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Article

Patterns and Driving Mechanism of C, N, P Ecological Stoichiometry in Plant-Litter-Soil Systems of Monoculture and Mixed Coastal Forests in Southern Zhejiang Province of China

by
Binghui Bao
1,†,
Xiaoling Huang
2,†,
Haidong Xu
3,
Hongtao Xie
2,* and
Xiangrong Cheng
4,*
1
College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China
2
Jiyang College, Zhejiang A&F University, Hangzhou 311800, China
3
Shandong Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Binzhou University, Binzhou 256603, China
4
East China Coastal Forest Ecosystem Long-Term Research Station, Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2023, 14(7), 1306; https://doi.org/10.3390/f14071306
Submission received: 23 April 2023 / Revised: 30 May 2023 / Accepted: 19 June 2023 / Published: 26 June 2023
(This article belongs to the Section Forest Ecology and Management)
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Abstract

:
Mixed forests are usually associated with higher resource utilization compared to the corresponding monocultures; however, the tree mixing effects of carbon (C), nitrogen (N), phosphorus (P) ecological stoichiometry in coastal forest ecosystems remains largely unknown. We compared the C, N, P stoichiometry in different ecosystem components (i.e., canopy layer, herb layer, litter layer, 0–20 cm and 20–40 cm soils) among two monocultures (Casuarina equisetifolia and Eucalyptus saligna) and their mixture in Taizhou, Zhejiang province, China. We also assessed the effects of the main microhabitat factors (wind speed, soil salinity, soil moisture and pH) on C, N, P stoichiometry. Two monocultures and their mixture showed the same elemental pattern of “low C and high P” for both the canopy and herb layers, and soil, indicating evident N limitations; however, the mixture intensified the N deficiency more. The mixture showed stronger correlations among the C, N, P stoichiometry than the monocultures. Redundancy and hierarchical partitioning analysis showed the overall and independent effects of the microhabitat factors on the C, N, P stoichiometry separately, in which soil moisture presented more effects on shallow soil (20–40 cm) C, N, and P, while soil salinity mainly affected the herb and litter layers; wind speed had greater effects on canopy layer C, N, P stoichiometry. These results are expected to provide a management reference for the regeneration of degraded plantations in the southern Zhejiang province of China.

1. Introduction

Carbon (C), nitrogen (N) and phosphorus (P) are fundamental chemical elements of the terrestrial ecosystem and participate in many physiological and ecological processes of the plant−litter−soil system [1,2]. C is the main constituent element of plants, while N and P mainly limit plant growth, affecting productivity and ecosystem functions [3]. Ecological stoichiometry addresses the mass balance of multiple nutrient elements at scales from organs to ecosystems; thus, it can be used to evaluate the quantitative relationships among the C, N, and P elements in the ecological process and estimate the nutrient limitation state [4]. A growing number of studies have evaluated the stoichiometric relationships of the C, N, and P elements in farmland, steppe, forests, and other ecosystems, but the results were barely consistent [5,6,7]. Generally, ecosystems tend to maintain relatively stable C:N:P ratios owing to stoichiometric homeostasis, but the C:N:P ratios might be changed by anthropogenic or natural disturbances, such as artificially converting monocultures into mixed plantations or natural succession [8,9,10].
Mixed plantations have been shown to capture limited resources due to canopy stratification and functional complementarity [11,12]. For example, in mixed stands, N fixing species mainly utilize atmospheric N, resulting in less competition among non-N2-fixers for soil N, while increased soil available N was negatively associated with soil available P; thus, affecting N and P utilization and N:P stoichiometry [13,14]. However, it remains poorly understood if mixed forests have advantages over monocultures on C sequestration and N, P accumulation in ecosystems that are frequently disturbed, such as coastal forest [15,16]. In addition, analyzing the driving factors of ecological stoichiometry is also a hotspot considering the accelerating global changes, since climatic variations, geographical conditions, soil properties and plant functional traits all have potential impacts on the ecological stoichiometry of C, N, and P nutrients in forest ecosystems; for instance, the temperature-plant physiological hypothesis proposes that low temperature facilitates higher concentrations of leaf N and P [17]. While on the Loess Plateau of north China, leaf N:P ratios increased with increasing latitude and decreasing mean annual temperature [18]. Eventually, the variations of C, N, P stoichiometry are coupled with plant primary production, respiration, and organic matter decomposition [19,20,21].
In different ecosystem components, i.e., plants, litter and soil, C, N, and P nutrients are closely related. Specifically, soil C, N, and P contents have critical impacts on the regional vegetation type and plant growth, while vegetation affects the soil nutrients through litter input and root exudates and vice versa [4,22]. Naturally, C, N, and P elements circulate continuously between the atmosphere, biosphere, and lithosphere, in which plant leaves fix C through photosynthesis, and return C to the soil through litter; soil N and P are absorbed by plants through the roots, and then return to the soil with litterfall, creating a complete cycle [23,24,25]. Established studies have focused on the C:N:P stoichiometric characteristics of various ecosystems; however, few have quantified the ecological stoichiometry of the plant−litter−soil system in coastal shelterbelt forests, despite how more complicated relationships could be expected due to the harsh stand conditions and frequent disturbances in coastal habitat [26,27]. Geographical and climatic conditions generally have strong impacts on C, N, P cycling, but microhabitats are also critical driving forces, even though their driving processes and the underlining mechanisms may vary between different communities [28,29].
Coastal shelterbelt forests are one of the typically vulnerable ecosystems located at the land−sea transition zone, characterized by strong wind, high salinity, and infertile soil, which are also the major stress factors affecting tree growth and nutrient absorption in coastal forests, especially on the C cycle and available N [30]. However, these forests have played significant roles in safeguarding the economic and social security of coastal regions, in addition to enriching the regional forestry resources and improving human settlements [31]. In recent decades, the coastal forests of subtropical China have been degrading in both stand quality and soil nutrient accumulation due to the degeneration of large areas of monocultures that were afforested 20~30 years ago, and which are badly in need of regeneration. On the other side, establishing mixed forests has been encouraged by many forest policies as a way to provide wider ranges of ecosystem services and to increase stability against climate change, compared to monocultures [32,33]. However, the overall proportion of mixed coastal forests is still well below expectations in eastern China, and the established principles for tree species mixing and forest types allocation have remained inadequate up to now [34,35]. To enhance the overall multifunctionality of coastal forests in China, more mixed forests have been afforested, and the previously dominant monocultures have been gradually converted into mixed forests [30].
The nature of tree species mixing is mutual ecological adaptation, i.e., tree species are not only affected by their surrounding environment but also by intraspecific and interspecific relationships, affecting the exchange and recycling of nutrients [36]. Effective tree species configuration promotes not only the virtuous cycle of nutrients but also forest productivity and ecosystem services [37,38]. However, comparative studies on the ecological stoichiometry characteristics of the C, N, and P elements in different coastal forests are still rare, especially between monocultures and mixtures. Therefore, we selected three coastal forests (i.e., Casuarina equisetifolia monoculture, Eucalyptus saligna monoculture, and their mixture) that are prevailing in the southern Zhejiang province to analyze the C, N, and P contents and their stoichiometry in the plant−litter−soil systems (canopy layer, herb layer, litter layer, 0–20 and 20–40 cm soil layer). We also explored the impact of major microhabitat factors (soil moisture, pH, salinity, and wind speed) on C, N, P stoichiometry in the coastal forest ecosystem. Our overall aim was to clarify the pattern and driving mechanism of C, N, P ecological stoichiometry in different coastal forests of subtropical China, the results will be helpful to reveal the C, N, and P nutrient status and provide a management reference for the regeneration of degraded coastal plantations in the southern Zhejiang province of China. Specifically, we hypothesized that: (1) mixed coastal forests have advantages over monocultures on C sequestration and N accumulation in above-ground plants; (2) coastal forest ecosystems are mainly limited by N, and tree mixing would exacerbate the nutrient’s limitation; and (3) wind speed and soil salinity are more important contributors impacting the C, N, P stoichiometry of plant−litter−soil systems in coastal forests. These results are expected to reveal the C, N, and P elemental patterns and their driving mechanism in the coastal ecosystem and may provide references for the management and strategy optimization of coastal forests.

2. Materials and Methods

2.1. Study Area

The study was conducted along the coast of Taizhou City, Zhejiang Province (121°08′–121°15′ E, 28°19′–28°21′ N) (Figure 1). A geographically muddy area that belongs to the subtropical marine humid climate zone with an elevation of 4.5 m above sea level. The average annual temperature and precipitation are 17.3 °C and 1649 mm, respectively, and the precipitation has a unimodal distribution pattern between June and October. The average relative air humidity is about 90%. Soils are mainly Oxisol in this area with high salinity, low organic matter and a deficient retention ability of moisture and nutrients. The canopy vegetations are prevailingly plantations with ages around 15–20 years, forming coastal forest shelterbelts that are 20–50 m in width along the coast. The main tree species and shrubs include Casuarina equisetifolia, Eucalyptus saligna, Robinia pseudoacacacia, Sapium sapium sebiferum, Taxodium ascendens, Sapindus mukorossi, Ligustrum compactum and Nerium indicum; the understory herbs are all naturally regenerated with little human disturbance.

2.2. Experimental Design

We used a triplet approach to select two monoculture coastal forests and their mixture, namely C. equisetifolia monoculture, E. saligna monoculture, and C. equisetifolia-E. saligna mixture, which are prevailingly dominant in southern Zhejiang, to compare their C, N, P stoichiometry. Non-forested lands in adjacent areas were treated as the control to assess how these afforested trees changed the plant−litter−soil system. The tree species composition and stand characteristics of each coastal forest and the non-forested land are shown in Table 1. Six sites were randomly selected in the study area upon prior surveys (Figure 1). In each site, four 20 m × 20 m plots (representing the three treatments and the control, separately) were set to investigate the canopy layer; we recorded the height, diameter at breast height (DBH) and frequency of each tree species within all the 24 plots. Meanwhile, three subplots (1 m × 1 m) were set in each plot for the herb layer to investigate the richness, height, and coverage of the herb species. The important value (IV) of each herb species was calculated as IV = (relative density + relative frequency + relative coverage). All the plots had the same geographical conditions (i.e., elevation and slope position) to maximize the homogeneity of abiotic environmental factors among them, making the tree species composition the only varying factor. Due to the scarcity of shrubs in coastal forests, no investigation and statistics were made for the shrub layer in this study.

2.3. Sampling Collection and Analysis

Leaf and soil samples were collected on sunny days in August 2020. We collected leaves from all the species in the canopy layer; for each species, five stems were randomly selected to sample mature and fully expanded leaves from four directions (east, west, north, and south) in the upper position of the tree canopy. For the herb layer, only species with the top 50% IVs were sampled to collect leaves from. A total of approximately 100 leaves were collected and mixed to obtain a composite sample using the quadrille method for each species in a plot. Soil samples were taken in each subplot with a quincunx-shaped sampling method. Soil samples of 0–20 cm and 20–40 cm were collected using a stainless soil auger (5 cm in diameter) and mixed into one compound sample, respectively. Litter samples were collected in November, fresh litter was collected in each subplot by species with three litter traps (1 × 1 m, 0.1-mm gauge). In non-forested lands, we took only stratified soil samples and leaf samples for the herb layer. All the leaf and litter samples were returned to the lab and dried at 65 °C to constant weights while the soil samples were air dried. All the samples were ground and screened using a 100-mesh sieve before the chemical analysis. The C and N contents of the samples were determined using an elemental analyzer (EURO Vector EA 3000, Milan, Italy), and the P content was determined using the molybdenum antimony anti-colorimetric method [39].

2.4. Microhabitat Factors

We measured the microhabitat factors that were greatly important to the growth of coastal forests, including wind speed, soil moisture, soil saltness and pH. Geographical factors, such as the slope, aspect, and altitude, and climatic factors such as temperature and precipitation, were not considered in this study because there were barely significant differences among the plots. Wind speed was measured with an anemometer from 9:00 a.m. to 16:00 on sunny days at 1.5 m height on the center point of each 20 m × 20 m plot for five consecutive days. Soil saltness, pH and moisture were measured with a soil nutrient tachometer (ST-TR02, Qingdao, China) at depths of 10 cm and 30 cm, separately, in each subplot and their mean value was used to represent the plot.

2.5. Data Analysis

The C, N, and P contents in the canopy layer, herb layer and litter layer of different coastal forests were calculated as the weighted average values of the C, N, and P contents of each species in the plot, with the IV of each species as the weighting factor, separately. The C:N:P ratios were based on the weighted C, N, and P contents. The data normality was evaluated before performing the following statistical analyses. If the data were non-normal, they were log-transformed or square root transformed to improve normality and reduce heteroscedasticity. General linear model (GLM) and multiple comparisons (LSD) were used to compare the differences in C, N, and P contents and their ratios among three coastal forests and different ecosystem components, with the forest type and ecosystem components as the fixed factors, respectively, and plot as a random factor. Pearson correlation analysis was used to evaluate the correlational relationships between the C, N, and P contents and their stoichiometric ratios in different coastal forests. CANOCO 5.0 was used for the redundancy analysis (RDA) to detect the overall effects of the main microhabitat factors on C, N, and P contents and their stoichiometric ratios. Meanwhile, we used the R package “rdacca.hp” to compute the individual explanatory ratio (effect) of each microhabitat on the C, N, and P contents and their stoichiometric ratios in the plant−litter−soil systems of the coastal forests [40]. Statistical analyses were conducted using SPSS 20.0 (IBM, Armonk, NY, USA) and Origin 9.1 (OriginLab, Northampton, MA, USA) with significance levels set at p < 0.05.

3. Results

3.1. C, N, P Contents in Plant-Litter-Soil Systems

Coastal forests had significantly higher C, N, and P contents than non-forested lands in all the ecosystem components. The highest C content for the canopy layer and herb layer were both found in the C. equisetifolia−E. saligna mixture, while the highest litter C content found in the E. saligna monoculture. The C. equisetifolia monoculture had significantly higher soil C contents than the other two coastal forests. The highest N content of the herb and litter layers were found in the C. equisetifolia monoculture, while that of the canopy layer, 0–20 cm and 20–40 cm soil were all found in the E. saligna monoculture. Variations of P content in each component were generally less than that of C and N, and few significant differences were detected except for litter and 0–20 cm soil P among the coastal forests (Table 2, p < 0.05). Among the components, C content was higher in the canopy layer > litter layer > herb layer > 0–20 cm soil > 20–40 cm soil. However, the N and P contents were both higher in the herb layer > canopy layer > litter layer > 0–20 cm soil > 20–40 cm soil.

3.2. C, N, P Stoichiometric Ratios in Plant–Litter–Soil Systems

The C, N, P stoichiometric ratios of coastal forests were significantly different from the non-forested lands. Among them, C:N ratios of components in the C. equisetifolia–E. saligna mixture were either the highest or significantly higher than that of other coastal forests. The highest C:P ratios of the canopy layer and litter layer were found in the C. equisetifolia monoculture, while the E. saligna monoculture had the highest soil C:P for both soil layers; the C. equisetifolia–E. saligna mixture had the highest C:P ratios for the herb layer. The N:P ratios of the herb layer and litter layer in the C. equisetifolia monoculture were significantly higher than in other coastal forests. The decreased plant N:P ratios of the mixture indicated that tree mixing would exacerbate the N limitation. However, the soil N:P ratios were significantly higher in the C. equisetifolia–E. saligna mixture (Table 3, p < 0.05). Among the components, C:N, C:P and N:P in the litter layer were higher than that of the canopy layer and herb layer, while the C:N:P ratios of the soil layers were significantly lower than that of the canopy layer and litter layer.

3.3. Correlations between the C, N, and P Contents and Their Stoichiometric Ratios in Plant–Litter–Soil Systems

Patterns in the correlational relationships of plant, litter and soil C, N, and P contents were different among the coastal forests. In the C. equisetifolia monoculture, the C content of the canopy layer was negatively correlated with the C content of the herb layer, but positively correlated with the C content of 20–40 cm soil. The N content of the canopy layer was positively correlated with the P content and C content in the herb layer, but negatively correlated with the C content in 20–40 cm soil. The P content in the canopy layer was positively correlated with the C content in the herb layer, but negatively correlated with the C content in 20–40 cm soil. In the E. saligna monoculture, the C content of the canopy layer was negatively correlated with the P content in both the canopy layer and herb layer, but positively correlated with the N content in the litter and 20–40 cm soil. The N content of the canopy layer was positively correlated with the C and N contents in the herb layer, separately. The P content of the canopy layer was positively correlated with that of the herb layer, but negatively correlated with the N of the litter layer. In contrast, in the C. equisetifolia−E. saligna mixture, the C content of the canopy layer not only positively correlated with the N content of this layer, but also with the C contents of the herb layer and litter layer. Canopy layer P content was positively correlated with herb layer P, but negatively correlated with litter layer P. Soil N content of the 0–20 cm layer was negatively correlated with that of the 20–40 cm layer. On the whole, the mixture showed stronger correlational relationships among the C, N, and P contents and their stoichiometry (Figure 2, p < 0.05).
Correlations between the C, N, P ratios of plant, litter, and soil were also different among the three coastal forests. In the C. equisetifolia monoculture, positive correlations were observed between the canopy layer C:N and canopy layer C:P, and the soil C:N and C:P of the 20–40 cm layer, separately. Canopy layer C:P had positive correlations with canopy layer N:P, and the soil C:P and N:P of the 20–40 cm layer. There was a negative correlation between C:N and C:P in the herb layer. The soil N:P of the 20–40 cm layer was negatively correlated with herb C:P and litter C:N. In the E. saligna monoculture, the canopy layer C:N was positively correlated with the litter layer C:P, but negatively correlated with the soil C:P of the 20–40 cm layer. There were negative correlations between litter layer C:N and canopy layer C:P and N:P. The soil C:N of the 20–40 cm layer was negatively correlated with herb C:P and N:P, and litter N:P. However, in the C. equisetifolia–E. saligna mixture, the canopy layer C:P and N:P were both correlated with herb C:P, litter C:N:P and the soil C:N of the 0–20 cm layer. Litter C:N was negatively correlated with both C:P and N:P in this layer. The soil C:P and N:P of the 0–20 cm layer were negatively correlated with the soil C:N and C:P of the 20–40 cm layer, while the soil C:N:P of the 20–40 cm layer was mutually positively correlated (Figure 3, p < 0.05).

3.4. Effects of Microhabitat Factors on C, N, P Stoichiometry in Plant–Litter–Soil Systems

Cumulative explanations of the C, N, and P contents and their ratios on axis Ⅰ and axis Ⅱ of the RDA were 96.5% and 96.16%, respectively, in the plant–litter–soil system, which could accurately reflect the overall relationships between the C, N, P stoichiometry and key microhabitat factors. Along the first axis of the RDA, soil moisture and wind speed had strong positive effects on the P content of the herb layer, soil P contents and the C:P ratios in the tree and litter layers. Soil pH had the greatest positive effect on soil C and N contents, as well as the soil C:P and N:P ratios. Along the second axis of the RDA, the salinity content mainly affects the N content of plants and litter, and then affects the N:P ratios (Figure 4A,B). Further hierarchical partitioning analysis revealed the independent effect of microhabitat factors on C, N, and P contents and their ratios; we found that canopy layer C, N, and P was more affected by wind speed while the herb layer and litter layer were both more evidently influenced by soil salinity. Surface soil (0–20 cm) C, N, and P was randomly impacted by the microhabitat factors while shallow soil (20–40 cm) C, N, and P was more obviously affected by soil moisture (Figure 5).

4. Discussion

4.1. C, N, P Ecological Stoichiometry in Monocultures and Mixed Forests

In this study, the C, N, P ecological stoichiometry of plant−litter−soil systems were compared among two monocultures and their mixture. We found that the C. equisetifolia monoculture had higher C, N, and P contents in both the below- and above-ground components, while the C, N, and P contents of the C. equisetifolia−E. saligna mixture were lower than expected, especially when its N and P accumulations were lower than both monocultures, which did not support our first hypothesis. This could be potentially related to the fewer species composition and younger age of our stands, since competition between species decreases when the species number is lower, also when the trees are younger; thus, the principle of complementarity is realized in full measure, and the stereochemical relations of C, N, and P could be changed, subsequently [41]. However, the above results could be a replenishment to the management strategies of mixed coastal forests [42]. However, the C. equisetifolia−E. saligna mixture displayed some potential advantages in plant C sequestration, and the litter decomposition might be quicker than the two monocultures as indicated by the lower litter nutrient contents; this might be conducive to above- and below-ground C cycling. The proposal of the “Redfield ratio” promoted the exploration of the proportional relationships between C, N, and P at different scales of the terrestrial ecosystems [43]. Prior studies showed that the C, N, and P contents of dominant plants in North-South transects of eastern China were 374.1–646.5 g/kg, 8.4–30.5 g/kg and 0.6–6.2 g/kg, respectively, in forest ecosystem [44]. In our results, the dominant plants’ C contents in the canopy layer and herb layer of the three coastal forests were relatively lower, while the N and P contents were within the above range. In addition, compared with the results of the C, N, and P contents in dominant plants in subtropical evergreen broad-leaved forests (C: 472.8 g/kg, N: 19.8 g/kg, P:1.54 g/kg), limited differences were found in leaf C and N contents from this study; however, their P contents were higher than our results [45]. Thus, plants of coastal forests in Zhejiang Province are in an elemental pattern of low C and high P. Moreover, leaf N:P ratios can be used to evaluate the nutrient limitation pattern of plants (N or P). Our results showed that the leaf N:P ratios of the three coastal forests ranged from 10.2 to 11.5, which were far below the average N:P ratio of typical evergreen broad-leaved forest (19.5), and also below the threshold value of the N limit (14.0); therefore, the coastal forests were limited by N availability; meanwhile, the mixed forests showed a decreased N:P ratio in the over-ground layers, indicating that tree mixing would intensify N restrictions in coastal forests, supporting our second hypothesis [46]. This was probably related to the complementary effects among the tree species [47]. In addition, the leaf C:N ranged from 23.2 to 25.9 in this study, which was similar to the results at the global scale (23.8); however, the leaf C:P (252.9–283.8) was obviously lower than the mean value of the global scale (300.9), which originated from the elemental pattern of low C and high P in the coastal forests of this study [48].
The C, N, and P contents of the litter layer have a significant impact on plant nutrient reabsorption and soil nutrient accumulation, which are not only closely related to the identity of canopy tree species but also the microbial decomposition rate and other environmental factors [49]. In this study, the C, N, and P contents in litter layer ranged within 402.3–446.6, 13.4–16.1, and 1.18–1.28, respectively, in which the litter C content was lower, while the litter P content was higher than that of typical evergreen broad-leaved forests in the subtropical region; the litter N content was basically approaching the average level, this was completely consistent with the elemental pattern of canopy layer C, N, and P. Additionally, compared with other types of plantation, the microbial activity in coastal habitats is relatively low due to its high soil salinity, alkalinity and poor nutrients [31]. The C:N:P ratio of litter affects the decomposition efficiency of microorganisms; a C:N ratio less than 40 or a C:P less than 600 indicates that the litter is relatively rich in N and P contents, which will be conducive to its faster decomposition by microorganisms [50]. In this study, the litter C:N and C:P ratios were both obviously lower than the threshold value, indicating that the litter could be decomposed and utilized by microorganisms more quickly; thus, accelerating the nutrients’ turnover and cycling to some extent. Soil C, N, and P are direct nutrient sources for plant growth; in plantations with a stand age of more than 10 years, soil nutrients are mainly affected by the aboveground vegetation type, and the efficiency of litter nutrient return is one of the key factors contributing to soil nutrients [51]. In this study, the soil C content (3.5–13.7 g/kg) and N content (0.28–1.35 g/kg) were both at a lower level, but the soil P content (0.56–0.74 g/kg) was much higher than that of the subtropical Chinese fir plantation [52]. This was consistent with the elemental pattern of low C and high P in the aboveground plants in this study, too.
Among the three coastal forests, the E. saligna monoculture had the highest soil C, and N contents, but the soil P content was not significantly different. Therefore, planting E. saligna could be a good choice to manage soil nutrients in the coastal forests of southern Zhejiang. The soil C and N content decreased greatly with increasing soil depth, while the soil P content had fewer changes, which was consistent with the established results [53]. This is because soil C and N are mainly derived from nutrient return from litter on the surface and in shallow soil, where microorganisms and soil animals are active in migrating the enriched nutrient elements from shallow soil to deeper soil, resulting in lower levels of nutrients in deep soil than in surface soil [54]. However, soil P mainly comes from the long-term differentiation of rocks; the weathering differentiation levels had little difference in the 0–40 cm soil layers [55]. In addition, the soil C:N ratio of this study was higher than the average soil C:N of terrestrial ecosystems in China (11.9), indicating that soil organic matter mineralization was slow in the coastal forest habitat and soil N content was low, which probably resulted from the high salinity and alkalinity of coastal soils, insufficient microorganism quantity, and poor soil enzyme activity, affecting the decomposition of organic matter and the mineralization of nutrients in the study area [29].

4.2. Coupling Relationships of C, N, P in Plant-Litter-Soil System

Plants, litter, and soil are fundamental ecosystem components during C, N, and P cycling, and their coupling relationship greatly impacts vegetation succession and microbes [56]. We found that the C, N, and P contents and their stoichiometric ratios of different layers had complex correlational relationships in the three coastal forests, indicating that the intricate coastal habitats had a huge impact on the stability of the plant−litter−soil relationships. Plants were mainly limited by N in this study, but plant (trees and herbs) N failed to show strong positive correlations with soil N, especially with the 0–20 cm soil N. This was probably because the study was conducted at a community scale, and the differences between the plant species might not be fully reflected at the community level. In the C. equisetifolia−E. saligna mixture, positive correlations were detected between the litter C content and plant C contents, which was consistent with most previous studies, indicating that a mixed forest would benefit litter decomposition better than monocultures [57]. Litter P content showed a significant negative correlation with the canopy layer and herb layer P contents, which conformed to the general process of the P geochemical cycle [58]. Higher litter P contents reflected the low efficiency of P uptake and utilization by plants. Beyond expectation, we found that the C, N, and P contents in plants were showing a clear decoupling trend with that of the surface soil (0–20 cm), this might be related to the soil weathering and erosion caused by persistent strong wind and frequent storm surges in the coastal habitat; deeper soils were more conducive than surface soil to stabilize the nutrients due to less external disturbance [35,59]. These decoupling trends were also found between the C: N: P ratios, especially between the 20–40 cm soil and herb layer, indicating the great impact of coastal habitat on C, N, and P relationships in the plant−litter−soil system. Among the three forest types, mixed forest showed more correlational relationships than the two monocultures between the C, N, and P contents and their stoichiometry, illustrating that mixed forests would accelerate C, N, and P coupling, which might be helpful to improve the availability and utilization efficiency of nutrients [60]. To sum up, the C, N, and P contents and ratios of the ecosystem components in the three coastal forests showed less significant coupling relationships than we expected; however, tree species mixing could be a good way to enhance the coupling relationships between the C, N and P nutrients. Further studies are needed to analyze the C, N, and P coupling relationships at the species scale and to reveal the allocation patterns of the C, N, and P elements among species in coastal forest ecosystems.

4.3. Effects of Microhabitat Factors on C, N, P Stoichiometry

Factors driving the ecological stoichiometric patterns of ecosystem C, N, and P can be categorized into three groups: climatic, geographical and soil properties, and their roles vary in ecosystems [61]. At a stand scale, key microhabitat factors often have a more direct and rapid influence on the nutrient status of the plant−litter−soil system [62]. Therefore, we selected four fundamental microhabitat factors that might greatly impact coastal forests to detect their effects on the C, N, P stoichiometry in this study. The RDA analysis showed the overall effects of the microhabitat factors on the C, N, P stoichiometry, in which soil moisture and wind speed had the most significant effects on herb and soil P stoichiometry; pH had the greatest positive effects on soil C and N stoichiometry; and soil salinity mainly affected the N stoichiometry of plants and litter. In coastal habitats, wind speed is closely related to soil moisture; when wind speed increases, surface soil moisture evaporates quicker, and the change in soil moisture affects the decomposition rate of litter and, subsequently, the release rate of P from litter; thus, changing the soil P content and P related ratios [63]. Since most herbs are annual plants and are sensitive to soil moisture variation; consequently, the leaf P stoichiometry was jointly affected by wind speed and soil moisture in this study [64]. Soil pH affects most soil chemical processes directly or indirectly, dominating interactions such as deposition, dissolution, adsorption, and desorption, as well as all the redox reactions in soil; it also significantly impacts soil nutrient availability [30,65]. In coastal habitats, a strong correlation is presented between the soil pH and salinity; soil with higher salinity generally has a higher pH. We found soil salinity and pH particularly affected the N:P ratios of different ecosystem components, indicating soil salinity and pH’s dominant roles in N and P stoichiometry, since the soil in the study area prominently featured high salinity and strong alkalinity. In addition, we also quantified the separate effects of microhabitat factors on C, N, P stoichiometry, which could further explain the importance of each factor on C, N, and P. It is worth noting that the overall and individual effects of microhabitat factors on the C, N, P stoichiometry could be slightly different in this study, which basically resulted from the different calculating principles of the RDA and hierarchical partitioning analysis; however, the general trends were consistent between the two methods [40]. Therefore, this study detailedly reflected the importance of microhabitat factors on C, N, and P nutrient migration and cycling in a coastal habitat and, thus, warrant habitat-particularity dependent strategies to enhance the nutrients’ utilization efficiency and restore the degraded coastal forests in subtropical China.

5. Conclusions

The C, N, and P contents of the plant−litter−soil systems in three 13-year coastal forests were significantly higher than that of the non-forested land. The C. equisetifolia−E. saligna mixture had the highest C contents but the lowest N contents for aboveground plants. The E. saligna monoculture had the highest soil C and N contents. The P content of each ecosystem component had few differences among the three coastal forests. These coastal forests showed evident N limitation, tree mixing even exacerbated the N limitation. However, the explicit coupling relationships of the C, N, and P nutrients in the plant−litter−soil systems at the community scale were not substantially clarified due to the complex and variable microhabitats of the coastal forests; however, the mixed forest showed an enhanced coupling relationship of C, N, and P compared to the monocultures. In the coastal forest habitats, wind speed, soil moisture, salinity and pH all had significant effects on the C, N, P stoichiometry; however, their magnitude varied across the different ecosystem components, indicating the huge particularity of coastal forest habitats, such as strong wind, high salinity and the alkalinity of soils, and their effects on nutrient cycling. These findings enhanced our understanding of the C, N, P stoichiometric characteristics and their driving mechanism in monoculture and mixed coastal forests; it also highlighted the necessity of microhabitat-dependent forest management in regenerating low-efficiency stands, so as to promote the carbon sequestration and nutrient cycling ability of coastal forests.

Author Contributions

B.B. and H.X. (Hongtao Xie) carried out the fieldwork and laboratory analysis, prepared the figures, and wrote the manuscript. X.C. and H.X. (Haidong Xu) revised the manuscript; X.H. (Hongtao Xie) and X.C. contributed substantially to the study design and supervised the field and laboratory personnel. All authors have read and agreed to the published version of the manuscript.

Funding

The research was supported by the National Key Research and Development Project (2019YFE0118900) and the National Natural Science Foundation of China (32101506).

Data Availability Statement

Data are available on request from the authors.

Acknowledgments

We are grateful to Xuefeng Lin for his assistance in the fieldwork.

Conflicts of Interest

The views and conclusions in this document are those of the authors and should not be interpreted as representing the opinions or policies of the funding agencies and supporting institutions. The authors declare that they have no conflict of interest.

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Figure 1. Experimental design and sampling sites of the study.
Figure 1. Experimental design and sampling sites of the study.
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Figure 2. Correlation of C, N, and P contents in the plant–litter–soil systems of different coastal forests. Data are Pearson correlation coefficients with a significant level at p < 0.05 (n = 6); C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P.
Figure 2. Correlation of C, N, and P contents in the plant–litter–soil systems of different coastal forests. Data are Pearson correlation coefficients with a significant level at p < 0.05 (n = 6); C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P.
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Figure 3. Correlation of the C, N, P stoichiometric ratios in the plant–litter–soil systems of different coastal forests. Data are Pearson correlation coefficients with a significant level at p < 0.05 (n = 6); C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C:N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N: P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
Figure 3. Correlation of the C, N, P stoichiometric ratios in the plant–litter–soil systems of different coastal forests. Data are Pearson correlation coefficients with a significant level at p < 0.05 (n = 6); C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C:N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N: P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
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Figure 4. Effects of microhabitat factors on C, N, and P contents (A) and their stoichiometric ratios (B) in the plant−litter−soil system. C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P; C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C: N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N:P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
Figure 4. Effects of microhabitat factors on C, N, and P contents (A) and their stoichiometric ratios (B) in the plant−litter−soil system. C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P; C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C: N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N:P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
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Figure 5. Independent effect of microhabitat factors on C, N, and P contents and their stoichiometric ratios in the plant−litter−soil systems of coastal forests based on hierarchical partitioning analysis. Percentages indicate the explanatory power of each microhabitat factor. C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P; C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C:N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N:P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
Figure 5. Independent effect of microhabitat factors on C, N, and P contents and their stoichiometric ratios in the plant−litter−soil systems of coastal forests based on hierarchical partitioning analysis. Percentages indicate the explanatory power of each microhabitat factor. C1: canopy layer C; N1: canopy layer N; P1: canopy layer P; C2: herb layer C; N2: herb layer N; P2: herb layer P; C3: litter layer C; N3: litter layer N; P3: litter layer P; C4: 0–20 cm soil C; N4: 0–20 cm soil N; P4: 0–20 cm soil P; C5: 20–40 cm soil C; N5: 20–40 cm soil N; P5: 20–40 cm soil P; C:N 1: canopy layer C:N; C:P 1: canopy layer C:P; N:P 1: canopy layer N:P; C:N 2: herb layer C:N; C:P 2: herb layer C:P; N:P 2: herb layer N:P; C:N 3: litter layer C:N; C:P 3: litter layer C:P; N:P 3: litter layer N:P; C:N 4: 0–20 cm soil C:N; C:P 4: 0–20 cm soil C:P; N:P 4: 0–20 cm soil N:P; C:N 5: 20–40 cm soil C:N; C:P 5: 20–40 cm soil C:P; N:P 5: 20–40 cm soil N:P.
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Table
Table 1. Stand characteristics of the non-forested land and three coastal forests.
Table 1. Stand characteristics of the non-forested land and three coastal forests.
Stand CharacteristicsNon-Forested
Lands		Casuarina equisetifolia
Monoculture		Eucalyptus saligna
Monoculture		C. equisetifolia−E. saligna Mixture
Initial density (stem. ha−1)-160016001600
Mean tree age (year)-131313
Altitude (m)4.04.54.54.0
C. equisetifolia (85%)E. saligna (80%)C. equisetifolia (50%)
Tree species and portion N. indicum (10%)S. sebiferum (15%)E. saligna (40%)
T. ascendens (5%)N. indicum (5%)N. Indicum (10%)
Species with top 50% importance value of the herb layerA. cristatum
S. viridis
H. scandens		C. rotundus
P. asiatica
S. viridis		A. cristatum
S. cannabina		A. australis
A. cristatum
Table
Table 2. Contents of C, N, and P in plant−litter−soil systems of different coastal forests.
Table 2. Contents of C, N, and P in plant−litter−soil systems of different coastal forests.
ParametersComponentsNon-Forested LandsCasuarina equisetifolia
Monoculture		Eucalyptus saligna
Monoculture		C. equisetifolia−E. saligna Mixture
Canopy layer/469.2 ± 4.7 Aa455.3 ± 5.2 Ba467.2 ± 3.8 Aa
Herb layer341.9 ± 4.6 Ba321.2 ± 8.0 Cb334.7 ± 9.1 Bc380.1 ± 4.1 Ac
C (g/kg)Litter layer/446.6 ± 6.8 Aa419.4 ± 3.3 Bb402.3 ± 6.2 Cb
0–20 cm soil6.3 ± 0.6 Cb10.4 ± 2.1 Bc13.7 ± 3.7 Ad10.7 ± 2.8 Bd
20–40 cm soil2.2 ± 0.4 Dc3.5 ± 0.7 Cd9.0 ± 2.1 Ae6.6 ± 1.3 Be
Canopy layer/19.0 ± 0.4 Ab19.6 ± 0.6 Ab17.9 ± 0.4 Bb
Herb layer26.4 ± 0.6 Ba33.5 ± 1.3 Aa25.3 ± 0.7 Ba20.3 ± 1.1 Ca
N (g/kg)Litter layer/16.1 ± 0.4 Ac15.9 ± 0.3 Ac13.4 ± 0.5 Bc
0–20 cm soil0.61 ± 0.04 Cb0.83 ± 0.14 Bd1.35 ± 0.43 Ad0.84 ± 0.21 Bd
20–40 cm soil0.26 ± 0.03 Cc0.28 ± 0.03 Ce0.63 ± 0.12 Ae0.35 ± 0.02 Be
Canopy layer/1.65 ± 0.05 ABb1.81 ± 0.10 Ab1.76 ± 0.06 Ab
Herb layer2.92 ± 0.06 Ba3.06 ± 0.15 Aa2.84 ± 0.06 Aa2.96 ± 0.09 Aa
P (g/kg)Litter layer/1.28 ± 0.05 Ac1.23 ± 0.03 Ac1.18 ± 0.06 Bc
0–20 cm soil0.48 ± 0.06 Cb0.74 ± 0.11 Ad0.61 ± 0.02 Bd0.62 ± 0.02 Bd
20–40 cm soil0.38 ± 0.03 Bc0.57 ± 0.02 Ad0.56 ± 0.01 Ad0.56 ± 0.02 Ad
Note: Data are the mean ± SD (n = 6). Different capital letters indicate significant differences between different coastal forests for the same component; different lowercase letters indicate significant differences between different components in the same coastal forest (p < 0.05).
Table
Table 3. Stoichiometric ratios of C, N, and P in plant–litter–soil systems of different coastal forests.
Table 3. Stoichiometric ratios of C, N, and P in plant–litter–soil systems of different coastal forests.
ParametersComponentsNon-Forested LandsCasuarina equisetifolia
Monoculture		Eucalyptus saligna
Monoculture		C. equisetifolia–E. saligna Mixture
Canopy layer/24.7 ± 0.7 ABb23.2 ± 0.9 Bb25.9 ± 0.3 Ab
Herb layer12.9 ± 0.5 Ba9.6 ± 0.5 Ce13.2 ± 0.6 Bc18.7 ± 1.2 Ac
C:NLitter layer/27.7 ± 0.6 Ba26.3 ± 0.4 Ba30.1 ± 1.3 Aa
0–20 cm soil10.5 ± 1.3 Bb12.7 ± 0.8 Ad10.8 ± 2.8 Bd13.5 ± 2.1 Ad
20–40 cm soil8.5 ± 1.7 Cc14.9 ± 2.3 Bc14.6 ± 3.4 Bc19.4 ± 2.6 Ac
Canopy layer/283.8 ± 12.2 Ab252.9 ± 16.8 Cb265.2 ± 10.2 Bb
Herb layer117.2 ± 2.7 Ba104.9 ± 6.2 Cc117.9 ± 3.4 Bc128.3 ± 4.6 Ac
C:PLitter layer/363.1 ± 12.9 Aa328.1 ± 6.5 Ca342.1 ± 14.9 Ba
0–20 cm soil13.2 ± 0.7 Cb14.1 ± 4.7 Cd22.4 ± 6.1 Ad17.2 ± 4.6 Bd
20–40 cm soil5.7 ± 1.3 Cc6.1 ± 1.4 Ce16.2 ± 4.1 Ae11.8 ± 2.4 Be
Canopy layer/11.5 ± 0.2 Ab10.9 ± 0.5 Bb10.2 ± 0.5 Bb
Herb layer9.1 ± 0.3 Ba10.9 ± 0.3 Ab8.9 ± 0.3 Bc6.8 ± 0.4 Cc
N:PLitter layer/13.1 ± 0.3 Aa12.5 ± 0.8 Aa11.4 ± 1.0 Ba
0–20 cm soil1.3 ± 0.2 Bb1.1 ± 0.3 Bc2.1 ± 0.6 Ad1.3 ± 0.3 Bd
20–40 cm soil0.7 ± 0.1 Bc0.4 ± 0.1 Cd1.1 ± 0. 2 Ae0.6 ± 0.1 Be
Note: Data are the mean ± SD (n = 6). Different capital letters indicate significant differences between different coastal forests for the same component; different lowercase letters indicate significant differences between different components in the same coastal forest (p < 0.05).
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Bao, B.; Huang, X.; Xu, H.; Xie, H.; Cheng, X. Patterns and Driving Mechanism of C, N, P Ecological Stoichiometry in Plant-Litter-Soil Systems of Monoculture and Mixed Coastal Forests in Southern Zhejiang Province of China. Forests 2023, 14, 1306. https://doi.org/10.3390/f14071306

AMA Style

Bao B, Huang X, Xu H, Xie H, Cheng X. Patterns and Driving Mechanism of C, N, P Ecological Stoichiometry in Plant-Litter-Soil Systems of Monoculture and Mixed Coastal Forests in Southern Zhejiang Province of China. Forests. 2023; 14(7):1306. https://doi.org/10.3390/f14071306

Chicago/Turabian Style

Bao, Binghui, Xiaoling Huang, Haidong Xu, Hongtao Xie, and Xiangrong Cheng. 2023. "Patterns and Driving Mechanism of C, N, P Ecological Stoichiometry in Plant-Litter-Soil Systems of Monoculture and Mixed Coastal Forests in Southern Zhejiang Province of China" Forests 14, no. 7: 1306. https://doi.org/10.3390/f14071306

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