Tree Diversity Drives Forest Stand Resistance to Natural Disturbances

Tree diversity drives associational resistance to herbivory at both forest edge and interior Virginie Guyot, Herve Jactel, Baptiste Imbaud, Laurent Burnel, Bastien Castagneyrol, Wilfried Heintz, Marc Deconchat, Aude Vialatte To cite this version: Virginie Guyot, Herve Jactel, Baptiste Imbaud, Laurent Burnel, Bastien Castagneyrol, et al.. Tree diversity drives associational resistance to herbivory at both forest edge and interior. Ecology and Evolution, Wiley Open Access, 2019, pp.1-12. ฀10.1002/ece3.5450฀. ฀hal-02268916฀ HAL Id: hal-02268916 https://hal.archives-ouvertes.fr/hal-02268916 Submitted on 21 Aug 2019 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Received: 16 October 2018 | Revised: 11 June 2019 | Accepted: 14 June 2019 DOI: 10.1002/ece3.5450 ORIGINAL RESEARCH Tree diversity drives associational resistance to herbivory at both forest edge and interior Virginie Guyot1,2,3 | Hervé Jactel2 | Baptiste Imbaud1 | Laurent Burnel1,3 | Bastien Castagneyrol2 1 DYNAFOR, INRA, Université de Toulouse, Castanet Tolosan, France 2 BIOGECO, INRA, Univ. Bordeaux, Cestas, France LTSER Zone Atelier «PYRÉNÉES GARONNE», Auzeville‐Tolosane, France 3 Correspondence Aude Vialatte, DYNAFOR, INRA, Université de Toulouse, F‐31326 Castanet Tolosan, France. Email: aude.vialatte@inra.fr Funding information European Union Seventh Framework Programme, Grant/Award Number: 265171 | Wilfried Heinz1,3 | Marc Deconchat1,3 | Aude Vialatte1,3 Abstract Tree diversity is increasingly acknowledged as an important driver of insect herbivory. However, there is still a debate about the direction of associational effects that can range from associational resistance (i.e., less damage in mixed stands than in mono‐ cultures) to the opposite, associational susceptibility. Discrepancies among published studies may be due to the overlooked effect of spatially dependent processes such as tree location within forests. We addressed this issue by measuring crown defolia‐ tion and leaf damage made by different guilds of insect herbivores on oaks growing among conspecific versus heterospecific neighbors at forest edges versus interior, in two closed sites in SW France forests. Overall, oaks were significantly less defoliated among heterospecific neighbors (i.e., associational resistance), at both forest edge and interior. At the leaf level, guild diversity and leaf miner herbivory significantly increased with tree diversity regardless of oak location within stands. Other guilds showed no clear response to tree diversity or oak location. We showed that herbi‐ vore response to tree diversity varied among insect feeding guilds but not between forest edges and interior, with inconsistent patterns between sites. Importantly, we show that oaks were more defoliated in pure oak plots than in mixed plots at both edge and forest interior and that, on average, defoliation decreased with increasing tree diversity from one to seven species. We conclude that edge conditions could be interacting with tree diversity to regulate insect defoliation, but future investigations are needed to integrate them into the management of temperate forests, notably by better understanding the role of the landscape context. KEYWORDS ecosystem functioning, forest edge, insect herbivory, plant diversity 1 | I NTRO D U C TI O N et al., 2017; Moreira, Abdala‐Roberts, Rasmann, Castagneyrol, & Mooney, 2016). Meta‐analyses showed an overall lower level Within the general biodiversity—ecosystem functioning frame‐ of insect damage in more diverse plant communities, both in work, a large body of research has been addressing associational agricultural (Letourneau et al., 2011) and forest ecosystems effects of plant diversity on resistance to insect herbivores (Jactel (Castagneyrol, Jactel, Vacher, Brockerhoff, & Koricheva, 2014; 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. © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Ecology and Evolution. 2019;00:1–12. www.ecolevol.org | 1 2 | GUYOT eT al. Jactel & Brockerhoff, 2007). Still, this general pattern masks a resistance depends on several biotic and abiotic factors such as large variation in the magnitude but also in the direction of as‐ host specificity, local climate or bottom‐up and top‐down processes sociational effects identified in the literature, particularly in for‐ which appear acting differently on different herbivores (Barton et est ecosystems, from positive (i.e., associational resistance, AR; al., 2015; Singer et al., 2014). Importantly, these processes may also Barbosa et al., 2009), neutral (e.g., Haase et al., 2015) to negative be affected by edge effects. First, different herbivore species may effects (i.e., associational susceptibility, AS; Schuldt et al., 2010). respond differently to forest edges (Ewers & Didham, 2006; Ries, Current knowledge about mechanisms driving associational ef‐ Fletcher, Battin, & Sisk, 2004) depending on their traits, for exam‐ fects in plants is largely derived from controlled experiments and ple, those driving dispersal and foraging behaviors. Second, differ‐ has been more commonly addressed in grasslands than in for‐ ences in abiotic factors between forest edges and forest interior ests. (Grossman et al., 2018; Meyer et al., 2017). Although such drive changes in leaf traits (Silva & Simonetti, 2009), which may have experiments perfectly control for plant richness and composition, cascading effects on herbivores (Bagchi, Brown, Elphick, Wagner, & they are designed to minimize other sources of variation in plant‐ Singer, 2018). Third, the activity of predators also differs between herbivore interactions like spatial variability. Yet, a better under‐ forest edges and interior (Bagchi et al., 2018; Maguire, Nicole, standing of ecological drivers of these interactions in real‐world Buddle, & Bennett, 2015; Pryke & Samways, 2011; Ries et al., 2004), ecosystems requires taking such spatial effects into account. thus leading to a differential top‐down control of insect herbivores At a time when the length of forest edges is sharply increas‐ between forest edges and forest interiors. Altogether, these find‐ ing due to fragmentation associated with road constructions, ag‐ ings suggest that tree location within forests (i.e., edge vs. interior) ricultural intensification, forest logging and housing development may affect associational effects in a way that differs among insect (Fahrig, 2003), the risk of forest pest damage is also increasing due herbivores. to higher recruitment of colonizing herbivores (Didham, Ghazoul, The main objective of our study was to compare the effect of Stork, & Davis, 1996), warmer temperature (due to sunlight) fa‐ tree species diversity on insect damage at forest edge versus interior voring poikilothermic organisms (Kouki, McCullough, & Marshall, for the whole community of herbivores (measured as total crown 1997; Saunders, Hobbs, & Margules, 1991), or higher probability defoliation, for example, Guyot, Castagneyrol, Vialatte, Deconchat, of abiotic disturbance like wind throw benefiting wood damaging & Jactel, 2016) and for specific feeding guilds of insect herbivores insects (Peltonen, 1999). Forest fragmentation has well docu‐ (Figure 1). We focused on oaks as target tree species and used a mented effects on insect herbivores through increased length of complete factorial design, sampling individual oak trees with con‐ edges and sharp contrasts between edges and interiors of forest specific versus heterospecific neighbors (hereafter referred to as fragments (Batary, Fronczek, Normann, Scherber, & Tscharntke, pure and mixed plots) at both edge and interior of the same forest 2014; Fahrig, 2003; Harper et al., 2005; Vodka & Cizek, 2013; patches. Wirth, Meyer, Leal, & Tabarelli, 2008). In particular, the species richness and composition of insect communities differ between forest edges versus interior (Barbosa, Leal, Iannuzzi, & Almeida‐ Cortez, 2005; Normann, Tscharntke, & Scherber, 2016; Pryke & Samways, 2011; Souza, Santos, Oliveira, & Tabarelli, 2016). In 2 | M ATE R I A L S A N D M E TH O DS 2.1 | Study sites addition, insect herbivory is generally greater at forest edges as The study was carried out in forest patches located in the valleys compared to forest interior (De Carvalho, Rodrigues Viana, & and hillsides of Gascony, a rural landscape of South‐Western France. Cornelissen, 2014; Maguire, Buddle, & Bennett, 2016; Thompson, Grayson, & Johnson, 2016). Some authors have proposed that this pattern is partially driven by increased abundance and diversity of plant resources and greater proportion of generalist herbivores at forest edges (De Carvalho et al., 2014; Rossetti, Tscharntke, Aguilar, & Batary, 2017). Yet, tree diversity generally triggers as‐ sociational resistance against specialist herbivore species while effects on generalist herbivore species are generally more variable (Castagneyrol, Jactel, Vacher, et al., 2014). It is therefore likely that the strength and direction of associational effects vary between forest edges and forest interior, which may have profound impli‐ cation for the dynamic of forest fragments. Yet, to the best of our knowledge, this possibility has rarely been addressed so far (but see van Schrojenstein Lantman et al., 2018). Tree species diversity has also different effects on different insect feeding guilds (Castagneyrol, Giffard, Péré, & Jactel, 2013; Vehviläinen, Koricheva, & Ruohomäki, 2007). Indeed, associational F I G U R E 1 Example of oak leaf presenting damage made by different insect feeding guilds (incl. leaf chewers, skeletonizers and miners) | GUYOT eT al. 3 F I G U R E 2 Study sites near Toulouse (SW France). Forest cover is presented for each site in gray (A for Aurignac and B for Lamothe). Forest patches that were studied are in black; white dots in these forest patches represent sampled plots The climate is temperate with oceanic and Mediterranean influ‐ distance was used to make sure that focal trees were under an ences and soils are mainly calcareous or molasses. Forest patches edge influence (Harper et al., 2005; Alignier & Deconchat, 2011). are dominated by oaks (Quercus petraea Liebl., Quercus robur L. and However, the focal tree of edge plots was not right at the edge of the Quercus pubescens Willd.) mixed with other native deciduous species patch, so as to be surrounded by other trees. Interior plots were lo‐ (Carpinus betulus L., Prunus avium (L.) L., Acer campestre L., Fraxinus cated in the inner area of the patch, at least 60 m far from the border. excelsior L. and Sorbus torminalis L. (Crantz)). Sampled plots were The adjacent land cover of forest patches was temporary grassland located in two close sites, Aurignac and Lamothe (260 km2 each) or annual crop field. The selected forest patches had no large forest 40 km apart from one another, where forest cover was 18% and 9% roads, clearings or recent cuttings in order to avoid internal edge respectively (Figure 2, Table 1). effects. The sampling design therefore resulted in two orthogonal factors (Location and Diversity), with two levels each. 2.2 | Plot selection in forest patches We established a total of 106 plots, within 16 forest patches (Table 1), between April and October 2012, with the agreements of forest owners. Patch surface area varied between 16 and 46 ha. Within each patch, we aimed at establishing at least four plots: one pure and one mixed plots, both at the edge of and within the patch. A sampling plot (appr. 200 m2) consisted of a focal oak tree surrounded by its closest neighboring trees, i.e., with no more than 3 m between neighboring tree crown and focal tree crown. According to the patch area and the distribution of oak species, most patches had more than four experimental plots, while a few had less, resulting in an unbal‐ anced number of replicates per modality of plot diversity × location (Table 1). Neighboring trees were either of the same oak species, i.e., pure plot, or of different trees species, i.e., mixed plots (in order of frequency: C. betulus, P. avium, Q. pubescens, A. campestre, F. excel‐ sior, Populus tremula L., Robinia pseudoacacia L., Castanea sativa Mill., S. torminalis, Fagus sylvatica L., Ulmus minor Mill., Pseudotsuga men‐ ziesii (Mirb.) Franco, Tilia platyphyllos Scop., Quercus rubra L., Corylus avellana L., Crataegus monogyna Jacq., Sorbus domestica L., Alnus glutinosa (L.) Gaertn., Betula pendula Roth, Fraxinus angustifolia Vahl, Malus sylvestris Mill. and Pinus pinaster Aiton). Tree species richness ranged from 3 to 7 species in mixed plots. Edge plots were located within a 30 m distance from the border of the patch. This threshold TA B L E 1 Characteristics of study sites with number of sampled forest patches, plots and neighboring trees Study sites Aurignac Saint‐Lys Total GPS coordinates 43°16′11.6″N 43°30′40.0″N 0°50′50.3″E 1°11′30.0″E Site elevation (mean) 323 m (±44) 201 m (±28) Forest cover 18.5% 9.2% Number of sampled forest patches 10 6 16 Number of sampled plots Pure Edge 13 2 15 Interior 11 6 17 Edge 22 13 35 Interior 24 15 39 70 36 106 730 376 1,106 Mixed Total Number of neigh‐ boring trees 4 | GUYOT eT al. To be included in the survey, focal oak trees had to fulfill four criteria, i.e., to be (a) Q. petraea or Q. robur (we did not distinguish where PACL represents the proportion of the living crown exposed to sunlight: between the two oak species because they are closely‐related spe‐ cies that can hybridize and are therefore difficult to distinguish in the PACL = field; furthermore they were assumed to be functionally equivalent PCL ( ) PCL 1 − PDBL ) ( )( ) 1 − PDBL + 1 − PCL 1 − PDBS ( (2) in terms of traits involved in oak‐herbivore relationship [Southwood, Wint, Kennedy, & Greenwood, 2004]), (b) dominant or codominant in the canopy (i.e., tree height compared to other trees of the stand) in order to standardize for the tree size, (c) surrounded at 360° by other trees in order to get standardized (symmetrical) crown shapes, and (d) at least 50 m from another sampled focal tree for the sake of independency. A tree was considered a neighbor of a focal oak if (a) its crown was at a maximum of 3 m away from the crown of the focal tree; (b) its diameter at breast height (DBH) was larger than 10 cm; and (c) its height was greater than half the average height of the can‐ opy (in order to exclude too small individuals, including saplings). The total sample of trees consisted in 106 focal oak trees (i.e., 106 experimental plots) and 1,106 neighboring trees (Table 1), i.e., each focal tree was surrounded by ca. 10 neighboring trees. 2.4 | Leaf damage assessment All focal oak trees were climbed to collect leaf samples from September 9th to 26th, 2013 (with the agreement of forest own‐ ers). Two branches were cut at random, one at the top and an‐ other one in the middle of tree crown, to obtain a leaf sample on each section of the crown (i.e., sun exposed and shady). On each branch, 50 leaves were collected at random and frozen at −18°C until damage assessment. Damage by seven different feed‐ ing guilds was visually assessed by a single person (BI). For leaf chewers and skeletonizers, we scored damage using seven classes of damage (0%, >0%–5%, >5%–10%, >10%–25%, >25%–50%, >50– 75, >75%). Chewing damage was assessed first, then skeletonizing damage was assessed on the remaining intact leaf area (Johnson, 2.3 | Crown defoliation assessment Bertrand, & Turcotte, 2016). For miners, rollers, tiers, gall makers Crown defoliation, i.e., foliar loss, in focal trees was estimated by and sap feeders, we counted the number of leaves with at least adapting the ICP Forests protocol (Eichhorn et al., 2010). One of the main differences was that insect damage was assessed on the whole crown, instead of the “assessable crown” only (see Guyot et al., 2015). To assess crown defoliation, a comparison was made be‐ one individual damage. The mean percentage of leaf area removed (defoliation) by chewers and skeletonizers and the percentage of leaves impacted by each of the other guilds (incidence) were calcu‐ lated for each sampled tree. tween the focal tree and a reference tree, i.e., a healthy tree with full foliage in the same forest patch. In our protocol, tree crown was separated in two sections, one exposed to sunlight and the other in the shade, as foliar loss may be also due to competition for light or natural pruning in the shaded part, given that oak trees are heliophil‐ ous. The assessment was done with binoculars by the same trained person (LB) in order to avoid observer bias. On each focal oak, the observer visually estimated the propor‐ tion of (a) crown volume exposed to sunlight (PCL), (b) dead branches in the two sections of the crown (PDBL for light exposed and PDBS for the shady section, respectively) and (c) defoliation in the two sections of the living crown i.e., the crown excluding dead branches (PDefL for the sun light exposed and PDefS for the shady section, re‐ spectively). To estimate the proportion of dead branches in each part of the crown, the total number of branches was counted. The following percentage classes were used for all proportion variables: 0%, >0%–1%, >1%–12.5%, >12.5%–25%, >25%–50%, >50%–75% and >75%. The crown was systematically assessed from two oppo‐ site points of view to account for total crown defoliation. The mean of damage class medians (i.e., medians of the two estimates for the two sides per tree) was used if a different score was attributed for different sides of the crown. The total percentage of crown defolia‐ tion TDef was then estimated as: ( ) TDef = PACL × PDefL + 1 − PACL × PDefS 2.5 | Statistical analyses To test the representativeness of crown assessment we first calcu‐ lated Pearson's correlations between TDef and each insect guild dam‐ age estimated with the leaf sample collected in the same focal oak trees. For each response variable (total crown defoliation TDef, guild diversity using a Shannon index and guild‐specific damage or abun‐ dance), we first built a beyond optimal linear mixed effect model in‐ cluding Site (Aurignac vs. Lamothe), Tree diversity (Pure vs. Mixed stands), Location (forest interior vs. forest edge) as fixed effects as well as every two‐ways interactions. We declared the forest patch (n = 16) as a random factor to account for variance arising from non‐ independent plots within the same patch. Data on leaf miners, leaf gallers, leaf tiers, leaf rollers and sap feeders were recorded as count data. For these response variables, we used generalized mixed effect models with a Poisson error family and log‐link. In a second model, we replaced the categorical factor plot diversity (pure vs. mixed) by actual tree species richness as continuous variable (ranging from 1 to 7 tree species). Models were built using lmer function in lme4 package (Bates, Mächler, Bolker, & Walker, 2015) in R version 3.4.4 (2018‐03‐15). For each response variable, we applied model selection based (1) on information theory. We ranked the 18 resulting models ac‐ cording to their Akaike's Information Criterion corrected for small | GUYOT eT al. sample size (AICc) and calculated the difference between model AICc and the AICc of the best model, i.e., the model with the lowest AICc. According to our sample size, models with ΔAICc < 2 can be 5 3.2 | Variation of guild‐specific damage and guild diversity with plot diversity and location interpreted as competing models with no evidence for one being Stand type or tree species richness, tree location or site had no sta‐ better than the other(s) (Burnham & Anderson, 2002). We also cal‐ tistically clear effects on guild‐specific damage or abundance, with culated model R to estimate model fit, and AICc weight. We cal‐ the exception of leaf miners (Table 2, Figure 3). For leaf miners, the culated variable importance as the sum of AICc weights of every best model was the complete model, with no other competing model models containing this variable as a predictor. Variable importance with ΔAICc < 2 (Table 2). Model coefficient parameter estimates in‐ corresponds to the probability that a given variable is included in dicated that stand type had a statistically clear effect on leaf‐mining the best model (Burnham & Anderson, 2002; Symonds & Moussalli, herbivores that was contingent on site (i.e., Site × Diversity inter‐ 2011). However, it does not represent the probability that an ex‐ action). Specifically, leaf‐mining herbivores were more abundant in 2 planatory variable is a good predictor of the response variable. We mixed stands than in pure stands; this effect was particularly strong therefore estimated model parameter coefficients and their 95% in Aurignac site and was much weaker and opposite in Lamothe site CI using model averaging. Model comparison was done using the (Figure 4a). However, replacing stand type by tree species richness dredge and model.avg functions in the MuMIn package in R (Bartoń, to characterize tree diversity around focal oaks did not confirm the 2018). fact that tree diversity had a statistically clear effect on leaf miners (Figure 4b). 3 | R E S U LT S Guild diversity was significantly influenced by Stand type and Site, regardless of whether tree diversity was characterized by stand type or tree species richness (Table 2 and Figure 3). Specifically, All sampled oak trees were damaged by insect herbivores. Crown guild diversity was greater in mixed stands than in pure stands and defoliation of focal trees (TDef ) was on average 15.1% (SE ± 1.1) increased with tree species richness. These effects were consis‐ and ranged from 1% to 51%. At forest edge, TDef was on average tent across sites, but the guild diversity was significantly lower in 22.3% (±3.0) and 11.7% (±1.5) in pure and mixed plots respec‐ Aurignac than in Lamothe (Figure 4a,b). tively, while in interior it was on average 16.9% (±2.7) and 14.7% (±1.8) in pure and mixed plots respectively. Leaf area removed by chewers ranged from 3% to 42% (mean = 13.4 ± 0.7%). On average, 4 | D I S CU S S I O N galls developed on 34.7% (±1.9) of sampled leaves, leaf miners on 22.1% (±0.9), sap feeders on 16.4% (±1.1), leaf tiers on 1.5% (±0.1) We showed that in both sites, oaks were more defoliated in pure oak and leaf rollers on 0.4% (±0.1). Crown defoliation was positively plots than in mixed plots at both edge and forest interior and that, and significantly correlated with leaf area removed by chewing on average, defoliation decreased with increasing tree diversity (1–7 herbivores (Pearson's correlations: r = 0.39, p < 0.001), and with species) demonstrating associational resistance patterns. However the incidence of tiers and gallers (r = 0.22, p = 0.026 and r = 0.19, we also found that relationships between herbivory at leaf scale and p = 0.044 respectively). tree diversity varied among insect feeding guilds and ranged from higher to equal in mixed plots as compared to pure plots. While dam‐ 3.1 | Effects of plot diversity and tree location on crown defoliation When tree diversity was defined as pure versus mixed plots (i.e., age made by some guilds differed between sites, they were inde‐ pendent of tree location at forest edges or interior. Herbivore guild diversity was also different between sites and increased with tree diversity whatever the oak location in both sites. stand type), the complete model was identified as the best model By considering both total crown defoliation and the leaf dam‐ (i.e., with the lowest AICc), with no other competing model with age or insect incidence associated to seven herbivore feeding ΔAICc < 2 (Table 2). However, the model coefficient parameters guilds, our study provides evidence for the debate on whether or indicated that only stand type had a statistically clear effect on not tree species diversity would lead to associational resistance in crown defoliation (Figure 3), whereby defoliation was on average natural environments. While many reasons have been proposed to lower in mixed plots than in to pure plots (Figure 4). Although re‐ explain discrepancies in the literature, including insect herbivores' tained in the best models, other predictors had no statistically clear host specificity (Castagneyrol, Jactel, Vacher, et al., 2014; Jactel effect on crown defoliation (Figure 3). This finding indicates that & Brockerhoff, 2007) or climatic conditions (Kambach, Kühn, the overall effect of tree diversity on crown defoliation was con‐ Castagneyrol, & Bruelheide, 2016), the methodology of herbiv‐ sistent across sites and location within forests. The results were ory assessment may be another potential explanation. Indeed, in comparable when stand type was replaced by tree species richness the present study focusing on oak species, we showed that tree to characterize tree diversity around focal oaks (Table 2, Figure 4) diversity effects appear also to differ on guild‐specific leaf dam‐ and consistently indicate that defoliation decreased with increasing ages versus total crown defoliation. A reason may be that the tree species richness. total crown defoliation encompassed cumulative effects of many 6 | GUYOT eT al. TA B L E 2 Final selection of best linear mixed models testing the effect of plot tree diversity (pure vs. mixed or tree richness), location (edge vs. interior) and site on total oak defoliation, guild diversity and guild‐specific damage or abundance Descriptor of tree diversity Stand type (pure vs. mixed) Weight R2m R 2c 913.17 0 0.52 0.08 0.23 Location + Site + Stand type + Location × Site + Location × Stand type + Site × Stand type 816.99 0 0.31 0.08 0.23 Location + Site + Stand type + Location × Site + Site × Stand type 818.54 1.55 0.14 0.12 0.33 Location + Site + Stand type + Location × Stand type + Site × Stand type 818.88 1.89 0.12 0.06 0.16 Model Defoliation Location + Site + Stand type + Location × Site + Location × Stand type + Site × Stand type Chewers AICc Location + Site + Stand type + Location × Site + Location × Stand type 818.98 1.99 0.12 0.42 0.42 Skeletonizers Wood 131.17 0 0.58 0.08 0.23 Site 132.53 1.36 0.29 0.12 0.33 Miners Location + Site + Stand type + Location × Site + Location × Stand type + Site × Stand type 970.59 0 0.64 0.08 0.23 Gallers Location + Site + Stand type + Location × Site + Location × Stand type + Site × Stand type 1,514.96 0 0.95 0.08 0.23 Tiers Wood 440.75 0 0.4 0.08 0.23 Rollers Wood 249.83 0 0.6 0.08 0.23 Sap feeders Location + Site + Stand type + Location × Site + Location × Stand type + Site × Stand type 1,451.45 0 0.93 0.08 0.23 Guild diversity Tree rich‐ ness (1 to 7 sp.) Delta Response Defoliation Chewers Skeletonizers Site −260.1 0 0.44 0.08 0.23 Site + Stand type −258.9 1.19 0.24 0.12 0.33 Wood −258.13 1.97 0.16 0.06 0.16 Location + Site +Tree richness + Location × Site + Location × Tree richness 922.01 0 0.26 0.08 0.2 Location + Site + Tree richness + Location × Site + Location × Tree richness + Site × Tree richness 922.18 0.17 0.24 0.14 0.34 Location + Site + Tree richness + Location × Site 923.62 1.61 0.12 0.09 0.21 Location + Site + Tree richness + Location × Site + Site × Tree richness 923.74 1.73 0.11 0.36 0.36 Location + Site + Location × Site 820.83 0 0.3 0.08 0.2 Location + Site + Tree richness + Location × Site + Site × Tree richness 822.56 1.74 0.12 0.14 0.34 Wood 131.17 0 0.58 0.08 0.2 Site 132.53 1.36 0.29 0.14 0.34 Miners Location + Site + Tree richness + Location × Site + Location × Tree richness + Site × Tree richness 979.12 0 0.46 0.08 0.2 Gallers Location + Site + Tree richness + Location × Site + Location × Tree richness + Site × Tree richness 1,521.49 0 0.89 0.08 0.2 Tiers Wood 440.75 0 0.47 0.08 0.2 Rollers Wood Sap feeders Location + Site + Tree richness + Location × Site + Location × Tree richness + Site × Tree richness Guild diversity Site Wood 249.83 0 0.7 0.08 0.2 1,458.38 0 0.84 0.08 0.2 −260.1 0 0.66 0.08 0.2 −258.13 1.97 0.25 0.14 0.34 Note: AICc, ΔAICc, weight, marginal (m) and conditional (c) R are given for models within a Δi = 2 units of the best model (i.e., the model with the lowest AICc). Patch identity (Wood) is given as random factor. 2 insect species since the beginning of the growing season, with at only one‐time point. Similarly, Sholes (2008) and Guyot et al. potential opposite response of some guilds to tree diversity and (2015) observed a significant decrease of insect damage in for‐ tree location, whereas the guild‐specific damages were estimated ests with higher tree diversity (AR) by evaluating final defoliation, GUYOT eT al. | 7 F I G U R E 3 Model coefficient parameter estimates from the linear mixed models testing the effect of plot diversity (D: pure vs. mixed), plot location (L: edge vs. interior) and site (S: Aurignac vs. Lamothe) on total oak defoliation, guild diversity and guild‐specific damage or abundance. Parameters estimates are given for fixed effects of models within a Δi = 2 units of the best model (i.e., the model with the lowest AICc). Patch identity is given as random factor. Black and white dots are significant and non‐significant predictors, as determined by 95% CI. For tree diversity, negative values indicate that the response variable was lower in mixed stands as compared to pure stands. For Location, negative values indicate that the response variable was lower at forest interior as compared to forest edges. For Site, negative values indicate that the response variable was lower at Lamothe as compared to Aurignac on mature trees. By contrast, Schuldt et al. (2010) and Wein et Guild diversity increased with tree species diversity, most prob‐ al. (2016) observed higher herbivory damage in mixed forests by ably due to higher colonization success in more diverse tree commu‐ studying insect herbivory on individual leaves, in spring, on young nities (Liebhold et al., 2018). A higher number of insect species with saplings. Methodological issues like coarse assessment of overall different feeding habits (i.e., of different feeding guilds) are likely to crown defoliation versus more accurate estimates but on much locate, find and eventually colonize a suitable host tree within more fewer individual leaves may have also influenced the observed diverse forests with trees of different size and qualities. And yet, be‐ patterns. cause not all guilds cause similar amount of visible defoliation, higher 8 | GUYOT eT al. | GUYOT eT al. 9 F I G U R E 4 Effect of stand type (pure vs. mixed, A) and tree species richness (B) on (i) total tree crown defoliation, (ii) leaf miner abundance and (iii) herbivore guild diversity on focal oaks. In A, dots represent mean percentage of crown defoliation per focal oak tree (±SE). In B, dots represent individual focal oak tree. Solid lines and shaded areas represent predictions from the models and corresponding confidence intervals (95%) herbivore diversity does not necessarily translate into higher crown this hypothesis (Alignier & Deconchat, 2011). To better understand damage. the processes that may cause different associational effects at the The role of host specificity in dominant insect herbivores is forest edge versus interior, it will be necessary to identify herbivo‐ known to be important in the response of herbivory to tree diver‐ rous species and characterize their biological traits (in particular diet sity, and it has been shown that AR is more likely to be observed specialization and dispersal abilities). against specialist than generalist insects (Castagneyrol, Jactel, Finally, landscape‐mediated edge effects could also interact with Vacher, et al., 2014). However in our study, we found in general no forest interior conditions to influence ecological processes in forest significant effect of tree diversity on damage by each feeding guild, patches (Garcia‐Romero, Vergara, Granados‐Pelaez, &, Santibanez‐ which might be due to the fact that we did not sample enough leaves Andrade, 2019). The site effects observed in our study suggest that to get a relevant estimate of their abundance. On the other hand, the landscape context might specifically affect insect‐tree interac‐ clear associational effects (being AR or AS) may be more likely to tions as demonstrated by contrasting responses of leaf miners to for‐ be observed when one focuses on abundance or damage made by a est diversity in the two study sites. Forest fragmentation can change well identified herbivore species (e.g., Plath, Dorn, Riedel, Barriois, the amount, quality and connectivity of habitat patches within a & Mody, 2012; Damien et al., 2016; Muiruri & Koricheva, 2016). On landscape (Hughes, Cobbold, Haynes, & Dwyer, 2015; Maguire et the contrary, when herbivory is assessed at the level of the herbi‐ al., 2016). Our two studied sites belong to the same biogeographical vore community (e.g., total damage with no identification of respon‐ area, but vary in their forest cover (18.5% vs. 9.2%). The amount of sible herbivore species), overall response to tree diversity might be habitat and distances between habitat patches are known to influ‐ blurred by opposite responses of different herbivore species. The ence metapopulation processes (Gilpin & Hanski, 1991) and hence only significant effect of tree diversity was observed on leaf miners the colonization probability of host trees by forest insect herbivores in our study. Contrary to expectation, abundance of those herbivore (Robert et al., 2018). Forest insect herbivory can be thus driven by a specialists increased with forest diversity (associational susceptibil‐ complex interplay between local tree diversity and stand isolation in ity). One possible explanation for the difference with the theory is the landscape (Castagneyrol, Giffard, Valdés‐Correcher, & Hampe, that we measured the number of leaf mines here, not the damage 2019). caused by leaf miners. Yet, the leaves may have accumulated mines made by several species, showing the same pattern of response to tree diversity as the diversity of herbivore guilds. AC K N OW L E D G M E N T S Our results provide no supporting evidence to the effect of tree The research leading to these results received funding from the location at forest edge or interior on herbivore‐plant interactions. European Union Seventh Framework Programme (FP7/2007‐2013) This result confirms those recently found by van Schrojenstein under grant agreement n°265171 for the FunDivEurope project. The Lantman et al. (2018) and Rossetti, Verena, Videla, Tscharntke, and PhD of VG was funded by INRA and the Aquitaine Region. We would Batary (2019), but contradicts Wirth et al. (2008) and Maguire et like to thank the technicians from INRA Toulouse for field assistance al. (2016) who showed that tree location can affect herbivory pat‐ and the climbers for collecting oak leaves (Guillaume Gauthier from terns. Numerous biotic and abiotic factors that can modify insect LiberTree association and the team from INRA Avignon). We also behavior or survival are acting at forest edge. Insects abundance thank Sylvie Ladet for maps and Michel Goulard for help with sta‐ and diversity are often higher at forest edge than in forest interior tistical analyses. (Reitz & Trumble, 2002). Herbivore's natural enemies like predatory birds (Terraube et al., 2016) and insect parasitoids (Peralta, Frost, & Didham, 2018) also show strong response to forest edge effects. Trees at the ecotone between forest patches and open habitats are C O N FL I C T O F I N T E R E S T None declared. probably more sunlit but also more accessible by those insects, which migrate or move from one forest patch to another at each genera‐ tion (Dulaurent et al., 2012; De Somviele, Lyytikainen‐Saarenmaa, AU T H O R C O N T R I B U T I O N S & Niemela, 2007). A reason for the absence of edge effect in our VG, HJ, MD and AV devised the conceptual idea of the study and de‐ study could be that the forest patches were too small, as edge ef‐ signed the experimental sampling; VG, LB collected field data; WH fects can occur at kilometer‐scales for some taxa (Ewers & Didham, designed the database; VG and BC conducted the statistical analy‐ 2008). Previous results on highly variable responses of vegetation ses; AV and VG led the writing of the manuscript; All coauthors made to edge effect in the same forest patches provide partial support to a significant contribution to the final manuscript. 10 | GUYOT eT al. DATA AVA I L A B I L I T Y S TAT E M E N T Herbivory data: GBIF https://doi.org/10.15468/nkxooz. https:// www.gbif.org/dataset/25ff1a48‐668d‐470a‐a149‐5fa0e8535971 ORCID Bastien Castagneyrol Aude Vialatte https://orcid.org/0000‐0001‐8795‐7806 https://orcid.org/0000‐0003‐2614‐2472 REFERENCES Alignier, A., & Deconchat, M. (2011). Variability of forest edge effect on vegetation implies reconsideration of its assumed hypothet‐ ical pattern. Applied Vegetation Science, 14, 67–74. https://doi. org/10.1111/j.1654‐109X.2010.01105.x Bagchi, R., Brown, L. M., Elphick, C. S., Wagner, D. L., & Singer, M. S. (2018). Anthropogenic fragmentation of landscapes: Mechanisms for eroding the specificity of plant‐herbivore interactions. 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