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Article

Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China

by
Li Wang
,
Xueyan Zhao
,
Guoyu Liu
,
Qing Wang
,
Fangyuan Wang
and
Yan Li
*
Xi’an Botanical Garden of Shaanxi Province (Institute of Botany of Shaanxi Province), Xi’an 710061, China
*
Author to whom correspondence should be addressed.
Forests 2024, 15(10), 1803; https://doi.org/10.3390/f15101803
Submission received: 18 September 2024 / Revised: 30 September 2024 / Accepted: 11 October 2024 / Published: 14 October 2024
(This article belongs to the Section Forest Ecology and Management)
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Abstract

:
Leaf-trait variation has traditionally been focused on both within and among species along environmental gradients, while leaf age has received less attention. By measuring leaf morphological, stomatal, and stoichiometric traits of 40 coexisting woody species in temperate forest in northern China, we analyzed their variation pattern and the correlations among different plant life forms and leaf age. We found that leaf age has significant effects on leaf functional traits. The young leaves of both shrub and tree species revealed a lower stoma density (SD) and a higher stoma length (SL), stoma width (SW), and leaf N content (LNC) than mature leaves. Shrub species have a higher SLA and SD than tree species for both young and mature leaves. The traits of young leaves generally revealed a higher variation than those of mature leaves. Although correlations between traits are similar between young leaves and mature leaves, the slopes of the SLA–SD and SD–LNC relationships were significantly affected by leaf age. These findings elucidate the adaptive changes of leaf traits during leaf maturation and underscore the trade-off between stomatal safety and efficiency, as well as the trade-off between leaf hydraulic and economic traits in temperate woody species during leaf development. We conclude that variation in leaf traits with age may play a potentially important role in understanding the ecological function of woody species in temperate forests.

1. Introduction

Leaf functional traits are regarded as key indicators to understand and predict the abundance and distribution of plant species under climate change at the global and local scale [1,2,3]. A suite of leaf traits related to morphology, stoichiometry, and physiological ecology has been measured to delineate major ecological strategies by integrating global trait data sets [1,4,5]. Within organ types, leaf traits consistently covary in a way described as ‘economics spectra’, which broadly summarize the trade-offs between fast-growing and slow-growing plants [3,6,7]. Leaf development is one of the fundamental processes of plant growth [8], and physiological, anatomical, and morphological traits significantly vary during leaf development [9]. Leaf demography and seasonal differences in leaf age compositions within forest canopy layers are the basis for explaining primary productivity and photosynthetic capacity estimates [10]. Therefore, leaf ontogenetic variations (leaf age) should be considered in studying plant ecological strategies and community assembly based on leaf functional traits.
At the leaf level, some leaf economic traits such as leaf nitrogen concentration (LNC) and specific leaf area (SLA) have been screened to accurately predict the change in maximum photosynthetic rate [11,12] and leaf lifespan for a wide range of species [13]. Regarding the changes in leaf size during leaf development, it not only reflects the light interception efficiency and carbon acquisition ability of plants, but also reflects the trade-off between carbon assimilation and water use efficiency of plants, which is crucial for plant growth regulation [14,15,16]. However, existing studies about changes in leaf functional traits with leaf age only focus on single species and minority traits such as the LNC, SLA, and photosynthetic rate [17,18,19], and the results change depending on plant life forms and growth forms, impeding the formation of common shifting patterns of leaf traits with leaf age. For example, the SLA (specific leaf area) of evergreen species often declines with leaf age because of the increase in leaf tissue density and the accumulation of carbon-rich compounds, while the changing pattern is not unique for deciduous species [20]. A recent meta-analysis synthesized developmental shifts in physical, chemical, and indirect defense traits during leaf maturation across 124 woody plant species [21]. However, the study only focused on defense syndromes during leaf development and the selected species are from different biomes. The trait developmental shifts in species with synchronous leaf flushing were stronger than those in species with asynchronous leaf flushing from different biomes [21]. More species and leaf traits with the same climate condition will provide new insights into the general characteristics of leaf-trait variation.
Leaf stomata is not only an important gateway for plants to balance the relationship between photosynthesis and transpiration, but also a key structure affecting atmospheric carbon and water cycling [22,23]. Stomatal density (SD) and stomatal size (SS) are two important stomatal traits and vary widely between plant species and according to environmental factors, such as temperature, light irradiance, water, soil nutrients, and atmospheric CO2 concentrations, etc. [24,25]. Therefore, stomatal traits play important role in leaf growth. So far, few studies have focused on the changes in stomatal traits with leaf age. Thus, investigating the changes of stomata characteristics during leaf development is crucial to elucidate plant carbon–water fluxes, and understand plant adaptive strategies in the context of ontogenetic shifts.
Here, we measured six continuous leaf traits of different leaf ages of 40 woody species in temperate forest; one trait pertained to leaf morphology, two to leaf stoichiometry, and three to leaf stoma. The major aim was (1) to explore the effects of leaf aging on leaf functional traits, and, further, to understand the difference between different plant growth forms, (2) to investigate the variations between leaf morphological traits, stoichiometric, and stomatal traits, and (3) to examine the relationships among different leaf traits and leaf ages.

2. Material and Methods

2.1. Study Site and Species Selection

The experiment was carried out in Loess Plateau and Qinling Mountains in Shaanxi Province of China, which are the main distribution areas of temperate deciduous forest in China. According to the vegetation distribution, three sites were selected in the study area from south to north for surveying community species composition. Two sites were in the Loess Plateau, and one site was in Qinling Mountains (Figure 1). At each site, one plot of 2500 m2 (50 m × 50 m) was established, and all tree (diameter at breast height > 1 cm) and shrub individuals were identified and their maximum and average height, abundance, and coverage were documented in June–July of 2022.
The climate of the sites is a similarly temperate continental monsoon climate. Mean annual rainfall is 550–650 mm and mean annual temperature is 11–14 °C, respectively (Table S1). Air relative moisture is 60%–65%. The soil is yellow-cinnamon soil and yellow-brown soil. In total, 155 mature and healthy individuals of 40 woody species were selected based on the community species composition and vertical structure (tree and shrub layer). The selected species belong to 16 families, and 25 are tree species and 15 are shrub species (Table S2).

2.2. Sampling and Trait Measurements

2.2.1. Morphology and Stoichiometry Traits

A total of 155 mature and healthy individuals of 40 woody species were selected and sampled. In each site, at least three individuals of focal species were selected and four branches from four direction at the middle of the canopy were labeled at early growing season (April). A digital camera was used to take a picture of each branch to record the number and status of leaves. According to the phenological characteristics of deciduous species in the study area, sampling was conducted at the mid-time of the growing season (June–July). For each branch, all leaves were classified into age categories based on Chavana-Bryant et al. [26]. Briefly, independently for each species, leaves were assigned age categories (young and mature) through visual assessment of leaf color, size, and rigidity. ‘Young’ described immature leaves (<2 months old, not fully expanded, and/or not fully green), which is generally at the tip of branch. ‘Mature’ described leaves that had recently reached maturity (fully expanded, green, and >2 months old). A digital camera was used to take a picture of each fresh leaf surface, and the leaf surface area (LA) was measured using Motic Images Plus 2.0. All leaves were placed inside a drying oven for a period of 72 h at 80 °C; then, the dry mass (MD) was measured. The SLA was calculated as the ratio of leaf area to dry mass (cm2•g−1). All leaves were then pooled together and ground to a fine powder using a ball mill. The LCC (leaf carbon concentrations) and LNC (leaf nitrogen concentrations) were then determined with an elemental analyzer (Euro Vector EA3000, Milan, Italy). The EA3000 Series is based on the well-established Dumas principle of dynamic flash combustion followed by gas chromatography separation of the resultant gaseous species (N2, CO2) and TCD detection.

2.2.2. Stomatal Traits

The nail-polish imprint method was used to examine stomatal traits [27]. A coat of transparent nail polish was put on the center of the underside of the leaf, left to dry, removed with tape, and placed on a glass slide. Stomatal prints were photographed by a Classica SK200 Digital light microscope (Motic China Group Co., Ltd., Guangzhou, China) at 200–400× magnification. Image-Pro Plus 6.0 (Media Cybernetics, Rockville, MD, USA) software was used to measure SL (μm) and SW (μm). After dividing leaves into grids of 100 × 100 μm, SD (mm−2) was calculated as the number of stomata per unit epidermal area. Over 20 randomly selected fields of view were averaged to obtain the SL and SD.

2.3. Data Analyses

Differences in traits among different life forms (trees and shrubs) and ages were analyzed by one-way analyses of variance (ANOVA). Post-hoc tests (Student–Newman–Keuls) were performed when required. We also constructed linear mixed-effects models to detect the effects of leaf age on leaf traits using the lme4 package in R, where study sites were treated as random effects and species; leaf age and their interaction were fixed effects in the models. Multivariate analyses of all traits were conducted by principal component analysis (PCA) for young leaves, mature leaves, and all leaves. Correlations between traits were evaluated using Pearson’s coefficients. The standardized major axis (SMA) estimation method was used to calculate the slope and intercept of the regression equation of any two leaf traits for each leaf age. A likelihood ratio test was used to test the heterogeneity of the regression slope and intercept [28]. All figures were performed by the package ‘ggplot’ in R version 4.1.0 [29].

3. Results

3.1. Variation in Leaf Traits

We found that leaf age has significant effects on leaf functional traits (Figure 2, Table 1). Young leaves of both shrub and tree species revealed a lower stoma density (SD) and a higher stoma length (SL), stoma width (SW), and leaf N content (LNC) than mature leaves (Figure 2). Shrub species had a higher SLA than tree species; moreover, the young leaves of shrub species showed a higher SLA than mature leaves. Shrub species have a higher SD than tree species for both young and mature leaves. The LCC did not show significant differences among different leaf ages and life forms (Figure 2). These results were consistent among all three sites (Figures S1–S3).
For all the species, traits of young leaves generally revealed a higher variation than those of mature leaves (Figure 3). Moreover, the variation of traits among the young leaves of tree species was higher than that of shrub species; the variation among mature leaves did not show significant differences between shrub and tree species (Figure 4).

3.2. Multidimensionality and Bivariate Trait Relationship

The PCA of the multiple traits revealed that the first two components explained >55% of the total variation (Figure 5). The different contributions of the traits of shrub and tree species led to the differences in traits between young and mature leaves (Figure 5, Table S3). However, the correlations between traits were similar among young leaves, mature leaves, and all leaves at an individual level (Figure 5). Overall, a notable inverse correlation was observed between SD and stomatal size (SW and SL) and SLA, as well as between SLA and leaf carbon content (LCC) (Figure 5). Stomatal length and width showed significant negative relationships with stomatal density within species for all the species (Figure 5). A significant positive relationship was found between SW and SL, LCC and SD, and SLA and LNC (Figure 5).
Further SMA analyses showed that the SMA slopes of the SLA–SD and SD–LNC relationships were different for leaves of different leaf ages (Figure 6). The elevation for the LNC–SLA correlation was slightly altered by leaf age (Figure 6).

4. Discussion

4.1. Effects of Leaf Age on Leaf Functional Traits of Different Life Forms

By measuring morphological, stomatal, and stoichiometric variations of leaf traits of 40 woody species in temperate forests, we found that leaf age has significant effects on leaf functional traits (Table 1). The young leaves of both shrub and tree species revealed a lower stoma density (SD) and a higher stoma length (SL), stoma width (SW), and leaf N content (LNC) than mature leaves.
Few studies have focused on the changes in stomatal size and density among leaves of different ages. A previous study on six woody species of Sorbus found an increasing stomatal density and stable stomatal size with the leaf area expansion [30], which is partly consistent with our results. However, another study on two shrub species found that the total stomatal density decreased with leaf area expansion, while the size of stomata increased gradually with leaf expansion [31]. Such a divergence may be related to the differences in plant functional groups. During leaf photosynthesis, stomata are turgor-operated valves that control water loss and CO2 uptake, and, thereby, the leaf stomatal functioning of a plant is closely related to water relation and biomass accumulation [32]. Generally, plants with larger stomata and a lower stomata density and showed greater growth rates; thus, the improved growth rate is attributed to a combination of higher metabolic temperatures, lower metabolic costs, and improved water status [33]. At the same time, smaller stomata generally respond faster than larger stomata; this observation was explained in terms of surface-to-volume ratios and the need for transporting solutes to drive movement [34,35]. Therefore, a smaller size and higher density of stomata ensures a fast response of mature leaves to summer heat in temperate zones.
In addition, the high nutrient content in young leaves is important for leaf development. A previous study also found that the LNC decreased with increasing leaf age and leaf area expansion for evergreen woody species [36]. Developing leaves are regarded as strong sinks, requiring carbohydrates and nutrients to construct the leaf anatomical structure and to improve high metabolic rates for leaf differentiation and expansion [21,37]. Even so, the young leaves of some plant species have been found to have a low nitrogen content, resulting in the ‘delayed greening’ syndrome, which is a syndrome found especially in tropical species that flush leaves synchronously [38]. The high LNC in our study may be due to the fact that the metabolism in leaves is at a high level at the young stage; in addition, growth requires high amounts of protein and nucleic acid, which increases the N concentrations [39]. By contrast, in mature leaves, most of the nutrients acquired by the plant are transported to other organs to meet the reproduction requirement; as a result, the N content in the leaves of the adult plants decreases.

4.2. Variation of Leaf Functional Traits among Different Life Forms

In general, shrub species have a higher SLA than tree species; moreover, the young leaves of shrub species showed a higher SLA than those of mature leaves. A higher SLA generally indicates a quick nutrient-obtaining strategy, shorter leaf lifespans, and a higher plant growth rate [40,41]. Light source availability declined in the understory of forest. Therefore, the high SLA of shrub leaves allows them to maintain a high photosynthetic efficiency [42]. The young leaves of shrub species showed a higher SLA than those of mature leaves, reflecting a faster increase in leaf area than leaf mass for shrub species. Some previous studies have also found that the SLA decreases with increasing leaf age for evergreen woody species [17,18,20,36]. However, in deciduous tree species, there is not a certain pattern found in the previous studies [20]. Therefore, the differentiation of leaf traits in leaf-age adaptive strategy shows functional differentiation because of heterogeneity of light resources.
Shrub species have a lower SD and higher stoma size than tree species for both young and mature leaves. Some previous studies have compared the interspecific differences in stomatal density, distribution, stomatal index for fully mature leaves [32,43]. A previous study on the mature leaves of species of Sorbus found that stomata lengths and densities were significantly larger in the shrub than that in the tree species [30]. The variation among species indicates a long-term response depending on the genetic background of each species and a reaction to short-term environmental changes [44,45]. Our study focused on both young and mature leaves. The lower stomata density of shrub species may indicate a, adaption to more humid conditions in the understory, and the higher stomatal size is a compensation to achieve a higher photosynthetic capacity [33].

4.3. Effects of Leaf Age on Trait Relationships

Although the correlations between traits are similar across different leaf ages, leaf age tends to affect the slope or elevation of the relationships between these traits.
Firstly, we found a significantly negative relationship between the SLA and SD and the LCC. Moreover, the SMA slopes of the SLA–SD relationships were different among leaves of different ages. Stomatal density decreases allometrically with increasing SLA, suggesting that the balance between leaf area and its matter may be associated with the guard cell number [46,47]. This result reflects a general link between the SD and morphological leaf traits. However, the covariation between the SLA and SD can respond to selection over short evolutionary periods because of environmental changes [47]. For example, the SLA was higher and the SD lower for shade leaves compared to sun leaves [48]. Changing irradiance (as well as other environmental conditions) induced changes in guard cell length and, therefore, stomatal density [49]. In our study, a higher slope of SLA-SD was found in mature leaves. This could come from an individual plasticity that allows the leaves to adapt quickly to their environment. It has been shown that the SD of young leaves depends on the state of stomatal conductance of older leaves [50]. Thus, the negative correlation between the SD and SLA is unlikely to be a result of a greater cell size via expansion of leaf cells in the bud after the end of the cell division.
Secondly, although there is a consistent positive relationship between the SLA and LNC for both young leaves and mature leaves, the elevation for the LNC–SLA correlation was slightly altered by leaf age because of the higher LNC of young leaves. The positive relationships between LNC and SLA have been confirmed in many previous studies at both global and region scales [3,5]. At the same time, the slopes in the interspecific trait relationships hold stable under environmental changes, while only their elevations vary. The elevation changes regarding trait relationships are mainly driven by asymmetrically interspecific responses contrary to the direction of the leaf economic spectrum [51]. In our study, the change in the elevation of trait relationships is probably because the structural traits (SLA) and chemical traits (N) have different strategies for adapting to changes in leaf aging [1,20].
Negative relationships between SD and stomatal size have been found in many studies of mature leaves at species level, indicating a stomatal safety–efficiency trade-off [27]. Our results further prove this trade-off relationship in leaves of different ages. Moreover, leaf age did not show significant effects on the relationship between slope and elevation. Therefore, there is a robust trade-off between stomatal size and density both across species and within species under leaf aging.

5. Conclusions

By quantifying morphological, stomatal, and stoichiometric traits for 40 coexisting woody species (including tree and shrub species), we found that leaf age significantly influences the variation and relationships of functional traits. The young leaves from both shrub and tree species exhibited a lower stomatal density (SD) but a higher stomatal length (SL), stomatal width (SW), and leaf nitrogen content (LNC) compared to mature leaves, illustrating how leaf traits adapt during maturation. The correlations between traits highlight the trade-offs between stomatal safety and efficiency, as well as between hydraulic and economic traits, throughout leaf development. Moreover, leaf age modulated the slope of SD–SLA and the elevation of LNC–SD. Therefore, we conclude that the variation in leaf traits of different ages may play a potentially important role in exploring the ecological function of woody species in temperate forests. Our results improve the understanding of age-dependent plasticity changes during leaf development for coexisting species in temperate forests.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15101803/s1, Table S1. Detailed information and sampling number of 40 woody species. Table S2. Detailed information and sampling number of 40 woody species. Table S3. Contribution of different traits in PC1 and PC2. Figure S1. Differences in specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and growth forms in Site 1. Different letters correspond to results of post-hoc tests after ANOVA. Figure S2. Differences in specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and growth forms in Site 2. Different letters correspond to results of post-hoc tests after ANOVA. Figure S3. Differences in specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and growth forms in Site 3. Different letters correspond to results of post-hoc tests after ANOVA.

Author Contributions

L.W. conceived the ideas and wrote the paper; X.Z., G.L., Q.W., F.W. and Y.L. completed the field work. All authors have read and agreed to the published version of the manuscript.

Funding

The study was financially supported by the Shaanxi Academy of Science Research Funding Project (2022-k14), Shaanxi Academy of Fundamental Science (2022JQ-189).

Data Availability Statement

The datasets supporting the conclusions of this article will be archived in Figshare upon acceptance.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Map of the study area showing sampling site in the topographic map of the Shannxi Province.
Figure 1. Map of the study area showing sampling site in the topographic map of the Shannxi Province.
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Figure 2. Differences in specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and life forms. Different letters correspond to results of post-hoc tests after ANOVA.
Figure 2. Differences in specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and life forms. Different letters correspond to results of post-hoc tests after ANOVA.
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Figure 3. Variable coefficient within species for mature and young leaves of 40 species. Traits: specific leaf area (SLA), stomatal density (SD), stomatal length (SL), stomatal width (SW), leaf nitrogen content (LNC), and leaf carbon content (LCC).
Figure 3. Variable coefficient within species for mature and young leaves of 40 species. Traits: specific leaf area (SLA), stomatal density (SD), stomatal length (SL), stomatal width (SW), leaf nitrogen content (LNC), and leaf carbon content (LCC).
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Figure 4. Differences in variable coefficients of specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and life forms. Different letters correspond to results of post-hoc tests after ANOVA.
Figure 4. Differences in variable coefficients of specific leaf area (SLA) (a), stomatal density (SD) (b), stomatal length (SL) (c), stomatal width (SW) (d), leaf nitrogen content (LNC) (e), and leaf carbon content (LCC) (f) among different leaf ages and life forms. Different letters correspond to results of post-hoc tests after ANOVA.
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Figure 5. PCA (a,c,e) and correlation matrix (b,d,f) of leaf traits for different leaf ages. Mature leaves, a and b; Young leaves, c and d; All leaves e and f. Traits: specific leaf area (SLA), stomatal density (SD), stomatal length (SL), stomatal width (SW), leaf nitrogen content (LNC), and leaf carbon content (LCC). *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Figure 5. PCA (a,c,e) and correlation matrix (b,d,f) of leaf traits for different leaf ages. Mature leaves, a and b; Young leaves, c and d; All leaves e and f. Traits: specific leaf area (SLA), stomatal density (SD), stomatal length (SL), stomatal width (SW), leaf nitrogen content (LNC), and leaf carbon content (LCC). *, p < 0.05; **, p < 0.01; ***, p < 0.001.
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Figure 6. The bivariate trait relationships of LCC and SLA (a), LNC and SLA (b), SD and SLA (c), LCC and SD (d), LNC and SD (e), SL and SD (f). R2 and p values were estimated from standard major axis (SMA) regression. Significant differences in slopes or elevation between trait relationships were noted by *.
Figure 6. The bivariate trait relationships of LCC and SLA (a), LNC and SLA (b), SD and SLA (c), LCC and SD (d), LNC and SD (e), SL and SD (f). R2 and p values were estimated from standard major axis (SMA) regression. Significant differences in slopes or elevation between trait relationships were noted by *.
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Table 1. Results of linear mixed-effects model analysis presenting the effect of leaf age and species on leaf traits.
Table 1. Results of linear mixed-effects model analysis presenting the effect of leaf age and species on leaf traits.
Source of VariationdfLNCLCCSLASLSWSD
SS%FSS%FSS%FSS%FSS%FSS%F
Species39.00 34.28 9.4252.29 8.7594.00 146.0984.63 40.3577.17 22.4892.45 136.03
Leaf age1.00 14.20 140.393.27 19.700.18 10.141.66 28.491.00 10.442.39 126.60
Species × age37.00 32.81 9.2713.74 2.362.51 4.022.93 1.44 4.19 1.25 1.67 2.53
Residuals185.00 18.71 30.70 3.31 10.78 17.64 3.49
Key to abbreviations: df, degree of freedom; %SS, percentage of the total sum of squares explained by each term. The numbers in bold indicate significant effects.
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Wang, L.; Zhao, X.; Liu, G.; Wang, Q.; Wang, F.; Li, Y. Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China. Forests 2024, 15, 1803. https://doi.org/10.3390/f15101803

AMA Style

Wang L, Zhao X, Liu G, Wang Q, Wang F, Li Y. Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China. Forests. 2024; 15(10):1803. https://doi.org/10.3390/f15101803

Chicago/Turabian Style

Wang, Li, Xueyan Zhao, Guoyu Liu, Qing Wang, Fangyuan Wang, and Yan Li. 2024. "Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China" Forests 15, no. 10: 1803. https://doi.org/10.3390/f15101803

APA Style

Wang, L., Zhao, X., Liu, G., Wang, Q., Wang, F., & Li, Y. (2024). Changes in Leaf Functional Traits with Leaf Age for Coexisting Woody Species in Temperature Forest of Northern China. Forests, 15(10), 1803. https://doi.org/10.3390/f15101803

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