# Quercus suber and Pinus pinea mixture alters leaf traits and reduces insect herbivory without affecting predation in a Mediterranean agroforestry system

Inês D.H. Ramires, Alexandra C Correia, Bastien Castagneyrol, Pedro Barcik, David Lloberas Lafuente, José Carlos Franco, Manuela Branco

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Inês D.H. Ramires, Alexandra C Correia, Bastien Castagneyrol, Pedro Barcik, David Lloberas Lafuente, et al.. Quercus suber and Pinus pinea mixture alters leaf traits and reduces insect herbivory without affecting predation in a Mediterranean agroforestry system. Forest Ecology and Management, 2025, 596, pp.123081. 10.1016/j.foreco.2025.123081. hal-05504584

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# Quercus suber and Pinus pinea mixture alters leaf traits and reduces insect herbivory without affecting predation in a Mediterranean agroforestry system

Inês D.H. Ramires<sup>a, *, b</sup>, Alexandra C. Correia<sup>b, c, d</sup>, Bastien Castagneyrol<sup>d, e</sup>, Pedro Barcik<sup>a, f</sup>, David Lloberas Lafuente<sup>a, e</sup>, José Carlos Franco<sup>b</sup>, Manuela Branco<sup>b, f</sup>

## ARTICLE INFO

### Keywords:

- Mixed forest

- Cork oak

- Stone pine

- Montado

- Integrated pest management

- Ecological interactions

- Sentinel live prey

## ABSTRACT

Understanding how tree species mixtures influence forest resistance and resilience to herbivory is critical in the face of global biodiversity loss and climate change. Insect herbivores and their natural enemies respond to changes in forest composition through both bottom-up (e.g., plant traits) and top-down (e.g., predator activity) mechanisms, but their relative importance in Mediterranean mixed forests remains understudied. We assessed insect herbivory and predation rates on cork oak (*Quercus suber*) in pure and mixed stands with stone pine (*Pinus pinea*) across seven forest sites in southern Portugal. Tree traits (specific leaf area, SLA; carbon/nitrogen ratio, C/N; canopy volume; tree height) and understory vegetation characteristics were also recorded. Herbivory was 52 % lower in mixed stand compared to pure stands, although this difference was only marginally significant (p = 0.078). SLA and C/N ratio showed negative trends with herbivory, indicating a potential role of leaf traits in mediating plant resistance. Predation rates did not differ significantly between pure and mixed stands but increased with lower canopy volume and tree height. These findings suggest that plant trait variability contributes to herbivory patterns and that promoting mixed-species stands may strengthen forest resilience. Overall, this study provides valuable insights into the role of tree species mixtures in improving forest resilience and could have significant implications for forest management and biodiversity conservation in Mediterranean ecosystems. Herbivory was 52 % lower in mixed stands compared to pure stands, although this difference was only marginally significant (p = 0.078)

## 1. Introduction

Insect herbivory may cause significant damage to trees, directly impacting forest-based goods production and ecosystem functionality, leading to biodiversity loss, habitat degradation, and a subsequent decline in its economic value. Their impact may be further intensified by global change through the increase in the frequency of extreme climatic events that disrupt growth and reproduction, placing additional stress on already vulnerable forests (Guegan et al., 2023; Pureswaran et al., 2018).

Tree canopies host a diverse range of herbivorous insects, including defoliators that significantly impact trees by reducing their overall

photosynthetic capacity and growth potential (Bilgin et al., 2010; Cárdenas and Gallardo, 2016; Nabity et al., 2013; Zvereva et al., 2012). All these effects can reduce the trees' health, making them more susceptible to other pests and diseases, climate change and decrease in productivity (Boyd et al., 2019). Under intense and recurrent defoliation events, tree health (the ability to grow, reproduce, and survive despite external pressures) may be compromised, potentially leading to long-term mortality.

The use of tree species mixture in the forest is one of the adaptive silviculture strategies cited by many studies to increase resilience to pests and diseases (Field et al., 2025; Guyot et al., 2016; Jactel et al., 2021). An increase in tree species richness further promotes herbivory

<footnote><sup>a</sup> Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa 1349-017, Portugal</footnote>

<footnote><sup>b</sup> Centro de Estudos Florestais, Laboratório Associado TERRA, Instituto Superior de Agronomia, Universidade de Lisboa, Tapada da Ajuda, Lisboa 1349-017, Portugal</footnote>

<footnote><sup>c</sup> Instituto Nacional de Investigação Agrária e Veterinária, I.P., Quinta do Marquês, Avenida da República, Oeiras 2780-159, Portugal</footnote>

<footnote><sup>d</sup> BIOGECO, INRA, Université Bordeaux, Cestas 33610, France</footnote>

<footnote><sup>e</sup> Departament de Geografia, Facultat de Geografia i Història, Universitat de Barcelona, Carrer de Montalegre 6, Barcelona 08001, Spain</footnote>

<footnote>* Corresponding author.
E-mail address: idhramires@isa.ulisboa.pt (I.D.H. Ramires).</footnote>
regulation through either bottom-up or top-down ecological mechanisms. Bottom-up processes include greater resource abundance in monocultures (resource concentration hypothesis by Root, 1973) which suggests that herbivores are more likely to thrive in environments dominated by a single host species. Additionally, resistance and defensive traits of host plants, as outlined in the associational hypothesis by Hunter and Price (1992), may be enhanced by facilitative interactions among tree species in mixtures, such as those mediated by mycorrhizal activity (Barcik, 2024). Furthermore, the presence of non-host plant species can disrupt herbivore host location, by interfering with their apparency through visual or chemical cues, thereby reducing their host-finding success (Prokopy and Owens, 2003). Also, the presence of less palatable or less nutritious plant species may interfere with feeding efficiency (Jactel et al., 2021).

Top-down mechanisms postulated by the natural enemy's hypothesis (Root, 1973), are driven by the increased abundance and diversity of natural enemies, including predators, parasitoids, and parasites (Staab and Schuldt, 2020; Stemmelen et al., 2022; Vidal and Murphy, 2018). These natural enemies exert biotic pressure on herbivore populations, contributing to their regulation. In mixed forests, higher diversity and abundance of these enemies are expected due to increased habitat complexity and a wider range of available prey. This may strengthen their role in controlling herbivory pressure.

The uniform and repetitive environment of monocultures provides a higher concentration of resources, which favours the establishment, population build-up, and further spread of specialist herbivores and pathogens due to the higher availability of their preferred host species (Kim and Underwood, 2015; Loranger et al., 2012). In contrast, mixed plantations create a more heterogeneous environment where specialist pests may have difficulties locating and exploiting their hosts efficiently. The presence of diverse tree species can foster a more robust community of natural enemies, contributing to pest suppression. Tree species mixture can also alter leaf traits, such as nutrient content or defensive chemicals, through changes in physical structures or secondary metabolites (Castagneyrol et al., 2018; Muiruri et al., 2019). These mechanisms can reduce overall damage, increase tree survival rates, and lead to healthier and more stable forest ecosystems. From a management perspective, however, mixed forest plantations offer both challenges and opportunities: while they enhance resilience and biodiversity, their management is often more complex than that of monocultures. Species with different growth rates, silvicultural requirements, and economic values must be carefully selected and managed to balance ecological benefits with commercial viability.

Although extensive research has explored the resistance of mixed forests in boreal and temperate regions (Alalouni et al., 2014; Martini et al., 2022; Castagneyrol et al., 2017), studies on Mediterranean mixed forests remain scarce. Mediterranean ecosystems are characterized by harsher edaphoclimatic conditions and lower tree densities compared to boreal and temperate forests (Lionello et al., 2006). One of the most characteristic and culturally significant ecosystems of the Mediterranean Basin is the evergreen oak forests, dominated by cork oak (*Quercus suber* L.) and holm oak (*Quercus rotundifolia* L.) (*Correia and Oliveira, 1999*). These agrosilvo-pastoral ecosystems form extensive mosaic-like landscapes that resemble savannas, called *montado* in Portugal (dehesa in Spain) which play a crucial role in supporting biodiversity, soil conservation, and rural livelihoods (Pinto-Correia et al., 2011; Pinto-Correia and Godinho, 2013). These ecosystems have co-evolved with human presence, and differ markedly from other temperate ecosystems. They are considered as biodiversity hotspots shaped by vertical plant layers and a heterogeneous mosaic landscape, resulting in high ecological complexity (Salemaa et al., 2023).

Thanks to their adaptive traits, cork oaks may be valuable for regions facing increased fires and drought events. However, cork oak trees are also vulnerable to several pests and diseases that can hinder their health and resilience to climate stresses, such as the spongy moth (*Lymantria dispar* L.), the cork jewel beetle (*Coraebus undatus* F.) or the oomycete

soil-borne plant pathogen (*Phytophthora cinnamomi* Rands) (Tiberi et al., 2016).

Given these challenges, promoting tree diversity has been suggested as an adaptive strategy in the montado. In Portugal, cork oak often co-exists with stone pine (*Pinus pinea* L.), a species of growing economic value due to its edible pine nuts (EUFORGEN, 2025; ICNF, 2019). However, it remains unclear whether mixing these species can enhance cork oak resistance to insect herbivores. Understanding how bottom-up and top-down mechanisms operate in cork oak-stone pine mixtures is essential to evaluate the potential of species mixing as a strategy to improve forest resilience against insect pests.

In this study, we examined how mixing cork oak (*Quercus suber*) with stone pine (*Pinus pinea*) affects cork oak susceptibility to insect herbivory, considering both bottom-up and top-down mechanisms. We combined observational data on herbivory and predation with environmental, structural, and physiological variables to assess potential mechanisms driving changes in herbivore pressure. Specifically, we:
1) Compared levels of insect herbivory in cork oak between pure and mixed stands using leaf damage assessment.
2) Correlated herbivory levels with leaf traits (e.g., SLA, C/N ratio), stand structure (e.g., shrub density), and dendrometric variables (e.g., tree height, canopy volume).
3) Assessed predation pressure using sentinel live prey to infer differences in predator activity between pure and mixed stands.
4) Evaluated the role of both tree- and stand-level predictors in shaping observed patterns of herbivory and predation.

We hypothesized:

- Herbivory levels would be lower in mixed stands than in pure cork oak stands, consistent with associational resistance and resource concentration hypothesis.

- Predation rates would be higher in mixed stands, consistent with the natural enemies hypothesis considering that a more diverse environment can increase top-down control.

This study is the first to test how cork oak-stone pine mixtures influence herbivory and predation patterns in Mediterranean *montado* systems and whether species mixing can be considered as a viable silviculture management strategy to reduce defoliator damage in cork oak. It is worth emphasising that the samples in this study were collected in adult stands, in some cases over 50 years old, with low tree density (80-200 trees per ha) originating from natural regeneration (only one stand is a plantation). These stands exhibit pronounced vertical and horizontal heterogeneity in tree canopy structure and understory vegetation. These features are characteristic of such Mediterranean ecosystems that are traditionally managed by landowners for pine nut and cork production, often in combination with cattle grazing (either by cows or sheep). This real-world context significantly strengthens the relevance of the present study. Consequently, the findings offer an accurate representation of landowners' decision-making processes and practical management strategies.

## 2. Materials and methods

### 2.1. Study area

We inventoried areas in the central and southern regions of mainland Portugal, characterized by mild winter temperatures (rarely going below 0°C) and hot and dry summers, with an average yearly precipitation ranging from 563 to 685 mm (Herrera García et al., 2019). These areas are agroforestry systems where cork oak (*Q. suber*) and stone pine (*P. pinea*) are managed for cork and pine nut production, in combination with livestock grazing (sheep or cows) in the understory. We selected seven sites in a north-south gradient (Fig. 1). In each site, we selected two stands: one representative of a pure cork oak stand and another a mixed stand composed of approximately 50 % of cork oaks and 50 % of stone pine trees, each consisting of a circular area with a 30-m radius
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Left panel - Location of the stands in Portugal (black dots), in which the colours represent the distribution of the species used in this work. Right panel – Example of the stands. Mixed (left) and pure cork oak (right). Circles refer to crown areas whereas the colours refer to the tree species (Stone pine as orange, cork oak as green).</figcaption></figure>

(2827 m²) (Fig. 1). Although management practices differed across each site, mostly because of different livestock grazing (none, ovine, or bovine) and other management practices, they were similar between stands within each site. The soils in most sites had similar characteristics with a sandy texture.

## 2.2. Stand inventory variables

In each stand, tree dendrometric variables were measured, including tree height, canopy diameter, canopy base height, and diameter at breast height (DBH). For cork oaks, the debarking height (m) was also recorded. Trees taller than 1,30 m were inventoried and georeferenced. Canopy volume was estimated as the volume of a cylinder bounded by the tree's total height and the canopy base.

Understory vegetation was assessed along four 30-meter transects originating from the stand centre in each cardinal direction, counting, measuring the height, and identifying at the species or genus levels every woody shrub that touched the line in the transect, at every meter. The data collected was averaged at site stand scale (richness, shrub height, and density of the four transects were aggregated and averaged for the height and the density). This variable was important as an indirect assessment of grazing by cattle. As there weren't enough replicates to formally test the effect of cattle on herbivory, the vegetation information provides a proxy information for soil conditions and the presence of cattle.

## 2.3. Insect herbivory

In June 2023, we collected with a telescopic scissor two branches of completely expanded leaves per cork oak tree, on five randomly selected trees per stand. Branches were stored in labelled plastic bags in cold conditions to prevent withering, and later replaced by brown paper bags. In the lab, 20 leaves (approximately) per branch were selected from tip to base on the right side of the branch (leaves showing their adaxial surface) for assessment.

We quantified insect herbivory in each sample as the proportion of leaf area damaged or eaten by insect herbivores defoliators (chewers,

skeletonized leaves and leaf miners). Although different herbivore species may cause different damage patterns, the majority of damage was caused by chewing insects, and due to the similarity of damage caused by different species we did not attempt to identify the species responsible for the observed damages. We visually estimated insect herbivory on a scale from 0 to 6, to rate leaf damage intensity: Score 0, for no damage; score 1, for 1–5 % damage; score 2, for 6–10 % of damage; score 3, for 11–25 % of damage; score 4, for 26–50 % of damage; score 5, for 51–75 % of damage; and score 6, for more than 76 % of damage. The scores were then averaged by multiplying the number of leaves in each category by the median of the damage class and dividing by the total number of leaves.

## 2.4. Specific leaf area (SLA)

We used 10 fresh leaves of one branch per tree to measure their surface area using WinSEEDLE software (Regent, Inc.), then dried them at 60°C for 48 h and weighed them. Specific Leaf Area (SLA) was calculated as the sample leaf area to the dry weight ratio.

## 2.5. Carbon/nitrogen ratio (C/N)

Ten leaves of one branch per tree were dried at 60°C for 48 h, ground into a fine powder, and analysed for total carbon (C) and nitrogen (N) content. The C and N were determined by the Soil and Plant Laboratory at Universidade de Trás-os-Montes e Alto Douro, through combustion a 1000 °C, using Primac 100 Skalar Analytical. The carbon was quantified with NIRD (near infrared detector) and the nitrogen with thermal conductivity. The C/N ratio was then calculated.

## 2.6. Predation

Predation was measured using sentinel live prey (Calliphoridae larvae and pupae). In April 2023, 20 larvae/pupae were placed in each of four trees, close to the centre of the stand, distributed in two vials with 10 larvae/pupae per vial. In pure cork oak stands the vials were placed in cork oaks, and in the mixed stands they were placed half in cork oak
and half in stone pine, approximately. In June, the protocol was adjusted to 10 baits in a vial per tree across 16 trees per plot. Baits were placed in open containers attached to 90 cm canes, fixed to tree trunks at a height of 2 m (Fig. 2). In both months, the vials remained in the field for a 15-day period. We used plastic vials of 65 mm in height and 38 mm in diameter.

Predation attempts were identified by the presence of bite marks on pupae or missing pupae and larvae, focusing predatory bird and arthropod activity. Predation attempts data from both months were aggregated as a single value, by summing.

## 2.7. Statistical analysis

Our ultimate interest lay in the effect of tree species composition on the trophic interactions between cork oaks, insect herbivores, and their predators. However, we could not exclude that site management – the density, height or richness of the understory vegetation modified by livestock grazing – had influenced these trophic interactions through changes in the characteristics of individual trees. To avoid spurious interpretations resulting from confounding factors, we first verified that stand-related variables did not influence tree characteristics.

We built an array of linear-mixed effect models (LMM) with gaussian error distribution, testing the effect of tree species composition (two-levels factor: Pure vs Mixed) as a fixed effect and Stand nested in Site as random factor on the height, circumference and canopy volume of the cork oaks we measured in each stand (model representation in Supplementary Materials, S1). We further tested the effect of tree species composition on the density, height, and richness of shrubs using three separate Generalized Linear models (GLM) with gaussian error distribution. Due to one replicate per stand, only Site was used as random factor.

Second, we analysed the effect of tree species composition and tree variables (Canopy volume and Tree height) as fixed effects on insect herbivory and leaf traits (SLA, C/N) in separate LMMs with Stand nested in Site as random factor.

Finally, we analysed the effect of tree species composition and tree variables on predation in GLM with data aggregated at the stand level. We fitted a model with a beta error distribution after transforming predation data as follows (Douma and Weedon, 2019):

$$p^* = [p(n - 1) + 1/c] / n$$

Where *p* is the proportion of predated sentinel prey, *n* is the number of prey, and *c* is the number of categories accounted for ($c = 2$, corresponding to predated vs. non-predated prey). Canopy volume as fixed effect in both herbivory and predation analysis had to be standardized for a better model fit.

We applied a model simplification procedure to each model, whereby we sequentially deleted non-significant predictors prior to

estimating the coefficients of the most parsimonious models. Residual analysis was performed in all models using KS (Kolmogorov-Smirnov), dispersion and outlier tests with DHARMA package (Supplementary Material, S1). To improve residuals fit we performed a logarithm transformation of the response variables - Canopy volume, Tree height and SLA. All models were run in the R Statistical Software (v4.4.2; R Core Team, 2024), with packages 'glmmTMB' (v1.1.9; Brooks et al., 2017), 'DHARMA' (v0.4.6; Hartig and Hartig, 2017), 'performance' (v0.12.3; Lüdecke et al., 2021) and 'ggeffects' (v2.0.0; Lüdecke, 2018).

# 3. Results

## 3.1. Stand inventory variables

Tree height, canopy volume, were comparable between pure and mixed stands (Table 1), highlighting that the effects of tree diversity on insect herbivores are not confounded by uncontrolled variability in these habitat features. Regarding shrub density, height, and diversity there were significant differences between stands (shrub density and number of species is higher in pure stands and shrub height is higher in mixed stands, Table 1). The residuals analysis confirmed the model's uniformity, dispersion and outliers are non-significant (Supplementary material, S1).

## 3.2. Leaf traits

The mean specific leaf area was slightly higher in cork oaks growing in mixed (74.25 ± 1.42 cm²/g) as compared to pure stands (71.3 ± 1.44 cm²/g). However, the difference was not statistically significant (F (df) = 0.86, *p* = 0.32). SLA was not influenced by canopy volume (0.00009 ± 0.0009, *p* = 0.35).

In relation to C/N ratios, the average values were slightly higher in pure cork oak stands (27.96 ± 0.97) as compared to mixed stands (26.20 ± 0.69). Again, the difference was not statistically significant (F (df) = 1.16, *p* = 0.24). C/N ratio was also not influenced by canopy volume (-0.0004 ± 0.003, *p* = 0.88). The residuals analysis confirmed the model's uniformity, dispersion and outliers are non-significant (Supplementary material, S1).

## 3.3. Herbivory

The average insect herbivory level was 52.2 % higher in pure (21.48 ± 2.22 %) as compared to mixed stands (14.11 ± 1.16 %). This difference was marginally statistically significant when the treatment (pure vs. mixture) was the only predictor in the model (F(df) = 10.23, $\beta$= 7.83 ± 4.44, *z* = 1.76, *p* = 0.078) as well as when C/N ratio (F(df) = 0.17, *p* = 0.83) and canopy volume or tree height were accounted for in the model (Table 2).

Insect herbivory decreased with increasing C/N. The same tendency is observed in the SLA (Fig. 3). The residuals analysis confirmed the models' uniformity, dispersion and outliers are non-significant

**Table 1**

Mean values, standard error and *p* value summary of stand and tree variables in mixed and pure stands of cork oak and stone pine. The results for tree variables contemplate cork oaks only. The variables were tested with GLM. The *n* is the total number of trees used in the mixed stands (Mx) and pure stands (Pr). In the case of the understory the *n* is the number of transects.

<table><thead><tr><th>Variables</th><th>Mixed stands</th><th>Pure stands</th><th>p-value</th><th>n (Mx|Pr)</th></tr></thead><tbody><tr><td>Tree Height (m)</td><td>6.03 ± 0.29</td><td>7.15 ± 0.18</td><td>0.57</td><td>144|273</td></tr><tr><td>Canopy Volume (m³)</td><td>151.51 ± 15.52</td><td>154.12 ± 10.11</td><td>0.54</td><td>144|273</td></tr><tr><td>Shrub Density (m)</td><td>0.13 ± 0.01</td><td>0.27 ± 0.01</td><td><strong>&lt; 0.001</strong></td><td>14|14</td></tr><tr><td>Shrub Height (m)</td><td>0.58 ± 0.03</td><td>0.44 ± 0.02</td><td>0.36</td><td>14|14</td></tr><tr><td>N° Shrub Species</td><td>1.27 ± 0.11</td><td>2.76 ± 0.12</td><td><strong>&lt; 0.001</strong></td><td>14|14</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Predation evaluation design. The open plastic vial with the sentinel prey, were attached to bamboo canes and the canes were attached to the trees at 2 m height.</figcaption></figure>
<caption>**Table 2**</caption>

Results of the models for assessing Herbivory. The first column lists the predictor variables, including Treatment (pure vs. mixed stands). The predictors marked with * were standardized. The predictors in bold were statistically significant. The R²c was not available due to negligible random effect variance.

<table><thead><tr><th>Model</th><th>Predictor</th><th>Estimate (±SE)</th><th>p-value</th><th>R<sup>2</sup>m</th></tr></thead><tbody><tr><td rowspan="2">Model 1</td><td>Intercept</td><td>13.74 (±3.16)</td><td>&lt; 0.001</td><td rowspan="2">0.24</td></tr><tr><td>Treatment</td><td>7.83 (±4.44)</td><td>0.078</td></tr><tr><td rowspan="2">Model 2</td><td>Intercept</td><td>13.64 (±3.18)</td><td>&lt; 0.001</td><td rowspan="2">0.23</td></tr><tr><td>Canopy volume*</td><td>-0.93 (± 1.15)</td><td>0.42</td></tr><tr><td rowspan="2">Model 3</td><td>Treatment</td><td>7.76 (±4.47)</td><td>0.082</td><td rowspan="2">0.24</td></tr><tr><td>Intercept</td><td>11.85 (±4.69)</td><td>0.012</td></tr><tr><td rowspan="2">Model 4</td><td>Tree height</td><td>0.24 (±0.44)</td><td>0.58</td><td rowspan="2">0.30</td></tr><tr><td>Treatment</td><td>7.84 (±4.39)</td><td>0.074</td></tr><tr><td rowspan="3">Model 5</td><td>Intercept</td><td>28.99 (±8.44)</td><td>&lt; 0.001</td><td rowspan="3">0.24</td></tr><tr><td>SLA</td><td>-0.20 (±0.10)</td><td>0.051</td></tr><tr><td>Treatment</td><td>6.82 (±4.51)</td><td>0.13</td></tr><tr><td rowspan="3">Model 5</td><td>Intercept</td><td>15.04 (±6.93)</td><td>0.030</td><td rowspan="3">0.24</td></tr><tr><td>C/N ratio</td><td>-0.05 (±0.24)</td><td>0.83</td></tr><tr><td>Treatment</td><td>8.01 (±4.43)</td><td>0.073</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Left panel - The relationship between the carbon-to-nitrogen (C/N) ratio and herbivory levels for two treatment groups: Mixed stands and Cork Oak pure stands. The yellow line and shaded band represent the predicted herbivory and confidence intervals for Mixed Stands, while the green dashed line and shaded band represent pure Cork Oak stands. Raw data points are shown, matching their respective treatment group colours. Right panel - The relationship between the specific leaf area (SLA) and herbivory levels for two treatment groups: Mixed stands and Cork Oak stands. The yellow line and shaded band represent the predicted herbivory and confidence intervals for Mixed Stands, while the green dashed line and shaded band represent pure Cork Oak stands. Raw data points are shown, matching their respective treatment group colours.</figcaption></figure>

(Supplementary Material, S1).

### 3.4. Predation

Predation rates were 3.7 % higher in mixed stands (0.85 ± 0.03 %) as compared to pure stands of cork oak (0.82 ± 0.02 %). Nevertheless, this difference between stands was not statistically significant when the treatment (pure vs. mixed) was the only predictor in the model (β= - 0.16 ± 0.42, z = - 0.37, p = 0.71). This lack of statistical significance between stand types remained consistent whether the treatment was the

only predictor in the model or when additional variables such as Canopy volume or Tree height were included (Table 3).

Even though treatment was not significant in any of the models, the addition of the Canopy volume (Model 2) as predictor had a significant effect on the Predation rates. Predation rates increase with the reduction of the canopy volume and the tree height (Fig. 4). Model diagnostics of predation models indicated some deviation from residual uniformity in the model 1 and 4 (Table 3), however the dispersion and outliers were not-significant (Supplementary Material, S1). The residuals analysis of the other models confirmed uniformity, dispersion and outliers are non-significant (Supplementary Material, S1).

### 4. Discussion

This study investigated whether mixing cork oak with stone pine can reduce insect herbivory in Mediterranean forests through bottom-up (leaf traits and stand structure) and/or top-down (predation) mechanisms. Specifically, we compared pure and mixed stands in terms of herbivory levels, leaf traits (SLA, C/N ratio), and predation rates using live sentinel prey. Our results showed that herbivory was lower (by 52.2 %) in mixed stands compared to pure stands, and this difference was marginally significant (p = 0.078). Predation rates were slightly higher in mixed stands (by 3.7 %), but the difference was not statistically significant. Nevertheless, canopy volume negatively influenced predation rates, suggesting that this structural factor may play a role in predator activity.

#### 4.1. Effect of tree species association on insect herbivory

##### 4.1.1. Bottom-up effects

Our results show that the average insect herbivory level was 52.2 % higher in pure as compared to mixed stands. This finding supports the associational resistance hypothesis (Brown and Ewel, 1987), which suggests that increased tree species association can reduce herbivore pressure by interfering with host-finding and other mechanisms (Barbosa et al., 2009). For example, non-host plant volatiles can disrupt the behaviour of herbivorous insects, namely by adversely affecting the calling behaviour of females and the orientation responses of males to sex pheromones (Wang et al., 2016; McCormick et al., 2017), or host location (Bengtsson et al., 2006; Knudsen et al., 2017). The reduced herbivory observed in mixed stands in our study aligns with previous studies in temperate and Mediterranean forests (Jactel and Brockerhoff, 2007; Jactel et al., 2021; Schultdt et al., 2014; Vehviläinen et al., 2008).

The pattern may be partly explained by the large phylogenetic distance between cork oak and stone pine (Castagneyrol et al., 2014; Wang and Ran, 2014), which likely limits the sharing of generalist herbivores and increases the potential for associational resistance. In pure stands, higher host tree density may amplify herbivore pressure through increased visibility and concentration of host cues, and increased

<caption>**Table 3**</caption>

Results of the models for assessing Predation rates. The first column are the predictor variables besides Treatment. The predictors with * were standardized. The predictors in bold were statistically significant. The R²c was not available due to negligible random effect variance.

<table><thead><tr><th>Model</th><th>Predictor</th><th>Estimate (SE)</th><th>p-value</th><th>R<sup>2</sup>m</th></tr></thead><tbody><tr><td rowspan="2">Model 1</td><td>Intercept</td><td>0.83 (±0.30)</td><td>0.006</td><td rowspan="2">0.04</td></tr><tr><td>Treatment</td><td>-0.06 (±0.16)</td><td>0.69</td></tr><tr><td rowspan="2">Model 2</td><td>Intercept</td><td>1.27 (±0.43)</td><td>0.003</td><td rowspan="2">0.90</td></tr><tr><td>Canopy volume*</td><td>-0.93 (±0.28)</td><td>&lt; 0.001</td></tr><tr><td rowspan="2">Model 3</td><td>Treatment</td><td>-0.31 (±0.42)</td><td>0.46</td><td rowspan="2">0.57</td></tr><tr><td>Intercept</td><td>2.49 (±1.41)</td><td>0.078</td></tr><tr><td rowspan="2">Model 4</td><td>Tree height</td><td>-0.16 (±0.12)</td><td>0.20</td><td rowspan="2">0.17</td></tr><tr><td>Treatment</td><td>-0.14 (±0.58)</td><td>0.81</td></tr><tr><td rowspan="3">Model 4</td><td>Intercept</td><td>0.60 (±0.42)</td><td>0.15</td><td rowspan="3">0.17</td></tr><tr><td>Bottom canopy</td><td>0.06 (±0.07)</td><td>0.43</td></tr><tr><td>Treatment</td><td>0.20 (±0.42)</td><td>0.64</td></tr></tbody></table>
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Left panel - The relationship between the tree height (m) and predation rates for the two treatment groups: Mixed stands and Cork Oak stands. The yellow line and shaded band represent the predicted predation and confidence intervals for Mixed Stands, while the green dashed line and shaded band represent pure Cork Oak stands. Raw data points are shown, matching their respective treatment group colours. Right panel - The relationship between the canopy volume (m³) and predation rates for the two treatment groups: Mixed stands and Cork Oak stands. The yellow line and shaded band represent the predicted predation and confidence intervals for Mixed Stands, while the green dashed line and shaded band represent pure Cork Oak stands. Raw data points are shown, matching their respective treatment group colours.</figcaption></figure>

herbivore population due to concentrated resources, in line with the resource concentration hypothesis (Root, 1973). Insects may be better able to locate host trees in homogeneous stands using chemical or visual signals (Castagneyrol et al., 2013). Leaf functional traits, including specific leaf area (SLA) and the carbon-to-nitrogen (C/N) ratio, can influence herbivore feeding behaviour by affecting leaf palatability (toughness) and nutritional quality. The ratio of leaf area to dry mass (SLA), is positively associated with nitrogen content and photosynthetic capacity (Pietsch et al., 2014), with higher SLA typically corresponding to softer, more palatable leaves (Hanley et al., 2007). Conversely, the C/N ratio reflects leaf nitrogen limitation; a higher ratio indicates lower nitrogen availability, and potentially reducing herbivore damage (Hao et al., 2015; Sun et al., 2018).

In our study, pure stands exhibited a non-significant trend toward lower SLA and higher C/N ratios compared to mixed stands. Although these traits were not statistically significant predictors of herbivory in our models, the results show important trends, with herbivory increasing with SLA and decreasing with C/N ratio. These patterns are consistent with prior findings that link SLA and leaf nitrogen to herbivory (Li et al., 2016).

The underlying causes of these trait differences likely involve both biotic and abiotic factors. Mixed stands may enhance soil nutrient availability through complementary resource use and changes in soil microbial communities (Brunel et al., 2017). Cork oak and stone pine have different mycorrhizal associations and nutrient acquisition strategies, with stone pine relying more heavily on fungal symbionts (Correia et al., 2018; Liese et al., 2018). Preliminary results from Barcik (2024) suggest that fungal diversity and soil quality are higher in mixed stands, potentially improving nutrient uptake for *Q. suber*.

Additionally, in our study, pure stands had higher host tree density,

which may have intensified intraspecific competition, limiting access to water and nutrients and with consequences over leaf morphometry and quality (Gouveia and Freitas, 2008). In contrast, shading from taller pines in mixed stands may prompt cork oaks to increase their specific leaf area (SLA) as a plastic response to lower light availability, enhancing light capture efficiency (Liu et al., 2016). Together, these mechanisms suggest that tree diversity can indirectly influence herbivory by altering plant physiological traits and resource allocation strategies. Other physiological traits not tested in this study may also influence the leaf characteristics, in particular chemical secondary compounds can affect the extent of leaf damage and may have contributed to patterns in our data (Poorter et al., 2004; Poeydebat et al., 2021).

Beyond tree-level effects, understory vegetation may also influence herbivory patterns by shaping the habitat and resources available to insect herbivores (Giffard et al., 2012). The understory can affect herbivore populations through three main factors: plant structure, nutritional quality, and productivity (Forbes et al., 2017). For example, larger understory plants can offer more habitat and greater visibility to insects, potentially facilitating their movement between understory and canopy (Haddad et al., 2001; Strauss et al., 2015). Nutritional quality is another important aspect, particularly the availability of limiting factors such as nitrogen, which can be enhanced by plant diversity (Burns et al., 2011). However, increased plant diversity may also lead to a broader array of defensive compounds, potentially deterring herbivores (Agrawal and Fishbein, 2006). Lastly, more productive understories—those generating higher amounts of vegetative biomass—can support larger and more diverse insect communities (Siemann, 1998).

In our study there were significant differences in woody understory between pure and mixed stands. Pure stands had a higher number of shrub species and density. However, we could not establish a relationship with these variables and herbivory.

### 4.1.2. Top-down effects

We did not find significant differences in predation rate between pure and mixed stands. However, predation was significantly influenced by canopy volume, with predation decreasing as canopy increased. This aligns with Staab and Schuldt (2020), who reviewed the natural enemy hypothesis in mixed forests. While this hypothesis suggests that diverse habitats support greater predator and parasitoid populations by increasing resource and prey availability (Russell, 1989), the review found that it does not always hold true in forest ecosystems. Other confounding factors—such as tree phylogeny, latitude, and structural complexity—can influence predator abundance and richness. Also, according to the associational resistance hypothesis, natural enemies of insect herbivores may gather on neighbouring plants for various reasons, and this aggregation could potentially influence the susceptibility of nearby focal plants to herbivory (Barbosa et al., 2009). Another possible explanation for the lack of differences between stand types lies in the composition and behaviour of the predator community. In this system, birds are the dominant predators and are known to feed on several cork oak pests (Ceia and Ramos, 2016). However, many bird species have broad foraging ranges and are capable of exploiting resources across both pure and mixed stands within the same site (Robinson and Holmes, 1982). This high mobility may reduce stand-level differences in predation pressure, potentially masking any localized effects of tree species composition. And given the naturally high biodiversity of *montado* systems, it is plausible that mixtures with pines may not greatly enhance predator diversity, which would potentially result in an increased top-down regulatory effect on herbivore populations.

The observed decrease in predation with increasing canopy volume may be explained by the greater structural complexity of voluminous canopy trees, which can reduce the efficiency of visually oriented predators, such as insectivorous birds. Šipoš and Kindlmann (2013) suggest that herbivorous insects living in complex canopies have a
greater chance of escaping from their enemies by exploiting spatial and temporal refuges. In this context, large or dense canopies may act as physical or visual barriers, interfering with predator detection and movement, thereby weakening top-down control. Although tree diversity can enhance predator presence, its effectiveness may be constrained by the physical complexity of the forest structure, which could reduce predator–prey encounter rates.

Possible interactions with understory plant-community composition and diversity may have also influenced the abundance and diversity of natural enemies, and consequently the predatory activity (Hertzog et al., 2017; Russell, 2015; Staab and Schuldt, 2020). In the studied stands the understory vegetation was affected by different management practices, including the presence or not of livestock grazing (sheep and cattle).

## 4.2. Limitations and further study possibilities

This study contributes to understanding the ecological functioning of Mediterranean mixed forests, showing that cork oak experiences reduced herbivory in mixed stands with stone pine, supporting the associational resistance hypothesis. However, several limitations must be acknowledged. The study was conducted in a year without a major herbivory outbreak, and overall herbivory levels were relatively low (mean: 21.48 ± 2.22 % in pure stands and 14.11 ± 1.16 % in mixed stands). Given the known cyclical fluctuations in herbivore pressure in montado systems, future studies should test the associational resistance hypothesis under outbreak years to determine whether it holds under more severe stress conditions.

Additional limitations include the small number of replicates and the lack of control over grazing systems, which varied across sites. It is possible that some marginally significant results might have reached stronger statistical significance with increased sampling effort. Livestock management is known to influence ecological structure, predator habitat, and shrub composition — all of which can affect herbivory and predation (Leidinger et al., 2019). Moreover, uncoordinated silvicultural interventions (such as unexpected pruning) were not standardized across sites and may have influenced canopy structure and related ecological processes. Standardized management or increased replicas could improve the understanding of the effect of these confounding factors in herbivory.

While this study found limited support for top-down control via predators, its nature may have missed more subtle or context-dependent interactions, that observational predation data (e.g. bird or arthropod quantification) could achieve. The use of sentinel prey of the Calliphoridae family, even though very common in predation studies as a proxy (Lövei and Ferrante, 2017), might not give the real dimension of predation rates in these systems.

Future research could assess species which produce the current damaged observed in cork oak leaves, which could provide information about the effect of mixed stands in opportunistic and species-specific defoliators. Also, assess herbivory in stone pine, particularly from important pests such as the pine processionary moth (Thaumetopoea pityocampa Schiff), to determine whether mixtures provide co-benefits for both species or whether trade-offs emerge. Also, it would be important to assess the effect of the mixture in other pests of the cork oak, namely *Coraebus undatus*, which causes a high impact on cork quality and its economic value. This is essential to evaluate the long-term viability of mixed-species stands in silvicultural planning. Despite the study's constraints, the results suggest that tree mixtures may offer a promising strategy for adaptive forest management. By contributing to lower herbivory levels under moderate pressure, mixed stands can enhance resilience to biotic stress while supporting multi-functional production systems through cork and pine nuts. To fully assess these benefits, future work should explore how these interactions evolve under varying environmental pressures and management regimes.

# 5. Conclusion

This study highlights the ecological benefits of mixing cork oak and stone pine in Mediterranean forests. We found that insect herbivory was significantly reduced in mixed-species stands compared to pure cork oak stands, while predation rates remained unaffected by stand composition. These results suggest that bottom-up mechanisms, might play a role in regulating herbivore pressure in comparison to top-down forces in this system. Importantly, tree height and canopy volume did not differ between stand types, indicating that the observed reduction in herbivory can be attributable to species mixing rather than these variables. We found some differences in the understory composition which might contribute to increase abundance of predators' activity although it was not translated in the experimental design. Promoting mixed-species stands could thus strengthen forest resistance to herbivores through enhanced plant trait variability. Overall, this study supports the integration of tree diversity as a management strategy to improve forest health and resistance, while also offering the potential for greater economic returns through the combined production of cork and pine nuts.

## CRediT authorship contribution statement

**Manuela Branco:** Writing – review & editing, Visualization, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization.
**Bastien Castagneyrol:** Writing – review & editing, Validation, Supervision, Software, Methodology, Formal analysis, Data curation.
**Pedro Barcik:** Writing – review & editing, Visualization, Investigation.
**David Lloberas Lafuente:** Writing – review & editing, Visualization, Investigation.
**José Carlos Franco:** Writing – review & editing, Supervision, Funding acquisition, Conceptualization.
**Inês D.H. Ramires:** Writing – review & editing, Writing – original draft, Visualization, Investigation, Formal analysis, Data curation.
**Alexandra C. Correia:** Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Project administration, Investigation, Funding acquisition.

## Funding sources

This work was supported by FCT - Fundação para a Ciência e Tecnologia, I.P. under the grant UI/BD/151512/2021, the research project CORKNUT (PCIF/MOS/0012/2019) and by project reference UIDB/00239/2020 of the Forest Research Centre, DOI 10.54499/UIDB/00239/2020 and LA/P/0092/2020 of Associate Laboratory TERRA, DOI 10.54499/LA/P/0092/2020.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgements

We thank the owners of the properties in which the study was carried out, namely Abegoria, Monte Besteiros, Cascavel, Espirra, Juncaveios, Quinta de Sousa, and Trepada, for allowing the setup of the permanent stands and collection of data. To the project CORKNUT for the financial and data collection support. To Joaquim Mendes, Patrizia Dall'ara, Samuel Soares and Jakov Čančar for assisting in sample collection on the field and Ana Sofia Ramires for the predation drawing scheme. Also, we would like to thank the Laboratório de Ecofisiologia Vegetal from Departamento de Recursos Naturais, Ambiente e Território (DRAT) for allowing the use of their equipment for the drying and grinding of our leaf samples for the SLA and C/N analysis.
# Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.foreco.2025.123081.

## Data Availability

Data will be made available on request.

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