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\begin{document}

\title{Herbivory on the pedunculate oak along urbanization range in Europe:
effects of local forest cover and insect feeding guild}



\author[1]{Elena Valdés-Correcher}%
\author[2]{Anna  Popova}%
\author[3]{Andrea  Galmán}%
\author[4]{Andreas Prinzing}%
\author[5]{Andrey Selikhovkin}%
\author[6]{Andy  Howe}%
\author[7]{Anna  Mrazova}%
\author[8]{Anne-Maïmiti  Dulaurent}%
\author[1]{Arndt  Hampe}%
\author[9]{Ayco Tack}%
\author[10]{Christophe Bouget}%
\author[11]{Daniela  Lupaștean}%
\author[12]{Deborah Harvey}%
\author[5]{Dmitry Musolin}%
\author[13]{Gabor  Lövei}%
\author[9]{Giada  Centenaro}%
\author[1]{Inge  Halder}%
\author[14]{Jonas Hagge}%
\author[15]{Jovan  Dobrosavljević}%
\author[16]{Juha-Matti  Pitkänen}%
\author[12]{Julia Koricheva}%
\author[17]{Katerina Sam}%
\author[18]{Luc Barbaro}%
\author[19]{Manuela Branco}%
\author[20]{Marco Ferrante}%
\author[9]{Maria  Faticov}%
\author[21]{Markéta Tahadlová}%
\author[22]{Martin M. Gossner}%
\author[23]{Maxime  Cauchoix}%
\author[24]{Michał Bogdziewicz}%
\author[11]{Mihai-Leonard  Duduman}%
\author[25]{Mikhail Kozlov}%
\author[6]{Mona  Bjoern}%
\author[5]{Nikita  Mamaev}%
\author[26]{Pilar  Fernandez-Conradi}%
\author[27]{Rebecca Thomas}%
\author[28]{Ross Wetherbee}%
\author[29]{Samantha  Green}%
\author[15]{Slobodan  Milanović}%
\author[30]{Xoaquin Moreira}%
\author[1]{Yasmine  Kadiri}%
\author[1]{Bastien Castagneyrol}%
\affil[1]{INRAE Nouvelle-Aquitaine Bordeaux Centre}%
\affil[2]{Russian Academy of Sciences}%
\affil[3]{Martin Luther University Halle Wittenberg}%
\affil[4]{ECOBIO}%
\affil[5]{Saint Petersburg State Forest Technical University named after S M Kirov}%
\affil[6]{University of Copenhagen}%
\affil[7]{Biology Centre Czech Academy of Sciences}%
\affil[8]{UniLaSalle}%
\affil[9]{Stockholm University}%
\affil[10]{INRAE Val de Loire Site de Nogent-sur-Vernisson}%
\affil[11]{University of Suceava}%
\affil[12]{Royal Holloway University of London School of Biological Sciences}%
\affil[13]{Aarhus Universitet}%
\affil[14]{Northwest German Forest Research Institute}%
\affil[15]{University of Belgrade}%
\affil[16]{Natural Resources Institute Finland}%
\affil[17]{Institute of Entomology Biology Centre Czech Academy of Sciences}%
\affil[18]{DYNAFOR}%
\affil[19]{Universidade de Lisboa}%
\affil[20]{University of the Azores - Angra do Heroísmo Campus}%
\affil[21]{Biology Centre CAS}%
\affil[22]{WSL}%
\affil[23]{CNRS}%
\affil[24]{Adam Mickiewicz University}%
\affil[25]{University of Turku}%
\affil[26]{URFM}%
\affil[27]{University of Reading}%
\affil[28]{Norwegian University of Life Sciences}%
\affil[29]{Coventry University}%
\affil[30]{Mision Biologica de Galicia}%


\vspace{-1em}



  
  \date{June 08, 2024}


\begingroup
\let\center\flushleft
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\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Urbanization is recognized as an important driver of the diversity and
abundance of tree associated insect herbivores, but its consequences for
insect herbivory are controversial. A likely source of variability among
studies is the insufficient consideration of intra-urban variability in
forest cover. With the help of citizen scientists, we investigated the
independent and interactive effect of urbanization and local canopy
cover on insect herbivory in the pedunculate oak (Quercus robur)
throughout most of its geographic range in Europe. The damage caused by
chewing insect herbivores as well as the incidence of leaf-mining and
gall-inducing herbivores consistently decreased with increasing
urbanization around focal oaks. Herbivory by chewing herbivores
increased with increasing forest cover, regardless of urbanization. In
contrast, an increase in local canopy cover buffered the negative effect
of urbanization on leaf-miners and strengthened its effect on
gall-inducers. These results show the complexity of plant-herbivore
interactions in urbanized areas, highlighting that the presence of local
canopy cover within cities has the potential to attenuate or modify the
effect of urbanization on biotic interactions.%
\end{abstract}%



\sloppy


\textbf{Herbivory on the pedunculate oak along urbanization range in
Europe: effects of local forest cover and insect feeding guild}

\textbf{Authors} :

Elena Vald\selectlanguage{ngerman}és Correcher\textsuperscript{1}, Anna
Popova\textsuperscript{2}, Andrea Galmán\textsuperscript{3, 4}, Andreas
Prinzing\textsuperscript{5}, Andrey V. Selikhovkin\textsuperscript{6},
Andy G. Howe\textsuperscript{7, 8}, Anna Mrazova\textsuperscript{9, 10},
Anne-Maïmiti Dulaurent\textsuperscript{11}, Arndt
Hampe\textsuperscript{1}, Ayco Jerome Michel Tack\textsuperscript{12},
Christophe Bouget\textsuperscript{13}, Daniela
Lupa\selectlanguage{romanian}ștean\textsuperscript{14}, Deborah Harvey\textsuperscript{15},
Dmitry L. Musolin\textsuperscript{6}, G\selectlanguage{ngerman}ábor L.
Lövei\textsuperscript{16}, Giada Centenaro\textsuperscript{17}, Inge Van
Halder\textsuperscript{1}, Jonas Hagge\textsuperscript{18, 19}, Jovan
Dobrosavljevi\selectlanguage{polish}ć\selectlanguage{english}\textsuperscript{20}, Juha-Matti
Pitk\selectlanguage{ngerman}änen\textsuperscript{21, 22}, Julia Koricheva\textsuperscript{15},
Katerina Sam\textsuperscript{9, 10}, Luc Barbaro\textsuperscript{23,
24}, Manuela Branco\textsuperscript{25}, Marco
Ferrante\textsuperscript{16, 26}, Maria Faticov\textsuperscript{12},
Markéta Tahadlová\textsuperscript{9, 10}, Martin
Gossner\textsuperscript{27, 28}, Maxime Cauchoix\textsuperscript{29},
Micha\selectlanguage{polish}ł \selectlanguage{english}Bogdziewicz\textsuperscript{30, 31}, Mihai-Leonard
Duduman\textsuperscript{14}, Mikhail V. Kozlov\textsuperscript{32}, Mona
C. Bjoern\textsuperscript{7}, Nikita A. Mamaev\textsuperscript{6}, Pilar
Fernandez-Conradi\textsuperscript{33}, Rebecca L.
Thomas\textsuperscript{15}, Ross Wetherbee\textsuperscript{34}, Samantha
Green\textsuperscript{35}, Slobodan Milanovi\selectlanguage{polish}ć\selectlanguage{english}\textsuperscript{20, 36},
Xoaqu\selectlanguage{ngerman}ín Moreira\textsuperscript{37}, Yasmine
Kadiri\textsuperscript{1}and Bastien Castagneyrol\textsuperscript{1}.

\textbf{Affiliations} :

1 -- Univ. Bordeaux, INRAE, BIOGECO, F-33612 Cestas, France

2 -- A. N. Severtsov Institute of Ecology and Evolution, Russian Academy
of Sciences, Leninsky 33, Moscow, 119071, Russia

3 -- Institute of Biology/Geobotany and Botanical Garden, Martin Luther
University Halle-Wittenberg, Germany

4 -- German Centre for Integrative Biodiversity Research (iDiv)
Halle-Jena-Leipzig, Germany

5 -- Research Unit ECOBIO (Ecosystems, Biodiversity, Evolution), UMR
6553, University of Rennes/Centre National de la Recherche Scientifique,
Campus Beaulieu, Bâtiment 14 A, 263 Av. du Général Leclerc, 35042
Rennes, France

6 -- Department of Forest Protection, Wood Science and Game Management,
Saint Petersburg State Forest Technical University, 194021 St.
Petersburg, Russia

7 -- Department of Geosciences and Natural Resource Management,
University of Copenhagen, Rolighedsvej 23, 1958 Frederiksberg C, Denmark

8 -- Forest Industries Research Centre, University of the Sunshine
Coast, Australia

9 -- Biology Centre of Czech Academy of Sciences, Entomology Institute,
Branisovska 31, Ceske Budejovice 370 05, Czech Republic

10 -- Faculty of Science, University of South Bohemia, Branisovska 1760,
Ceske Budejovice 370 05, Czech Republic

11 -- UniLaSalle, AGHYLE, UP.2018.C101, SFR Condorcet FR CNRS 3417,
FR-60026 Beauvais, France

12 -- Department of Ecology, Environment and Plant Sciences, Stockholm
University, 114 18 Stockholm, Sweden

13 -- Forest Ecosystems' Research Unit -- Biodiversity team Domaine des
Barres, INRAE, Nogent-sur-Vernisson, France

14 -- ''\selectlanguage{romanian}Ștefan cel Mare'' University of Suceava, Forestry Faculty,
Applied Ecology Lab. University Str. 13, Suceava, Romania

15 -- Dept of Biological Sciences, Royal Holloway, University of London,
Egham Surrey, UK

16 -- Department of Agroecology, Flakkebjerg Research Centre, Aarhus
University, Slagelse, Denmark

17 -- Department of Ecology, Environment and Plant Sciences, Stockholm
University, Stockholm, SE

18 -- Forest Nature Conservation, Northwest German Forest Research
Institute, Prof.-Oelkers-Str. 6, 34346 Hann. M\selectlanguage{ngerman}ünden, Germany

19 -- Forest Nature Conservation, Georg\selectlanguage{english}-August\selectlanguage{english}-University Gottingen,
Busgenweg 3, 37077 Gottingen, Germany

20 -- Department of Forest Protection, Faculty of Forestry, University
of Belgrade, Kneza Vi\selectlanguage{polish}š\selectlanguage{english}eslava 1, Belgrade, Serbia

21 -- Forest Health and Biodiversity, Natural Resources Institute
Finland (LUKE), Latokartanonkaari 9, 00790, Helsinki, Finland

22 -- Spatial Foodweb Ecology Group, Department of Agricultural
Sciences, University of Helsinki, Helsinki, Finland

23 -- Dynafor, Univ. Toulouse, INRAE, Castanet-Tolosan, France

24 -- CESCO, Museum national d'Histoire naturelle, CNRS, Sorbonne-Univ.,
Paris, France

25 -- Centro de Estudos Florestais, Instituto Superior de Agronomia,
Universidade de Lisboa, 1349-017 Lisboa, Portugal

26 -- Azorean Biodiversity Group, cE3c -- Centre for Ecology, Evolution
and Environmental Changes, University of the Azores, Azores, Portugal

27 -- Forest Entomology, Swiss Federal Research Institute WSL,
Z\selectlanguage{ngerman}ürcherstrasse 111, CH-8903 Birmensdorf, Switzerland

28 -- Department of Environmental Systems Science, Institute of
Terrestrial Ecosystems, ETH Zürich, Zürich, Switzerland

29 -- Station d'Ecologie Théorique et Expérimentale du CNRS, Moulis,
France

30 -- Department of Systematic Zoology, Faculty of Biology, Adam
Mickiewicz University, Umutlowska 89, 61\selectlanguage{english}-614 Poznan, Poland

31 -- Laboratoire EcoSystemes et Societes En Montagne, INRAE Univ
Grenoble Alpes, 2 rue de la Papeterie, BP 76 F-38402
Saint-Martin-d'Heres cedex, France

32 -- Department of Biology, University of Turku, Turku 20014, Finland

33 -- INRAE, UR629 Ecologie des Forets Mediterraneennes (URFM), Avignon
84914, France

34 -- Faculty of Environmental Sciences and Natural Resource Management,
Norwegian University of Life Sciences, Aas, Norway

35 -- Centre for Agroecology, Water and Resilience, Coventry University,
Ryton Organic Gardens, Coventry, CV8 3LG, UK

36 -- Department of Forest Protection and Wildlife Management, Faculty
of Forestry and Wood Technology, Mendel University in Brno, Zemedelska
3, 613 00 Brno, Czech Republic

37 -- Mision Biologica de Galicia (MBG-CSIC), Apdo. 28, 36080
Pontevedra, Galicia, Spain

\textbf{Corresponding author} : ELENA VALDES-CORRECHER, Univ. Bordeaux,
INRAE, BIOGECO, F-33612 Cestas,
France.\emph{elena.valdes.correcher@gmail.com}; Telephone number:
+330769962199.

\textbf{Introduction}

Urbanization is one of the major drivers of global change (Lambert et
al., 2015; Rossetti et al., 2017). It causes fragmentation, isolation
and degradation of natural habitats (Pickett et al., 2001; Zipperer et
al., 2000) in addition to creating warmer and drier conditions for both
plants and animals (Chai et al., 2019; Taha, 1997; Wang et al., 2017).
As a consequence, urbanization results in the simplification of
ecological communities and the alteration of ecosystem processes such as
biotic interactions (Bang and Faeth, 2011; Fenoglio et al., 2020; Magura
et al., 2010; McDonnell and Hahs, 2015). Understanding how the nature
and strength of species interactions change along urbanization gradients
could help us to unravel the mechanisms driving changes in species
distribution and composition, which remain insufficiently known (but see
Kozlov, Lanta, Zverev, \& Zvereva, 2015; Moreira et al., 2019; Turrini,
Sanders, \& Knop, 2016).

Plant-herbivore interactions play a pivotal role in ecosystems and
consequently are one of the most studied biotic interactions (Jamieson
et al., 2012; Stam et al., 2014). Analyses of insect herbivory patterns
on woody and herbaceous plants along urban-rural gradients have received
increasing attention in recent decades (Dreistadt et al., 1990; Kozlov
et al., 2017; Moreira et al., 2019; Raupp et al., 2010). Several studies
measured the response of a single herbivore species (Parsons and Frank,
2019; Turrini et al., 2016), that of different herbivore feeding guilds
(Cuevas-Reyes et al., 2013; Kozlov et al., 2017; Moreira et al., 2019)
or the diversity and abundance of herbivores (Fenoglio et al., 2020) in
urban \emph{vs} rural environments (but see Parsons \& Frank, 2019).
Although there seems to be a general tendency towards reduced insect
abundance and diversity in urban settings as compared to rural
environments (Fenoglio et al., 2020), there is no consensus on whether
insect herbivory is higher (Parsons and Frank, 2019; Turrini et al.,
2016) or lower (Fenoglio et al., 2020; Kozlov et al., 2017; Moreira et
al., 2019) in urban compared to rural habitats. Given these mixed
findings, a better understanding of the underlying ecological factors
driving urbanization effects on insect herbivory is needed.

Several factors may explain the inconsistent effects of urbanization on
insect herbivory reported in the literature. First, insect herbivore
species vary markedly in their susceptibility to changing abiotic
conditions (Van Der Putten et al., 2010) and might therefore exhibit
different patterns of abundance and damage on focal host plants in
urban\emph{vs} rural areas (Kozlov et al., 2017; Moreira et al., 2019).
In this sense, urban habitats are often associated with stressful
climatic conditions (i.e., cities are warmer and drier than surrounding
rural environments; Calfapietra, Penuelas, \& Niinemets, 2015; Dale \&
Frank, 2014; Meineke \& Frank, 2018) where endophagous herbivore guilds,
e.g., leaf-mining and leaf-galling herbivores, could outperform
exophagous herbivores, e.g., leaf chewers (Koricheva et al., 1998).
Second, cities differ greatly in the amount of vegetation they harbour.
The local tree cover (i.e., both overall tree density and potential host
tree abundance) is a strong driver of urban biodiversity and trophic
interactions between trees, insect herbivores and their enemies
(Herrmann et al., 2012; Long and Frank, 2020; Meyer et al., 2020;
Stemmelen et al., 2020). More isolated trees frequently offer fewer
resources to insect herbivores (Chavez-Pesqueira et al., 2015), leading
to a decrease in insect herbivory (Long and Frank, 2020). Isolated trees
are also key (micro) habitats having a disproportionate importance for
foraging predators, especially bats and birds (DeMars et al., 2010;
Fischer et al., 2010; James Barth et al., 2015; Le Roux et al., 2018).
At the same time, climatic conditions also vary with local tree cover
resulting in high temperature and light intensity in more isolated
trees, which may also influence insect herbivores (Dale and Frank, 2014;
Shrewsbury and Raupp, 2000). In this way, the amount and distribution of
green areas -- and in particular that of trees -- could interfere with
the effect of urbanization on leaf herbivory. Thus, the relative
importance of all these explanatory mechanisms needs to be confirmed
along an urbanization gradient that ranges from 'green islands' with
high tree density to almost fully paved areas with only a few isolated
trees.

In this study, we investigated the independent and interactive effects
of urbanization and local canopy cover on insect herbivory on the
pedunculate oak (\emph{Quercus robur} L., 1753) throughout most of its
geographic range in Europe. To this end, we quantified herbivory as the
proportion of leaf area consumed by chewing insect herbivores as well as
the incidence of leaf-mining and gall-inducing herbivores in leaf
samples collected by professional scientists and schoolchildren in
European countries between 2018 and 2020. We specifically predicted
that: (a) insect herbivory decreases with urbanization and increases
with canopy cover; (b) the effects of urbanization and canopy cover on
leaf herbivory vary among the herbivore guilds; and (c) urbanization and
local canopy cover have an interactive effect on insect herbivory that
vary among herbivore guilds. Overall, this work provides one of the most
comprehensive studies yet, testing for effects of urbanization on
plant-herbivore interactions and shedding light into potential
mechanisms underlying such effects.

\textbf{Material and methods}

\textbf{Model system}

The pedunculate oak is one of the most common dominant deciduous tree
species in European forests. It is also a popular ornamental tree in
European urban areas (Eaton et al., 2016). Its distribution range spans
from central Spain (23degN) to southern Fennoscandia (63degN) (Eaton et al.,
2016). \emph{uercus robur} is associated with a large community of
generalist and specialist herbivorous insects belonging to different
feeding guilds (chewers, skeletonizers, gall-inducers, leaf-miners,
suckers and xylophagous) (Markovi\selectlanguage{polish}ć \selectlanguage{english}and Stojanovi\selectlanguage{polish}ć, \selectlanguage{english}2011; Moreira et al.,
2018; Southwood et al., 2005). These ecological characteristics make the
pedunculate oak a suitable model species for measuring the effects of
urbanization and forest cover on plant-herbivore interactions.

\textbf{Sampling network}

The present study is part of an ongoing citizen science project that
involved so far a total of 93 participants, including 41 scientists and
52 partner schools from 17 European countries (Castagneyrol et al.,
2019; Vald\selectlanguage{ngerman}és-Correcher et al., 2021) covering most of the native
geographical range of the pedunculate oak (\textbf{Figure 1A} ). We
geolocalized and surveyed a total of 298 mature oak trees in forest and
urban areas during 2018 (n = 132), 2019 (n = 56), and 2020 (n = 113)
(\textbf{Figure 1} ).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Figure 1.} A map showing the location of trees sampled in 2018
(yellow circles), 2019 (blue circles) and 2020 (brown circles) by
scientists and partner schools (A). Panels B-E show examples of 200 m
radius buffers centered on sampled oak trees, with varying percentages
of local canopy cover and urbanization. Panel B has 100 \% of local
canopy cover and 0 \% of urbanization; panel C has 45 \% of local canopy
cover and 40 \% of urbanization; panel D has 0 \% of local canopy cover
and 100 \% of urbanization; and panel E has 30~\% of local canopy cover
and 10~\% of urbanization. An interactive version of this map (A) is
also included in the supplementary material as \textbf{Figure A} . The
aerial images (B, C, D and E) are based on images from Bing maps, 2021.

\textbf{Leaf herbivory}

In early summer (about 10--12 weeks after oak budburst at each
location), scientists and partner schools haphazardly selected four low
hanging branches per tree facing opposite directions. They haphazardly
collected 30 leaves per branch (total: 120 leaves per tree). Then, 60
leaves were drawn blindly to reduce unconscious bias in leaf sampling.
Scientists oven-dried leaves for at least 48 h at 45\selectlanguage{ngerman}°C right after
collection (n = 203 oaks). Leaves collected by partner schools (n = 98
oaks) were oven-dried when received by the project coordinators, to
warrant optimal preservation prior to herbivory assessment.

Three response variables were used to characterize leaf herbivory
(Valdés-Correcher et al., 2021): leaf damage (i.e., the percentage of
leaf area removed by insect herbivores), leaf-miner incidence (i.e., the
proportion of leaves with leaf-mines) and leaf-gall incidence (i.e., the
proportion of leaves with galls). Herbivory was visually scored by
assigning each to one of the following classes: 0, 0.1--5.0, 5.1--10.0,
10.1--15.0, 15.1--25.0, 25.1--50.0, 50.1--75.0 or \textgreater{}75\%,
where the percentage represented the proportion of leaf surface removed
by chewing herbivores, or mined by leaf-miners. We then used the
midpoint of each class to average herbivory at the tree level (see
Valdés-Correcher et al., 2021 for details). We did not assess damage
caused by sucking insects because punctures vary widely among species
and for some species are not very visible (Schaefer and Panizzi, 2000).

\textbf{Landscape characteristics and climatic data}

We defined the degree of urbanization around focal trees as the
percentage of impervious surface (including roads and buildings) in a
buffer with a radius of 200 m centered on the focal oaks based on oak
coordinates as retrieved from Google Maps by project partners (Meyer et
al., 2020; Parsons and Frank, 2019). We also calculated the percentage
of local canopy cover within a 20 m buffer (excluding open areas and
grasslands). We used this buffer size of local canopy cover because the
local abundance of trees is a strong driver of urban biodiversity
(Herrmann et al., 2012; Long and Frank, 2020; Meyer et al., 2020;
Parsons and Frank, 2019; Stemmelen et al., 2020). To that aim we used
the High Resolution Layers of the CORINE land cover datasets with 10 m
resolution and with reference year 2018 (± 1 year). Tree Cover Density
extracted from the CORINE dataset consists of tree cover density in a
range from 0 to 100\%, while the urbanization extracted from the CORINE
dataset consists of artificially sealed areas (imperviousness ranging
from 1 to 100\%). We assumed that landscape characteristics did not
change during the survey period (2018-2020).

To control for variability in herbivory that is influenced by local
climatic conditions (Valdés-Correcher et al., 2021), we extracted spring
temperature and precipitation (mean temperature and precipitation in
April-June) data from the WorldClim database (Hijmans et al., 2005) on
the basis of the oak coordinates. Spring temperature and precipitation
correspond to the period when most of the partners collected the leaves
and also the main period of activity of insect herbivores on oak.
Urbanization and local canopy cover were slightly negatively correlated
(Pearson r = -0.38, \emph{P} \textless{} 0.05), and were independent of
latitude (Urbanization: Pearson r = 0.02, \emph{P} \textgreater{} 0.05;
Local canopy cover: Pearson r = 0.04, \emph{P} \textgreater{} 0.05) and
climate (Temperature and urbanization: Pearson r = -0.02,
\emph{P}\textgreater{} 0.05; Temperature and local canopy cover: Pearson
r = -0.12, \emph{P} \textless{} 0.05; Precipitation and urbanization:
Pearson r = 0.03, \emph{P} \textgreater{} 0.05; Precipitation and local
canopy cover: Pearson r = 0.01, \emph{P} \textgreater{} 0.05). Although
latitude was negatively correlated with temperature (Pearson r =
-0.76,\emph{P} \textless{} 0.05) and precipitation (Pearson r =
-0.70,\emph{P} \textless{} 0.05) which could have caused collinearity
issue, a previous study found that climatic variables were better
predictors of variation in herbivory and therefore decided to only
include climatic variables in the models (Valdés-Correcher et al.,
2021).

\textbf{Statistical analysis}

All analyses were run in the \emph{R} (R Core Team, 2020) with
packages\emph{MuMIn} (Barto\selectlanguage{polish}ń, \selectlanguage{english}2020) and \emph{lme4} (Bates et al.,
2018). We analysed each of the response variables separately with
generalized linear mixed-effects models. We tested the effects of
urbanization, local canopy cover and their interaction on leaf damage
with Gaussian error distribution and identity link (the results were the
same with a beta-distribution and log-link), and on the incidence of
leaf-miners and gall-inducers with binomial error distribution and
logit-link in separate models. The data was not overdispersed, visual
inspection of raw-data did not call for zero-inflated models, the
distribution of residuals met model assumptions.

In each model, Urbanization (\%), Local canopy cover (\%), Urbanization
\selectlanguage{ngerman}× Local canopy cover, Year (as a factor), Spring temperature (°C) and
Spring precipitation (mm) were included as fixed effects; and Partner ID
as a random factor to account for the fact that some partners surveyed
multiple trees and/or several years.

We analysed the data in the framework of information theory (Burnham and
Anderson, 2002). We first built three models, one for each response
variable separately (leaf damage, gall-inducer and leaf-miner
incidences). We scaled and centred all continuous predictor variables
prior to modelling to make their coefficients comparable, and verified
that uncontrolled correlations among explanatory variables were unlikely
to bias model coefficient parameter estimates (all variance inflation
factors {[}VIF{]} lower than 2) (Zuur et al., 2009). We then applied a
procedure of parsimonious model selection based on the Akaike's
Information Criterion corrected for small sample sizes (AICc) and
considered every model in a range of 2 units of AICc to the best model
as equally likely (Arnold, 2010). We calculated the AIC weight
(\emph{w\textsubscript{i}} ) -- i.e., the probability that a given model
is the best model within the set of candidate models -- and also the
relative variable importance (RVI) as the sum
of\emph{w\textsubscript{i}} of every model including this variable. When
multiple models were competing with the best model (i.e., when several
models with \selectlanguage{greek}Δ\selectlanguage{english}AICc \textless{} 2), we implemented a multi-model inference
approach, constructing a consensus model that comprised the selected
variables from the set of best models. We subsequently averaged their
effect sizes over all models in the set of best models,
utilizing\emph{w\textsubscript{i}} as the weighting parameter (i.e.,
model averaging). A certain predictor was deemed to have a statistically
significant effect on the response variable if its 95\% confidence
interval did not bracket zero.

\textbf{Results~}

Urbanization in a buffer of 200 m radius was on average 9.72 \selectlanguage{ngerman}± 0.91 \%
(± SE, n = 298 trees) and ranged from 0 to 70 \%. Local canopy cover in
a buffer of 20 m radius centered on focal oaks was on average 46.51 ±
1.90 \% and ranged from 0 to 100 \% cover.

Leaf damage was on average 7.72 ± 0.33 \%. Model selection retained the
percentage of urbanization and local canopy cover, year and spring
precipitation as important predictors explaining variability in leaf
damage (\textbf{Figure 2A, Table A} ). Specifically, leaf damage
significantly decreased with increasing urbanization (from 8.23 to
5.59~\% along the range of urbanization, \textbf{Figure BA} ) and
increased with local canopy cover (from 7.16 to 8.71 \% along the range
of local canopy cover, \textbf{Figure BD} ). Leaf damage varied across
years and was significantly greater in 2019 and lower in 2020 as
compared to 2018 (\textbf{Figure 2A} ). Leaf damage decreased
significantly with increasing spring precipitation (\textbf{Figure 2A}
).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Figure 2.} Standardized parameter estimates averaged across the
best competing models testing the effects of percentage of urbanization
and local canopy cover, their interaction, year, mean spring temperature
and/or mean spring precipitation (n = 298) on leaf damage (A) and the
incidence of gall-inducing (B) and leaf-mining (C) herbivores. Circles
and error bars represent standardized parameter estimates and
corresponding 95\% CI. The vertical dashed line centered on zero
indicate the null hypothesis. Black and grey circles indicate
significant and non-significant effect sizes, respectively. The year
2018 is the intercept and was contrasted with the years 2019 and 2020.

Insect galls were present on 6.34 \selectlanguage{ngerman}± 0.01\% of the inspected leaves.
Model selection retained the percentage of urbanization and local canopy
cover, their interaction, year, spring temperature, and spring
precipitation as important predictors explaining variability in
leaf-gall incidence (\textbf{Figure 2B, Table A} ). In particular,
gall-inducer incidence significantly decreased with increasing
urbanization (from 6.30 to 5.00 \% along the urbanization
range,\textbf{Figure 2B} , \textbf{Figure BB} ) and with increasing
local canopy cover (from 8.00 to 0.06 \% along the range of local canopy
cover,\textbf{Figure 2B, Figure BE} ). The effect of urbanization on
gall-inducer incidence was, however, contingent on local canopy cover
(significant urbanization × local canopy cover
interaction;\textbf{Figure 2B, Figure 3A} ): the negative effect of
urbanization on gall-inducer incidence was more pronounced when there
was a greater canopy cover around focal oaks. The incidence of
gall-inducers was significantly lower in 2019 and 2020 as compared to
2018, and significantly increased with increasing spring temperature
(\textbf{Figure 2B} ). Spring precipitation had no consistent effect on
gall-inducer incidence (\textbf{Figure 2B} ).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Figure 3} . Interactive effect of percentage of urbanization and
of local canopy cover (measured as the cover of urban and local canopy
cover within a buffer of 200 and 20 m radius, respectively) on the
incidence of gall-inducing (A) and leaf-mining herbivores (B).

Leaf miners were present in 17.98 \selectlanguage{ngerman}± 0.01 \% of the sampled leaves. Model
selection retained the percentage of urbanization, local canopy cover,
their interaction, year and spring precipitation as important predictors
explaining variability in leaf-miner incidence (\textbf{Figure 2C, Table
A} ). Specifically, leaf-miner incidence significantly decreased with
increasing urbanization (from 21.33 to 1.00 \% along the range of
urbanization, \textbf{Figure 2C, Figure B} ). The effect of urbanization
on leaf-miner incidence was, however, contingent on local canopy cover
(significant urbanization × local canopy cover
interaction;\textbf{Figure 2C, Figure 3B} ): the negative effect of
urbanization on leaf-miner incidence was more pronounced when there was
a lower canopy cover around focal oaks. It was significantly lower in
2019 and 2020 as compared to 2018 (\textbf{Figure 2C} ). Spring
precipitation and local canopy cover had no consistent effect on
leaf-miner incidence (\textbf{Figure 2C} , \textbf{Figure B} ).

\textbf{Discussion}

Our study revealed that urbanization can consistently reduce insect
herbivory on the pedunculate oak throughout its geographic range. The
effect of urbanization was partially modulated by the percentage of
canopy cover around oaks, with differences among herbivore feeding
guilds. Specifically, we found that urbanization and local canopy cover
had independent and opposite effects on overall leaf damage. In
contrast, effects of urbanization on gall-inducer and leaf-miner
incidence depended on local canopy cover, with a more pronounced
negative effect of urbanization on gall-inducer and leaf-miner incidence
when there was a greater and lower local canopy cover, respectively.
These results show the complexity of plant-herbivore interactions in
urbanized areas, highlighting that local habitat characteristics within
cities have the potential to attenuate or modify the effect of
urbanization on biotic interactions.

\textbf{Effect of urbanization on herbivory}

We found that the incidence of both gall-inducing and leaf-mining
herbivores decreased with increasing urbanization, suggesting that the
abundance of these species decreased with urbanization. This result
agrees with previous reports that have shown that urbanization reduces
the abundance and diversity of several guilds of insect herbivores (Barr
et al., 2021; Dobrosavljevi\selectlanguage{polish}ć \selectlanguage{english}et al., 2020; Fenoglio et al., 2020;
Herrmann et al., 2012; Kozlov et al., 2017; Moreira et al., 2019) with
the noticeable exception of sap-feeding herbivores (de Andrade and
Rivkin, 2020; Parsons and Frank, 2019). For instance, Herrmann et al.
(2012) found lower species richness of galler communities on the valley
oak (\emph{Quercus lobata} ) in urban areas than in natural areas.
Similarly, Dobrosavljevi\selectlanguage{polish}ć \selectlanguage{english}et al. (2020) found lower richness, abundance
and diversity of leaf-miner communities on the pedunculate oak in urban
areas than in natural areas.

We also found that leaf damage decreased with increasing urbanization
around focal oaks. Although this result aligns with the observation that
the incidence of gall-inducing and leaf-mining herbivores decreased with
increasing urbanization, it is important to consider that leaf damage
(i.e., the amount of biomass consumed by chewing herbivores) may not
scale proportionally with the abundance and diversity of insect
herbivores. Several other ecological factors that are influenced by
urbanization may determine the amount of damage caused by chewing
herbivores. They include the top-down control of herbivore populations
by their enemies (Kozlov et al., 2017; Planillo et al., 2021; Turrini et
al., 2016) as well as plant defenses and quality (Moreira et al., 2019;
Thompson et al., 2016). The correlative nature of our data does not
allow further robust inferences on the mechanisms underlying the
observed patterns.

\textbf{Effect of local canopy cover on herbivory}

Herbivory varied with canopy cover in the immediate vicinity of oaks,
but this effect was guild specific: there was an independent positive
effect of local canopy cover on herbivory, a negative effect on
gall-inducing herbivores, and no effect on leaf-mining herbivores.
Whereas several studies have compared herbivore abundance or diversity,
and sometimes herbivory, between urban and forested environments
(Herrmann et al., 2012; Kozlov et al., 2017; Moreira et al., 2019), only
a handful of them have addressed the effect of urban tree density on
insect herbivores (Barr et al., 2021; Christie et al., 2010; Christie
and Hochuli, 2005; Herrmann et al., 2012; Long and Frank, 2020; Meyer et
al., 2020; Raupp et al., 2010). Their findings were contradictory with
reports of both higher (Christie and Hochuli, 2005) and lower (Herrmann
et al., 2012; Long and Frank, 2020) herbivory in isolated trees as
compared to trees growing in larger forest patches. This effect of local
canopy cover also mirrors variability in the response of herbivory to
the size of forest fragments (De La Vega et al., 2012; Kaartinen and
Roslin, 2011; Simonetti et al., 2007; Vald\selectlanguage{ngerman}és-Correcher et al., 2019). We
therefore refrain from putting forth any particular mechanism that may
underlay the patterns we observed. However, we speculate that denser
tree canopies may have buffered micro-climatic variations (Coley and
Barone, 1996; Dale and Frank, 2014; Yamasaki and Kikuzawa, 2003), which
may have been particularly favourable to chewing herbivores that are
external feeders (Savilaakso et al., 2009) and at the same time
unfavorable to leaf-galling herbivores, as they benefit from high
temperatures (Valdés-Correcher et al., 2021). Alternatively, top-down
forces also vary with local canopy cover and may consequently influence
insect herbivory. For instance, predation activity of birds (Stemmelen
et al., 2020) and the abundance of birds (Valdés-Correcher et al., 2019)
increase with increasing local canopy cover. However, if the observed
negative association between herbivory and forest cover would have been
mediated by bird predation, it would have displayed the opposite
pattern. Deciphering the relative importance of the mechanisms acting
upon insect herbivores will represent a major step forward in our
understanding of insect herbivory in urban environments.

\textbf{Interactive effect of urbanization and local canopy cover on
herbivory}

Cities are heterogeneous environments where greenness may vary widely.
The design of our study allowed us to partially disentangle the response
of herbivory to the joint variation in urbanization and local canopy
cover. We found that increasing local canopy cover modulated the effect
of urbanization on some herbivores. Specifically, the negative effect of
urbanization on gall-inducing herbivores strengthened with increasing
local canopy cover, whereas increasing local canopy cover annulled the
effect of urbanization on leaf-mining herbivores. Urbanization and local
canopy cover have antagonistic effects on the microclimate and enemy
pressure. Cities are warmer than the surrounding rural areas as a result
of the ``heat island effect'' (Kalnay and Cai, 2003; Parker, 2010; Roth
et al., 1989), which is buffered by the presence of trees (Loughner et
al., 2012; Nuruzzaman, 2015). Likewise, forest patches in urban
environments serve as habitats for both herbivores and predators, which
is likely to modify the strength of horizontal (herbivores-herbivores)
and vertical (herbivores-predators) interactions in urban trees (Long et
al., 2019; Long and Frank, 2020). Endophagous herbivores such as
gall-inducers and leaf-miners are more sheltered from the environment
than ectophagous herbivores. Thus, ectophagous herbivores may be more
sensitive to local environmental conditions than endophagous herbivores.
For instance, we found a positive relationship between the incidence of
gall-inducing herbivores and temperature. It is possible that by
buffering the heat island effect, the presence of a denser canopy
reduced the incidence of gall-inducers on oaks. On the contrary,
leaf-mining herbivores were found to be favoured by lower (Gaston et
al., 2004) or intermediate temperatures (Valdés-Correcher et al., 2021).
For these herbivores, a denser canopy could have negated the heat island
effects, creating more favourable habitats. We cannot exclude that the
interactive effect of urbanization and canopy cover was partially
dependent on differential predation rates, but this could not be
investigated in the present study.

\textbf{Effect of climate on insect herbivory}

Climatic variables were included in the analyses to take into account
that oaks were sampled along a latitudinal gradient. They had a
significant effect on insect herbivory and this effect varied among
feeding guilds. Consistently with previous studies (Kozlov et al., 2016;
Valdés-Correcher et al., 2021), we found that precipitation had a
negative effect on leaf damage; temperature had a positive effect on
gall-inducer incidence, whereas leaf-miner incidence did not vary with
climate. The differences in the effect of climate among feeding guilds
may be due to differences in insect herbivore strategies to survive
different climatic conditions, which was discussed extensively in a
previous paper (see Valdés-Correcher et al., 2021).

\textbf{Conclusions}

Our simultaneous consideration of the effect of urbanization and local
canopy cover on insect herbivory provides novel insights into
plant-herbivore interactions. We found that insect herbivory responds
simultaneously to both urbanization and local canopy cover in the
pedunculate oak in the major part of its geographic range. Importantly,
our results highlight that urbanization has a negative effect on insect
herbivory across the three feeding guilds. However, local canopy cover
as well as its interaction with urbanization influenced insect herbivory
of different feeding guilds differently. Thus, local canopy cover within
cities has the capacity to mitigate or modify the effect of urbanization
on biotic interactions, as it influences the effect of urbanization on
herbivores differently. Therefore, this study supports the importance of
maintaining trees in urban areas as it may consequently contribute to
the preservation of biodiversity of insect herbivores in urban areas.
Important insights will be gained by investigating the mechanisms
driving these patterns, in particular by deciphering the interactive
effects of urbanization and canopy cover on the microclimate and enemy
pressures herbivores are exposed to.

\textbf{Acknowledgments}

This study was carried out with financial support from the French
National Research Agency (ANR) in the frame of the Investments for the
Future Programme, within the Cluster of Excellence COTE (Continental To
coastal Ecosystems: evolution, adaptability and governance)
(ANR-10-LABX-45) and was further funded by the BNP Paribas Foundation as
part of its Climate \& Biodiversity Initiative the citizen science
project Tree Bodyguards.

The authors warmly thank all the young European citizens and their
teachers who made this study possible. They also thank the professional
scientists who kindly agreed to participate in this study: Alexander
Kozel (Belarusian State Technological University and American
Psychological Association), Andreas Schuldt (Forest Nature Conservation,
Georg-August-University Göttingen, Göttingen, German), Aurélien Sallé
(Laboratoire de Biologie des Ligneux et des Grandes Cultures, INRAE,
Université d'Orléans), Chloe Mendiondo and Claire Colliaux (Department
of Agroecology, Aarhus University, Flakkebjerg Research Centre, DK-4200
Slagelse, Denmark), György Csóka (Department of Forest Protection, NARIC
Forest Research Institute, Mátrafüred, Hungary), Lars Opgennoorth
(Biodiversity and Conservation Biology, Ecological Genetics, Swiss
Federal Research Institute WSL, Birmensdorf, Switzerland), Laurent
Augusto (INRAE, Bordeaux Sciences Agro), Marija Popovi\selectlanguage{polish}ć \selectlanguage{english}(Faculty of
Forestry, University of Belgrade, Belgrade, Serbia), Mickael Pihain
(Research Unit ``Ecosyst\selectlanguage{ngerman}èmes, Biodiversité, Evolution'', University of
Rennes 1/CNRS, 35042 Rennes, France), Olivier Bouriaud (Applied Ecology
Laboratory, Forestry Faculty, ``\selectlanguage{romanian}Ștefan cel Mare, University of Suceava,
Suceava, Romania), Stefan K. M\selectlanguage{ngerman}üller (Freie evangelische Schule Lörrach),
Tomas Roslin (Department of Ecology; Swedish University of Agricultural
Sciences), Valentin Queloz (Forest Entomology, Swiss Federal Research
Institute WSL) and Vojtech Lanta (Institute of Botany CAS, Dukelská 135,
37901 T\selectlanguage{polish}ř\selectlanguage{english}ebo\selectlanguage{polish}ň, \selectlanguage{english}Czech Republic). They also thank Michael Scherer-Lorenzen
(Geobotany, Faculty of Biology, University of Freiburg) for the help
during the coordination of the research.

\textbf{Author contributions}

EVC and BC designed the study, analysed the data and led the writing.
EVC and BC coordinated the research, with help from DH, MB, MMG and RT.
AG, AGH, AMD, A. Prinzing, CB, DH, DLM, GL, IVH, JD, JH, JK, KS, LB, M.
Branco, MC, MCB, M. Bogdziewicz, M. Ferrante, MMG, MVK, PFC, RLT, RW, SG
and XM collected data and gave critical comments on the manuscript; and
AM, AP, AVS, DL, GC, JMP, M. Faticov, MLD, MT, NAM, SM and YK
contributed data.

\textbf{Data accessibility statement}

We declare that after acceptance of our manuscript we will archive our
data in a publicly accessible repository such as Dryad.

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