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Article

Tree Canopies Drive δ13C and δ15N Patterns in Mediterranean Wood Pastures of the Iberian Peninsula

by
Mercedes Ibañez
1,2,
Salvador Aljazairi
1,
María José Leiva
3,
Cristina Chocarro
2,
Roland A. Werner
4,
Jaleh Ghashghaie
5 and
Maria-Teresa Sebastià
1,2,*
1
Group of Biodiversity, Functional Ecology and Global Change (ECOFUN), Program on Bioeconomy, Health, and Governance, Forest Science and Technology Centre of Catalonia (CTFC), 25280 Solsona, Spain
2
Department of Agriculture and Forestry Science and Engineering and Agrotecnio (DCEFA), School of Agrifood and Forestry Engineering and Veterinary Medicine (ETSEAFIV), University of Lleida (UdL), 25198 Lleida, Spain
3
Plant Biology and Ecology Department, University of Sevilla (US), 41080 Sevilla, Spain
4
Department of Environmental Systems Science, Institute of Agricultural Sciences, ETH Zurich, 8092 Zurich, Switzerland
5
Laboratoire d’Ecologie Systématique et Evolution (ESE), Université Paris-Saclay, CNRS, AgroParisTech, 91190 Gif-sur-Yvette, France
*
Author to whom correspondence should be addressed.
Land 2025, 14(6), 1135; https://doi.org/10.3390/land14061135
Submission received: 28 March 2025 / Revised: 7 May 2025 / Accepted: 14 May 2025 / Published: 22 May 2025
(This article belongs to the Special Issue Observation, Monitoring and Analysis of Savannah Ecosystems)
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Abstract

:
Mediterranean wood pastures are the result of traditional silvo-pastoral uses that shaped these ecosystems into a mosaic of trees and open grassland. This ecosystem structure is generally associated with increased soil fertility under tree canopies. However, the response of herbaceous plant functional types (PFTs)—grasses, legumes, and non-legume forbs—to these heterogeneous microenvironments (under the canopy vs. open grassland) remains largely unknown, particularly regarding carbon (C) and nitrogen (N) acquisition and use. Even less is known about how different tree species and environmental conditions influence these responses. In this study, we aim to assess how tree canopies influence carbon and nitrogen cycling by comparing the effects of traditional oak stands and pine plantations on herbaceous PFTs and soil dynamics. For that we use C and N content and natural isotopic abundances (δ13C and δ15N) as proxies for biogeochemical cycling. Our results show that ecosystem C and N patterns depend not only on herbaceous PFTs and the presence or absence of tree canopies but also on tree species identity and environmental conditions, including climate. In particular, pine-dominated plantations exhibited lower nitrogen availability compared to those dominated by oak, suggesting that oak stands may contribute more effectively to enhance soil fertility in Mediterranean wood pastures. Furthermore, the canopy effect was more pronounced under harsher environmental conditions, highlighting the role of trees in buffering environmental stress, particularly in arid regions. This suggests that changes in tree cover and tree species may drive complex changes in ecosystem C and N storage and cycling.

1. Introduction

Mediterranean wood pastures or oak savannahs (called dehesas in Spain and montados in Portugal) are semi-natural savannah-like ecosystems that result from traditional silvo-pastoral uses, in which an herbaceous and an arboreal layer (mostly Quercus species) coexist [1]. They are one of the largest agroforestry systems in Europe [2], covering 3.5–4 million ha, mostly along the southwest of the Iberian Peninsula [3], and are also present in other world regions with Mediterranean climates, mainly in California [4,5,6]. Mediterranean wood pastures have traditionally provided a wide variety of silvo-pastoral goods and services, including the production of forage, acorns, timber, and cork. These uses have shaped the ecosystem into a mosaic of trees and open grassland. However, the tree coverage in Mediterranean wood pastures is changing. Traditional silvo-pastoral uses are declining with more intensive farming, including plantations of fast-growing trees, mostly Eucalyptus and Pinus species. Another threat is the shrub encroachment due to land abandonment, and there is a worrying lack of tree regeneration [7,8,9], with the consequent implications that this may have on ecosystem functioning and specifically on carbon (C) and nitrogen (N) cycling and storage [10].
In this regard, the assessment of the C and N concentration in the different ecosystem compartments in combination with the natural abundance of C and N isotopes (δ13C and δ15N) can be used as a good proxy to assess C and N acquisition and cycling processes [11,12,13,14]. Generally, tree canopies modify the organic matter input and enhance soil C and N content [15,16].
This can leave an imprint in the δ15N plant biomass, via changes in the amount and the type of N sources, N cycling steps, and the microbial community [17,18]. Also, the δ13C level can be taken as being indicative of CO2 and water exchange relationships [19]. Light reduction under the canopy generally increases stomatal conductance, making possible more discrimination against 13C and generating organic matter depleted in 13C [20,21,22,23]. Hence, a “canopy effect”—defined as the ecological influence exerted by tree canopies—on the C and N content and the natural isotopic composition (δ13C and δ15N) of the different ecosystem compartments is expected. However, such effects in Mediterranean wood pastures are still poorly understood, especially as traditional Quercus stands are frequently replaced by other tree species like Pinus pinea L. plantations [8], potentially altering ecosystem dynamics through changes in litter quality and soil dynamics [24,25]. In addition, the herbaceous layer of Mediterranean wood pastures is highly diverse in plant species [26], with presence of grasses and legume (hereafter “legumes”) and non-legume forbs (hereafter “forbs”). These plant functional types (PFTs) differ in their nitrogen (N) and light-use strategies, which also affect CO2 acquisition [27,28,29,30]. Therefore, their responses to tree canopies are expected to vary. However, to our knowledge, no study has separately examined the tree’s influence on grasses, legumes, and forbs.
In this study, we aim to fill these knowledge gaps by assessing how tree canopies influence carbon and nitrogen cycling in Mediterranean wood pastures. Specifically, we investigate (1) whether different PFTs exhibit distinct C and N contents and isotopic signatures (δ13C and δ15N) depending on the microenvironment (under canopy vs. open grassland); (2) whether these canopy influences differ between Quercus species and Pinus pinea L. plantations; and (3) whether the observed patterns are consistent across sites along an altitudinal and climatic gradient. For that purpose, we used C and N content and the isotopic ratios (δ13C and δ15N) in the PFTs, the belowground biomass, and the soil as a proxy of C and N cycling processes.

2. Materials and Methods

2.1. Study Sites and Experimental Design

Field work was carried out in the spring of 2016, coinciding with the most productive period of the system. Study sites were the same as reported in Ibañez et al. (2021), distributed in two locations in the southwest of the Iberian Peninsula [1]: Doñana Natural Park (DN, 37°15′34″ N, 6°19′55″ W, 30 m a. s. l.) and Sierra Morena mountains (SM, 37°39′50″ N, 5°56′20″ W, 296 m a. s. l.). Both locations have a Mediterranean climate regime [31] with warm, dry summers and mild winters. However, SM is slightly cooler and wetter than DN, with a mean annual temperature in SM of 16.8 °C and 18.1 °C in DN and a mean annual precipitation in SM of 648 mm and 543 mm in DN. SM soils have a texture between sandy clay loam and clay. DN soils are sandier than SM, with a sandy loam texture (Table S1). Grasslands in both locations are dominated by herbaceous annual species, including grasses, forbs, and legumes. Both locations are extensively grazed at similar stocking rates by cattle and goats: DN has 0.40 livestock units (LSU) ha−1, and SM has 0.36 LSU ha−1.
At both sites, we conducted a survey focused on Mediterranean wood pastures typical of the region. The surveyed locations included SM-ilex, dominated by Quercus ilex L., and DN-suber, dominated by Quercus suber L., both the most abundant stands in the Iberian Peninsula; DN-mixed, where a mixture of Q. ilex and Q. suber predominates, representing the second most abundant stand type; and DN-pinea, where Pinus pinea dominates, a species frequently planted to replace traditional canopies [8]. Tree densities (trees ha−1) for these systems were on average 34 ± 1 in SM-ilex, 26 ± 1 in DN-mixed, 26 ± 4 in DN-suber, and 48 ± 6 in DN-pinea (MJ. Leiva, personal communication, 2016), consistent with the typical values for these systems in the region [8].
Within each wood pasture, we selected four tree individuals of each species: SM-ilex (Q. ilex), DN-suber (Q. suber), DN-mixed (Q. ilex and Q. suber), and DN-pinea (P. pinea). Trees were of similar size within each species, with the following average diameters at breast height: Q. ilex 43 ± 3 cm, Q. suber 63 ± 3 cm, and P. pinea 57 ± 6 cm. The presence or absence of tree canopies defined two distinct sampling areas: under canopy (UC) and open grassland (OG). Based on in situ field observations, we defined the UC area as a 1 m radius around the selected tree trunk, while the OG area was located at least 3 m away, a distance considered sufficient to be clearly outside the canopy’s influence. Thus, we established four UC and four OG sampling areas in SM-ilex, DN-suber, and DN-pinea, respectively, and eight UC and eight OG sampling areas in DN-mixed (as there was Q. ilex and Q. suber), which resulted in 40 sampling areas (20 UC and 20 OG).
In each sampling area (UC and OG), we surveyed the plant functional types (PFTs) of the herbaceous layer, including forbs, grasses, and legumes. For that, we collected leaves from at least 10 individuals of the dominant species of each plant functional type (PFT). These included grasses (Bromus hordeaceus L. and Hordeum vulgare L.), forbs (Calendula arvensis L., Chamaemelum mixtum L., Crepis capillaris L., Erodium moschatum L., and Geranium molle L.), and legumes (Ornithopus sativus Brot. and Trifolium subterraneum L.). The PFT composition from the same study locations was used to interpret and discuss our results [1].
Also, we extracted two soil cores per sampling area (9 cm2 and 0–10 cm depth) for soil and belowground biomass (BGB) analysis, respectively. In the laboratory, one of the cores was washed and filtered through a 0.2 mm pore size strainer to obtain the BGB. Coarse elements were manually removed from the BGB sample if any. The second soil core was sieved at 2 mm to exclude coarse elements and roots. All the collected samples were oven-dried at 60 °C until reaching a constant weight and ground using a ball mill (MM200, Retsch, Asturias, Spain). Samples were then tin encapsulated (Courtage Analyse Service, Mont Saint-Aignan, France) for carbon (C) and nitrogen (N) content and isotopic natural abundance determination (Section 2.2).

2.2. Determination of Carbon and Nitrogen Content and Isotopic Natural Abundance

Isotopic composition (δ13C and δ15N) was calculated as a deviation of the isotope ratio (R = 13C/12C or R = 15N/14N) of the samples from the ratio of the corresponding international standard (δ = (Rsample/Rstandard) − 1), VPDB for δ13C, and air-N2 for δ15N [32]. For that, we used glutamic acid (δ13C = −28.319‰, δ15N = −3.983‰), acetanilide (δ13C = −27.787‰, δ15N = +1.6‰), and N-1 (δ15N = +0.40‰) as laboratory standards for all the samples except soils. Standards were calibrated against the international reference materials USGS40 for carbon (δ13C = −26.389‰V-PDB) and IAEA-N-1 for nitrogen (δ15N = +0.43‰Air-N2). Sample preparation was carried out at the Institut de Biologie des Plantes at the Université Paris-Saclay. Subsequently, the samples were analysed at the Isolab of the Grassland Sciences group at ETH Zurich using a Flash EA 1112 Series elemental analyser (Finnigan MAT, Bremen, Germany) coupled to a DeltaPlusXP isotope ratio mass spectrometer (Finnigan MAT, Bremen, Germany) via a 6-port valve [33] and a ConFlo III interface [34].
For the soil samples, we used acetanilide (δ13C = −27.22‰, δ15N = −4.43‰), caffeine (δ13C = −42.56‰, δ15N = −5.79‰), and tyrosine (δ13C = −24.00‰, δ15N = +5.16‰) as laboratory standards, which were calibrated using NBS-22 for carbon (δ13C = −30.03‰V-PDB) and IAEA-N-1 for nitrogen (δ15N = +0.43‰Air-N2). Soil samples were both prepared and analysed at the Isolab of the Grassland Sciences group at ETH Zurich. The analytical precision, based on repeated measurements of laboratory standards, was ±0.111‰ for δ13C and ±0.127‰ for δ15N.

2.3. Data Analysis

We ran linear models on the C and N content and the isotopic composition (δ13C, δ15N) of each PFT (forbs, grasses, and legumes), BGB, and soil, as a function of location (SM-ilex, DN-mixed, DN-suber, DN-pinea) and canopy (OG, UC). Final models were selected by a stepwise procedure based on the Akaike information criterion (AIC), using the stepAIC function, MASS package [35]. Linear models were also applied to explore the relationships between C and N dynamics within or between ecosystem compartments when applicable. Only the most explanatory and parsimonious models are presented and discussed. All data analyses were performed using R software [36].

3. Results

Legumes presented the highest C and N content (Figure 1a,b), as well as the most 13C- (Figure 1b) and 15N- (Figure 1c) depleted tissues compared to forbs and grasses. Also, when comparing grasses to forbs, grasses had generally higher N content than forbs (Figure 2a, p-value t-test < 0.001) and tended to present lower δ15N values (Figure 2b). N content was consistently higher under the canopy than in the open grassland across all three plant functional types (PFTs) (Figure 1b). Moreover, forbs presented a differential canopy effect dependent on location (DN vs. SM) in their δ13C (Figure 3a) and δ15N (Figure 3b). Thus, forbs presented more 13C-depleted tissues under the canopy than in the open grassland in the DN area, especially in DN-mixed and DN-pinea (Table 1), while such a canopy effect was not observed in SM-ilex (Table 1 and Figure 3a). Similarly, the N content in forbs increased under the canopy in DN, especially noticeable in DN-mixed and DN-pinea (Table 1), while the N content in forbs in SM-ilex did not show any difference between under the canopy and the open grassland (Figure 3b and Table 1).
On the other hand, BGB had higher C content under the canopy than in the open grassland in all Quercus-species-dominated locations (SM-ilex, DN-mixed, DN-suber, Figure 4), while in the P. pinea-dominated region, the C content in the BGB decreased under the canopy compared to the open grassland (Table 2 and Figure 4).
Soil C and N contents were consistently higher under the canopy (Table 3 and Figure 5a,b), and soil C and N were positively correlated (R2 0.9, p < 0.001, Figure 5c). At the same time, BGB δ15N tended to be lower with increasing soil N content (R2 0.31, p < 0.08, Figure 6).

4. Discussion

4.1. The Canopy Effect on Plant Functional Types of the Herbaceous Layer

The evaluation of plant functional types (PFTs) of the herbaceous layer (forbs, grasses, and legumes) reveals intricate interactions between tree canopies and C and N acquisition and use. Despite their superior N-fixing abilities and efficient CO2 exchange (Figure 1), legumes were not dominant in the ecosystem, particularly under tree canopies, where the microenvironment did not favour their abundance [1]. The capacity of legumes to fix atmospheric nitrogen has been reported to be not specially favoured under a canopy [37], and also legumes may be constrained by their high light requirements [5,38,39].
Furthermore, we hypothesize that under a canopy, legumes may be outcompeted by species better adapted to N-rich conditions. Thus, our results indicate that grasses, in particular, benefited from the increased soil N availability found under the canopy. This is evident in their higher N content (Figure 2a) and generally lower δ15N values (Figure 2b) compared to forbs, suggesting that grasses are highly efficient at N uptake and/or exploiting symbiotic N sources [18]. Notably, nitrogen transfer between legumes and grasses (a source of symbiotic N; Figure 1d) is more efficient than between legumes and forbs [40,41], which enhances the competitive advantage of grasses. Additionally, grasses’ fibrous root system [41,42,43] likely enhances their ability to absorb N from the upper soil layers, including symbiotically fixed N. In contrast, forbs generally have taproots, which may be less effective in this process [41]. This may make grasses very competitive and able to thrive in high-N environments [44], via increasing their biomass often at the expense of forbs and legumes.
Certainly, such competitive advantages of grasses, especially their high nitrogen-use efficiency, make grasses also strong competitors in N-poor environments. However, in N-poor environments, legumes and forbs are also good competitors, as legumes can enhance their N fixation capacity [45], and forbs may be able to access nutrients in deeper soil layers due to their deeper root system, making legumes and forbs able to maintain or even surpass grasses under limiting N conditions. Overall, this intricate interplay between nutrient availability and plant functional traits is shaping the community composition in Mediterranean wood pastures.

4.2. The Canopy Effect in Representative Mediterranean Wood Pastures: Quercus vs. Pinus pinea Canopies

Our results suggest that the canopy effect may differ when comparing Quercus species stands and P. pinea plantations. This was detected on the canopy effect on the C content in the BGB, with a higher C content under the canopy than in the open grassland in Quercus-species-dominated canopies (SM-ilex, DN-suber and DN-mixed), while P. pinea (DN-pinea) presented the opposite pattern (Figure 4).
This may be explained by the generally higher investment in root biomass that plants present when soil N is low, since plants may invest more in root biomass to explore the soil for nutrients, which can increase root C content [46]. Thus, the lower C content in the BGB detected in DN-pinea under the canopy compared to the open grassland (Table 2 and Figure 4) could be indeed driven by low N availability. The environment under the canopy in DN-pinea had low soil N content, along with BGB tissues showing the highest δ15N (Figure 6). This suggests that N availability for plants was low, leading to restricted 15N discrimination.
Indeed, the litter of P. pinea has low N content, lower than the litter of Quercus species [24,47], and exhibits a strong mulching capacity and allelopathic properties. Specifically, pine litter can inhibit seed germination and hinder seedling establishment through both the physical barrier that it creates by covering the soil and the release of allelochemical compounds [48]. Also, a reduced phosphorus uptake under pine needles has been described [49]. Characteristics that combined may hinder the growth of the herbaceous layer [50] and could be driving these differences in the N availability and eventually drive an increase in the root C content [51] to obtain a limiting resource [52,53]. Moreover, this interestingly suggests that the current change in traditional stands needs further attention because a change in the tree species may imply profound changes in ecosystem C and N storage and cycling [54,55], changes that may go a priori unnoticed.

4.3. The Canopy Effect Along an Altitudinal/Climatic Gradient

Our results also suggest that the canopy effect can be site-dependent when comparing locations along an altitudinal/climatic gradient. This is shown by the almost neutral canopy effect found on the δ13C and N content of forbs in SM-ilex, in contrast to the strong canopy effect detected in DN (DN-suber, DN-mixed, and DN-pinea, Figure 3). Interestingly, this pattern aligns with the canopy effect on the net ecosystem CO2 exchange patterns reported by [1]. The authors reported from the same study locations (i) a strong canopy effect in DN (DN-suber, DN-mixed, and DN-pinea), wherein there was net CO2 uptake in the open grassland but CO2 emissions under the canopy, while (ii) in SM-ilex, the canopy effect was neutral, and there was a net CO2 uptake both under the canopy and in the open grassland. These findings, combined with our δ13C values, suggest that the stomatal conductance is similar between both microenvironments in SM, therefore similar 13C discrimination rates are possible, in contrast to the strong differences found in DN, where more restrictive environmental conditions likely amplify the canopy effect. Furthermore, this suggests that under less restrictive environmental conditions, the microenvironment beneath the canopy is similar to the open grassland. However, as conditions become more restrictive, the canopy effect strengthens. This agrees with other authors that described a more pronounced canopy effect under more restrictive conditions, such as increased aridity [56] on soil fertility [57] and/or productivity [58].
Ultimately, these findings underscore the crucial role of trees in driving ecosystem fertility and buffering extreme conditions. From a management perspective, this highlights the importance of optimizing tree cover based on multiple ecosystem functions in conjunction with local environmental conditions.

5. Conclusions

Changes in tree coverage and tree species may cause profound changes in C and N dynamics in Mediterranean wood pastures mediated by the herbaceous plant functional types (PFTs). PFTs interacted with the tree–open grassland mosaic in particular ways. This is shown, for instance, by the higher N content and generally lower δ15N of grasses compared to forbs, which suggests that grasses were highly competitive in terms of N acquisition, and this was probably one of the causes of their dominance under the canopy, where there was higher soil N content. The canopy effect was dependent on the tree species dominating the wood pasture. N availability in P. pinea appeared lower than in Quercus-dominated locations, which, in turn, influenced the canopy effect on the C content of the BGB. The lower nitrogen availability under Pinus pinea may result from its recalcitrant, nitrogen-poor litter and allelopathic effects, with slow decomposition and nutrient cycling. In addition, the canopy effect was also generally more pronounced with increasing environmental constraints (as is DN vs. SM). These findings suggest that prioritizing Quercus in Mediterranean wood pastures can be a management action to optimize soil fertility and highlight the relevance of trees as buffers of extreme conditions, especially in more arid environments. Our results can be used to better understand the interactions among ecosystem compartments in Mediterranean wood pastures by showing the canopy effect under different tree species, local conditions, and on the PFT of the herbaceous layer.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land14061135/s1, Table S1: Texture fractions and USDA texture classification of the study sites. Texture fractions determined by densimetry; Table S2: Main species identified in the field per plant functional type (forbs, grasses and legumes).

Author Contributions

Conceptualization, M.I., S.A., M.J.L. and M.-T.S.; data curation, M.I.; formal analysis, M.I.; funding acquisition, M.J.L. and M.-T.S.; investigation, M.I., S.A., M.J.L., C.C., R.A.W., J.G. and M.-T.S.; methodology, M.I., S.A., C.C., J.G. and R.A.W.; project administration, M.J.L. and M.-T.S.; resources, M.J.L., J.G. and M.-T.S.; supervision, M.J.L., C.C., J.G. and M.-T.S.; writing—original draft, M.I.; writing—review and editing, M.I., S.A., M.J.L., C.C., R.A.W., J.G. and M.-T.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the Spanish Science Foundation FECYT-MINECO: BIOGEI (GL2013-49142-C2-1-R) and IMAGINE (CGL2017-85490-R) projects and supported by a FPI fellowship to Mercedes Ibañez (BES-2014-069243).

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials, further inquiries can be directed to the corresponding author.

Acknowledgments

Thanks to all the colleagues who collaborated in laboratory and fieldwork tasks: Antonio Rodríguez, Miquel Sala, Helena Sarri, and Gianluca Segalina. Our special thanks to Dehesa de Gato S. L. state and Doñana Research Coordination Office for their support and facilities.

Conflicts of Interest

The authors declare no conflicts of interest.

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Land 14 01135 g001
Figure 1. Means ± 1 standard error per PFT and canopy (open symbols indicate open grassland and solid symbols indicate under the canopy): (a) C content; (b) N content; (c) δ13C; and (d) δ15N.
Figure 1. Means ± 1 standard error per PFT and canopy (open symbols indicate open grassland and solid symbols indicate under the canopy): (a) C content; (b) N content; (c) δ13C; and (d) δ15N.
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Figure 2. Relationship between (a) grass N content and forb N content and (b) grass δ15N and forb δ15N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error. The diagonal line indicates a 1:1 relationship.
Figure 2. Relationship between (a) grass N content and forb N content and (b) grass δ15N and forb δ15N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error. The diagonal line indicates a 1:1 relationship.
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Figure 3. (a) Forb δ13C and (b) forb N content per location and canopy (open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error.
Figure 3. (a) Forb δ13C and (b) forb N content per location and canopy (open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error.
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Figure 4. Mean C content in belowground biomass (BGB) ± 1 standard error, per location and canopy: open grassland (OG) and under the canopy (UC).
Figure 4. Mean C content in belowground biomass (BGB) ± 1 standard error, per location and canopy: open grassland (OG) and under the canopy (UC).
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Figure 5. (a) Mean soil C ± 1 standard error; (b) mean soil N ± 1 standard error; and (c) relationship between soil C and soil N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). The diagonal slashed line indicates the linear trend.
Figure 5. (a) Mean soil C ± 1 standard error; (b) mean soil N ± 1 standard error; and (c) relationship between soil C and soil N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). The diagonal slashed line indicates the linear trend.
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Figure 6. Relationship between soil N and belowground biomass (BGB) δ15N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error; the diagonal slashed line indicates the linear trend.
Figure 6. Relationship between soil N and belowground biomass (BGB) δ15N (shapes = ○●SM-ilex, □■DN-mixed, ▽▼DN-suber, △▲DN-pinea; open symbols indicate open grassland, and solid symbols indicate under the canopy). Mean ± 1 standard error; the diagonal slashed line indicates the linear trend.
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Table 1. Linear modelling of δ13C (‰) and N content (%) in forbs as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
Table 1. Linear modelling of δ13C (‰) and N content (%) in forbs as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
Forb δ13C (‰)Forb N Content (%)
Est.SEtpEst.SEtp
(Intercept)−28.20.2−154.92<0.0012.20.210.70<0.001
Location (DN-mixed)−0.50.2−2.340.02−0.80.2−3.140.002
Location (DN-suber)−0.20.2−0.790.4−0.90.3−3.43<0.001
Location (DN-pinea)−0.40.2−1.690.09−0.60.3−2.330.02
Canopy−0.50.1−3.72<0.0010.00.30.170.9
DN-mixed × canopy 0.90.32.480.01
DN-suber × canopy 0.40.41.070.3
DN-pinea × canopy 0.90.42.240.03
R2Adj0.15 <0.0010.34 <0.001
Table 2. Linear modelling of C content (%) in belowground biomass (BGB) as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
Table 2. Linear modelling of C content (%) in belowground biomass (BGB) as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
BGB C Content (%)
Est.SEtp
(Intercept)30120.12<0.001
Location (DN-mixed)221.030.3
Location (DN-suber)422.040.05
Location (DN-pinea)924.07<0.001
Canopy431.370.2
Location (DN-mixed) × canopy230.550.6
Location (DN-suber) × canopy−13−0.250.8
Location (DN-pinea) × canopy−83−2.230.03
R2Adj0.41 0.001
Table 3. Linear modelling of soil C and N content (%) as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
Table 3. Linear modelling of soil C and N content (%) as a function of location and canopy. Location with SM-ilex as the reference level and canopy with open grassland (OG) as the reference level. Estimates of the explanatory variables (Est.), standard error (SE), t, and p-value. Only significant (p < 0.05) models are shown in the table.
Soil C Content (%)Soil N Content (%)
Est.SEtpEst.SEtp
(Intercept)2.10.45.73<0.0010.180.036.77<0.001
Location (DN-mixed)−1.10.4−2.650.01−0.100.03−3.310.002
Location (DN-suber)−0.20.5−0.430.7−0.020.03−0.680.5
Location (DN-pinea)−0.80.5−1.730.09−0.090.03−2.630.01
Canopy1.80.36.20<0.0010.110.025.39<0.001
Location (DN-mixed) × canopy
Location (DN-suber) × canopy
Location (DN-pinea) × canopy
R2Adj0.53 <0.0010.51 <0.001
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MDPI and ACS Style

Ibañez, M.; Aljazairi, S.; Leiva, M.J.; Chocarro, C.; Werner, R.A.; Ghashghaie, J.; Sebastià, M.-T. Tree Canopies Drive δ13C and δ15N Patterns in Mediterranean Wood Pastures of the Iberian Peninsula. Land 2025, 14, 1135. https://doi.org/10.3390/land14061135

AMA Style

Ibañez M, Aljazairi S, Leiva MJ, Chocarro C, Werner RA, Ghashghaie J, Sebastià M-T. Tree Canopies Drive δ13C and δ15N Patterns in Mediterranean Wood Pastures of the Iberian Peninsula. Land. 2025; 14(6):1135. https://doi.org/10.3390/land14061135

Chicago/Turabian Style

Ibañez, Mercedes, Salvador Aljazairi, María José Leiva, Cristina Chocarro, Roland A. Werner, Jaleh Ghashghaie, and Maria-Teresa Sebastià. 2025. "Tree Canopies Drive δ13C and δ15N Patterns in Mediterranean Wood Pastures of the Iberian Peninsula" Land 14, no. 6: 1135. https://doi.org/10.3390/land14061135

APA Style

Ibañez, M., Aljazairi, S., Leiva, M. J., Chocarro, C., Werner, R. A., Ghashghaie, J., & Sebastià, M.-T. (2025). Tree Canopies Drive δ13C and δ15N Patterns in Mediterranean Wood Pastures of the Iberian Peninsula. Land, 14(6), 1135. https://doi.org/10.3390/land14061135

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