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Article

Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures

by
Yuhua Ma
1,
Fengyu Xu
1,2,
Jingya Wei
1,
Wei Wang
1,
Zhen Wu
3,
Duanyang Xu
1,
Fasih Ullah Haider
4,
Xu Li
4,* and
Yan Dong
5,*
1
College of Civil and Architecture Engineering, Chuzhou University, Chuzhou 239000, China
2
Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
3
College of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China
4
Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
5
College of Biology and Food Engineering, Chuzhou University, Chuzhou 239000, China
*
Authors to whom correspondence should be addressed.
Forests 2024, 15(9), 1642; https://doi.org/10.3390/f15091642
Submission received: 16 August 2024 / Revised: 11 September 2024 / Accepted: 15 September 2024 / Published: 18 September 2024
(This article belongs to the Special Issue Ecological Dynamics of Tropical Forests: Structure, Species Richness and Regeneration)
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Abstract

:
Ecological restoration and biodiversity are currently hot issues of global environmental concern. However, knowledge about the specific impacts of restoration duration on understory vegetation diversity remains limited. Therefore, this study comprehensive employed a spatial approach to compare the differences in understory plant diversity and species composition among secondary forests with varying ecological restoration ages (0, 10, 30, 60, and 90-year-old stands) in Huangfu Mountain National Forest Park. This methodology allowed us to clarify the key factors affecting the composition of the understory plant community and investigate the regulatory mechanisms influencing changes in understory plant diversity. The results showed that shrub Shannon’s index value, shrub evenness, herb Shannon’s index value, herb richness, and herb evenness were significantly affected by the years of restoration, with 10 years and 90 years being the highest and 60 years being the lowest. Substrate diversity was the main factor influencing plant diversity in the shrub layer. Overstory richness, soil C/N, soil C, soil N, soil bacterial Observed OTUs, soil bacterial Chao1, soil bacterial Pielou_e, and substrate diversity were the drivers of plant diversity in the herb layer. Overstory evenness had a direct effect (0.256) and an indirect effect (0.284) on herb evenness through light availability and fungal Simpson’s index value. Light availability directly negatively affected herb evenness (−0.360). In addition, 52.6% of the factors affecting the herb evenness index were from the arboreal layer evenness, light availability, and fungal Simpson’s index value. To sum up, moderate disturbance of the understory environment of natural secondary forests can be carried out after 10 years of restoration, which is more conducive to the increase of understory plant diversity. This comprehensive study provides a theoretical basis for formulating ecological restoration measures for secondary forests, particularly in understanding the optimal timing and nature of disturbance in the restoration process, reassuring the audience about the validity and reliability of the findings.

1. Introduction

Forest biodiversity is rapidly declining, underscoring the urgent need for ecologists to investigate and address this pressing issue [1,2,3]. Understory vegetation, a major component of plant diversity in forest ecosystems, influences energy flow, nutrient cycling, biodiversity, and regeneration capacity [2,4]. Understanding understory vegetation is crucial to understanding forest ecosystems’ functioning. The stability of plant communities is a comprehensive reflection of community structure and function, reflecting the anti-disturbance ability of forests and the recovery ability of community structure after further disturbance [5]. Therefore, studying community stability can help understand vegetation communities’ current status and succession patterns. With its significant impact on the sustainable development of regional ecology, economy, and society, ecological restoration is exemplified by China’s natural forest restoration project, the world’s only large-scale ecological construction project focusing on protecting natural forest resources [6,7]. China’s impressive achievements in this project protect precious natural forest resources and promote ecological environment improvement and sustainable economic and social development for forested areas.
Changes in vegetation and environment often accompany ecological restoration processes. As the number of years of restoration increases, the structure of tree species changes considerably, and forest structure is a key factor influencing seedling survival and species diversity of understory plants [8]. The forest structure, microenvironment, and stand conditions created by the upper tree species determine the composition, structure and distribution pattern of understory plants with heterogeneity [9]. With the increase of restoration years, due to the long-term lack of anthropogenic disturbance, the vegetation cover becomes larger, the plant apoplastic residues pooled on the soil surface input a large amount of C to the soil, the organic C reserves increase, coupled with the relatively small soil disturbance during the restoration process, the surface cover is limited, basically only rely on the decomposition of leafy residues in the surface layer of the soil to be converted into organic matter and then replenish the soil, so that soil nutrient reserves are more stable [10,11,12].
Advancing our knowledge of soil micro-environmental dynamics and understory plant diversity is essential for developing effective conservation strategies and promoting ecological restoration. Light, a crucial factor in the growth and development of understory plants during the restoration of forest ecosystems, plays a significant role [13]. Light directly affects plant functional traits, and differences in lower light availability are instrumental in shaping these forest communities [14]. With ecological restoration projects, the density of the forest canopy increases, altering the light conditions of the understory and reducing the potential for photosynthesis of understory plants [15,16]. It is essential to comprehend the dynamic changes of understory plant diversity in natural forests during ecological restoration and the mechanisms that influence understory transformation over time [3].
Natural vegetation restoration is an effective way to improve soil conditions and promote land development. Rapid changes in plant community composition and diversity during vegetation development may be accompanied by changes in soil physico-chemical properties and microbial characteristics [2,3,17]. Microorganisms, as the primary decomposers in terrestrial ecosystems, can acquire resources to build their biomass and influence the flow of ecosystem materials, which can strongly regulate the cycling of carbon and nutrients along the soil-plant-atmosphere continuum, with potential feedback on ecosystem function [18,19]. Vegetation restoration is essentially an interaction between above-ground plants and below-ground microorganisms, and changes in the composition of existing vegetation after restoration can affect microbial diversity and composition [2,3,20]. However, the relative contribution of microbial community factors and soil properties in determining vegetation in restored ecosystems still needs to be clarified.
Plant-soil microbial communities are important components of forest ecosystems. In forest ecosystems, plants influence soil microorganisms as they cycle material and energy with the surrounding environment, altering soil ecology or nutritional status directly or indirectly and affecting soil microbial communities and structures and their ecological effects [17,18]. Soil microorganisms are involved in the decomposition of organic matter, enhance the effectiveness of plant nutrients, improve soil structure and hydrological properties, increase plant productivity and diversity, and play a role in climate regulation and biogeochemical nutrient cycling [19,20]. In turn, soil microorganisms affect vegetation, such as certain mycorrhizal and nitrogen-fixing microorganisms that influence plant growth and others that promote root secretion [21]. Studying the relationship between plant diversity and soil microbial diversity provides a complete theoretical basis for understanding how plant-microbe interactions affect plant diversity and is of great significance for a deeper understanding of the mechanism of action between plants and soil microorganisms, as well as the practice of forest ecological restoration.
Ecological restoration and biodiversity are currently very significant issues of global ecological concern [1,3,10]; however, knowledge about the specific impacts of restoration duration on understory vegetation diversity remains limited. This study, conducted in the Huangfu Mountain National Forest Park, took the natural secondary forests under different ecological restoration years (0, 10, 30, 60, and 90-year-old stands, or 0 a, 10 a, 30 a, 60 a and 90 a stands) as the objective of the research. The study hypothesized that improved environmental conditions would increase understory plant diversity with longer restoration duration. The study compared the differences in understory plant community characteristics among different ecological restoration years, clarified the key factors affecting the understory plant community characteristics, and focused on exploring the driving mechanism regulating the changes of understory plant diversity in natural secondary forests. These findings provide a theoretical basis for the ecological restoration of the natural secondary forests and the conservation of biodiversity and offer hope for the future of our forests and ecosystems.

2. Materials and Methods

2.1. Study Area

Huangfu Mountain National Forest Park’s unique location on the northern edge of the subtropical humid monsoon climate zone offers a fascinating study area. It experiences summer rain and heat simultaneously, with warm and dry winters and abundant sunlight throughout the year. The average annual temperature is 14.3 °C; the average annual precipitation is 939–1031 mm; the inter-annual variation of precipitation is significant; the annual precipitation distribution is not uniform, mostly concentrated in June to August, and the average annual relative humidity is 80%–85%. The year-round dominant wind direction is easterly, mostly southeasterly in summer and northwesterly in winter.
The area has been subject to long-term degradation due to disturbances such as deforestation and overgrazing. However, significant efforts have been made to restore forest biodiversity. These efforts include implementing natural forest protection measures, such as installing woodland fencing nets. As a result, the area now hosts a variety of plant species including Quercus acutissima, Zelkova serrata, Acer buergerianum, Lindera glauca, Acer tataricum and Trachelospermum jasminoides.

2.2. Sampling Design

Using a spatial instead of temporal approach, natural secondary forests with similar stand conditions and recovery years of 10, 30, 60, and greater than 90 years (denoted as 90 a) and anthropogenically disturbed natural secondary forests (denoted as 0 a) were selected as the study objects, with the area of the forest stand varying from about 3 to 10 ha for each recovery year (Figure 1) [3]. Three 20 m × 20 m sample plots were selected in each natural secondary forest stand representing different ecological restoration years, and the sample plots were required to be far away from the forest edge (Table 1). To mitigate spatial autocorrelation and minimize sampling subjectivity, we employed stratified random sampling, which is essential for any statistical test to make inferences about the population of interest [3]. Initially, we utilized forest history survey data to identify all available stands (with stand identification numbers) for each age class (i.e., the sampling frame). Subsequently, we utilized a random number generator in Microsoft Excel 2023 (and R studio, version 4.2.3) to match random numbers with standard numbers in the database. The matched stands were selected as candidate stands for sampling.

2.3. Field Measurements

We set up 20 m × 20 m sample plots within each survey area using random sampling [3,11,12]. The sample plots were chosen to avoid the edge effect of the forest floor. The sample plots’ topography, latitude and longitude, elevation, slope direction, and slope gradient were also recorded. The species, number, height, and diameter at breast height of tree layer plants (tree height ≥ 4 m) in the sample plots were documented and used 5 m × 5 m squares sub-plot within the sample plot and surveyed shrub layer (1.3 m ≤ tree height < 4 m) with detailed information. Similarly, we set up ten small sample plots of 1 m × 1 m in each sample plot, surveyed herb layer plants (tree height < 1.3 m), and recorded details of the species [11,12,22]. These data were used to determine the plant diversity index.
Within each herb sample plot, at 1.3 m height, percentage canopy openness (approximating the percentage of the sky portion not covered by leaves) was measured using a spherical densitometer in each direction (North, South, East and West), as suggested. The mean (LM) of the canopy openness was measured in each sample to represent the average light availability, and standard deviation (LSD) was used to describe the value of light heterogeneity (Light variability) [3,10,23]. Within each 20 m × 20 m sample plot, the percentage cover of aboveground bare rock, apoplastic material, exposed soil, upturned rooted soil, and fallen coarse dead wood debris was estimated and calculated using the formula for Shannon’s diversity index, which was used to obtain the substrate diversity index (SubD to assess the heterogeneity of the soil matrix) (Equation (1)).
SubD = −∑(Pi·lnPi)
In the sample plot, Pi is the percentage of total heterogeneous cover of bare rock, apron, exposed soil, upturned rooted soil, and fallen coarse dead wood debris.
Within each 20 m × 20 m sample plot, we randomly selected 3–5 sample points, and after removing the top layer of material, soil samples were collected with a ring knife at 0–20 cm on the left side of the soil profile, and obtained mixed soil samples divided into two samples. One part of the mixed soil samples was quickly placed in an insulated box with dry ice to determine soil microbial diversity. The other part of the mixed soil samples was stored at room temperature to determine soil water content (SWC), pH and carbon (C) and nitrogen (N) elements. The procedures for measuring SWC, soil pH, C, N and soil microbial diversity were based on the methodology described by Ma et al. (2021) and Zhou et al. (2023) [23,24].

2.4. Data Analysis

We utilized one-way variance analysis (ANOVA) to assess shrub-herb layers’ environmental factors and plant diversity. Post hoc tests were applied to identify significant differences between groups, and Bartlett and Shapiro tests were performed to validate assumptions associated with chi-square and normality.
Furthermore, multivariate techniques such as permutational multivariate analysis of variance (PerMANOVA) are used to assess the effect of restoration years on shrub-herb layer plant communities. To visualize species composition data and evaluate community structure in uneven forest stands, Nonmetric Multidimensional Scaling (NMDS) was applied. To identify indicator species in different restoration-year forests, we applied the “indicator species” package. Using the Godron Stability Measurement Method, we measured community trends based on species composition through quadratic fitting to assess community stability [3].
We left no stone unturned in assessing the relationship between plant communities and environmental variables. We explored tree layer diversity, soil properties, and bacterial/fungal diversity. The envfit function in the “vegan” package was applied, and we generated NMDS ordination plots with environmental variable projections to show correlations. Finally, we explored the effects of key factors on plant diversity using correlation analysis and constructed a structural equation model (SEM) using the “lavaan” package. These complete analyses were performed in R (version 4.2.3).

3. Results

3.1. Effects of Years of Ecological Restoration on Understory Plant Diversity in Natural Secondary Forests

The findings of our study revealed that shrub Shannon’s index (p = 0.042), shrub evenness (p = 0.019), herb Shannon’s index (p = 0.002), herb richness (p = 0.027) and herb evenness (p = 0.005) were significantly affected by restoration years (Figure 2). Shrub Shannon’s index, herb Shannon’s index, herb richness and herb evenness were higher at 10 a and 90 a of restoration and lower at 60 a of restoration compared to other restoration years. Shrub evenness was lowest at 60 a.

3.2. Effects of Years of Ecological Restoration on the Composition of Understory Plant Communities in Natural Secondary Forests

The findings of the study revealed significant differences in the plant species composition of both the shrub layer (p = 0.001) and herb layer (p = 0.001) at different restoration years (Figure 3). The species composition of the shrub layer of natural secondary forests restored at 30 a, 60 a and 90 a can be well separated from those without ecological restoration and restored at 10 a in the sorting space, which produces an obvious separation effect. The restoration of 30 a and 60 a overlaps with restoration of 90 a, suggesting that they share the same species, fostering a sense of connection to the natural process of restoration. Similarly, the species composition of the herb layer of natural secondary forests restored at 0 a, 10 a and 60 a were well separated from those restored at 30 a and 90 a in the sorting space, which produces an obvious separation effect. The herb layer of natural secondary forests in restoration 30 a and 90 a overlapped, further emphasizing the shared species in the restoration process.
From Figure 4, the simulation curve for the restoration 10 a plant community is y = −0.0105x2 + 1.64x + 37.2 (d = 9.34); the simulation curve for the restoration 30 a plant community is y = −0.0127x2 + 1.85x + 34.5 (d = 8.48); and the simulation curve for the restoration 60 a plant community is y = −0.0059x2 + 0.85x + 70.5 (d = 4.45). This indicates that the community of restoration 60 a is the most stable; the plant communities of restoration 10 a and restoration 30 a are less stable.
The analysis results of indicator species showed that in the early stage of recovery, the herb layer was mainly occupied by tree seedlings like Zelkova serrata (IndVals = 0.969, p = 0.009) and Oplismenus undulatifolius (IndVals = 0.664, p = 0.018), as well as the vine plant, Trachelospermum jasminoides (IndVals = 0.605, p = 0.030). After 10 years of recovery, the herb layer was transformed, now dominated by sunny perennial herb plants like Agrimonia pilosa (IndVals = 1.00, p = 0.017) and Stephania japonica (IndVals = 1.00, p = 0.017), as well as the annual herb plant, Trachelospermum jasminoides (IndVals = 1.00, p = 0.017). After 30 years of recovery, the shrub layer became more supportive, fostering the growth of warm and humid small seedlings like Alangium chinense (IndVals = 0.972, p = 0.023) and Persicaria filiformis (IndVals = 0.845, p = 0.040), while the herb layer also supported the warm and humid perennial fern plant, Cyrtomium fortune (IndVals = 0.803, p = 0.048). This highlights the intricate and complementary roles of the herb and shrub layers in supporting different species as the recovery period increases. As the recovery period increases, the positive tree species that prefers light, Lindera glauca (IndVals = 0.761, p = 0.014), becomes the indicator species for restoring the 60 year shrub layer. The indicator species for the herb layer are the light-loving plants Commelina communis (IndVals = 0.944, p = 0.011) and Certataricum subsp. Ginnala (IndVals = 0.920, p = 0.022) (Table 2). After 90 years of restoration, the indicator species for the shrub layer are the light tolerant and barren mulberry plant, Maclura tricuspidata (IndVals = 0.920, p = 0.022), and the rose family plant, Rubus idaeus (IndVals = 0.778, p = 0.013), while the herb layer lacks indicator species.

3.3. Effects of Years of Ecological Restoration on the Environmental Factors in Natural Secondary Forests

The study found that overstory stand basal area, overstory species richness, soil bacterial Observed OTUs, soil bacterial Chao1, light availability, soil carbon, soil nitrogen, and soil carbon to nitrogen ratio (C/N) were significantly influenced by different restoration years (Figure 5). These findings have significant implications for the field of ecology and environmental science, as they highlight the complex and dynamic nature of ecological restoration. Notably, soil C/N was highest at 10 a of restoration, with overstory stand basal area, soil C, and soil N being lowest. In contrast, at 60 a of restoration, overstory stand basal area, overstory species richness, soil C, soil N, and light availability were highest, and soil bacterial Observed OTUs, bacterial Chao1, and bacterial Pielou evenness index values were lowest.

3.4. Multiple Relationships between Plant-Microbe-Environmental Resource Availability and Heterogeneity in Ecological Restoration Processes

The results of the redundancy analysis (Figure 6) showed that substrate diversity was a key factor influencing plant community composition in the shrub layer. Overstory richness, soil C/N, soil C, soil N, soil bacterial Observed OTUs, soil bacterial Chao1, soil bacterial Pielou evenness values, and substrate diversity were key influences on plant community composition in the herb layer. The results of structural equation modelling showed that overstory evenness had a direct effect (0.256) and an indirect effect (0.284) on herb evenness through light availability and fungal Simpson’s index. Light availability directly negatively affected herb evenness (−0.360). A significant 52.6% variation affecting herb layer uniformity came from overstory layer uniformity, light availability, and fungal Simpson’s index (Figure 7). These findings have practical implications for understanding and managing plant communities in ecological systems.

4. Discussion

Years of ecological restoration significantly affected shrub cover and richness, herb evenness, Shannon’s index (a measure of species diversity in a community) of the herb layer, and understory species composition [3,25,26]. The species composition of the shrub layer was significantly different in natural secondary forests restored for 10 a, 30 a, 60 a and 90 a. The Shannon index and richness of the shrub layer were higher in the restored 10 a sites. They restored 90 a stands more than in the other restoration years. They were lowest in the restored 60 a stand, and shrub evenness was lowest in the restored 60 a stand, and Shannon index, richness, and evenness of the herb layer reached the highest in the restored 10 a and 90 a stands and were lowest in the restored 60 a stand (Figure 2). These findings were consistent with previous studies of understory restoration, in which species richness of the understory shows a cyclical fluctuating trend of increasing, then decreasing, and then increasing again [3,27]. This may be because, before 10 a of restoration, the upper stand had low depression and sufficient light, leading to the rapid growth of light-loving shrub plants in the understory and a rapid increase in shrub cover and species diversity of understory plants [9,28]. The slight decrease in herb cover and increase in species diversity in the understory after 10 years of restoration may be because of limited resource availability (e.g., light and light transmission) was filtered by the upper trees and shrub plants, and sun-loving herb plants began to decrease, reducing the strength of the positive diversity effect of the understory plants, since the positive diversity effect is primarily a result of the increase in resource utilization [29,30]. The results of the change in light availability mentioned above confirmed this point.
The plant community stability from 10 a to 30 a of restoration was at its lowest, aligned with the findings of the Huang et al. (2023) [5] study on the community stability of natural forests. This decrease in stability may be attributed to the more intense competition in the pre-restoration period [31,32]. In the 60 a of restoration, the species richness of the tree layer was at its highest, but the evenness was very low. Reduced stand depression, increased understory light, and the highest soil C and N content led to increased competition for living space and nutrients among plants, eliminating some sun-loving plants. On the other hand, the forest was not fully depressed, and the shade-tolerant plants could not grow stably, leading to decreased species richness in the understory [2,3,25,33]. In restoration 90 a, the substrate diversity increased due to the gradual accumulation of apoptotic and coarse woody residues, and some warm and humid shrub-loving plants appeared. The understory plant composition structure was gradually complicated, increasing species diversity and evenness in the shrub layer and herbs [26,34]. These findings have significant implications for ecology, particularly in understanding the dynamics of plant communities in restored ecosystems.
Soil nutrient content is an important indicator of forest soil quality, which is significant for setting up and managing secondary forests. In this study, the duration of forest closure had a significant effect on soil C and N as well as soil C/N, which is consistent with the findings of previous studies [3,11,12]. This may be because the litter increased with the duration of forest closure, and the decomposition of litter increased nutrients in the soil [12]. Soil C/N, soil C, soil N, and substrate diversity were identified as the key factors influencing plant diversity in the herb layer, aligning with the findings of Ma et al. (2024) [3]. The elements of soil C and N, along with substrate diversity, provided favorable conditions for the growth and reproduction of understory plants in the early stage of restoration. However, as the number of inter-specifics increased, competition for these elements intensified, decreasing plant diversity in the understory. The results of soil C, N, and C/N changes further confirm the importance of soil C/N in influencing plant diversity. In conclusion, soil C/N emerges as the driving factor of understory plant diversity, highlighting its crucial role in comprehensively describing the spatial variation characteristics of soil C and N and accurately analyzing the factors influencing the diversity of understory plants [3,32,35].
As a basic condition for plant growth and development, soil’s physical and chemical properties can directly reflect its physical structure and nutrient status, directly or indirectly affecting plant growth and development and their diversity [3,32,35]. The correlation results showed that understory plant diversity was significantly positively correlated with soil environmental factors. It is indicated that soil nutrient content greatly influences understory plant diversity. Redundancy analysis showed that soil pH, C, soil N, C/N, and light availability were the driving factors of understory plant diversity. Among them, soil C content showed an overall increasing trend with increasing forest age, which agreed with the findings of Liu et al. (2023) [29], and contrasted with those of Zhang et al. (2017) [14]. This was attributed to the different characteristics of litter accumulation in different stand types, which affected soil C transformation and accumulation. Soil N content generally increased with ecological restoration, with a slight decrease in the 90 a forest stands. This might be because some understory plants were in a period of rapid growth, which resulted in a strengthened consumption of soil N. The soil N content of plantations was also significantly correlated with soil C content, with a slight decrease in the 90 a stands.
In this study, it was found that as the duration of forest closure increased, the uniformity of vegetation in the tree layer increased, which decreased the light availability, which in turn led to a negative effect of light availability on the uniformity of herbaceous plants, which is in line with the results of previous studies. The evenness of the overstory layer significantly increased with the duration of forest closure by increasing the fungi Simpson’s index, which in turn increased the evenness of plants in the herbaceous layer. This may be because fungi’s increased diversity accelerates apoplastic material’s decomposition, increasing soil resources available to herbaceous plants [12,23]. Soil microbes are drivers of plant diversity and productivity in terrestrial ecosystems [36]. Studies on the factors affecting microbial drivers can help us understand the soil microbial maintenance mechanism after forest closure. Therefore, in this study, the multivariate relationships among plants, soil microorganisms and environmental resources were analyzed by structural equation modelling, and the results showed that the area of tree breast height breaks could not only directly affect bacterial diversity but also indirectly through soil carbon to nitrogen ratio and understory shrub cover. Compared to herbaceous plants, woody plants have a greater impact on soil fungal communities because plant species differ in the amount and type of nutrient inputs to the soil [37], which in turn leads to changes in the microbial community structure and diversity of the soil. Previous studies have shown that soil fungal abundance is positively correlated with tree and shrub species richness [38], and the same results were obtained in this study, where we found that Simpson’s abundance of soil fungi was positively correlated with tree species evenness. This may be due to the large lignin content in woody debris, mainly decomposed by fungi, and the symbiosis of ectomycorrhizal fungi with woody plants [39]. These findings have practical implications for understanding and managing plant communities in degraded forest ecosystems.
The study compared the differences in understory plant community characteristics among different ecological restoration years, clarified the key factors affecting the understory plant community characteristics, and focused on exploring the driving mechanism regulating the changes of understory plant diversity in natural secondary forests. These findings provide a theoretical basis for the ecological restoration of the natural secondary forests and the conservation of biodiversity and offer hope for the future of our forests and ecosystems. In addition, the findings of this study also serve as a valuable reference for forestry departments to formulate future planning strategies and propose practical recommendations to enhance forest health and promote sustainable ecosystem management.

5. Conclusions

The current study has shown that the natural secondary forest exhibits the highest understory plant diversity at 10 a and 90 a of restoration, gradually declining at 60 a. This decline can be attributed to the moderate disturbance observed after 10 a of restoration, which is conducive to reducing the cost of forestation and increasing understory plant diversity. As an integral component of the forest ecosystem, understory vegetation plays a pivotal role in maintaining the stability and productivity of the forest ecosystem. The change in the understory plant community resulting from different years of ecological restoration represents a crucial link in our understanding of plant succession in subtropical natural secondary forests. Moreover, it is a key factor in predicting the ecosystem response to ecological restoration. These findings enhance our understanding of forest ecology and inspire the development of practical ecological restoration measures in natural secondary forests.

Author Contributions

Conceptualization, Y.M., Y.D., F.U.H. and X.L.; methodology, Y.M., J.W. and X.L.; software, Y.M.; validation, X.L., F.X. and Z.W.; formal analysis, Y.M., F.X. and W.W.; investigation, Y.M., J.W., F.X. and D.X.; data curation, Y.M.; writing—original draft preparation, Y.M., F.U.H. and F.X.; writing—review and editing, Y.M., Y.D. and X.L.; supervision, X.L.; project administration, Y.M.; funding acquisition, Y.M. and Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Provincial Forestry Research and Innovation Research Project of Anhui “Research on Forest Plant Diversity Restoration Techniques”, the Outstanding Young Research Project of Universities and Colleges of Anhui Provincial Department of Education (2022AH030110), Anhui Province University Natural Science Research Foundatio(2024AH051402, 2022AH051123) and the Natural Science Foundation of China (42307055).

Data Availability Statement

Data will be made available on request.

Acknowledgments

We thank Tao Huang, Xiaoxiang Hou, Qiying Sun, Rui Hua, Yangyang Chen and Xingyu Zhu for their assistance in the field and laboratory.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location of sample sites.
Figure 1. Location of sample sites.
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Figure 2. Effects of different years of ecological restoration on understory plant diversity. Note: All data are presented as the mean ± SE (n = 3). Values for boxplots are medians, 75% observations in boxes, and whiskers above and below the box indicate 95th and 5th percentiles. Different letters indicate significant differences between different restoration years (p < 0.05). Different lowercase letters indicate the significance of different ecological restoration years at the 0.05 level.
Figure 2. Effects of different years of ecological restoration on understory plant diversity. Note: All data are presented as the mean ± SE (n = 3). Values for boxplots are medians, 75% observations in boxes, and whiskers above and below the box indicate 95th and 5th percentiles. Different letters indicate significant differences between different restoration years (p < 0.05). Different lowercase letters indicate the significance of different ecological restoration years at the 0.05 level.
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Figure 3. Species composition of understory plants in natural secondary forests with different years of ecological restoration. Note: Ellipses represent the standard error of the score-weighted mean corresponding to different restoration years.
Figure 3. Species composition of understory plants in natural secondary forests with different years of ecological restoration. Note: Ellipses represent the standard error of the score-weighted mean corresponding to different restoration years.
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Figure 4. Changes in vegetation community stability under different years of ecological restoration. Note: (a–e): Community stability in 0, 10, 30, 60, 90 years of restoration, R2: goodness of fit, (d): Euclidean distance between the intersection coordinates of the community stability model (x, y) and the ideal stability coordinates (20, 80). Yellow line: ideal stable point coordinates; green line: plot stability point coordinates; red line: the fitted curve of the relative frequency of species accumulation to the inverse of the cumulative total.
Figure 4. Changes in vegetation community stability under different years of ecological restoration. Note: (a–e): Community stability in 0, 10, 30, 60, 90 years of restoration, R2: goodness of fit, (d): Euclidean distance between the intersection coordinates of the community stability model (x, y) and the ideal stability coordinates (20, 80). Yellow line: ideal stable point coordinates; green line: plot stability point coordinates; red line: the fitted curve of the relative frequency of species accumulation to the inverse of the cumulative total.
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Figure 5. Effects of different years of ecological restoration on environmental factors. Note: All data are presented as the mean ± SE (n = 3). Values for boxplots are medians, 75% observations in boxes, and whiskers above and below the box indicate 95th and 5th percentiles. Different letters indicate significant differences between forest ages (p < 0.05).
Figure 5. Effects of different years of ecological restoration on environmental factors. Note: All data are presented as the mean ± SE (n = 3). Values for boxplots are medians, 75% observations in boxes, and whiskers above and below the box indicate 95th and 5th percentiles. Different letters indicate significant differences between forest ages (p < 0.05).
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Figure 6. Drivers affecting species composition of understory plants. Note: Overstory Stand basal area (OSBA), Overstory Shannon index (OH), Overstory richness (OS), Overstory evenness (OJ), Soil bacterial Observed OTUs (BO), Soil bacterial Chao1 (BC), Soil bacterial Simpson (BS), Soil bacterial Pielou_e (BP), Soil fungal Observed OTUs (FO), Soil fungal Chao1 (FC), Soil fungal Simpson (FS), Soil fungal Pielou_e (FP), Light availability (LM), light heterogeneity (LSD), substrate diversity (subD), soil carbon (C), soil nitrogen (N), soil carbon to nitrogen ratio (C.N), soil pH (pH) and soil water content (WC). Vector lengths represent correlations (r) between soil bacterial communities and soil properties; red and blue vectors indicate significance p < 0.05 and >0.05, respectively.
Figure 6. Drivers affecting species composition of understory plants. Note: Overstory Stand basal area (OSBA), Overstory Shannon index (OH), Overstory richness (OS), Overstory evenness (OJ), Soil bacterial Observed OTUs (BO), Soil bacterial Chao1 (BC), Soil bacterial Simpson (BS), Soil bacterial Pielou_e (BP), Soil fungal Observed OTUs (FO), Soil fungal Chao1 (FC), Soil fungal Simpson (FS), Soil fungal Pielou_e (FP), Light availability (LM), light heterogeneity (LSD), substrate diversity (subD), soil carbon (C), soil nitrogen (N), soil carbon to nitrogen ratio (C.N), soil pH (pH) and soil water content (WC). Vector lengths represent correlations (r) between soil bacterial communities and soil properties; red and blue vectors indicate significance p < 0.05 and >0.05, respectively.
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Figure 7. Structural equation modeling to analyze the regulatory mechanisms of changes in plant evenness in the herb layer. Note: Orange and gray solid arrows represent significant positive and negative effects (p < 0.05), respectively. Numbers next to the variables represent the variance explained by the model (R2), and numbers on the arrows represent standardized path coefficients.
Figure 7. Structural equation modeling to analyze the regulatory mechanisms of changes in plant evenness in the herb layer. Note: Orange and gray solid arrows represent significant positive and negative effects (p < 0.05), respectively. Numbers next to the variables represent the variance explained by the model (R2), and numbers on the arrows represent standardized path coefficients.
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Table 1. Characteristics (mean ± SD, n = 3) of the study plots in study sites.
Table 1. Characteristics (mean ± SD, n = 3) of the study plots in study sites.
Time Since Closing (Years)LongitudeLatitudeAltitudeCanopy DensityShrubs Layer (%)Herbs Layer (%)Direction
0118°00′35″32°20′14″132.0–145.50.13 ± 0.02 ab19.09 ± 11.33 b21.77 ± 2.68 aSouth
10118°00′26″32°20′33″171.7–187.40.07 ± 0.07 bc34.02 ± 7.02 ab19.84 ± 6.71 aSouth
30118°00′29″32°20′39″134.5–182.80.06 ± 0.02 c40.76 ± 20.66 ab20.23 ± 4.27 aSouth
60118°00′36″32°20′06″123.0–135.10.14 ± 0.02 a59.00 ± 30.67 a16.31 ± 3.80 aSouth
90117°59′45″32°19′56″268.3–293.00.05 ± 0.02 c60.04 ± 8.78 a15.61 ± 3.11 aSouth
Note: Different letters indicate a significant difference at α = 0.05 between years since restoration.
Table 2. Indicator species in the understory shrub and herb layers in natural secondary forests.
Table 2. Indicator species in the understory shrub and herb layers in natural secondary forests.
Time Since Closing
(Years)		Indicator SpeciesLife FormsSpecificity SensitivityIndicator Valuep
Shrub layer
30Alangium chinenseShrub0.858810.9720.023
Persicaria filiformisHerb0.714310.8450.040
60Lindera glaucaShrub0.578910.7610.014
90Maclura tricuspidataShrub0.846210.9200.022
Rubus idaeusShrub0.604810.7780.013
Herb layer
0Zelkova serrataTree0.939110.9690.009
Oplismenus undulatifoliusHerb0.440810.6640.018
Trachelospermum jasminoidesVine0.365910.6050.030
10Stephania japonicaVine1.000011.0000.017
Trachelospermum jasminoidesHerb1.000011.0000.017
Agrimonia pilosaHerb1.000011.0000.017
30Cyrtomium fortuneiHerb0.645510.8030.048
60Commelina communisHerb0.890910.9440.011
Certataricum subsp. ginnalaShrub0.845810.9200.020
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Ma, Y.; Xu, F.; Wei, J.; Wang, W.; Wu, Z.; Xu, D.; Haider, F.U.; Li, X.; Dong, Y. Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures. Forests 2024, 15, 1642. https://doi.org/10.3390/f15091642

AMA Style

Ma Y, Xu F, Wei J, Wang W, Wu Z, Xu D, Haider FU, Li X, Dong Y. Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures. Forests. 2024; 15(9):1642. https://doi.org/10.3390/f15091642

Chicago/Turabian Style

Ma, Yuhua, Fengyu Xu, Jingya Wei, Wei Wang, Zhen Wu, Duanyang Xu, Fasih Ullah Haider, Xu Li, and Yan Dong. 2024. "Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures" Forests 15, no. 9: 1642. https://doi.org/10.3390/f15091642

APA Style

Ma, Y., Xu, F., Wei, J., Wang, W., Wu, Z., Xu, D., Haider, F. U., Li, X., & Dong, Y. (2024). Ecological Restoration Increases the Diversity of Understory Vegetation in Secondary Forests: An Evidence from 90 Years of Forest Closures. Forests, 15(9), 1642. https://doi.org/10.3390/f15091642

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