Diversity and Distributions. 2023;29:1263–1277.
Received: 2 May 2022
Revised: 17 June 2023
Accepted: 13 July 2023
DOI : 10.1111/ddi .13755
Nonnative plant invasion increases urban vegetation structure
and influences arthropod communities
J. Christina Mitchell1 | Vincent D'Amico III2 | Tara L. E. Trammell3 | Steven D. Frank1
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2023 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd.
1Department of Entomology and
Plant Pathology, North C arolina State
University, Raleigh, North Carolina, USA
2USDA Forest Service, Northern Research
Station, NRS- 08, Newark, Delaware, USA
3Department of Plant and Soil Sciences,
University of Delaware, Newark,
J. Christina Mitchell, Department of
Entomology and Plant Pathology, North
Carolina State University, Campus Box
7613, Raleigh, NC 27965, USA.
North Carolina Forest Service; North
Carolina Invasive Plant Council; North
Carolina State University Department
of Entomology and Plant Patholog y;
U.S. Department of Agriculture, Grant/
Award Number: 2016- 70006- 25827
and 2018- 70006- 28914; U.S. Geological
Survey, Grant/Award Number:
G19AP00041; University of Delaware
Editor: Marion Pfeifer
Aim: Ecological theory and empirical evidence indicate that greater structural com-
plexity and diversity in plant communities increases arthropod abundance and diver-
sity. Nonnative plants are typically associated with low arthropod abundance and
diversity due to lack of evolutionary history. However, nonnative plants increase the
structural complexity of forests, as is common in urban forests. Therefore, urban for-
ests are ideal ecosystems to determine whether structural complexity associated with
nonnative plants will increase abundance and diversity of arthropods, as predicted
by complexity literature, or whether structural complexity associated with nonnative
plants will be depauperate of arthropods, as predicted by nonnative plant literature.
Location: We sampled 24 urban temperate deciduous and mixed forests in two cites,
Raleigh, North Carolina and Newark, Delaware, in the eastern United States.
Methods: We quantified ground cover vegetation and shrub layer vegetation in each
forest and created structural complexity metrics to represent total, nonnative and
native understory vegetation structural complexity. We vacuum sampled arthropods
from vegetation and quantified the abundance, biomass, richness and diversity of spi-
ders and non- spider arthropods.
Results: Nonnative plants increase understory vegetation complexity in urban for-
ests. In Raleigh and Newark, we found suppor t for the hypotheses that dense vegeta-
tion will increase arthropod abundance and biomass, and against the hypothesis that
nonnative vegetation will decrease arthropods. Urban forest arthropod abundance
and biomass, but not diversity, increased with greater nonnative and native structural
Main Conclusions: Invaded urban forests may provide adequate food in the form of
arthropod biomass to transfer energy to the next trophic level, but likely fail to pro-
vide ecological services and functions offered by diverse species, like forest special-
ists. Urban land managers should survey urban forests for nonnative and native plant
communities and prioritize replacing dense nonnative plants with native species when
allocating vegetation maintenance resources.
MITCHELL et al .
1 | INTRODUC TION
Ecological theory and empirical evidence indicate that vegetation
structural complexity and plant diversity increase arthropod abun-
dance and diversity (Andow, 1991; Borer et al., 2012; Carmona
& Landis, 1999; Haddad et al., 2009; Root, 1973; Thomas &
Marshall, 1999; Tilman, 1999). Denser and more complexly- structured
veget ation can provi de mor e foo d and sh elte r reso u rce s to ar thr opods
than simple structured vegetation (Landis et al., 2005; Tilman, 1999).
One aspect of vegetation complexity is species diversity. Diverse plant
communities offer more diverse resources to generalist and special-
ist arthropods compared to monotypic plant communities, including
diverse plant and prey food resources, reproductive and nesting re-
sources, and microclimates (Haddad et al., 2009; O'Brien et al., 2017;
Thomas & Marshall, 1999). Diverse plant communities therefore sup-
port greater arthropod abundance and diversity (Haddad et al., 20 09,
O'Brien et al., 2017, Thomas & Marshall, 1999). Changes in plant
communities affect each trophic level differently, altering amounts
of herbivore and predator species in arthropod communities (Ebeling
et al., 2014; Haddad et al., 2009; Koricheva & Hayes, 2018; O'Brien
et al., 2017; Schuldt et al., 2014; Southwood et al., 1982).
Arthropods form a necessary component of the global food web
for a suite of wildlife and are often ecologically tied to plant com-
munities. This group is diverse, demonstrating variable responses
to changes in the environment (Haddad et al., 2009; Hamilton
et al., 2013; Koricheva & Hayes, 2018). Arthropods are experi-
encing global declines, which can disrupt energy transfer in food
webs and affect ecosystem services (Hallmann et al., 2017; Lister
& Garcia, 2018; Sánchez- Bayo & Wyckhuys, 2019). Arthropods are
a particularly important food resources for birds, providing calcium
and amino acids, and arthropods in urban forests are often crucial
to bird success in urban environments (Long & Frank, 2020; Nagy
& Holmes, 2005; Seress et al., 2018). The phenology of strict her-
bivores like caterpillars, the larval form of butterflies and moths in
the order Lepidoptera, are reliant on particular plant communities
(Koricheva & Hayes, 2018). When changes in plant communities
occur, herbivore communities can respond with changes in abun-
dance and biomass (Koricheva & Hayes, 2018), or rich ne ss and diver-
sity (Haddad et al., 2009). Strict predators like spiders, in the order
Araneae, are an ecologically important taxa (New, 1999) and can be
indirectly tied to plant communities that sustain large communities
of prey (Haddad et al., 2009). One study reported a greater effect of
plant diversity on predators than on herbivores, suggesting plants
may affect predators independent of herbivore dynamics (Koricheva
& Hayes, 2018). Haddad et al. (2009) found a threefold increase
in predator abundances in areas of high plant richness, without a
similar increase in herbivorous prey, suggesting differing dynam-
ics between plant diversity and herbivore and predator responses.
Together, changes in plant communities can drastically alter arthro-
pod abundance, biomass, richness and diversity.
As the number and abundance of nonnative plant species in-
creases, it is important to understand any effect nonnative plants
may have on the environments and communities in which they in-
teract (Haddad et al., 2009; Koricheva & Hayes, 2018). Nonnative
plant species can increase forest structural complexity and influ-
ence plant diversity (Dyderski & Jagodziński, 2020; Hartman &
McCar thy, 2008; Trammell & Carreiro, 2011). Nonnative plant in-
vasion can increase plant diversity by adding novel species to an
area (Kowarik, 2011; Maskell et al., 2006), which may contribute
to greater structural complexity and increase arthropod diversity
(Borer et al., 2012; Landsman et al., 2020). Alternatively, nonnative
plant invasion can reduce plant diversity by outcompeting native spe-
cies and suppressing native species growth (Tanner & Gange, 2013;
Trammell et al., 2012), which can reduce resources and subsequently
arthropod diversity (Ballard et al., 2013; Burghardt & Tallamy, 2013;
Richard et al., 2018; Tallamy, 2004; Tallamy & Shropshire, 2009).
Additionally, nonnative plant species are geographically separated
from their native arthropod community and therefore lack an evo-
lutionary history with arthropods native to the invaded area. This
means that adding nonnative plants to a community does not nec-
essarily increase food resources for local herbivores and can reduce
arthropod diversity as existing species are outcompeted (Adams
et al., 2009; Kadlec et al., 2018; Narango et al., 2018). Arthropods
frequently encounter nonnative plants in human- dominated land-
scapes, both in residential plantings and in disturbed areas, where
nonnative plants released from the ornamental plant trade often
thrive (Dyderski & Jagodziński, 2019; Lehan et al., 2013; Pickett
& Cadenasso, 2009; Reichard & White, 2001). Nonnative plant in-
vasions are common in urban forests which are often adjacent to
managed landscapes and frequently disturbed by human activities
(Malkinson et al., 2018; Pickett et al., 20 01).
Forests in urban areas are being recognized for their potential to
conserve native species and natural resources (Aronson et al., 2014;
Ives et al., 2016; Kowarik, 2011; Mcdonald et al., 2008; Trammell
et al., 2020). Urban forests can contain diverse native biotic commu-
nities, including plants (Aronson et al., 2014; Ives et al., 2016; Kühn
et al., 2004; Pregitzer et al., 2 019; Trammell et al., 2020), arthropods
(Agra Iserhard et al., 2018; Croci et al., 2008; de Andrade et al., 2019;
Landsman et al., 2 019; Tonietto et al., 2011), birds, mammals, rep-
tiles, and amphibians (Aronson et al., 2014; Croci et al., 2008; Lerman
et al., 2021; MacGregor- Fors et al., 2016; Nielsen et al., 2014), bu t are
often degraded by city infrastructure expansion and development,
altered environmental conditions like the urban heat island effect
and pollution, and nonnative species invasions (Beninde et al., 2015;
Malkinson et al., 2018; Mcdonald et al., 2008; McDonnell et al., 1997;
Pickett et al., 2001; Seto et al., 2012). Nonnative plants are
arthropod communities, insects, native, nonnative, spiders, understory structural diversity,
MITCHELL et al.
particularly common in urban forests (Aronson et al., 2015; Burton &
Samuelson, 2008; Malkinson et al., 2018; McKinney, 2008; Mitchell
et al., 2023b). Th ere for e , we can use the un derstorie s of ur ban fo r e s t s
to disentangle the effects of dense vegetation from dense native or
nonnative vegetation and determine whether hypotheses from plant
complexity literature or nonnative plant literature better explain
tren ds in arth ropod abun dance and diversity. We studied th is topic in
two cities, to determine if relationships between plant and arthropod
communities are consistent, or not, in different regions with differ-
ent nonnative plant communities. Previous reports suggest plant and
arthropod communities differ between cities at different latitudes
(Long et al., 2019; Mitchell et al., 2023b; Youngsteadt et al., 2017).
We were interested in addressing (1) whether arthropods responded,
in abundance, biomass, richness or diversit y metrics, to the presence
of understory vegetation, or specifically to the presence of native or
nonnative vegetation, and (2) whether a difference in response could
be detected at the order level (all arthropods) or family level (spiders
only). We analysed spiders separately from other arthropods be-
cause they are strict predators and an ecologically important taxon
(New, 1999), abundant and gave an opportunity to compare trends
at a refined taxonomic resolution. We also analysed relationships be-
tween caterpillar abundance and biomass, and total, nonnative and
native structural complexity, to determine if a strict herbivore group
responded differently than arthropods combined.
2 | METHODS
2.1 | Site selection and vegetation sampling
This research was conducted in Raleigh, North Carolina (35.778928,
- 78.639183) and Newark, Delaware (39.683016, - 75.753548) USA as
part of the FRAME (FoRests Among Managed Ecosystems, ht t p s : //
sites.udel.edu/frame/) network of forests used to study urban for-
est ecology. We sampled 12 urban forests in each city for a total of
24 temperate deciduous and mixed forests within the eastern US
(Mitchell et al., 2023b, EMS Figure 1). We established a 25 m × 25 m
flagged grid within each forest and randomly selected 10 points
from each, with the stipulation that they could not be immediately
next to each other. We sampled plant communities at these points,
hereafter called sampling locations, during the summer growing sea-
son in Newark forests in 2015 and in Raleigh forests in 2017, for a
total of 239 sampling locations (one small forest only accommodated
nine; Mitchell et al., 2023b; Trammell et al., 2020). Plant communities
within the FRAME have been extensively described, including over-
story and understory trees and understory woody and herbaceous
vegetation (Table 1; Landsman et al., 20 19; Mitchell et al., 2023b;
Trammell et al., 2020). We measured understory vegetation at two
strata within a 2.5- m radius (19.6- m2 area) flagged circle surround-
ing sampling locations; we estimated percentage cover by ground
layer vegetation, and we counted stems in the shrub layer vegeta-
tion. We defined ground vegetation as any plant species, including
woody and herbaceous species, <0.5 m tall. We estimated percentage
cover by nonnative and native ground vegetation, and identified the
most abundant nonnative and native species. We defined a nonna-
tive species as one not occurring in the lower 48 states of America
prior to 1600 CE (Gleason & Cronquist, 1991; Trammell et al., 2020;
Weakley, 2015). We defined shrub layer vegetation as any plant stem,
including woody and herbaceous species, reaching 1.0 m or taller and
less than or equal to 2.5- cm diameter at breast height (1.4 m; Nowak
et al., 2008; Figure 1). We identi fie d and categorized cou nted stems as
native or nonnative, and we combined ground cover and stem density
species identifications to determine total understory plant richness.
All species were identified in the field with select identifications con-
firmed by the North Carolina State University Herbarium Curator.
2.2 | Arthropod collecting and processing
We collected arthropods within each forest from the same locations
established for plant community sampling (N = 239) but expanded the
sampling circle to 5 m radius (78.5 m2). In 2019, vacuum samples were
collected twice in Raleigh between June 14– 19 and July 17– 19 and in
Newark between June 22– 24 and July 22– 25. Understory vegetation
FIGURE 1 Schematic diagram (left) showing the flagged grid across the sampled forest area (white dots) and 10 sampling locations (dark
green dots) where plant and arthropod sampling occurred; a depiction (right) of how understory plant stems were counted (adapted from
Mitchell et al., 2023b, figure 1).
MITCHELL et al .
was vacuumed for 3 min (Figure 2); conte nt s were contained in a mesh
bag and stor ed in the fie ld in a large kill jar until returne d to the lab and
transferred samples to the freezer until processing (Mitchell, 2021).
All non- arthropod material was carefully removed from vacuum
samples in the lab prior to arthropod identification and weighing
(Mitchell, 2021). Arthropods were identified to order and placed
in separate, based on sampling location, pre- weighed 1.5 mL vials
(VWR® Micro Centrifuge Tubes, Cat. No. 10025- 724) and topped
with 95% ethanol for temporary storage. If present, caterpillars (213
larval Lepidoptera from 20 0 sampling locations) were placed in a sec-
ond pre- weighed vial and topped with 95% ethanol. Spiders (order
Araneae) were identified further to family (Bradley, 2 019; Ubick
et al., 2009), and placed in a third pre- weighed vial and topped with
95% ethanol. To quantify biomass, vials were left open under a hood
for 24 h to allow excess ethanol to evaporate, then dried in a 50°C
drying oven for 48 h (McCluney et al., 2017). Once dry, all vials were
clos ed an d weighed in millig rams and biom ass was dete rmi ned by su b-
tracting each vial's empty weight from its full weight (Mitchell, 2021).
2.3 | Vegetation structural complexity metrics
To separate the effects of nonnative and native vegetation from the
structure of all understory vegetation, we created three similarly
constructed vegetation structural complexity metrics. Each metric
was created using three vegetation variables collected from the same
sampling locations (N = 239): percentage ground cover, stem counts
and understory species diversity, which was determined using the
Shannon diversity index (H). To represent total structural complex-
ity, our metric incorporated percentage of total ground cover, total
stem counts and shrub layer plant diversity. We combined data from
both cities to determine the full data range for total ground cover
(1%– 100%), total stem counts (1– 182), and total shrub layer diversity
(0.1– 1.8); this was to ensure valid comparisons between cities. Since
each vegetation variable was measured in a different unit (percent,
count, number), we divided each range of raw data values sampled
for each variable into five, equally divided bins (equivalent to 0.1– 1.0,
1.1– 2.0, 2.1– 3.0, 3.1– 4.0, 4.1– 5.0) that represented increasing com-
plexity. Each raw data value was associated with its representative
bin of increasing complexity (1– 5; least to most complex), and once
all raw data values were reassigned with a bin number, we summed
bin numbers across the three variables to create a metric value rep-
resenting total understory structural complexity for each sampling
location (possible range: 0– 15). The nonnative and native complexity
metrics were then created using the same bin ranges created for the
total complexity metric, to ensure they were at comparable scales
for analyses. However, the nonnative structural complexity metric
was created using raw data values of percentage nonnative ground
cover, nonnative stem counts and nonnative understory diversity,
while the native structural complexity metric was created using raw
data values of percentage native ground cover, native stem counts
and native understory diversity.
TAB LE 1 Summary of urban forest size and dominant plant species found within the sampled area.
City Average forest size (ha)
Average sampled forest
Most dominant over story
Most dominant understory
Raleigh, NC 13.3 3.7 Pinus taeda Ligustrum sinense
Newark, DE 42.7 6.8 Acer rubrum Rosa multiflora
Note: Dominance was determined for overstor y vegetation (above 2.5- cm diameter at breast height; 1.4 m) by incorporating species abundance and
volume. Dominance was determined for understory vegetation (<2.5- cm diameter at breast height; 1.4 m) by abundance.
FIGURE 2 Differences between (a) high structural complexity and (b) low structural complexity, as found within one urban forest in
MITCHELL et al.
2.4 | Statistical analyses
All analyses were conducted in R version 4.0.5 (R Core Team, 2021).
We pooled arthropod data collected at our two time points by sam-
pling location (N = 239) and calculated total abundance, biomass,
richness (order level for non- spider arthropods and family level for
spiders), and Shannon diversity index (H; order level for non- spider
arthropods and family level for spiders) for non- spider arthropods
and spiders. We separately analysed relationships between caterpil-
lar abundance and biomass, and total, nonnative and native struc-
To determine how well native and nonnative plants predicted
total structural complexity, we used linear regression analyses to
elucidate relationships between predictor variables (nonnative un-
derstory richness, native understory richness, nonnative structural
complexity metric, and native structural complexity metric) and
the response variable, total structural complexity metric. Our re-
sponse variable met the assumptions for normalcy, so we fit these
regressions to a gaussian distribution (Ives, 2015; Zuur et al., 2010).
Though we anticipated a Poisson distribution, comparisons of ‘best
fit’ confirmed the use of gaussian models in analyses. To determine
how arthropods responded to total structural complexity, we used
linear regressions to determine relationships between our predictor
variable, total structural complexity, and arthropod metric response
variables (non- spider arthropod and spider abundance, biomass,
ri chnes s and div ersit y). We lo g (x + 1) transformed non- spider arthro-
pod and spider abundance and biomass data to improve normalcy
but did not transform non- spider arthropod and spider richness or
diversity, and fit regressions to a gaussian distribution (Ives, 2015,
Zuur et al., 2010). To determine how arthropods responded specifi-
cally to nonnative and native structural complexity, we used the lmer
function from the ‘lme4’ package (Bates et al., 2015) to create mixed
effect models for each city. We specified nonnative plant structural
complexity, native plant structural complexity, and their interaction
as our predictor variables and ran models for each of the follow-
ing response variables: non- spider arthropod abundance, biomass,
richness, diversity and spider abundance, biomass, richness and di-
versity. Forest site (N = 24) was included in all models as a random
3 | RESULTS
3.1 | Plant origin and understory plant structural
In both cities, total structural complexity increased as nonnative
understory plant richness increased (Raleigh: r2 = .350, p < .001;
Newark: r2 = .200, p < .001; Figure 3a) and as nonnative structural
complexity increased (Raleigh: r2 = .570, p < .001; Newark: r2 = .530,
p < .001; Figure 3c). In Raleigh, total structural complexity had no
relationship with native understory plant richness (r2 = .020, p = .156;
Figure 3b), but increased as native structural complexity increased
(r2 = .210, p < .001; Figure 3d). In Newark, total structural complexity
increased as native understory plant richness increased (r2 = .260,
p < .001; Figure 3b) and as native structural complexity increased
(r2 = .630, p < .001; Figure 3d).
3.2 | Understory plant structural complexity and
Responses varied by city, but non- spider arthropods and spiders
shared consistent trends across all tested relationships. The ar-
thropod orders Araneae (spiders), Diptera (flies), Hemiptera (true
bugs), and Hymenoptera (sawflies, wasps, bees, and ants) were
most abundant in both cities and accounted for 88.9% of all ar-
thropods in Raleigh and 76.3% in Newark (see Tables S1.1 and S1.2
in Appendix S1). In Newark, arthropod abundance (non- spiders:
r2 = .100, p < .001, Figure 4a; spiders: r2 = .040, p = .028, Figure 4b)
and biomass (non- spiders: r2 = .230, p < .001, Figure 4c; spiders:
r2 = .030, p = .046, Figure 4d) increased as total structural complex-
ity increased. There was no effect of total structural complexity
on arthropod richness (non- spiders: r2 = .008, p = .307, Figure 4e;
spiders: r2 = .001, p = .947, Figure 4f), however, there was a nega-
tive effect on arthropod diversity (non- spiders: r2 = .080, p = .002,
Figure 4g; spiders: r2 = .040, p = .038, Figure 4h). In Raleigh, biomass
(non- spiders: r2 = .040, p = .030; spiders: r2 = .050, p = .010), but
not abundance (non- spiders: r2 = .010, p = .540; spiders: r2 = .020,
p = .090), increased as total structural complexity increased. There
was no effect of total structural complexity on arthropod richness
(non- spiders: r2 = .010, p = .185; spiders: r2 = .001, p = .793) or di-
versity (non- spiders: r2 = .010, p = .658; spiders: r2 = .030, p = .080).
In both cities, caterpillar abundance (Raleigh: r2 = .002, p = .640;
Newark: r2 = .018, p = .139) and biomass (Raleigh: r2 = .001, p = .750;
Newark: r2 = .020, p = .140) had no significant relationship with total
structural complexity (Figure 5a,d).
3.3 | Nonnative and native plant structural
complexity and arthropod communities
In Raleigh, non- spider arthropod abundance (r2 = .330, p = .050;
Figure 6a) and biomass (r2 = .400, p = .010; Figure 6c) increased as
nonnative structural complexity increased. The nonnative structural
complexity metric did not correlate with any other non- spider or
spider arthropod metric (p > .05). There was no significant effect of
the native structural complexity metric (p > .05), or the interaction
between the nonnative and native structural complexity metrics
(p > .05), on non- spider or spider arthropods (Figure 6).
In Newark, non- spider arthropod abundance increased both
as nonnative (r2 = .450, p = .031) and native (r2 = .450, p = .001;
Figure 7a) structural complexity metrics increased. Non- spider ar-
thropod biomass also increased with increased nonnative (r2 = .500,
p = .001) and native (r2 = .500, p = .001; Figure 7c) structural com-
plexity metrics and there was a significant negative interaction
MITCHELL et al .
between these metrics (p = .001). We interpret this interaction as
the positive relationship between nonnative and native structural
complexity metrics and non- spider arthropod biomass being weaker
when one of those metrics is high, which makes sense considering
the sum of both values does not exceed 100 in our dataset, and both
metrics cannot continuously increase (Table S1.3). Spider abun-
dance (r2 = .180, p = .037; Figure 7b) and biomass (r2 = .360, p = .018;
Figure 7d) increased as native structural complexity increased.
There were no significant responses of non- spider arthropod or
spider richness (p > .05) or diversity (p > .05) to nonnative or native
structural complexity metrics (see Table S1.3 in Appendix S1). When
considering caterpillars alone, neither caterpillar abundance or bio-
mass had a significant response to nonnative (Figure 5b,e) or native
(Figure 5c,f) structural complexity metrics, in either city.
4 | DISCUSSION
Based on the consistency in direction and strength in linear re-
sponse, total structural complexity in urban forest understories was
more related to nonnative plant richness and structural complex-
ity than native plant richness and structural complexity (Figure 3).
This indicates understory structural complexity in the urban forests
we sampled consisted more of nonnative plant structure than na-
tive plant structure. Increased understory vegetation complexity
increased arthropod abundance and biomass (Figure 4), despite
the associated increase in nonnative vegetation. Total structural
complexity generally increased arthropod abundance and biomass
but had no effect on arthropod richness, and reduced diversity in
Newark. This indicates the increase in arthropod abundance was
FIGURE 3 Influence of (a) nonnative understory plant richness, (b) native understory plant richness, (c) nonnative structural complexity,
and (d) native structural complexity on total understory structural complexity (collected from sampling points, N = 239). Raleigh sites are
shown in orange and Newark sites are shown in purple, significant relationships shown with 95% confidence intervals. Data points were
jittered to reduce overlap.
FIGURE 4 Influence of total structural complexity on (a) non- spider arthropod and (b) spider abundance, (c, d) biomass, (e, f) richness, and
(g, h) diversity (collected from sampling points, N = 239). Raleigh sites are shown in orange and Newark sites are shown in purple, significant
relationships shown with 95% confidence intervals. Note the y axes are fitted to the displayed data and not consistent across all graphs; data
points were jittered to reduce overlap.
MITCHELL et al.
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not evenly distributed (Gotelli, 2008), suggesting only certain non-
spider orders and spider families increased in abundance as total
structural complexity increased.
These results suggest urban forests invaded by nonnative plants
can support some arthropod populations which in turn provide food
resources for other wildlife, including birds, that depend on calcium
and amino acid- rich foods to feed their young (Frank et al., 2019;
Long & Frank, 2020; Nagy & Holmes, 2005; Parsons et al., 2020).
Birds rely on many food resources, but caterpillars are a particularly
importance source of protein for developing young (Cramp, 1998).
Previous reports suggest native plant species are essential for ar-
thropod communities required by insectivorous and other bird spe-
cies (Burghardt & Tallamy, 2013, 2015; Tallamy & Shropshire, 20 09)
and that nonnative plants can indirectly reduce bird population
growth (Narango et al., 2018). While our arthropod collection pro-
tocol was not designed to quantify urban forest caterpillar commu-
nities specifically, we employed a consistent sampling technique and
investigated how caterpillar abundance and biomass correlated with
understory vegetation structural complexity. We found no relation-
ship between caterpillars and total, nonnative or native structural
4.1 | Plant origin and understory plant
Relationships between total structural complexity and nonnative
and native understory plant richness differed by city. Previous re-
ports detailing FRAME vegetation communities found Raleigh for-
ests had more nonnative understory vegetation and Newark forests
had more native understory vegetation (Mitchell et al., 2023b). The
most abundant understory species found in Raleigh were primarily
nonnative (Nonnative: Hedera helix, Ligustrum sinense, Lonicera ja-
ponica, Microstegium vimineum, Vinca sp.; Native: Smilax rotundifolia,
Vitis rotundifolia) with vining and low- growing herbaceous structure.
Newark's most abundant understory species were primarily native
(Native: Clethra alnifolia, Lindera benzoin, Thelypteris noveboracensis,
Toxicodendron radicans, Viburnum dentatum; Nonnative: Lonicera
japonica, Rosa multiflora) with a combination of shrub and vining
or low- growing herbaceous structure (Mitchell et al., 2023b). The
presence of a nonnative shrub (Rosa multiflora), also common in our
Newark forests (Trammell et al., 2020), was found to increase for-
est structure in rural Maryland forests (Landsman & Bowman, 2017).
In Raleigh, increased native species richness did not contribute to
FIGURE 5 Influence of total structural complexity, nonnative structural complexity, and native structural complexity on (a– c) caterpillar
abundance and (d– f) biomass (from sampling points where immature lepidoptera were collected, N = 200). Raleigh sites are shown in orange
and Newark sites are shown in purple, no significant relationships were detected. Data points were jittered to reduce overlap.
FIGURE 6 Influence of nonnative (orange) and native (pale orange) structural complexity metrics on (a) non- spider arthropod and
(b) spider abundance, (c, d) biomass, (e, f) richness, and (g, h) diversity in Raleigh (collected from sampling points, N = 119). Significant
relationships shown with 95% confidence intervals. Data points were jittered to reduce overlap.
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increased total structural complexity, while increased native species
richness did contribute to increased total structural complexity in
Newark. In Raleigh, this suggests total structural complexity is so
predominately comprised of nonnative plants that an increase in na-
tive species richness does not increase vegetation structure.
4.2 | Understory plant structural complexity and
Arthropod metrics generally increased with greater total structural
complexity, but specific relationships differed by city. Similarly, other
studies have shown variable responses of arthropod communities
to vegetation structural complexity. Greater understory structural
complexity is associated with greater insect and spider abundance,
but reduced sider richness, in rural Maryland forests (Landsman &
Bowman, 2017), greater arthropod occupancy in Australian urban
green spaces (Threlfall et al., 2017), greater butterfly richness in
urban Brazilian forests (Orlandin & Carneiro, 2021), and reduced
ant richness in Australia woodlands (Lassau & Hochuli, 2004). These
comparisons suggest a similarity in vegetation structure serving as
food resources and refugia for arthropods, but enforce the species-
and regionally- specific nature of these relationships. From our re-
sults, non- spider arthropod and spider diversity in Newark were
the only arthropod response metrics to negatively correlate with
increased structural complexity (Figure 4). Dense shrub layer veg-
etation correlated with reduced carabid beetle diversity in French
urban forests (Croci et al., 2008), while Argentinian forests with low
vegetation complexity had reduced arthropod diversity (Gardner
et al., 1995). Relationships with arthropod diversity are likely more
nuanced than trends among abundance and biomass because spe-
cies have specific life history traits, for example host specificity and
behaviour with or without other organisms, that may not always be
known and would contribute to unpredictably. Non- spider arthro-
pod diversity in Raleigh was greater than in Newark, yet spider di-
versity was similar among cities. This may indicate some influence
of Raleigh's greater proportion of nonnative plant species on non-
spider arthropod diversity, as Landsman and Bowman (2017) re-
ported greater spider diversity in areas of dense nonnative ground
cover compared to structurally less complex control areas.
Due to logistics of resources and the global pandemic, we were
unable to collect temporally paired vegetation and arthropod com-
munity datasets, which may limit the interpretability of our results
and conclusions. Additionally, the low taxonomic resolution of our
arthropod dataset likely masks the specific responses that could be
found if we had identified arthropods to the genus or species level.
However, we argue th at our us e of a large order level dataset, plus th e
companion analyses using spiders identified at a more refined taxo-
nomic level, is appropriate for our purpose of understanding broad
relationships between plant and arthropod communities across a
regional scale. And perhaps, the order and family level results pre-
sented here represent a conservative detection of real response.
4.3 | Nonnative and native plant structural
complexity and arthropod communities
Significant relationships between arthropod metrics and nonnative
and native structural complexity were less numerous than those be-
tween arthropod metrics and total structural complexity. Responses
differed by city, but in general, structurally complex nonnative and
native vegetation was associated with increased arthropod abun-
dance and biomass and did not correlate with richness and diversity.
We suggest this is because increased ground cover and stem count
is more linearly related to increased physical structure than species
diversity. In an uninvaded, predominately native understory, it could
be reasonable to assume that as native plant richness increases, so
does the volume and therefore structure of the understory. However,
nonnative species, by definition, have limited evolutionary histories
in their areas of invasion and tend to become invasive by their ability
to rapidly propagate and spread (Aronson et al., 2007). Therefore,
plant diversity could be lower in an urban forest heavily invaded by
a few dominant species, compared to a less- invaded urban forest
dominated by multiple species historically evolved for the area and
conseque ntly less dense. This then disrup ts a theoretic al linear cor re-
lation between understory density and diversity, as the relationship
between density and diversity diverge once total vegetation is sepa-
rated into nonnative and native species with unique life histories.
Previous reports documented that nonnative plant richness cor-
related with reduced arthropod abundance and biomass (Landsman
& Bowman, 2017 ), nonnative plant density was associated with
increased arthropod abundance and spider diversity (Landsman
et al., 2020), and native plant richness and density correlated with
increased arthropod abundance and biomass (Adams et al., 2020;
Landsman & Bowman, 2017; Threlfall et al., 2017). In studies com-
paring arthropod communities between nonnative and native con-
geners, native plants had greater arthropod abundance, biomass,
and richness (Ballard et al., 2013; Southwood et al., 2004). In Raleigh,
insect predator abundances were similar on nonnative and native
congeners of urban trees, but predator community composition on
nonnative congeners differed from those on native species (Frank
et al., 2019). Together, these reports indicate that nonnative and
native plant richness and structural complexity influence arthropod
metrics and alter arthropod community compositions.
FIGURE 7 Influence of nonnative (purple) and native (pale purple) structural complexity metrics on (a) non- spider arthropods and
(b) spider abundance, (c, d) biomass, (e, f) richness, and (g, h) diversity in Newark (collected from sampling points, N = 120). Significant
relationships shown with 95% confidence intervals. Yellow star indicates a significant interaction; data points were jittered to reduce
MITCHELL et al .
4.4 | Conclusions and management implications
We documented support from two cities for the hypothesis that
greater vegetation complexity will increase arthropod abundance
and biomass, and against the hypothesis that nonnative vegetation
will decrease arthropod abundance and biomass. We found evi-
dence in urban forests that greater nonnative and native structural
complexity was associated with increased arthropod abundance
and biomass, but not diversity, as predicted by plant complexity lit-
erature. Native, not nonnative, structural complexity was associated
with increased spider abundance and biomass in Newark, but non-
native plants were not depauperate of arthropods, as predicted by
nonnative plant literature. This suggests urban forests invaded by
nonnative plants may still provide adequate food biomass to trans-
fer energy to the next trophic level but may not provide adequate
resources to support the full suite of species found in urban forests.
This could indicate that heavily invaded urban forests may fail to
provide ecological services and functions offered by diverse spe-
cies integral to forest ecosystems, like forest specialists (Magura &
Lövei, 2021; Martinson & Raupp, 2013; Mitchell et al., 2023b).
Urban land managers should consider plant species origin when
managing urban green space and prioritize the removal of non-
native structure and replacement with native species when allo-
cating vegetation maintenance resources. While total vegetation
complexity correlated with increased arthropod abundance and
biomass, we onl y support the plant in g of native species to promote
arthropod abundance and biomass. Nonnative plant invasion can
reduce plant diversity (Trammell et al., 2012), which can deplete
available resources for arthropods and reduce diversity (Narango
et al., 2018; Tallamy, 2004; Tallamy & Shropshire, 2009). But non-
native vegetation removal alone is not sufficient; once removed of
nonnatives, areas can be left barren and susceptible to further in-
vasion if not revegetated with native species (Moore et al., 2023).
Specific species depend on geographic location, but our results
suggest fast growing and persistent nonnative species, particu-
larly vining and evergreen species, would be primary targets for
removal. Following removal, cleared areas should be planted with
native ground cover and shrub layer plant species that produce
berries, nuts or other resources in addition to foliage to support
native species from multiple trophic levels. This report details rela-
tionships between urban forest arthropods and understory vege-
tation structural complexity, and demonstrates that nonnative and
native structural complexity exert different influences on arthro-
pod abundance and biomass.
ACKNO WLE DGE MENTS
We would like to acknowledge the City of Raleigh, Town of Cary,
North Carolina State University, US Forest Service, City of Newark
and University of Delaware for providing access to research sites.
Annemarie Nagle provided logistical support. Lawrence Long,
Michael Just, Kristi Backe, Caleb Wilson and Jane Petzoldt provided
advice regarding research design and statistical analyses. Catherine
Crofton, Doua Jim Lor, Logan Tyson, Kyle Sozanski, Hannah Frank,
Maggie Hamilton, Covel McDermot, Eric Moore, Carl Rosier,
Zach Ladin, Matt McDermitt, Nathaly Rodriguez, Andrew Adams,
Alyanna Wilson, R. Kevin Aiken, Laney Kimble, Sophia Copeman,
Molly Carlson, Chandler Purser, Shawn Janairo, Owen Cass and R.
David Mitchell helped in the field and laboratory. We appreciate
data and access provided by FRAME researchers. Rebecca Irwin,
Christopher Moorman, Clyde Sorenson and anonymous reviewers
provided critical insights and suggestions that improved the manu-
script. Funding was provided by the United States Department of
Agriculture (2016- 70006- 25827 and 2018- 70006- 28914), United
States Geological Survey (G19AP00041), North Carolina Forest
Service, North Carolina Invasive Plant Council, North Carolina State
University Department of Entomology and Plant Pathology, and the
University of Delaware Research Foundation.
CONFLICT OF INTEREST STATEMENT
The authors have no relevant financial or nonfinancial interests to
DATA AVAIL AB ILI T Y STATE MEN T
Data used in this article are archived at: https://sites.udel.edu/frame/
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This study is a product from the collaborative FRAME (FoRests
Among Managed Ecosystems,) project initiated by researchers
with the USDA Forest Service and the University of Delaware.
The project uses observational and experimental studies of
plants, invertebrates, and vertebrates to develop better man-
agement of urban forest fragments. This study uses existing and
newly established FRAME forest research sites to determine
large-scale effects of nonnative plant invasion on forest struc-
ture and arthropod communities.
Author contributions: Conceptualization: J. Christina Mitchell,
Vincent D'Amico, Tara L. E. Trammell, Steven D. Frank;
Methodology: J. Christina Mitchell, Vincent D'Amico, Tara L. E.
Trammell, Steven D. Frank; Formal analysis and investigation: J.
Christina Mitchell; Writing - original draft preparation: J. Christina
Mitchell, Steven D. Frank; Writing - review and editing: J. Christina
Mitchell, Vincent D'Amico, Tara L. E. Trammell, Steven D. Frank;
Funding acquisition: J. Christina Mitchell, Vincent D'Amico, Tara
L. E. Trammell, Steven D. Frank; Resources: Vincent D'Amico, Tara
L. E. Trammell, Steven D. Frank; Supervision: Vincent D’Amico,
Tara L. E. Trammell, Steven D. Frank.
Additional supporting information can be found online in the
Supporting Information section at the end of this article.
How to cite this article: Mitchell, J. C., D’Amico, V. III,
Trammell, T. L. E., & Frank, S. D. (2023). Nonnative plant
invasion increases urban vegetation structure and influences
arthropod communities. Diversity and Distributions, 29,
1263–1277. https://doi.org /10.1111/ddi.13755