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\begin{document}

\title{Phylogenetic relatedness to native congeners drives insect abundance and
diversity hosted by non-native trees}



\author[1]{Andreas Schweiger}%
\author[2]{Bernd Berauer}%
\author[3]{Melanie Assel}%
\author[3]{Sarah Bienwald}%
\author[3]{Florian Kittler}%
\author[3]{Elisabeth Obermaier}%
\author[3]{Marianne Lauerer}%
\affil[1]{University of Hohenheim Faculty of Agricultural Sciences}%
\affil[2]{University of Hohenheim}%
\affil[3]{Universitat Bayreuth}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\selectlanguage{english}
\begin{abstract}
Non-native trees are of major importance in forestry and urban greening
but are controversially discussed with regard to their effects on native
biodiversity. Existing literature reports positive as well as negative
biodiversity effects of non-native trees. Geographic, climatic and
phylogenetic distance between the non-native and native tree species are
named as important factors shaping these biodiversity effects. However,
studies with a large geographic and taxonomic coverage are missing. Here
we tested the effects of geographic, climatic and phylogenetic distance
on resident insect abundance and diversity for 77 native and non-native
tree species in a common garden trial. We identified phylogenetic
distance of tree species to be the main driver of insect abundance and
diversity with a negative effect of increasing phylogenetic distance and
stronger effects for phytophagous than for non-phytophagous insects.
This highlights the necessity to account for phylogenetic history shared
between native and non-native congeners when managing non-native trees.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Non-native tree species have been extensively planted during the last
centuries and are nowadays of major economic importance and, thus,
prominent in many forests throughout the world (Branco \emph{et
al.}2015; Campagnaro \emph{et al.} 2023; Wohlgemuth \emph{et al.} 2022).
Non-native tree species dominate globally already 44\% of plantation
forests (FAO 2020). Reasons named for their intensive use include higher
productivity compared to native trees and a better performance under
changing climatic conditions accompanied with positive effects on
wood-derived services such as provision of timber, pulp, firewood and
fodder (Branco \emph{et al.} 2015; K\selectlanguage{ngerman}ärvemo \emph{et al.} 2023;
Pötzelsberger \emph{et al.} 2020; Wohlgemuth \emph{et al.} 2022).

Besides their economic importance, non-native tree species become
increasingly relevant in the discussion on resilient future forestry in
environments which become unsuitable for native tree species
(Wohlgemuth\emph{et al.} 2022). Climatic changes -- especially climatic
extreme events such as increasing drought -- show large-scale effects on
forested ecosystems with major implication for the management of these
systems but also for the retrievable goods and services. Drastic forest
diebacks have been observable in the last years, raising the question
about tree species that will be able to cope with these novel, climatic
conditions. Being better adapted to certain future climates, many
foresters already select for non-native tree species to maintain
timber-related services of forests under increasingly changing climates
(Canadell \& Raupach 2008; Ennos \emph{et al.} 2019; Sims 2004).

Undesired effects on resident species and ecosystem functioning such as
declines of biodiversity, increases of disturbance frequency or
disruptions of native reference states of forests are, however,
important arguments against non-native tree planting (Campagnaro\emph{et
al.} 2023; Pötzelsberger \emph{et al.} 2020). Furthermore, massive
declines of terrestrial insects, which have been observed in Europe in
the last decades (Hallmann \emph{et al.} 2017) are assumed to be linked
to land use change and habitat loss (Eggleton 2020) among other factors
(Müller \emph{et al.} 2023; Seibold \emph{et al.} 2019). Land use change
in forests is directly related to changes in forest management including
changes in native and non-native tree planting. All these concerns
resulted in a large body of legislation that has been created in many
European countries during the last years -- all of which aim for the
regulation of non-native tree species establishment in forests
(Pötzelsberger \emph{et al.} 2020). Furthermore, transnational
legislative counter measures have been released which define alien
species of concern for the European Union (EU Regulation No 1143/2014;
Wohlgemuth \emph{et al.} 2022).

Effects of non-native tree species on native biodiversity have been
assessed by numerous studies and often come to controversial results.
Negative effects on local biodiversity have been reported for understory
vegetation (Lanta \emph{et al.} 2021; Taylor \emph{et al.} 2016),
saproxylic insects (Vogel \emph{et al.} 2021) and fungi (Buée \emph{et
al.} 2011; Schmid \emph{et al.} 2014). Wohlgemuth et al. (2022) conclude
that non-native trees most often decreased both, insect and arthropod
diversity. Although these negative biodiversity effects of non-native
tree species predominate in literature, positive effects on the
diversity of microorganisms, insects and other arthropods as well as for
bryophytes and lichens are reported by several studies (see
Wohlgemuth\emph{et al.} 2022 for a recent summary of studies). Spatial
and taxonomic bias in the conducted studies (i.e. predominantly
regional-scale case studies with single or few species being compared)
has been named as one of the reasons for inconsistency in the observed
effects (Branco \emph{et al.} 2015; Kärvemo \emph{et al.} 2023). This
inconsistency challenges the implementation of general management
strategies. Studies with extensive geographic and taxonomic coverage,
which might help to partly resolve these inconsistencies are missing so
far (Wohlgemuth \emph{et al.} 2022).

Prominent theorical concepts such as the enemy release hypothesis
predict non-native trees to be less relevant for resident insect
herbivores the more distant their geographic and climatic occurrence or
their phylogenetic relation to native congeners is. Abundances and
diversity of resident insects inhabited by non-native trees should
therefore be higher the closer a respective non-native species is
phylogenetically related to a native congener or the more similar
climatic and or geographic spaces occupied by the native and the
non-native are. Several empirical studies confirm these theoretical
assumptions. The presence of native, congeneric species and the
geographical extent of non-native trees in Europe has been shown to be
positively correlated with the number of recruited resident insect
species and the herbivore damage on non-natives (Branco \emph{et
al.}2015). Performance of non-natives under different temperatures at
the sites of introduction has been furthermore shown to be closely
related to the climatic conditions under which the non-native species
naturally occur (Bayón \emph{et al.} 2021). Furthermore, numerous
studies provide evidence that phytophagous insects are more likely to be
shared between native and non-native plants when phylogenetic distance
decreases (e.g. Novotny \emph{et al.} 2006; Ødegaard \emph{et al.} 2005;
Weiblen\emph{et al.} 2006). In a global meta-analyses, Vila et al.
(2015) conclude similar impacts of closely related non-native plants on
resident species richness. However, the phylogenetic impact of
non-native host trees on diversity of inhabited species has not been
explicitly tested so far (Kärvemo \emph{et al.} 2023). Furthermore, no
exhaustive testing on the importance of geographic vs. climatic vs.
phylogenetic distance on the effects of non-native species on resident
insect abundances and diversity have been conducted so far. Most
previous studies lack the comparison of impacts of native vs. non-native
organisms in a common habitat (i.e. common-garden setting) although such
comparison is considered to be critical to control for environmental
effects on insect diversity such as local differences in population
dynamics or environmentally induced differences in host plant fitness
(Agrawal \& Kotanen 2003; Schierenbeck \emph{et al.} 1994).

In this study we try to close this knowledge gap by quantifying the
effects of non-native tree species for four dominant and economically
important Central European tree genera (\emph{Acer} , \emph{Betula}
,\emph{Fraxinus} and \emph{Quercus} ) with a total of 77 globally
occurring, congeneric species in a common garden experimental setting.
With this geographically and taxonomically extensive dataset we aim to
test the importance of geographic vs. climatic vs. phylogenetic distance
between the native species and their non-native congeners regarding
their effects on insect abundance and diversity. Phylogenetic distance
reflects the distance between the non-native tree species and a dominant
native congener. Geographic and climatic (i.e. mean annual temperature,
annual precipitation sum and continentality) distance reflect the
distance between the non-native species' distribution area and the study
area. All three drivers have been proposed to strongly affect
plant-arthropod-interactions in non-native plant species (Keane \&
Crawley 2002; Parker \emph{et al.} 2012; Torchin \& Mitchell 2004).

Based on existing theory and empirical evidence we hypothesize, that
abundance and diversity of insects inhabiting non-native tree species
decreases with increasing geographic, climatic and phylogenetic distance
between the non-native and the native congener. We furthermore tested
the effect size of each of the three drivers in explaining insect
abundance and diversity to evaluate each driver's relative importance.

\textbf{Material \& Methods}

Field surveys

Our study was conducted in the Ecological-Botanical Garden (EBG) in
Bayreuth, Germany (49°55'45'' N, 11°35'10'' E, c. 365 m a.s.l.)
(Kreyling, Schmid, \& Aas, 2015). The EBG, as well as the larger region
of Upper Franconia, underlies an oceanic to continental climate, with an
annual average temperature of 8.2°C and an average annual precipitation
of 724~mm. The months with the highest amount of precipitation and
average temperature are June (75~mm, 16.2°C) and July (88~mm, 18.1°C,
based on a time series ranging from 1991 to 2020,
http://www.bayceer.uni-bayreuth.de/). Being established in 1978 planting
began in the early 1980s. Many of the tree species examined in this
study were planted in the first years after the garden was established.
The EBG can therefore be considered as a large-scale common-garden
experiment.

Our investigations include 24 species of \emph{Acer,} 11 species
of\emph{Betula} , 13 species of \emph{Fraxinus} and 29 species
of\emph{Quercus} . The genera \emph{Acer} was sampled in 2020, while the
genera \emph{Betula} , \emph{Fraxinus} and \emph{Quercus} were sampled
in 2021. (see Table S1). Insect sampling was performed only on sunny
days with no to minimal wind and was aborted when the conditions got
markedly worse. Sampling was conducted at least two full days after the
last rainfall event, as bad weather conditions such as heavy rain and
strong winds negatively affect insect activity (Weisser \emph{et al.}
1997) and/or may knock insects off the plants (Kobori \& Amano 2003).
Tree individuals were sampled at three sampling dates starting at the
end of May and ending at the end of August (see Table S2).

Sampling was performed using a beating tray (72~cm diameter, bioform
e.K., product number A13a) with an attached sampling flask. Six branches
were sampled per tree by hitting each branch three times with a wooden
stick (5~cm diameter), and subsequently collecting the insects from the
tray. Only larger branches, directly connected to the main stem, were
chosen for sampling. Branches between 2 and 9~m above ground were used,
starting with the lowest branches on each tree. Only free-hanging
branches were used for sampling, meaning branches that did not directly
affect other branches during beating. To prevent any subconscious
decisions regarding the potential usability of branches, random branches
were chosen from four directions, and, when possible, two different
heights on the tree. The same branches were used in each sampling run.

Sampling flasks were marked and frozen overnight at -18°C. Insects were
separated from debris and plant material and preserved in 96\% ethanol
for identification. Sampled insects were quantified and determined to
order-level in the laboratory, using a stereo microscope (Leica S6E,
Leica Microsystems GmbH). Orders Coleoptera and Hemiptera were
sub-sampled for further determination on lower taxonomic levels.
Coleopterans were identified to species-level using relevant literature
(Assing \& Schülke 2012; Freude \emph{et al.} 1965), digital references
(Lompe 2022) and by an expert (Boris Büche, Berlin). Individuals of the
weevil superfamily (Coleoptera: Curculionoidea, families Anthribidae,
Brentidae, Rhynchitidae and Curculionidae) were sent to an expert for
determination to species-level (Peter Sprick, Hanover) as were the
Heteroptera individuals (Markus Bräu, Munich). Data from all three
sampling dates were pooled for statistical analyses.

To assess potential effects of conditions on and around the sampled
trees we assessed diameter at breast height, total tree height and
number of congeners within a ten-meter radius (see Table S1). We
selected these parameters to represent individuals' fitness,
respectively, integrated growth performance as well as the amount of
phylogenetic related individuals within the crown area.

Data processing

\emph{Geographic \& climatic distances}

We extracted georeferenced occurrence records for all 77 investigated
tree species from GBIF and BIEN using the respective R
packages\emph{rgbif} (Chamberlain \emph{et al.} 2023) and \emph{BIEN}
(Maitner 2023). Both datasets have been combined and occurrence records
have been cleaned following the workflow described by Zizka \emph{et
al.} (2019) using the package \emph{CoordinateCleaner} {[}removing:
''capitals'', ''centroids'', ''equal'', ''gbif'', ''institutions'',
''outliers'', ''seas'', ''zeros'', ``duplicates''{]}.

For each occurrence record, we extracted the BIOCLIM variables mean
annual temperature (1), total annual precipitation (12), mean
temperature of the warmest quarter (10) and mean temperature of the
coldest quarter (11) from CHELSA (v. 2.1, Karger \emph{et al.} 2017,
2018). We calculated continentality as the temperature difference
between the warmest quarter and the coldest quarter (BIOCLIM10 --
BIOCLIM11). Similarly, we extracted climate data for the EBG Bayreuth
with longitude of 11.57893 and latitude of 49.94782. We scaled all
geographic and climatic data to the centre of the botanical garden in
Bayreuth {[} (x -- x\textsubscript{Bayreuth}) / sd(x){]}. Thereby, the
calculated geographic and climatic distances represent an environmental
distance to the botanical garden in Bayreuth.

We calculated hypervolumes of each species geographic (longitude \&
latitude) and climatic (mean annual temperature, total annual
precipitation \& continentality) distribution area. Next, we calculated
the Euclidean distance between the botanical garden in Bayreuth and the
geographic as well as the climatic centroid of each species. Please
note, as the geographic distribution area of species can be disjunct, it
thereby can have multiple possible centroids. If so, we calculated the
mean of the centroids' distances to the EBG Bayreuth after splitting the
hypervolumes. The calculations of hypervolumes and the splitting were
conducted using the R-package \emph{hypervolume} (Blonder \emph{et
al.}2023).

\emph{Phylogenetic distance}

We calculated phylogenetic distances of each tree species within a genus
to a genera specific native reference species, namely, \emph{Betula
pendula} , \emph{Fraxinus excelsior} , \emph{Quercus robur} and
\emph{Acer platanoides} . The phylogenetic trees and distance
calculations in this study were constructed and calculated by using the
native reference species, \emph{Betula pendul} a and \emph{Fraxinus
excelsio} r, as a root (i.e., a phylogenetic distance of zero), and
calculating the time of the last divergence event between the most
closely related species from the last common ancestor species. The next
divergence event was then calculated from the last common ancestor to
the following one, and so on. The phylogenetic distances for each
studied tree species to the native reference species was extracted from
available literature, by using chronograms that displayed the divergence
time between species in million years before present (myr). A study from
the Iranian\emph{Betula} population was used as a baseline for
\emph{Betula} (Bina\emph{et al.} 2016), with additions added with the
consideration of further studies (Wang \emph{et al.} 2016) to construct
a phylogenetic tree spanning the \emph{Betula} species considered in
this study. The classifications into subgenera and sections follows a
taxonomic revision, spanning the whole genus (Ashburner \& McAllister
2013). The phylogeny and biogeography of genus \emph{Fraxinus} is
well-resolved and generally accepted in literature, following numerous
revisions over the last two decades (Hinsinger \emph{et al.} 2013;
Olofsson \emph{et al.}2019; Wallander 2008). The phylogenetic tree by
Hinsinger et al. (2013) was used as a baseline for \emph{Fraxinus} ,
while the classification into sections follows Olofsson et al. (2019),
with the omitted sections being included from Hinsinger et al. (2013).
To examine phylogenetic distances in the genus \emph{Quercus} the
phylogenies of Xu et al. (2019) and of Pearse \& Hipp (2009) were used,
for the genus \emph{Acer}that of Li et al. (2019).

\emph{Measures of insect diversity}

The collected insects included specimens of the following orders:
Orthoptera, Dermaptera, Blattodea, Mecoptera, Lepidoptera, Neuroptera,
Coleoptera, Hemiptera, Diptera, Hymenoptera, Thysanoptera and
Psocoptera. we calculated the following indices for Coleoptera (beetles)
and Heteroptera (true bugs) as well as for different feeding guilds,
i.e. phytophageous and non-phytophageous insects (beetles and true bugs
pooled) with the omnivore and zoo-phytophageous species counting into
both camps (see Table S3): 1) The number of occurring species (i.e.
species richness), 2) the Shannon-index (using the vegan R-package;
Oksanen \emph{et al.} 2022) and 3) the number of individuals (i.e.
abundance). Additionally, we investigated the abundance of all collected
insects. We did not calculate total insect diversity (Shannon-index) and
species richness as not all specimens could be determined to the species
level.

Prior to any analyses we calculated the z-scores for each biodiversity
variable and removed outliers, defined as z \selectlanguage{english}[?] \textbar{}4\textbar{}
corresponding to a probability of 0.003\%. Outliers have only been
detected in the number of individuals of three species (\emph{Acer
campestre} , \emph{Betula pubescens} , \emph{Quercus acutissima} ).

Statistical analyses

To investigate the effect of ecological distance on insect
biodiversity\emph{per se} , we calculated generalized linear models of
the form\emph{biodiversity} \textasciitilde{} \emph{distance} \emph{*
host-tree-genera + RDA1} and a negative binomial distribution. To
account for effects of local, environmental conditions we calculated a
constrained redundancy analysis (RDA) conditioned on the tree genera for
each Heteroptera, Coleoptera and total insects respectively. We used the
Hellinger transformed insect diversity matrix as dependent variable and
diameter at breast height, total tree height and the amount of congenera
within a ten-meter radius as independent variables. This RDA represents
the explained variance of the insect diversity matrix with respect to
the tree individual fitness (in form of growth parameters) and the
proximity of congeners, which both might influence the diversity and
abundance of insects. We use the first axis of the RDA (RDA1) to account
for these local environmental effect in the analysis. We removed all
individuals with the respective biodiversity measure of zero prior to
calculations of the generalized model. For the models with Shannon index
we used a gaussian distribution and for models of number of species and
number of individuals we used a negative binomial distribution. The
chosen distributions reflect common distributions in biodiversity
analysis for the respective parameters. We report marginal r2 values,
Pearsons r2 for models with gaussian distribution and trigamma
calculated r2 for models with negative binomial distribution following
Nakagawa et al. (2017). To compare if the distance effects are stronger
for phytophageous then non-phytophageous insects, we followed a similar
procedure as described above, though including insect genera as
covariate within the generalized linear model:
\emph{biodiversity}\textasciitilde{} \emph{distance} \emph{*
host-tree-genera * insect-genera + RDA1} . Model assumptions were
assessed visually (QQplots) and tested for overdispersion using package
\emph{DHARMa}(Hartig 2022). All analysis and visualization were done
using R and the packages \emph{tidyverse} (Wickham 2023), \emph{MASS}
(Venables \& Ripley 2002), \emph{DHARMa} (Hartig 2022), \emph{effects}
(Fox \emph{et al.} 2022), \emph{lme4} (Bates \emph{et al.} 2023),
\emph{MuMIn} (Barton 2020).

\textbf{Results}

Phylogenetic distance between non-native host trees and their native
congeners was the main explanatory of resident insect abundance (i.e.
number of individuals) whereas the effects of geographic as well as
climatic distances were not significant (Figure 1). Insect abundance
declined with increasing phylogenetic distance for all four tree genera.
In contrast, insect abundance responded differently for the different
tree genera with respect to climatic and geographic distance (Fig. 1a \&
b). Number of insects tended to increase with climatic distance
for\emph{Acer} and \emph{Betula} and with geographical distance
for\emph{Quercus} and \emph{Fraxinus} , but both not significantly. A
significant negative effect of phylogentic distance was also observable
for Heteroptera (true bugs) as well as Coleoptera (beetles) abundance,
diversity and species richness (Figs. 2 \& 3). Climatic distance showed
significant effects on Heteroptera abundance and diversity whereas
geographic distance significantly affected Heteroptera abundance (Fig.
3). For the beetles, neither climatic nor geographic distances did
significantly affect insect abundance, diversity or species richness
(Fig. 2). Effects were generally stronger for Heteroptera than for
Coleoptera.

The effect of phylogenetic distance on abundance, Shannon diversity and
species richness of Coleoptera and Heteroptera was visibly stronger for
phytophagous species in comparison to non-phytophagous species (Fig. 4).
Similar patterns were observable for the effects of climatic and
geographic distance (see Fig. 4a \& b). We identified a total of 144
different Coleoptera species, with the majority (61.8\%) being
phytophageous, followed by zoophageous (17.4\%), mycophagous (9.7\%),
detritivor (4.2\%) and omnivor (1.4\%), with one xylomycovor species
(all classified as non-phytophagous). The predominance of phytophageous
beetles holds true at a tree genera level for \emph{Acer} (70 total
species, 52.9\% phytophageous), \emph{Betula} (36,
69.4\%),\emph{Fraxinus} (42, 61.9\%) and \emph{Quercus} (54, 64.8\%).
For Heteroptera, with a total of 51 identified species, the prominent
feeding guild was zoophag (43.1\%), followed by phytophag (27.5\%),
zoophytophag (23.5\%), and omnivor (5.9\%). Similar, the
genera\emph{Betula} (24 total Heteroptera species, 50\% of dominant
feeding guild), \emph{Fraxinus} (20, 60\%), \emph{Quercus} (27, 48.1\%)
were predominantely inhabited by zoophagous Heteroptera, only
\emph{Acer}(11, 45.5\%) was dominated by phytophagous species.

\textbf{Discussion}

Existing literature reports both, positive as well as negative effects
of non-native plant species on resident biodiversity. However, negative
effects have been noted more frequently especially for insect diversity
(see Wohlgemuth \emph{et al.} 2022 for a recent meta-analysis on the
effects). Contradicting findings always raise the question about global
drivers of the observable effects, that might help to reconcile such
contrasting findings existent in the published literature. Geographic,
climatic and phylogenetic distance between the non-native plant species
and its native congeners or area of introduction have been named as
three dominant drivers of the strength and direction of the effects of
non-native plant species on biodiversity. In our study, we identified
phylogenetic distance between non-native and native tree species to be
the main diver of resident insect abundance and diversity with lower
insect abundance and diversity being recorded on more phylogenetically
distant, non-native species. This predominance of the phylogenetic
effect in contrast to geographic or climatic factors might relate to the
dominant role of evolutionary forces shaping plant-insect interactions
such as the process of coevolution.

There is increasing consensus, that diversity of phytophagous arthropods
resulted from balanced rates of successful colonization of the new host,
speciation on the respective host and local extinction (Farrell \emph{et
al.} 1992). The main mechanism driving the positive relationship between
phylogenetic relatedness among host plants and their herbivore
colonization is proposed to be a high similarity of functional traits
involved in host plant selection or host resistance (Pearse \emph{et
al.} 2013; Ricciardi \& Ward 2006). Whether a shared phylogenetic
history between plant species can explain similarities in inhabited
insect communities thereby strongly depends on the degree of
conservatism of such herbivore related traits (Fine \emph{et al.} 2006).
Insect-plant associations are reported to be generally very conservative
with respect to the evolution of new host affiliations and, thus, may
persist over extensive periods of the phylogenetic history
(Farrell\emph{et al.} 1992; Farrell \& Mitter 1994). Closely related
host plant species are therefore expected to be more likely to be
colonized by the same, specialized insect species due to a high degree
of phylogenetic conservatism being reported for morphological and
chemical plant traits that regulate interactions with herbivores
(Brandle \emph{et al.} 2008; Gilbert \& Webb 2007; Whitfeld \emph{et
al.} 2012). Proportion of specialized, herbivorous insects are generally
reported to be high (Ali \& Agrawal 2012; Price \emph{et al.} 2011).
However, many plant functional traits affecting plant-insect
interactions are strongly shaped by the abiotic environment (e.g. leaf
thickness and hairs, thickness of the cuticula as a response to low
water availability and/or high radiation etc.) -- a fact that might
challenge plant-insect trait matching dynamics acting over evolutionary
time scales in variable environments.

Already Darwin proposed in his naturalization hypothesis that non-native
plants are more likely to invade if they lack close relatives in their
new range (Darwin 1859). Several studies highlight a positive
relationship between the abundance and phylogenetic relatedness of
non-native plants with their native congeners and the likelihood that
the non-native species get colonized by native herbivores
(Gossner\emph{et al.} 2009; Kirichenko \& Kenis 2016; Neuvonen \& Niemela
1981; Roques \emph{et al.} 2006). This phylogenetic effect on
plant-herbivore interactions has been shown to be especially strong for
tropical plant-insect herbivore interactions, where 25\% of the variance
in herbivore community similarity between tropical tree species was
explained by the phylogenetic similarity of the host tree species
(Weiblen \emph{et al.} 2006). Furthermore, host switches of phytophagous
insects have been reported for the temperate region to be more probable
to happen between related host tree species than between more unrelated
host species which co-occurred in the same habitat (Brandle \& Brandl
2006). Another impressive though anecdotal example of a high degree of
phylogenetic conservatism in host-plant insect interactions is reported
for Douglas-fir (\emph{Pseudotsuga menziesii} (Mirb.) Franco), a
non-native, economically important tree species with no close relatives
in Europe. In the 130 years since this species has been introduced to
Europe, it has recruited only 87 arthropod species, despite being the
most planted, non-native tree species in European forest systems
(Roques\emph{et al.} 2006). These are only 33.9\% of the arthropod
species richness found on Douglas-fir in its native range in North
America. Our results show that such a strong phylogenetic effect on
plant-insect interactions of non-native trees is not a peculiarity of
single tree species but a general phenomenon with extensive geographic
and taxonomic coverage. In our study these effects have been detected
for non-native species of native tree genera, showing that this effect
even holds true on lower taxonomic levels.

Our results furthermore show that the effect of phylogenetic distance on
resident insect abundance, species richness and diversity is visibly
stronger for phytophagous insect species in comparison to
non-phytophagous species. This reflects theoretical assumptions proposed
for the enemy release hypothesis (ERH), one of the most prominent
hypotheses in plant-related invasion biology. It states that
host-specific herbivores are left behind when a plant species is
transferred to a new area that haven't been occupied before (Keane \&
Crawley 2002). This lack of native antagonists in a plant host's
introduced range can favour its vitality and spread (Adams \emph{et
al.}2009; Cincotta \emph{et al.} 2009). Lower trait similarity between
phylogenetically distant, non-native plants and their native congeners
in the area of introduction has been proposed as an underlying,
prominent mechanism explaining the establishment success of such
non-natives (Gossner \emph{et al.} 2009). In this framework, our results
would basically mean, that such release effects might be stronger, the
more phylogenetically distant non-native plant species will be to their
native counterparts on place (for empirical evidence see e.g.
Ness\emph{et al.} 2011).

Although phylogenetic distance turned out to be the predominant, global
driver in our study, other context-specific drivers of the effects of
non-native plants on resident biodiversity have to be expected to be
important on local scale (Wohlgemuth \emph{et al.} 2022). Local drivers
such as density effects (i.e. trees planted in mono- vs. mixed stands;
Adams \emph{et al.} 2009; Yang \emph{et al.} 2019) or differences in
species pools of arthropods (Miles \emph{et al.} 2019 in the context of
urbanisation) are named to be important. However, these effects might
not play out in a common garden setting such as ours, where all tree
species are experiencing a very similar abiotic and biotic environment
and, thus, genetic differences might predominate the responses
(Allen\emph{et al.} 2017). Local differences in environmental conditions
might overwrite the effects of phylogenetic differences between
non-native species and their native congeners when comparing different,
local study sites. Other exogenic factors such as time since
introduction in a new biogeographic realm (i.e. residence time) can play
an additional, crucial role for native insect - non-native host plant
interactions (Brandle \emph{et al.} 2008; Sheppard \& Brendel 2021).
Further investigations on other tree genera and species, as well as in
other geographical areas will be needed to test the relative importance
of local vs. global drivers of non-native tree species on resident
insect communities. Coordinated, spatially distributed, common garden
experiments would help to advance in this direction. Tree collections in
botanical gardens can provide a fruitful basis for such kind of
investigations.

\textbf{Conclusions}

Our study highlights, that effects of non-native trees on resident
insect abundance and diversity do not depend on the geographical
proximity of the area of origin, as often assumed especially by
practitioners in forestry, but predominately on the phylogenetic history
non-natives share with their resident, native counterparts. Our study
furthermore shows, that non-native tree species should be regarded
differentiated and that impacts of non-native trees on insect
communities in the introduced range differ according to their
relatedness to native congeners. While closely related non-native
congeners hosted a higher number of insect individuals and species, more
distantly related non-natives of the same genus inhabit significantly
less species and individuals. This highlights the necessity of account
for phylogenetic history as a global driver of the effects of non-native
tree species in future alien species and forest management. This study
was performed with four of the most important tree genera of the
temperate zone. Our results therefore can provide important input for
tree species selection and management in forestry and urban greening in
the future.

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\textbf{Figures and figure legends}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\emph{\textbf{Figure 1.} Effects of climatic, geographic and
phylogenetic distance of non-native host trees to their native congeners
on the abundance of inhabited insects. Effects of the three types of
distances as well as the interacting effect of host tree genus and the
effect of additional, local, environmental factors of the study site
(i.e. diameter at breast height, total height, number of congeners
within ten-meter radius, all summarized by the first axis of a
redundancy analysis RDA1) is shown in each of the three panels (based on
a generalized linear model). Please note that coloured solid (fit) and
dashed (95\%-confidence intervals) lines represent genera predictions of
the full model -- not genera specific models. Yet, the here shown genera
predictions of the full model are similar to the genera specific model
prediction.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\emph{\textbf{Figure 2.} Effects of climatic, geographic and
phylogenetic distance of non-native host trees to their native congeners
on the abundance, diversity and species richness of Coleoptera (i.e.
beetles). Effects of the three types of distances as well as the
interacting effect of host tree genus and the effect of additional,
local, environmental factors of the study site (i.e. diameter at breast
height, total height, number of congeners within ten-meter radius, all
summarized by the first axis of a redundancy analysis) is shown in each
of the three panels (based on a linear mixed effect model). Please note,
that coloured solid (fit) and dashed (95\%-confidence intervals) lines
represent genera predictions of the full model -- not genera specific
models. Yet, the here shown genera predictions of the full model are
similar to the genera specific model prediction.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\emph{\textbf{Figure 3.} Effects of climatic, geographic and
phylogenetic distance of non-native host trees to their native congeners
on the abundance, diversity and species richness of true bugs
(Heteroptera). Effects of the three types of distances as well as the
interacting effect of host tree genus and the effect of additional,
local, environmental factors of the study site (i.e. diameter at breast
height, total height, number of congeners within ten-meter radius, all
summarized by the first axis of a redundancy analysis) is shown in each
of the three panels (based on a linear mixed effect model). Please note,
that coloured solid (fit) and dashed (confidence intervals) lines
represent genera predictions of the full model -- not genera specific
models. Yet, the here shown genera predictions of the full model are
similar to the genera specific model prediction.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Figure 4.} \emph{Effects of climatic, geographic and
phylogenetic distance of non-native host trees to their native congeners
on abundance, diversity and species richness of phytophagous (green
dots) vs. non-phytophagous (purple dots) insects (Heteroptera and
Coleoptera). Depicted are R\textsuperscript{2}-values of linear models
where the different tree genera and insect taxa (i.e. beetles or true
bugs) were accounted for as co-variables {[}biodiversity
\textasciitilde{} distance * host-tree-genera * insect-taxa (i.e.
Coleoptera/Heteroptera) + RDA1{]}. Details on the feeding guilds
summarized under phytophagous and non-phytophagous are given in the
methods section.}



\textbf{Supplementary Material}

\textbf{Table S1.} Information on the sampled tree individuals.
Abbreviations: Diameter at breast height (DBH).

Species Year DBH {[}cm{]} Total height {[}m{]} Nbr. of congeners

of sampling in 10~m radius

\emph{Acer campestre} 2020 17.2 9 11

\emph{Acer} \emph{campestre} 2020 13.8 6 2

\emph{Acer} \emph{cappadocicum} 2020 25.1 11 3

\emph{Acer} \emph{carpinifolium} 2020 7.2 5 3

\emph{Acer} \emph{circinatum} 2020 4.8 4 1

\emph{Acer} \emph{davidii} 2020 4 4 2

\emph{Acer} \emph{elegantulum} 2020 10.6 4 1

\emph{Acer} \emph{ginnala} 2020 6.3 6 4

\emph{Acer} \emph{ginnala} 2020 10.55 6 5

\emph{Acer} \emph{ginnala} 2020 27 8 2

\emph{Acer} \emph{grandidentatum} 2020 24.8 9 1

\emph{Acer} \emph{heldreichii} 2020 19.1 10 6

\emph{Acer} \emph{mono} 2020 6.1 6 3

\emph{Acer} \emph{monspessulanum} 2020 21.05 10 7

\emph{Acer} \emph{negundo} 2020 18.9 7 2

\emph{Acer} \emph{opalus} 2020 5.4 5 8

\emph{Acer} \emph{palmatum} 2020 10 7 5

\emph{Acer} \emph{platanoides} 2020 21.15 9 0

\emph{Acer} \emph{pseudoplatanus} 2020 6.5 6 12

\emph{Acer} \emph{pubipalmatum} 2020 1.65 2 2

\emph{Acer} \emph{rubrum} 2020 26.55 11 1

\emph{Acer} \emph{saccharinum} 2020 22.3 10 5

\emph{Acer} \emph{saccharum} 2020 15.25 9 3

\emph{Acer} \emph{semenovii} 2020 20.35 7 5

\emph{Acer} \emph{tataricum} 2020 22 6 1

\emph{Acer} \emph{tegmentosum} 2020 4.65 5 0

\emph{Acer} \emph{triflorum} 2020 6.5 6 3

\emph{Betula} \emph{alleghaniensis} 2021 50 8 0

\emph{Betula} \emph{ermanii} 2021 25 12.3 1

\emph{Betula} \emph{fruticosa} 2021 4 3 0

\emph{Betula} \emph{humilis} 2021 5 3.5 2

\emph{Betula} \emph{lenta} 2021 16.2 10.6 4

\emph{Betula} \emph{maximowicziana} 2021 5.5 1.5 0

\emph{Betula} \emph{occidentalis} 2021 12.2 8.5 2

\emph{Betula} \emph{papyrifera} 2021 18 8 0

\emph{Betula} \emph{pendula} 2021 9 8 0

\emph{Betula} \emph{pendula} 2021 53 15 0

\emph{Betula} \emph{pubescens} 2021 16.5 10.5 2

\emph{Betula} \emph{pubescens} 2021 25 7 3

\emph{Betula} \emph{tianschanica} 2021 38 12 0

\emph{Fraxinus} \emph{americana} 2021 26 9 0

\emph{Fraxinus} \emph{angustifolia} 2021 28 14 0

\emph{Fraxinus} \emph{angustifolia} 2021 27.5 9.5 0

\emph{Fraxinus} \emph{angustifolia} \emph{oxycarpa} 2021 2 2.6 0

\emph{Fraxinus} \emph{bungeana} 2021 13 6 1

\emph{Fraxinus} \emph{latifolia} 2021 27 9 1

\emph{Fraxinus} \emph{chinensis} \emph{rhynchophylla} 2021 17 9 0

\emph{Fraxinus} \emph{excelsior} 2021 21 7.5 2

\emph{Fraxinus} \emph{latifolia} 2021 13.5 9 2

\emph{Fraxinus} \emph{mandshurica} 2021 13 7 2

\emph{Fraxinus} \emph{ornus} 2021 23 9 0

\emph{Fraxinus} \emph{pennsylvanica} 2021 15 7 1

\emph{Fraxinus} \emph{profunda} 2021 18.5 9.5 0

\emph{Fraxinus} \emph{quadrangulata} 2021 12 7 1

\emph{Fraxinus} \emph{velutina} 2021 30 12 1

\emph{Quercus} \emph{acutissima} 2021 11 8 0

\emph{Quercus} \emph{alba} 2021 21 8 1

\emph{Quercus} \emph{bicolor} 2021 15 6 2

\emph{Quercus} \emph{cerris} 2021 44 14 1

\emph{Quercus} \emph{coccinea} 2021 32 13 0

\emph{Quercus} \emph{dalechampii} 2021 32 8 0

\emph{Quercus} \emph{dentata} 2021 26 9 4

\emph{Quercus} \emph{falcata} 2021 21 9 4

\emph{Quercus} \emph{hartwissiana} 2021 26 8 0

\emph{Quercus} \emph{imbricaria} 2021 31.8 9 5

\emph{Quercus} \emph{liaotungensis} 2021 8 5 3

\emph{Quercus} \emph{libani} 2021 33 10 0

\emph{Quercus} \emph{lobata} 2021 11 6 0

\emph{Quercus} \emph{macranthera} 2021 33 8 0

\emph{Quercus} \emph{macrocarpa} 2021 26 7 0

\emph{Quercus} \emph{michauxii} 2021 16 8 1

\emph{Quercus} \emph{nigra} 2021 10 4 0

\emph{Quercus} \emph{nuttallii} 2021 18 10 2

\emph{Quercus} \emph{palustris} 2021 46 15 3

\emph{Quercus} \emph{petraea} 2021 18 8 4

\emph{Quercus} \emph{pubescens} 2021 27 9 0

\emph{Quercus} \emph{pyrenaica} 2021 27 9 0

\emph{Quercus} \emph{robur} 2021 18 7 1

\emph{Quercus} \emph{robur} 2021 15 7 0

\emph{Quercus} \emph{robur} 2021 42 11 1

\emph{Quercus} \emph{rubra} 2021 38 8 6

\emph{Quercus} \emph{serrata} 2021 18 8 4

\emph{Quercus} \emph{shumardii} 2021 31 10 2

\emph{Quercus} \emph{stellata} 2021 13 6 0

\emph{Quercus} \emph{variabilis} 2021 7 6 0

\emph{Quercus} \emph{velutina} 2021 32 10 3

\textbf{Table S2.} Insect sampling dates for each of the four tree
genera.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Genus & Sampling 1 & Sampling 2 & Sampling 3\tabularnewline
\midrule
\endhead
\emph{Acer} & 18.05.-20.05.2020 & 17.06.-19.06.2020 &
13.07.-14.07.2020\tabularnewline
\emph{Betula} & 31.05.-01.06.2021 & 06.07.2021 &
07.08.2021-25.08.2021\tabularnewline
\emph{Fraxinus} & 10.06.-15.06.2021 & 12.07.-20.07.2021 &
09.08.-25.08.2021\tabularnewline
\emph{Quercus} & 10.06-16.06.2021 & 12.07-13.07.2021 as well as 19.07.
and 20.07.2021 & 09.08.-12.08.2021 as well as 25.08.2021\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table S3.} Summary on insect feeding guilds per sampled tree
genus.

Insect order Tree genera Insect feeding guild Nbr. of species Proportion
of total

per feeding guild species richness per genus

Heteroptera \emph{Acer} phytophag 5 0.45

\emph{Acer} zoophag 3 0.27

\emph{Acer} zoophytophag 3 0.27

\emph{Betula} omnivore 3 0.13

\emph{Betula} phytophag 7 0.29

\emph{Betula} zoophag 12 0.50

\emph{Betula} zoophytophag 2 0.08

\emph{Fraxinus} phytophag 5 0.25

\emph{Fraxinus} zoophag 12 0.60

\emph{Fraxinus} zoophytophag 3 0.15

\emph{Quercus} phytophag 6 0.22

\emph{Quercus} zoophag 13 0.48

\emph{Quercus} zoophytophag 8 0.30

Coleoptera \emph{Acer} mycophag 10 0.14

\emph{Acer} phytophag 37 0.53

\emph{Acer} xylomycophag 1 0.01

\emph{Acer} zoophag 15 0.21

\emph{Acer} NA 7 0.10

\emph{Betula} detritivore 3 0.08

\emph{Betula} omnivore 1 0.03

\emph{Betula} phytophag 25 0.69

\emph{Betula} zoophag 7 0.19

\emph{Fraxinus} detritivore 4 0.10

\emph{Fraxinus} mycophag 2 0.05

\emph{Fraxinus} omnivore 1 0.02

\emph{Fraxinus} phytophag 26 0.62

\emph{Fraxinus} xylomycophag 1 0.02

\emph{Fraxinus} zoophag 8 0.19

\emph{Quercus} detritivore 4 0.07

\emph{Quercus} mycophag 3 0.06

\emph{Quercus} omnivore 2 0.04

\emph{Quercus} phytophag 35 0.65

\emph{Quercus} zoophag 10 0.19

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

