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Article

Differences in Leaf Functional Traits of Quercus rehderiana Hand.-Mazz. in Forests with Rocky and Non-Rocky Desertification in Southwest China

by
Xiao-Long Bai
1,2,
Tu Feng
1,2,
Shun Zou
1,2,
Bin He
1,2,
Yang Chen
1,2 and
Wang-Jun Li
1,2,*
1
College of Ecological Engineering, Guizhou University of Engineering Science, Bijie 551700, China
2
Guizhou Province Key Laboratory of Ecological Protection and Restoration of Typical Plateau Wetlands, Guizhou University of Engineering Science, Bijie 551700, China
*
Author to whom correspondence should be addressed.
Forests 2024, 15(8), 1439; https://doi.org/10.3390/f15081439
Submission received: 29 July 2024 / Revised: 11 August 2024 / Accepted: 14 August 2024 / Published: 15 August 2024
(This article belongs to the Section Forest Ecophysiology and Biology)
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Abstract

:
Quercus rehderiana Hand.-Mazz. belongs to Quercus sect. Heteroallenes’ of the Fagaceae family. It is widely distributed in forests with rocky and non-rocky desertification in Guizhou Province of Southwest China. However, our knowledge of the adaptation strategies of Quercus in forests with rocky desertification is surprisingly lacking. In this study, 16 leaf traits (morphological, anatomical, and chemical) of Quercus rehderiana were investigated in 15 individuals in five 20 × 20 m quadrants of forests with rocky and non-rocky desertification. The aim was to analyze their strategies of adaptation to arid and poor-soil environments in forests with rocky desertification. The results showed that Quercus rehderiana leaves in forests with rocky desertification had a greater leaf thickness, specific leaf area, abaxial epidermis thickness, and sponge mesophyll thickness but a lower leaf area than in forests with non-rocky desertification. Quercus rehderiana leaves in forests with rocky desertification had higher calcium and magnesium concentrations and a higher N:P ratio but lower potassium and phosphorus concentrations than in forests with non-rocky desertification. The results of principal component analysis showed that forests with rocky desertification tended to show resource-conserving strategies with thicker leaf tissue and a lower nutrient concentration, while forests with non-rocky desertification tended to show resource acquisition strategies with a greater leaf area and potassium concentration. In resource-poor environments, species that adopt conservative resource strategies are more likely to survive; therefore, we forecasted that more conservative, slow-growing Quercus rehderiana will be more stable over time.

1. Introduction

Quercus rehderiana Hand.-Mazz. is a genus of Quercus in the Fagaceae family that has important ecological significance and economic value for reasons including biodiversity maintenance, soil and water conservation, carbon storage, and energy demand [1]. Over the last few decades, the distribution range and original habitat of Quercus have gradually decreased due to the intensification of climate change and human disturbances combined with the lack of sustainable management [2]. Many species of animals associated with ecological connections, with plants of this genus especially, suffer from this [3,4]. Therefore, the stability of the ecosystem and the sustainable development of the social economy (in terms of fodder, fuelwood, charcoal, agricultural tools, bee boxes, etc.) are seriously threatened [5]. To date, a number of previous studies have focused on the population structure; spatial distribution [2,6,7]; and adaptations of the leaf, stem, and root traits of Quercus to different altitude gradients and environmental factors [8,9,10]. It is worth noting that Quercus rehderiana is distributed in forests with both rocky and non-rocky desertification in Guizhou Province [2]. However, a comprehensive understanding of the mechanism of adaptation of the functional traits of Quercus rehderiana to forests with rocky desertification is still lacking.
Plants with resource-acquiring ecological strategies have a greater specific leaf area, photosynthetic rate, and nutrient concentration, while those with resource-conserving strategies have the opposite [11,12]. Previous studies found that leaves in forests with rocky desertification adopted resource-conservating adaptation strategies because of their higher photosynthetic rate, water use efficiency, photosynthetic rate, phosphorus concentration, and adaxial and abaxial epidermis thickness than those of leaves of non-karst forest trees [13]. It is still an open question as to whether plants in forests with rocky desertification use resource-conservating or resource-acquiring strategies. Therefore, a comparative analysis of the functional traits of plants in forests with rocky and non-rocky desertification is helpful in revealing the physiological and ecological adaptation of plants to habitats that have undergone rocky desertification [13,14,15].
Due to water scarcity in forests with rocky desertification, plants need thicker leaves and leaf tissues and a greater specific leaf area but a lower leaf area and leaf dry matter content to maintain water storage in the plant body and capture more light resources. Therefore, we hypothesized that Quercus rehderiana leaves in forests with rocky desertification have a greater specific leaf area, leaf thickness, abaxial epidermis thickness, and spongy mesophyll thickness but a lower leaf area and leaf dry matter content than those in forests with non-rocky desertification. In addition, forests with rocky desertification have poor soil (more P limitation) and are rich in calcium and magnesium, resulting in the enrichment of calcium and magnesium in plants but lower phosphorus and potassium concentrations. Therefore, we hypothesized that Quercus rehderiana leaves in forests with rocky desertification have higher calcium and magnesium concentrations and a higher N:P ratio but lower phosphorus and potassium concentrations than in forests with non-rocky desertification. The results of this study are of practical significance for the prediction of the population dynamics of Quercus with the frequency of drought events and the aggravation of rocky desertification.

2. Materials and Methods

2.1. Study Site

The study area was located in Weining, Bijie City, northwestern Guizhou Province (103°36′–104°30′ E, 26°30′–27°25′ N; 2200 m a.s.l.). The study site is influenced by the monsoon climate, and the mean annual precipitation is ca. 1000 mm. The mean annual temperature is 12 °C. The soil types include yellow soil, yellow brown soil, and purple soil, and the pH value is 5.50. Due to disturbances and destruction resulting from human activities, the shrub and herb layers are sparse. The shrub layer mainly includes Corylus yunnanensis, Coriaria nepalensis, and Rhododendron simsii. The herbaceous layers include Plantago asiatica, Prunella vulgaris, Rubia cordifolia, Viola philippica, and a variety of ferns, such as Aratiostegia perdurans [16].
Rocky desertification is a phenomenon of vegetation and soil degradation and land productivity decline, and large areas of rock are exposed to the surface due to natural climate change and unreasonable human activities [17]. The environment of high temperatures, drought, and poor soil in forests with rocky desertification seriously restricts the growth and development of vegetation [18]. In addition, the soil in forests with rocky desertification is typically deficient in phosphorus [19] and rich in calcium [20].

2.2. Sampling

The classification of rocky desertification and non-rocky desertification is based on Li’s report; that is, the vegetation coverage of forests with rocky desertification is less than 50%, the rock exposure is more than 60%, and the average soil thickness is less than 15 cm [21]. From July to September 2021, five 20 m × 20 m quadrats were set on top of a mountain with low vegetation coverage, high rock exposure, and a thin soil layer, representing forests with rocky desertification. Five 20 m × 20 m quadrats were set on the foot of the mountain, where there was high vegetation coverage, low rock exposure, and a thick soil layer, representing forests with non-rocky desertification. We divided each 20 m × 20 m quadrat into four small quadrats of 10 m × 10 m. There was no Quercus rehderiana Hand.-Mazz. in some of the small quadrats in the forests with rocky desertification. Therefore, we selected 3 out of 4 small quadrats and selected Quercus rehderiana near the center of each small quadrat to collect leaves. For every individual, we used high pruning to cut branches and collected intact, healthy, mature, and sun-exposed leaves. We put the leaf samples into a sampling box containing an ice pack and brought it back to the laboratory for later trait measurement.

2.3. Trait Measurements

Plant functional traits are morpho-physio-phenological traits that potentially impact plant fitness through their effects on individuals’ growth, reproduction, and survival [22]. The leaf is an important organ of plant photosynthesis and is the most sensitive to environmental changes [11]. The effects of environmental changes on plant populations and communities are often reflected by the functional traits of leaves [23]. The functional traits of plant leaves indicate plants’ resource acquisition and utilization abilities and their resistance to adversity [24,25]. The synergistic or trade-off relationship of multiple leaf traits reflects the ecological strategy of plants [11,26,27].
Leaf functional traits were determined according to Cornelissen et al. (2003) [28] and Perez-Harguindeguy et al. (2016) [29]. Three to five leaf samples (one individual selected only three leaf samples, and twenty-nine individuals selected five leaf samples) were collected per individual to measure the leaf area (LA) using an HP Scanjet M231 scanner and the ImageJ software (https://imagej.en.softonic.com/ accessed on 22 May 2023). We measured the leaf fresh weight using an electronic balance (0.0001 g), and then leaf samples were oven-dried at 70 °C for 48 h. The specific leaf area (SLA) and dry matter content (LDMC) of the leaves were calculated. The SLA was the leaf area divided by the leaf dry weight. The LDMC was the dry weight divided by the fresh weight. Five to seven leaf tissue cross-section pictures were taken using a Binocular Biological Microscope (Leica DM2500, Wetzlar, Germany), and the leaf thickness (LT), adaxial epidermis thickness (Ada), abaxial epidermis thickness (Aba), palisade mesophyll thickness (PT), and spongy mesophyll thickness (ST) values were measured using the ImageJ Software (https://imagej.en.softonic.com/ accessed on 22 May 2023).
Leaf N, P, K, Ca, and Mg play an important role in organism composition and the regulation of the physiological mechanisms of plant growth and development [30]. The dried leaf samples were ground to a fine powder with a crusher and then passed through a 60-mesh sieve. The nitrogen concentration (N) and carbon concentration (C) were measured with a Dumas-type combustion C-N elemental analyzer (Vario MAX CN, Elementar Analysensysteme GmbH, Hanau, Germany). Phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) were measured with an inductively coupled plasma atomic-emission spectrometer (iCAP 7400, Thermo Fisher Scientific, Bremen, Germany) [31,32]. The C:N ratio was calculated as a proxy of carbon assimilation when plants absorbed nutrients [33]. The N:P ratio was calculated as an indicator of nutrient limitation [34].

2.4. Data Analyses

Data on the leaf functional traits were used for single individuals. All data were log10-transformed to an approximate normal distribution before analysis. The difference between leaf traits was analyzed using an independent-sample t-test with the stats package. The correlation between traits was analyzed with Pearson’s correlation using the Hmisc package. A principal component analysis (PCA) was used to evaluate trait associations using the vegan package. All analyses were performed in R version 4.4.0 (R Core Team 2024).

3. Results

The LA, LDMC, P, and K in the forests with non-rocky desertification were significantly higher than those in the forests with rocky desertification (Figure 1A,D,K,L; Table S1). The LT, SLA, Aba, ST, N:P, Ca, and Mg in the environment with rocky desertification were significantly higher than those in forests with non-rocky desertification (Figure 1B,C,F,H,N,O,P). There were no significant differences in Ada, PT, C, N, and C:N between forests with rocky and non-rocky desertification (Figure 1E,G,I,J,M; Table S1).
For the leaf morphological and anatomical traits, the SLA was negatively related to the LDMC in forests with rocky desertification (R = −0.67, p < 0.01), but this relationship was not significant in forests with non-rocky desertification (R = −0.12, p = 0.67) (Figure 2A). LT was positively related to LA (R = 0.55, p = 0.03) (Figure 2B) and Aba (R = 0.52, p = 0.04) (Figure 2C) in forests with non-rocky desertification, but this relationship was not significant in forests with non-rocky desertification (R = 0.34, p = 0.22; R = 0.48, p = 0.07). LT was positively related to ST both in forests with non-rocky desertification (R = 0.97, p < 0.01) and forests with rocky desertification (R = 0.89, p < 0.01) (Figure 2D). ST was positively related to LA in forests with rocky desertification (R = 0.52, p = 0.04), but this relationship was not significant in forests with non-rocky desertification (R = 0.26, p = 0.34) (Figure 2E). PT was positively related to ST both in forests with non-rocky desertification (R = 0.66, p < 0.01) and in forests with rocky desertification (R = 0.70, p < 0.01) (Figure 2F).
For all of the functional traits, N was positively related to P in forests with non-rocky desertification (R = 0.63, p = 0.01), while these were non-significantly negatively related in forests with rocky desertification (R = −0.04, p = 0.90) (Figure 3A). The LDMC was negatively related to K in forests with non-rocky desertification (R = −0.61, p = 0.02), but this relationship was not significant in forests with rocky desertification (R = −0.26, p = 0.35) (Figure 3B). K was negatively related to Aba in forests with non-rocky desertification (R = −0.69, p < 0.01), while these were non-significantly positively related in forests with rocky desertification (R = 0.37, p = 0.17) (Figure 3C). Ca was negatively related to LA (R= −0.57, p = 0.03) (Figure 3D), C (R= −0.93, p < 0.01) (Figure 3I), and K (R = −0.68, p < 0.01) (Figure 3J) in forests with rocky desertification, but this relationship was not significant in forests with non-rocky desertification (R = −0.26, p = 0.36; R= −0.33, p = 0.22; R = −0.47, p = 0.08). Ca was negatively related to LT (R = −0.63, p = 0.01) (Figure 3E), Aba (R = −0.63, p = 0.03) (Figure 3G), and ST (R = −0.62, p = 0.01) (Figure 3H) in forests with rocky desertification, while these were non-significantly positively related in forests with non-rocky desertification (R = 0.26, p = 0.35; R = 0.35, p = 0.20; R = 0.39, p = 0.16). Ca was positively related to the LDMC in forests with rocky desertification (R = 0.56, p = 0.03), but this relationship was not significant in forests with non-rocky desertification (R = 0.33, p = 0.22) (Figure 3F). Mg was negatively related to SLA in forests with non-rocky desertification (R = −0.63, p = 0.01) (Figure 3K), while these were non-significantly positively related in forests with rocky desertification (R = 0.27, p = 0.34). Mg was positively related to P in forests with non-rocky desertification (R = 0.57, p = 0.03) (Figure 3L), while these were non-significantly negatively related in forests with rocky desertification (R = −0.34, p = 0.22).
The results of the principal component analysis based on 16 traits of 30 individuals showed that the first and second components accounted for 42.59% and 18.64% of the total variance, respectively (Figure 4). The first axis was positively correlated with traits that were representative of leaf Mg and Ca concentrations. At the opposite end were individuals with high LA and K. The second axis correlated positively with Aba, ST, and LT and negatively with P. The forests with rocky desertification exhibited a negative correlation with high leaf area, high phosphorus concentration, and potassium concentration, indicating the adoption of a resource-acquiring strategy. Individuals with rocky desertification and non-rocky desertification overlapped less in the multivariate trait space, indicating that the resource strategies were different (Figure 4).

4. Discussion

Our results showed that Quercus rehderiana Hand.-Mazz. leaves in forests with rocky desertification had higher LT, SLA, Aba, and ST but lower LA and LDMC than those in forests with non-rocky desertification, which was consistent with our first hypothesis (Figure 1). Regarding leaf nutrients, forests with rocky desertification had higher N:P ratios and Ca and Mg concentrations but lower P and K concentrations, which was consistent with our second hypothesis. Interestingly, another study in Guizhou Province found that plants in forests with rocky desertification had higher LT, LA, SLA, and LDMC than those in forests with non-rocky desertification [35]. The Ca and Mg concentrations in the leaves of plants in forests with rocky desertification were higher than those of plants in forests with non-rocky desertification; however, there were no significant differences in the leaf N and P concentrations [14,36].
Compared with Quercus aquifolioides (Table 1), the leaves of Quercus rehderiana in forests with both rocky and non-rocky desertification had lower LT, SLA, PT, and ST but higher LA, while the LDMC was similar [37,38]. Compared with other studies of leaf nutrients (Table 2), the C concentration and C:N ratio of Quercus rehderiana leaves in forests with both rocky and non-rocky desertification were higher than those in other species of Quercus [9,39,40,41]. The N concentration in Quercus rehderiana leaves in forests with both rocky and non-rocky desertification was higher than that in Quercus sect. Heterobalanus as reported by Li et al. (2018) [39] and in Quercus aquifolioides as reported by Liu et al. (2012) [41], but it was lower than the value reported by Li et al. (2023) [9]. The P and K concentrations of Quercus rehderiana leaves in forests with both rocky and non-rocky desertification were lower than those in other species of Quercus (Table 2) [9,38,41]. The Ca concentrations in Quercus rehderiana leaves in forests with both rocky and non-rocky desertification were higher than those in Quercus aquifolioides [41]. The Mg concentration in Quercus rehderiana leaves was similar to that in Quercus aquifolioides [41] in forests with rocky desertification, but it was lower in forests with non-rocky desertification. The N:P ratio in Quercus rehderiana leaves in forests with both rocky and non-rocky desertification was similar to that in Quercus variabilis [40] but lower than that in Quercus semicarpifolia [9] and Quercus semicarpifolia [40], while it was higher than that in Quercus aquifolioides [41] and other species of Quercus sect. Heterobalanus [39]. This difference can be influenced by genetic and environmental factors such as elevation, rainfall, temperature, and soil type.
LT is related to resource acquisition, water and nutrient conservation and utilization efficiency, and carbon dioxide assimilation in plants [42,43]. Plants with thicker leaves are more efficient at conserving and using water and nutrients [44]. LT is usually thinner in humid and nutrient-rich areas than in harsh environments [45]. Our study found that the leaves of Quercus rehderiana in forests with rocky desertification (150.70 µm vs. 127.77 µm) were thicker than those in forests with non-rocky desertification, which indicated that soil nutrients and other environmental resources in forests with rocky desertification are poor. Interestingly, studies in different regions have found different results (Table 3). In particular, Zhang et al. (2020) reported that the LT was greater in forests with rocky desertification than in forests with non-rocky desertification in Guizhou Province [35]. However, Fu et al. (2019) found that there were no significant differences in LT between forests with rocky and non-rocky desertification in Yunnan Province [13]. This may be related to the use of stable rock water by species in tropical and subtropical forests with rocky desertification [46,47]. SLA reflects the resource utilization and conservation capacity of plants [48]. Generally, a high SLA indicates that tree species adopt resource-acquiring strategies [49]. Our study found that the SLA of Quercus rehderiana in forests with rocky desertification (58.52 cm g−1 vs. 50.99 cm g−1) was significantly higher than that in forests with non-rocky desertification. The results of this study were similar to those of a study on rocky desertification in Guizhou Province [35]. However, a study in Yunnan Province did not find significant differences in SLA between forests with rocky and non-rocky desertification [13]. This may have been due to the fact that Guizhou is cloudy in comparison with the climatic conditions in Yunnan Province, and plants enhance light capture by increasing their SLA to adapt to environmental conditions with less light [50]. We found that the leaves of forests with rocky desertification had a higher Aba (11.80 µm vs. 9.49 µm) and ST (62.35 µm vs. 52.58 µm) than those in forests with non-rocky desertification, which was partly consistent with the results of other studies on mountains with rocky desertification [51]. The anatomical traits of plants in mountainous areas with rocky desertification include thicker palisade tissue, tightly packed spongy mesophyll, and a thicker epidermis to resist drought or reduce water loss during transpiration [50,52]. Previous studies acknowledged that LA is closely related to plant water status and influences the light capture and carbon acquisition abilities of plants, thereby influencing photosynthesis [53,54,55]. The LDMC is related to leaf resistance, and plants with high LDMC can survive well in resource-poor habitats [28]. Plants in areas with rocky desertification generally present a combination of low leaf area and high leaf dry matter content (LDMC), which means that plants adapt to the physiological drought caused by a shallow karst soil layer and soil water leakage [50]. The results of our study also confirmed that forests with rocky desertification had a lower LA and higher LDMC.
We found that the leaf P concentration was lower in forests with rocky desertification (0.82 mg g−1 vs. 0.97 cm g−1) than in forests with non-rocky desertification, which was consistent with the report by Fu et al. (2017) (Table 3) [13]. This may have been caused by the availability of P in the soil [56]. K is involved in stomatal movement, osmotic regulation, and enzyme activation, and it can increase the photosynthetic rate of plants by increasing the chlorophyll content [56,57]. However, studies on K in forests with rocky desertification are few compared with studies on other elements [58]. The results showed that the content of Ca (9.29 mg g−1 vs. 6.61 cm g−1) and Mg (1.33 mg g−1 vs. 1.05 cm g−1) concentrations in forests with rocky desertification was significantly higher than that in forests with non-rocky desertification, which was consistent with the results for other forests with rocky desertification [59]. This may have been due to the chemical dissolution of soluble carbonate rocks by groundwater and surface water in karst areas, which makes the soil rich in Ca and Mg and causes them to accumulate in plants [60]. The leaf N:P ratio can be used as an important indicator of plant nutrient limitation, and it was divided into three levels: N:P ratio < 14 (N limitation) and > 16 (P limitation), and 14 ≤ N:P ratio ≤ 16 (limitation of N and P or not) [34,61,62]. We found that the N:P ratios in forests with both rocky and non-rocky desertification were higher than 16, indicating that P is a growth-limiting nutrient for Quercus rehderiana, supporting our second hypothesis.
Table 3. Differences in leaf traits between forests with rocky and non-rocky desertification according to different scholars. An en-dash indicates that data could not be obtained from the figures.
Table 3. Differences in leaf traits between forests with rocky and non-rocky desertification according to different scholars. An en-dash indicates that data could not be obtained from the figures.
TraitForests with Rocky Desertification Forests with Non-Rocky Desertification SignificanceReference
LT1719.75P < 0.01This study
−−P < 0.05[35]
188176P > 0.05[13]
SLA58.5250.99P < 0.01This study
−−P < 0.05[35]
157158P > 0.05[13]
Aba11.89.49P < 0.01This study
13.5311.2P > 0.05[51]
ST62.3552.58P < 0.01This study
45.2972.45P < 0.05[51]
P0.820.97P < 0.01This study
1.741.12P < 0.05[13]
Ca9.296.61P < 0.05This study
2.190.92P < 0.05[59]
Mg1.331.05P < 0.05This study
0.330.2P < 0.05[59]
Functional correlations among plant functional traits exist, and they represent the fundamental trade-offs or synergies among these traits [11,27,63]. In the present study, we found negative correlations between SLA and LDMC in forests with rocky desertification (Figure 2). These correlations have been well-established in previous studies (Table 4) [44,64]. We found that LA was significantly and positively correlated with LT in forests with rocky desertification, which was consistent with the findings of Zhong et al. (2018) [50] and Long et al. (2023) [65]. In addition, we found that LA was positively related to ST. Plants with a greater light demand also tend to have a higher leaf water storage capacity and resistance to the diffusion of CO2 to the blade surface [66,67]. The positive correlation between leaf area and leaf tissue thickness in this study implies that plants in forests with rocky desertification need to capture more light resources while preventing water loss from leaves due to high-temperature transpiration. However, the Ca in plant leaves was significantly negatively correlated with the thickness of various tissues in habitats with rocky desertification (Figure 3). This may be because Ca can form calcium pectinate with pectic acid, thereby stabilizing the structure of cell walls and actively promoting the formation of cytoplasm and organelles, thus reducing the investment in supporting structural tissues [68,69]. It is concluded that C is negatively correlated with Ca, indicating that a higher Ca concentration in plants is not conducive to C storage; thereby, plant primary productivity decreases [70]. In this study, there was a significant negative correlation between Ca and K in forests with rocky desertification. Large amounts of Ca are not conducive to the absorption of other elements, such as Mg and K [71]. This indicates that there is an obvious antagonistic effect on the selective absorption of Ca and K in forests with rocky desertification. Similar results were also reported in a study of plant communities in Maolan National Nature Reserve [72].

5. Conclusions

In summary, we compared the differences in 16 leaf traits of Quercus rehderiana Hand.-Mazz. in forests with rocky and non-rocky desertification. We found that leaf morphological, anatomical, and nutrient traits have obvious differences between forests with rocky and non-rocky desertification. Forests with non-rocky desertification had thick leaves, a high tissue thickness, and high nutrient concentrations, while forests with rocky desertification had a high calcium and magnesium content.
There were synergistic and trade-off relationships among leaf functional traits. We inferred that Quercus rehderiana in forests with rocky desertification adopted a resource-conserving strategy to adapt to the arid and poor soil of environments with rocky desertification. Species with resource-conserving strategies are more stable over time. Accordingly, our findings have practical significance for the prediction of the population dynamics of Quercus with the frequency of drought events and the aggravation of rocky desertification.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f15081439/s1, Table S1. The mean value and SE for leaf area, leaf thickness, specific leaf area, leaf dry matter content, adaxial epidermis thickness, abaxial epidermis thickness, palisade mesophyll thickness, spongy mesophyll thickness, carbon concentration, nitrogen concentration, phosphorus concentration, potassium concentration, C:N ratio, N:P ratio, calcium concentration, and magnesium concentration of Quercus rehderiana Hand.-Mazz. in forests with rocky and non-rocky desertification.

Author Contributions

X.-L.B. and W.-J.L. conceived and designed the experiment. X.-L.B., T.F., S.Z. and Y.C. collected data. X.-L.B. and B.H. analyzed the data. X.-L.B. and W.-J.L. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the Bijie Science and Technology Project (bikelianhe[2023]23), the Bijie Science and Technology Project (bikelianhe[2023]10), the Project of Guizhou Science and Technology Fund (qiankehejichu-ZK-[2024]key077), the Guizhou Provincial Science and Technology Project (qiankehejichu-ZK-[2022]yiban167), the Bijie Talent Team of Biological Protection and Ecological Restoration in Liuchong River Basin (202112), and the Regional First-Class Discipline of Ecology in Guizhou Province (XKTJ[2020]22).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Acknowledgments

The authors thank the Public Technology Service Center of Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences for analyzing the foliar nutrient concentrations and offering an electron microscope. The Weining County Forestry Bureau provided logistic support.

Conflicts of Interest

The authors declare no conflicts of interest.

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Forests 15 01439 g001
Figure 1. T-test for differences in leaf traits between forests with rocky and non-rocky desertification. LA, leaf area; LT, leaf thickness; SLA, specific leaf area; LDMC, leaf dry matter content; Ada, adaxial epidermis thickness; Aba, abaxial epidermis thickness; PT, palisade mesophyll thickness; ST, spongy mesophyll thickness; N, nitrogen concentration; C, carbon concentration; P, phosphorus concentration; K, potassium concentration; C:N, C:N ratio; N:P, N:P ratio; Ca, calcium concentration; Mg, magnesium concentration. (A–P) indicates the serial number of figures. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Figure 1. T-test for differences in leaf traits between forests with rocky and non-rocky desertification. LA, leaf area; LT, leaf thickness; SLA, specific leaf area; LDMC, leaf dry matter content; Ada, adaxial epidermis thickness; Aba, abaxial epidermis thickness; PT, palisade mesophyll thickness; ST, spongy mesophyll thickness; N, nitrogen concentration; C, carbon concentration; P, phosphorus concentration; K, potassium concentration; C:N, C:N ratio; N:P, N:P ratio; Ca, calcium concentration; Mg, magnesium concentration. (A–P) indicates the serial number of figures. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Forests 15 01439 g001
Forests 15 01439 g002
Figure 2. Pearson’s correlation between leaf morphological and anatomical traits in Quercus rehderiana Hand.-Mazz. in forests with rocky and non-rocky desertification. LA, leaf area; LT, leaf thickness; SLA, specific leaf area; LDMC, leaf dry matter content; Aba, abaxial epidermis thickness; PT, palisade mesophyll thickness; ST, spongy mesophyll thickness. RD, rocky desertification; NRD, non-rocky desertification. (A–F) indicates the serial number of figures. p < 0.05, significant difference; p > 0.05, no significant difference; R, correlation coefficient.
Figure 2. Pearson’s correlation between leaf morphological and anatomical traits in Quercus rehderiana Hand.-Mazz. in forests with rocky and non-rocky desertification. LA, leaf area; LT, leaf thickness; SLA, specific leaf area; LDMC, leaf dry matter content; Aba, abaxial epidermis thickness; PT, palisade mesophyll thickness; ST, spongy mesophyll thickness. RD, rocky desertification; NRD, non-rocky desertification. (A–F) indicates the serial number of figures. p < 0.05, significant difference; p > 0.05, no significant difference; R, correlation coefficient.
Forests 15 01439 g002
Forests 15 01439 g003
Figure 3. Pearson’s correlations between functional traits of Quercus rehderiana in areas with rocky and non-rocky desertification. N, nitrogen concentration; P, phosphorus concentration; LDMC, leaf dry matter content; K, potassium concentration; Aba, abaxial epidermis thickness; LA, leaf area; LT, leaf thickness; ST, spongy mesophyll thickness C, carbon concentration; Ca, calcium concentration; Mg, magnesium concentration. RD, rocky desertification, NRD, non-rocky desertification. (A–L) indicates the serial number of figures. p < 0.05, significant difference; p > 0.05, no significant difference; R, correlation coefficient.
Figure 3. Pearson’s correlations between functional traits of Quercus rehderiana in areas with rocky and non-rocky desertification. N, nitrogen concentration; P, phosphorus concentration; LDMC, leaf dry matter content; K, potassium concentration; Aba, abaxial epidermis thickness; LA, leaf area; LT, leaf thickness; ST, spongy mesophyll thickness C, carbon concentration; Ca, calcium concentration; Mg, magnesium concentration. RD, rocky desertification, NRD, non-rocky desertification. (A–L) indicates the serial number of figures. p < 0.05, significant difference; p > 0.05, no significant difference; R, correlation coefficient.
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Figure 4. The biplot of the first two axes of the principal component analysis (PCA) for the relationships of leaf functional traits and the loadings of the fifteen individuals in forests with rocky desertification and fifteen individuals in forests with non-rocky desertification. RD, rocky desertification; NRD, non-rocky desertification. See the text for trait abbreviations. All leaf traits were log10-transformed before the analysis.
Figure 4. The biplot of the first two axes of the principal component analysis (PCA) for the relationships of leaf functional traits and the loadings of the fifteen individuals in forests with rocky desertification and fifteen individuals in forests with non-rocky desertification. RD, rocky desertification; NRD, non-rocky desertification. See the text for trait abbreviations. All leaf traits were log10-transformed before the analysis.
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Table 1. Leaf morphological traits of different Quercus species according to different scholars. RD, forests with rocky desertification; NRD, forests with non-rocky desertification.
Table 1. Leaf morphological traits of different Quercus species according to different scholars. RD, forests with rocky desertification; NRD, forests with non-rocky desertification.
SpeciesLALTSLALDMCAdaAbaPTSTReference
RD—Quercus rehderiana17.00150.7058.520.56 5.3411.80 15.19 62.35 This study
NRD—Quercus rehderiana19.75127.7750.990.58 5.109.49 14.77 52.58 This study
Quercus aquifolioides10.2 70.740.45 [37]
Quercus aquifolioides 419–777 151–325151–351[38]
Table 2. Leaf nutrients of different Quercus species according to different scholars. RD, forests with rocky desertification; NRD, forests with non-rocky desertification.
Table 2. Leaf nutrients of different Quercus species according to different scholars. RD, forests with rocky desertification; NRD, forests with non-rocky desertification.
SpeciesCNPKCaMgC:NN:PReference
RD—Quercus rehderiana498.00 15.01 0.82 3.67 9.29 1.33 33.24 18.47 This study
NRD—Quercus rehderiana494.80 15.34 0.97 6.15 6.61 1.05 32.45 16.04 This study
Quercus aquifolioides14.51.77.54.91.336.878.53[41]
Quercus semicarpifolia453.2426.792.89 16.9825.03[9]
Quercus sect. Heterobalanus 477.8813.831.26 36.511.69[39]
Quercus fabrei 21.9625.26[40]
Quercus variabilis 27.0819.22[40]
Table 4. Correlations of paired traits according to different scholars.
Table 4. Correlations of paired traits according to different scholars.
y~xForests with Rocky DesertificationForests with Non-Rocky DesertificationReference
RPRP
SLA~LDMC−0.67<0.01−0.12>0.05This study
−0.42<0.01 [64]
−0.36<0.01 [44]
−0.92<0.001[37]
LA~LT0.55<0.05 This study
0.37<0.001 [65]
0.65<0.01 [50]
LT~Aba0.52<0.05 This study
0.74<0.01[38]
LT~ST0.89<0.010.97<0.01This study
0.95<0.01[38]
C~Ca−0.93<0.01 This study
−0.4<0.01 [65]
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Bai, X.-L.; Feng, T.; Zou, S.; He, B.; Chen, Y.; Li, W.-J. Differences in Leaf Functional Traits of Quercus rehderiana Hand.-Mazz. in Forests with Rocky and Non-Rocky Desertification in Southwest China. Forests 2024, 15, 1439. https://doi.org/10.3390/f15081439

AMA Style

Bai X-L, Feng T, Zou S, He B, Chen Y, Li W-J. Differences in Leaf Functional Traits of Quercus rehderiana Hand.-Mazz. in Forests with Rocky and Non-Rocky Desertification in Southwest China. Forests. 2024; 15(8):1439. https://doi.org/10.3390/f15081439

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Bai, Xiao-Long, Tu Feng, Shun Zou, Bin He, Yang Chen, and Wang-Jun Li. 2024. "Differences in Leaf Functional Traits of Quercus rehderiana Hand.-Mazz. in Forests with Rocky and Non-Rocky Desertification in Southwest China" Forests 15, no. 8: 1439. https://doi.org/10.3390/f15081439

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