce spanworm by collecting moths
with pheromone traps along two transects that crossed the leading edge
of winter moth spread in the Northeast region. One of these transects
was located along Route 2 in Massachusetts (hereafter the
``Massachusetts transect'') and was sampled over a 12-year period (from
2007 to 2018) where a gradient across decreasing extreme cold winter
temperatures has been hypothesized to limit the distribution of winter
moth (Elkinton, Lance, Boettner, Khrimian, \& Leva, 2011). The second
transect is located along the coast of southern Connecticut following
Route 1 (hereafter the ``Connecticut transect'') and was sampled over a
3-year period (2016-2018). This second transect was added so that we
could compare the role of winter temperatures on the geographic location
of the hybrid zone as temperatures along the Connecticut transect are
milder than at any point along the Massachusetts transect, and
geographic settling would therefore be independent of low winter
temperatures. With these data, we explore: 1) the structure and movement
of the hybrid zone in the Northeast, 2) changes in the rate of
hybridization over time, and 3) the impacts of environmental gradients
and population densities in the regulation of the hybrid zone.

\textbf{Methods and Materials:}

\emph{Pheromone surveys}

In Massachusetts, for each year from 2007-2018, adult male moths were
collected using pheromone-baited lures (Great Lakes IPM, Vestaburg, MI;
Elkinton et al., 2010, 2011) hung in plastic bucket traps (Gempler's
Inc., Janesville, WI) at points along the Massachusetts transect (Figure
1). These included 49 unique localities; however, due to factors such as
road construction, early-season snow, ice storms, vandalism, and mouse
predation, an average of 22 trap localities (\selectlanguage{ngerman}± 1.5) were sampled each
year, with a minimum of 16 traps in 2015 and a maximum of 32 traps in
2017 and 2018. In addition, after 2009, we discontinued monitoring traps
close to the Boston Metropolitan area (T21-T25) in an effort to conserve
survey resources because these traps were entirely composed of winter
moth individuals (Elkinton et al., 2014). From 2007-2016, moths were
collected from traps twice during the sampling period (late November
through early January), coinciding with observations of male moth
flight. In 2017, moths were collected during the same period weekly, and
in 2018, traps were sampled bi-weekly. For the Connecticut transect
(Figure 1), pheromone traps were deployed from 2016-2018. These included
19 localities in 2016, though due to factors mentioned above, in 2017
and 2018, only 18 and 17 of these localities were sampled, respectively.
Along this transect, moths were collected weekly from late November
through early January. A list of trap locations is provided in
Supplemental Table S1. Upon collection, moths were removed from traps,
placed in glassine envelopes (Uline Inc., Pleasant Prairie, WI), and
stored at -80°C. The total number of moths collected over the flight
period in each trap was counted to provide an estimate of relative
population density surrounding each trap location.

\emph{DNA extraction and microsatellite genotyping}

For the Massachusetts transect from 2007-2016, up to 20 moths were
selected haphazardly from each trap's pooled sampling (i.e., from
combining the contents of the two collection events). For the
Massachusetts transect traps from 2017 and 2018, and from all
Connecticut transect traps, 20 moths were selected haphazardly from each
collection event (i.e., each weekly or bi-weekly collection event was
processed independently). Prior to the isolation of genomic DNA, the
wings and uncus were preserved as morphological vouchers as these
contain characters that may be useful for species identification
(Griffin, Chandler, Andersen, Havill, \& Elkinton, 2020; Troubridge and.
Fitzpatrick 1993). The remaining body parts were placed in a 2.0 ml
microcentrifuge tube (USA Scientific Inc., Ocala, FL) with 100 \selectlanguage{greek}µ\selectlanguage{english}l of PBS
buffer (Sigma Aldrich, St. Louis, MO) and homogenized with a sterile
3/16'' stainless steel bead (GlenMills Inc., Clifton, NJ), using a
FastPrep-24 Sample Homogenizer (MP Biomedicals, Santa Ana, CA). DNA was
extracted and purified using the EZNA\selectlanguage{ngerman}® Tissue DNA extraction kit (Omega
Bio-tek; Norcross, GA), following the manufacturer protocols.

From each sample, 11 polymorphic microsatellite loci were amplified
following Havill et al. (2017), and run with the GeneScan 500 LIZ size
standard (Thermo Fisher Scientific; Waltham, MA), on a Thermo Fisher
Scientific 3730xl DNA Analyzer at the DNA Analysis Facility on Science
Hill at Yale University. Fragment lengths were scored in the software
GENEIOUS v. R11 (https://www.geneious.com), using the microsatellite
plugin.

\emph{Classification of samples to species and hybrid categories}

The probability of assignment (\emph{Z} ) of each sample as a pure Bruce
spanworm, a pure winter moth, or a hybrid (either F1, F2, Bruce
spanworm-backcross, or winter moth-backcross) was estimated using the
Bayesian-assignment program NewHybrids v 1.1 b3 (Anderson, 2008;
Anderson \& Thompson, 2002). We used uniform priors, random starting
seeds, burn-in periods of 100,000 generations, and a post-burn-in
runtime of 1,000,000 generations. A separate dataset was run for each
transect and year combination to reduce assignment errors, given that
individuals from one year could be the offspring of individuals from the
previous year. Datasets were then filtered so that only individuals with
\selectlanguage{english}[?] 10 successfully scored loci were included. Four independent runs were
performed for each dataset, and the assignment scores were then averaged
across runs. We interpreted samples with\emph{Z} \selectlanguage{english}[?] 0.75 to any one
category as obtaining ``strong support'', and samples with 0.5 \selectlanguage{english}[?]
\emph{Z} \textless{} 0.75 as obtaining ``moderate support''. If a sample
was not assigned to any category with \emph{Z} \selectlanguage{english}[?] 0.5, it was classified
as having ``weak support'' to the category with the highest \emph{Z}
score.

To determine whether there was temporal or spatial variation in
hybridization rates across each transect, the mean proportions of
hybrids were calculated by dividing the number of genotyped individuals
from each trap classified to one of the four hybrid categories by
NewHybrids (as described above). Differences between years and between
traps were compared using an analysis of variance (ANOVA) as implemented
in R v 4.0.2 (R Core Team, 2020).

\emph{Hybrid zone movement}

For each transect-year we fit hybrid zone equilibrium cline models using
population ancestry proportions to estimate the shape and center of the
hybrid zone. First, for each transect, the distance (in km) of each trap
from the respective westernmost trap for that transect (trap T00
{[}42.6714deg N, 73.0145deg W{]} for the Massachusetts transect, and trap
CT01 {[}41.0798deg N, 73.7054deg W{]} for the Connecticut transect), was
calculated using the Latitude/Longitude Distance Calculator available at
(https://www.nhc.noaa.gov/gccalc.shtml). Then, for each transect-year,
the population coefficient of assignment (\emph{Q} ) to Bruce spanworm
at each trap was estimated using the software program Structure v.2.3.2
(Falush, Stephens, \& Pritchard 2003; Pritchard, Stephens, \& Donnelly,
2000) based on two population (\emph{K=} 2) analyses using the admixture
model, correlated allele frequencies, and default settings, with random
starting values, runtimes of 200,000 generations, and burn-in periods of
20,000 generations, for each year-transect combination. Finally, using
the R package `hzar' v 0.2-5 (Derryberry, Derryberry, Maley \&
Brumfield, 2014), a null model, plus three different hybrid-zone models:
1) minimum and maximum frequencies fixed to 0 and 1, and with no
exponential decay tails, 2) minimum and maximum frequencies as free
parameters, with no exponential decay tails, and 3) minimum and maximum
frequencies as free parameters, with both tails as independent
parameters, were used to estimate the center of the hybrid zone based on
three independent analyses with chain lengths of 100,000 generations,
burn-in periods of 10,000 generations, using random starting variables
for each analysis. The maximum likelihood values for each run were then
compared to determine which model provided the best fit to the observed
dataset, from which the center of the hybrid zone and the hybrid cline
was estimated for each transect-year combination.

\emph{Comparison of minimum winter temperatures}

To document differences in minimum winter temperatures along the
Massachusetts and Connecticut transects, daily minimum temperatures were
extracted from PRISM daily minimum temperature rasters available from
the PRISM Climate Group at http://prism.oregonstate.edu in ArcMap v.
10.7.1 (Esri Inc., West Redlands, CA) for each trap location along both
transects from December 1\textsuperscript{st} through March
31\textsuperscript{st} from 2007-2018. At each trap, these results were
then averaged to produce a mean of the yearly minimum temperatures
across the twelve-year period. To determine whether there were
differences between trap localities within a transect, and globally
between the two transects, linear regression analyses were performed
with the mean of the minimum temperatures as the response variable and
distance and state as predictor variables in R.

\textbf{Results:}

\emph{DNA extraction and microsatellite genotyping}

After filtering, 9,983 adult moths were included in the analyses. This
included an average of 367.1 +- 14.81 moths per year from 2007-2016 plus
1,369 and 811 moths in 2017 and 2018, respectively, for the
Massachusetts transect, and 1,374.3 +- 123.7 moths per year from
2016-2018 for the Connecticut transect.

\emph{Classification of samples to species and hybrid categories}

Across both transects, 4,026 moths were classified as winter moth
(\emph{n} = 4,026 with strong support, and \emph{n} = 1 with moderate
support), 5,434 as Bruce spanworm (\emph{n =} 5,432 with strong
support,\emph{n} = 1 with moderate support, and \emph{n} = 1 with weak
support), and 523 as one of the four hybrid-categories with the majority
(\emph{n}= 281) being classified as F1 hybrids (\emph{n} = 254 with
strong support, \emph{n} = 23 with moderate support, and \emph{n} = 4
with weak support), 155 individuals as F2 hybrids (\emph{n} = 125 with
strong support, \emph{n} = 23 with moderate support, and \emph{n} =7
with weak support), 86 individuals as winter moth-backcrosses (\emph{n}
= 60 with strong support, \emph{n} = 18 with moderate support, and
\emph{n} = 8 with weak support) and 1 individual as a Bruce
spanworm-backcross (with moderate support). The number of moths
classified to each hybrid category along the Massachusetts transect is
presented in Table 1 and along the Connecticut transect in Table 2. The
proportions of individuals classified as winter moth, Bruce spanworm, or
to one of the four hybrid classes are presented in Figures 2 and 3a for
the Massachusetts and Connecticut transects, respectively. The numbers
of individuals assigned to each hybrid classification are presented in
Figures 4 and 3b for the Massachusetts and Connecticut transects,
respectively.

On average, we observed a hybridization rate of 5.67\% +- 0.62\% across
years along the Massachusetts transect. We found no significant
difference in hybridization rates among years along the Massachusetts
transect (P=0.332, F=1.139, df=11), however, we did observe a
significant difference in mean hybridization rates among traps for all
years combined (P=0.0024, F=1.98, df=32), though none of the pairwise
comparisons among traps were significant based on Tukey's HSD test
(Figure 5). Along the Connecticut transect, we observed a hybridization
rate of 5.97\% +- 0.91\% across years, with significant differences in
hybridization rates between years (P=0.0285, F=3.817, df=2), with the
hybridization rates between the 2017 and 2018 transect surveys being
significantly different based on Tukey's HSD test (adjusted P= 0.027).
As per the Massachusetts transect, significant differences were also
observed among traps for all years combined (P=0.0082, F=2.569, df=18),
though none of the pairwise comparisons were significant based on
Tukey's HSD test (Figure 6).

\emph{Hybrid zone movement}

For eight of the transect-years, the best fit of was the model with free
minimum and maximum frequencies and no tails, for six transect-years it
was the model with fixed frequencies and no tails, and for one
transect-year it was the model with free frequencies with tails (Table
3; Supplementary Figures S1 and S2). For the Massachusetts transect, the
analyses for 2009, 2011, and 2012 resulted in cline shapes with minimum
or maximum frequencies that did not approach 0 and 1 (Supplemental
Figure S2). This result was likely due to the fact that for those years,
we did not sample far enough into the Bruce spanworm (2009) or winter
moth (2011 and 2012) dominated areas. Consequently, these years were
left out of Figure 7 as the centers could not be accurately estimated
(Table 3). Cline analyses of the hybrid zones along the Massachusetts
and Connecticut transects indicated that the center of the hybrid zones
moved westward during our study period (Figures 7 and 8). Along the
Massachusetts transect, in 2007 the center of the hybrid zone was
located approximately 131 km from trap T00, and by 2018 the center of
the hybrid zone was located approximately 103 km from trap T00 (Table 3
and Figure 7). During our survey period, the location of the center of
the hybrid zone moved 3.1 km from 2007 to 2008, then moved more rapidly
from 2008 to 2010 (6.2 km/yr), then moved steadily westward from
2014-2017 (2.4 km/yr), before retreating eastward 7.7 km in 2018. Along
the Connecticut transect, in 2016 the center of the hybrid zone was
located approximately 109 km from trap CT01, in 2017 it moved
approximately 8.9 km west, and in 2018 the center of the hybrid zone
retreated approximately 3.1 km east (Table 3). It is therefore possible
that while we did not sample this transect prior to 2016, that a similar
westward shift occurred along the Connecticut transect as we found along
Massachusetts. For both transects, the mean population density of moths
increases dramatically just east of the hybrid zone center in the region
where winter moth is dominant (Figures 7 and 8). For the Massachusetts
transect, the cline width varied from 9.62 to 69.42 km across years with
a mean of 39.03 +- 7.01 km, and for the Connecticut transect, the cline
width varied from 26.82 to 50.3 km across years with a mean of 40.18 +-
6.97 km (Table 3).

\emph{Comparison of minimum winter temperatures}

There was a highly significant difference in the mean of the minimum
winter temperatures observed during sample period between the two
transects (t = -20.849, P \textless{} 0.001). For the Massachusetts
transect, there was also a highly significant difference across the
transect (t = 12.02, P \textless{} 0.001) with traps located in western
Massachusetts having mean minimum winter temperatures near -24degC and
those in eastern Massachusetts having mean minimum winter temperatures
near -20degC (Figure 9). The sharp increase in temperatures in the eastern
third of the Massachusetts transect (Figure 9) is associated with a
sharp decline in landscape elevation between 75 to 100 km from T00. In
contrast, there were no significant differences observed across the
Connecticut transect (t = -0.773, P \textgreater{} 0.05), with traps
located across the transect having minimum winter temperatures at or
around -17 to -16degC, and all traps on this transect located at or near
sea level.

\textbf{Discussion:}

Documenting the establishment and formation of new hybrid zones in real
time is critical for understanding the spatial and temporal nature of
these regions of genetic interchange (Abbott et al., 2013; Mallet,
2005). In addition, understanding the dynamics of hybridization between
native and non-native species may be particularly important for
understanding how invasive species become established and spread,
because reproducing with a native species could alleviate Allee effects
that limit the establishment of small populations due to stochastic
disturbances and mate-finding (Ellstrand \& Schierenbeck, 2000;
Espeland, 2013; Mesgaran et al., 2016; Pfennig, Kelly, \& Pierce, 2016;
Yamaguchi, Yamanaka, \& Liebhold, 2019). Here, we document the real time
formation of a clinal (sensu Taylor et al., 2015) hybrid zone, following
the introduction of the invasive winter moth to the northeastern United
States. Our analyses suggest that the location of the center of this
hybrid zone might not be regulated primarily by environmental variables,
but appears to be behaving as a tension hybrid zone. Tension hybrid
zones are characterized by their independence from environmental
variables, narrow geographic width, low frequencies of hybridization,
and with the geographic location determined by a balance between
dispersal (dependent on population density) and selection against
hybrids (Barton \& Hewitt, 1985; Key, 1968; Smith, Hale, Kearney,
Austin, \& Melville, 2013). As shown by examining our two transects, the
hybrid zone is narrow, with a mean of \textasciitilde{} 40 km across all
years in both transects, and hybridization rate is low
(\textasciitilde{} 6 \% in both transects). The location of the hybrid
zone also appears to be dependent on population size, which would
influence dispersal rate because the center of the hybrid zone is near
the region where the population size of winter moth drops to where it is
similar to the endemic Bruce spanworm populations (Figures 7 and 8). The
final feature of a tension zone, low hybrid fitness, has also been
demonstrated in this system. Laboratory rearing of winter moth and Bruce
spanworm produced 93.5 and 94.1\% viable eggs, respectively, while
crosses between winter moth females and Bruce spanworm males produced
60.8\% viable eggs and crosses between Bruce spanworm females and winter
moth males produced just 22.1\% viable eggs (Havill et al., 2017). The
near complete lack of Bruce spanworm backcrosses also indicates low
hybrid fitness in this system (Havill et al., 2017; Andersen et al.,
2019; this study). Interestingly, these two species appear to have few
pre-zygotic barriers to hybridization since they share the same sex
pheromone (Elkinton et al., 2011) and have overlapping mating flight
periods (Andersen, unpublished data). The barriers to hybridization in
this system, therefore, appear to be almost entirely made up of
post-zygotic incompatibilities resulting from \textgreater{} 500,000
years of allopatric divergence (based on an averaged observed
mitochondrial percent divergence between these two species of 7.5\%
documented in Gwiazdowski, Elkinton, DeWaard, \& Sremac, 2013; and the
newly calibrated mitochondrial mutation rate of approximately 14.5\% per
million years for insects presented in Key, Frederick, \& Schul, 2018).

Separating environmental factors (e.g., climate, land use, etc.) from
population factors (e.g., dispersal, abundance, hybrid fitness, etc.),
may not always be entirely feasible, and could, in part, explain why
there is a paucity of documented examples of this type of hybrid zone
between an introduced and a native species. However, by comparing our
two transects that differed in extreme minimum temperatures
(Massachusetts from -20degC to -24degC, and Connecticut \textasciitilde{}
-17degC), our results indicate that extreme minimum winter temperatures
are not constraining the geographic location or width of the winter moth
x Bruce spanworm hybrid zone. That said, it should be noted that
researchers in Europe have observed that populations of winter moth can
rapidly adapt to changes in environmental conditions (van Asch, Salis,
Holleman, van Lith, \& Visser, 2013), and as such the winter moth x
Bruce spanworm hybrid zone presents an exciting system to study the
combined roles of local adaptation and hybridization in the
establishment an invasive species under changing climate regimes.

In contrast to direct environmental constraints on the location of the
hybrid zone, we believe that population factors are more important for
explaining the differences in relative population densities of these two
species and therefore the stability and dynamics of the hybrid zone. One
such constraint might be top-down pressure by natural enemies of both
species. The biological control of winter moth in North America is one
of the best-known examples of the successful use of importation
biological control (Van Driesche et al., 2010) to reduce the ecological
and economic impacts of a non-native forest defoliator with a broad host
range (Elkinton et al., 2015; Embree, 1966; Kimberling et al., 1986;
Roland \& Embree, 1995). Recently, Elkinton et al\emph{.} (2021) showed
that the introduction of a single specialist natural enemy to the
Northeast was able to convert winter moth to non-pest status. These
introduced natural enemies have been incredibly effective at reducing
the abundance of winter moth in high density locations, but at low
densities, numerous authors have found that native pupal parasitoids
play an important role in regulating winter moth population sizes
(Frank, 1967a, 1967b; Horgan, 2005; Horgan \& Myers, 2004; Latto \&
Hassell, 1987; Raymond et al., 2002; Roland, 1994; Roland \& Embree,
1995, Broadley 2018). For example, in the Northeast, Broadley (2018)
found that mortality caused by native generalist pupal parasitoids was
lowest in the eastern coastal regions and increased as she sampled
locations into the western interior portions of this region. Pupal
parasitism could therefore play an important role in limiting the
population sizes of both species, and as a result providing the
necessary balance for a tension hybrid zone to exist in this system (see
Taylor et al., 2015). It will be interesting to observe whether the
location of the hybrid zone shifts east as the population density of
winter moth continues to decrease due to the impacts of biological
control. Indeed, the eastward retreat of the hybrid zone in 2018, the
last year of our study (Figures 7 and 8), may indicate that this has
begun.

It is commonly acknowledged that during the invasion process, the
probability of establishment of non-native species can be influenced by
native predators, parasitoids, competitors, and/or microbial communities
through a process known as biotic resistance (Alpert, 2006; Dawkins \&
Esiobu, 2016; Kimbro, Cheng, \& Grosholz, 2013; Levine, Adler, \&
Yelenik, 2004). For several decades there has been considerable concern
expressed in the literature about the risk of hybridization between
native and introduced species resulting in the ``hybridization to
extinction'' of the native species (Allendorf et al., 2001; Ayres,
Zaremba, \& Strong, 2004; Hinton, 1975; Levin, 2002; Levin,
Francisco-Ortega, \& Jansen, 1996; Prentis, White, Radford, Lowe, \&
Clarke, 2007; Rhymer \& Simberloff, 1996; Todesco et al., 2016; Wolf,
Takebayashi, \& Rieseberg, 2001). Under a tension hybrid zone model,
however, the continued exchange of genetic material and the resulting
production of low-fitness hybrids, could result in a reduction in the
rate of spread of the introduced species by stabilizing the geographic
center of the hybrid zone, creating what we believe is an
underappreciated form of biotic resistance to invasion
(\emph{sensu}Levine et al., 2004). As such, we encourage additional
research into the possible role of hybridization for limiting the
establishment and spread of non-native species.

\emph{Conclusions}

Here we present, to our knowledge, the first example of the real-time
establishment of a clinal hybrid zone between a non-native invasive
insect pest and a native species. This hybrid zone appears to be a
tension hybrid zone, with hybrid individuals having reduced fitness
compared to their parents, with the geographic center of the hybrid zone
constrained by the population sizes of the two parent-species, rather
than directly in relationship to an environmental or landscape variable.
By examining two transects (separated by less than 125 km), we find
evidence that the temporal and spatial dynamics of hybrid zones are
complex, and we encourage further examination of the spatial and
temporal dynamics of hybrid zones between native and non-native species
so that comparative analyses can be conducted. Lastly, our results
highlight the importance of long-term datasets for the study of
evolutionary biology and invasion ecology, and we encourage future work
to reexamine the movement and stability of this hybrid zone.

\textbf{Acknowledgments:} The authors are extremely grateful to Ron
Weeks at USDA APHIS for encouraging our research into the population
genetics of winter moth. We would also like to thank Stephanie Sayson,
DeAdra Newman, David Mikus, and Brian Griffin for their laboratory
assistance, and Rodger Gwiazdowski and Michelle Labbe for comments on
earlier versions of this manuscript. Funding was provided by grants from
USDA APHIS AP17PPQS\&T00C068, AP18PPQS\&T00C070, and AP19PPQFO000C125,
awarded to JSE, and USDA Forest Service, Northern Research Station award
17-CR-11242303-066 to AC.



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\textbf{Data Accessibility:} Genotype scores for all samples are
provided as a structure datafile in single-column format in the
Supplemental files.

\textbf{Author Contribution:} All authors contributed to the study
design and the preparation of the manuscript. JCA and NPH analyzed the
genetic datasets. JLC analyzed the climate dataset. GHB and JLC
collected field samples. AC and JSE provided laboratory access.

\textbf{Tables and Figures:}

\textbf{Table 1:} Number of moths classified as winter moth, Bruce
spanworm, F1 hybrids (``F1''), F2 hybrids (``F2''), winter
moth-backcross, or Bruce spanworm-backcross for each surveyed transect
year from 2007-2018 in Massachusetts using NewHybrids.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Year} & \textbf{Winter Moth} & \textbf{Bruce Spanworm} &
\textbf{F1} & \textbf{F2} & \textbf{Winter Moth-Backcross} &
\textbf{Bruce Spanworm-Backcross}\tabularnewline
\midrule
\endhead
2007 & 110 & 227 & 12 & 0 & 3 & 0\tabularnewline
2008 & 164 & 195 & 7 & 0 & 1 & 0\tabularnewline
2009 & 298 & 132 & 28 & 2 & 14 & 0\tabularnewline
2010 & 85 & 223 & 7 & 3 & 7 & 0\tabularnewline
2011 & 147 & 240 & 29 & 1 & 0 & 0\tabularnewline
2012 & 129 & 203 & 20 & 1 & 3 & 0\tabularnewline
2013 & 154 & 167 & 17 & 0 & 2 & 0\tabularnewline
2014 & 133 & 178 & 25 & 2 & 4 & 0\tabularnewline
2015 & 177 & 123 & 18 & 1 & 0 & 1\tabularnewline
2016 & 181 & 182 & 8 & 0 & 7 & 0\tabularnewline
2017 & 326 & 975 & 15 & 14 & 29 & 0\tabularnewline
2018 & 257 & 527 & 24 & 1 & 2 & 0\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 2:} Number of moths classified from 216-2018 in
Connecticut as per Table 1.\selectlanguage{english}
\begin{longtable}[]{@{}lllllll@{}}
\toprule
\textbf{Year} & \textbf{Winter Moth} & \textbf{Bruce spanworm} &
\textbf{F1} & \textbf{F2} & \textbf{Winter Moth-Backcross} &
\textbf{Bruce spanworm- backcross}\tabularnewline
\midrule
\endhead
2016 & 549 & 746 & 44 & 9 & 6 & 0\tabularnewline
2017 & 793 & 681 & 14 & 103 & 7 & 0\tabularnewline
2018 & 514 & 625 & 13 & 18 & 1 & 0\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table 3:} Best-fit cline model and geographic location of the
cline center of the winter moth x Bruce spanworm hybrid zone for the
Massachusetts transect for each year from 2007-2018, and Connecticut
transect for 2016-2018, estimated using the R package `hzar'. The
confidence interval two log likelihood units above and below the center
and width values are in parentheses. Cline centers and widths for 2009,
2011, and 2012 could not be estimated due to failures in model
conversion.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Transect} & \textbf{Year} & \textbf{Model} & \textbf{Cline
Center (km)} & \textbf{Cline Width (km)}\tabularnewline
\midrule
\endhead
Massachusetts & 2007 & Fixed frequencies, no tails & 130.64 (129.05,
132.18) & 14.02 (10.83, 18.33)\tabularnewline
Massachusetts & 2008 & Free frequencies, no tails & 127.56 (126.05,
128.95) & 9.87 (6.62, 14.16)\tabularnewline
Massachusetts & 2009 & Free frequencies, no tails & N/A &
N/A\tabularnewline
Massachusetts & 2010 & Fixed frequencies, no tails & 115.23 (109.97,
121.12) & 69.42 (53.42, 92.55)\tabularnewline
Massachusetts & 2011 & Free frequencies, no tails & N/A &
N/A\tabularnewline
Massachusetts & 2012 & Free frequencies, no tails & N/A &
N/A\tabularnewline
Massachusetts & 2013 & Free frequencies, with tails & 107.13 (103.42,
110.49) & 49.07 (39.11, 63.1)\tabularnewline
Massachusetts & 2014 & Fixed frequencies, no tails & 104.66 (100.41,
108.57) & 53.66 (42.19, 68.94)\tabularnewline
Massachusetts & 2015 & Fixed frequencies, no tails & 102.44 (98.79,
105.68) & 42.84 (34.17, 54.8)\tabularnewline
Massachusetts & 2016 & Fixed frequencies, no tails & 98.64 (94.24,
102.52) & 47.57 (38.02, 60.16)\tabularnewline
Massachusetts & 2017 & Free frequencies, no tails & 95.84 (93.03, 97.21)
& 9.62 (5.89, 21.3)\tabularnewline
Massachusetts & 2018 & Fixed frequencies, no tails & 103.58 (100.4,
106.66) & 55.17 (47.25, 64.7)\tabularnewline
Connecticut & 2016 & Fixed frequencies, no tails & 109.23 (106.75,
111.97 & 43.41 (37.25, 49.11)\tabularnewline
Connecticut & 2017 & Fixed frequencies, no tails & 100.31 (97.22,
103.19) & 50.3 (40.56, 58.34)\tabularnewline
Connecticut & 2018 & Fixed frequencies, no tails & 103.42 (101.01,
105.77) & 26.82 (21.85, 32.84)\tabularnewline
\bottomrule
\end{longtable}

\textbf{Hosted file}

\verb`image1.emf`  available at \url{https://authorea.com/users/388368/articles/539000-real-time-geographic-settling-of-a-hybrid-zone-between-the-invasive-winter-moth-operophtera-brumata-l-and-the-native-bruce-spanworm-o-bruceata-hulst}

\textbf{Figure 1.} Locations of survey traps along the Massachusetts
transect (blue) and the Connecticut transect (yellow). The western and
eastern most points along each transect are labeled for reference, as
are the traps most proximal to the center of the hybrid zone in 2018.

\textbf{Hosted file}

\verb`image2.emf`  available at \url{https://authorea.com/users/388368/articles/539000-real-time-geographic-settling-of-a-hybrid-zone-between-the-invasive-winter-moth-operophtera-brumata-l-and-the-native-bruce-spanworm-o-bruceata-hulst}

\textbf{Figure 2.} Proportional assignment of individuals collected
along the Massachusetts transect as either pure winter moth (black),
pure Bruce spanworm (white), or to one of four hybrid categories (grey)
in NewHybrids.

\textbf{Hosted file}

\verb`image3.emf`  available at \url{https://authorea.com/users/388368/articles/539000-real-time-geographic-settling-of-a-hybrid-zone-between-the-invasive-winter-moth-operophtera-brumata-l-and-the-native-bruce-spanworm-o-bruceata-hulst}

\textbf{Figure 3.} Proportional assignment of individuals collected
along the Connecticut transect as either pure winter moth (black), pure
Bruce spanworm (white), or to one of four hybrid categories (grey) in
NewHybrids (A). The number of genotyped individuals classified as F1
hybrids (red), F2 hybrids (orange), or winter moth backcrosses (blue)
are presented in part B.

\textbf{Hosted file}

\verb`image4.emf`  available at \url{https://authorea.com/users/388368/articles/539000-real-time-geographic-settling-of-a-hybrid-zone-between-the-invasive-winter-moth-operophtera-brumata-l-and-the-native-bruce-spanworm-o-bruceata-hulst}

\textbf{Figure 4.} The number of genotyped individuals classified as F1
hybrids (red), F2 hybrids (orange), or winter moth backcrosses (blue) as
calculated in NewHybrids.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Figure 5.} The average percentage (\selectlanguage{ngerman}± SE) of genotyped
individuals classified as hybrids in 2007-2018 (A), and the average
percentage (± SE) of genotyped individuals classified as hybrids at each
trap (B) for all years across the Massachusetts transect.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Figure 6.} The average percentage (\selectlanguage{ngerman}± SE) of genotyped
individuals classified as hybrids in 2016-2018 (A), and the average
percentage (± SE) of genotyped individuals classified as hybrids at each
trap (B) for all years across the Connecticut transect.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Figure 7.} Cline analysis showing the fit of the best model
based on the proportional assignment of populations to the Bruce
spanworm genetic cluster (\emph{Q} ) for each sampled year along the
Massachusetts transect (top) and the geographic center \selectlanguage{ngerman}± 2LL as
estimated in the R package `hzar' (middle). The number of individuals
collected at each trap averaged across the 2007-2018 sample years
(bottom). Distances are presented in relationship to T00.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

\textbf{Figure 8.} Cline analysis showing the fit of the best model
based on the proportional assignment of populations to the Bruce
spanworm genetic cluster (\emph{Q} ) for each sampled year along the
Connecticut transect (top) and the geographic center \selectlanguage{ngerman}± 2LL as estimated
in the R package `hzar' (middle). The number of individuals collected at
each trap averaged across the 2016-2018 sample years (bottom). Distances
are presented in relationship to CT01.

\textbf{Hosted file}

\verb`image9.emf`  available at \url{https://authorea.com/users/388368/articles/539000-real-time-geographic-settling-of-a-hybrid-zone-between-the-invasive-winter-moth-operophtera-brumata-l-and-the-native-bruce-spanworm-o-bruceata-hulst}

\textbf{Figure 9.} Mean absolute minimum temperatures as extracted from
the PRISM dataset for trap locations along the Massachusetts transect
(dashed line) and the Connecticut transect (solid line) from December
1\textsuperscript{st} through March 31\textsuperscript{st} for
2007-2018. Distances are presented in relationship to T00 for the
Massachusetts transect, and CT01 for the Connecticut transect.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1---Winter-Moth-Survey-Traps/Figure-1---Winter-Moth-Survey-Traps}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-2---Route-2---Stacks---Proportions---All-Years/Figure-2---Route-2---Stacks---Proportions---All-Years}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-3---Route-1---Proportions-and-Hybrid-Classes/Figure-3---Route-1---Proportions-and-Hybrid-Classes}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-4---Route-2---Stacks---Hybrid-Classes---All-Years/Figure-4---Route-2---Stacks---Hybrid-Classes---All-Years}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-5---Route-2---Hybrid-Averages/Figure-5---Route-2---Hybrid-Averages}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-6---Route-1---Hybrid-Averages/Figure-6---Route-1---Hybrid-Averages}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-7---MA-all-years-95credible-cline-plot-updated/Figure-7---MA-all-years-95credible-cline-plot-updated}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-8---CT-all-years-95credible-cline-plot/Figure-8---CT-all-years-95credible-cline-plot}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-9---20210827-WM-mean-abs-min-winter-temp/Figure-9---20210827-WM-mean-abs-min-winter-temp}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

