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Article

Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus

by
Wenzhen Zong
1,
Zhengni Chen
1,2,
Quanlin Ma
1,*,
Lei Ling
1,2 and
Yiming Zhong
1,2
1
Gansu Academy of Forestry, Lanzhou 730020, China
2
Gansu Xinglong Mountain Forest Ecosystem Positioning Research Station, Lanzhou 730020, China
*
Author to whom correspondence should be addressed.
Atmosphere 2025, 16(7), 890; https://doi.org/10.3390/atmos16070890
Submission received: 21 May 2025 / Revised: 8 July 2025 / Accepted: 18 July 2025 / Published: 20 July 2025
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
Browse Figures
Versions Notes

Abstract

The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and carbon (C) reservoir in China. Studying the main drivers of C density changes in forest ecosystems is crucial to enhance the C sink potential of those ecosystems in ecologically fragile regions. In this study, four stand types at different succession stages in the transition zone of Xinglong Mountain were selected as the study objective. The C densities of the ecosystem, vegetation, plant debris, and soil of each stand type were estimated, and the related driving factors were quantified. The results showed that the forest ecosystem C density continuously increased significantly with natural succession (381.23 Mg/hm2 to 466.88 Mg/hm2), indicating that the ecosystem has a high potential for C sequestration with progressive forest succession. The increase in ecosystem C density was mainly contributed to by the vegetation C density, which was jointly affected by the vegetation characteristics (C sink, mean diameter at breast height, mean tree height), litter C/N (nitrogen), and surface soil C/N, with factors explaining 95.1% of the variation in vegetation C density, while the net effect of vegetation characteristics was the strongest (13.9%). Overall, this study provides a new insight for understanding the C cycle mechanism in ecologically fragile areas and further improves the theoretical framework for understanding the C sink function of forest ecosystems.

1. Introduction

The increase in atmospheric carbon dioxide (CO2) concentration due to human activities (e.g., fossil fuel burning and deforestation) is recognized as one of the main drivers of global climate change [1]. The utilization of the C sequestration potential of forests, as a core component of the global C cycle in terrestrial ecosystems, is considered an important mitigation strategy to reduce the atmospheric CO2 concentration [2,3]. Therefore, accurately investigating the drivers of C stocks in forest ecosystems and quantifying their effects at the regional and even global scales are important for a thorough understanding of forest’s C dynamics and their potential to mitigate climate change.
The dynamics of forest ecosystem C sinks are jointly regulated by external climatic factors (e.g., temperature and precipitation) and internal factors (e.g., vegetation, litter, and soil characteristics). In the study of large-scale spatial patterns, the influence of climate factors on forest ecosystem C sinks is particularly significant [4,5,6,7]. Studies have shown that climate factors have significant time-lagged and cumulative effects on vegetation growth [8,9], and that both of these effects show significant heterogeneity across climate regions, as well as between vegetation types [9,10]. For example, in the semi-arid tropics, precipitation and temperature drying effects may carry over with at least a 2-year lag time to influence the net primary productivity [11]. In arid and semi-arid regions of the globe, this time-lag is approximately one month, and vegetation growth in response to temperature changes at low and middle latitudes lags by 1–3 months [9]. One study found that the cumulative effect of temperature is negligible in most of Arctic and northern temperate zones but up to 2–3 months in arid/semi-arid areas [8]. Cumulative drought affects photosynthesis processes in 52.11% of the global vegetation cover, with an average cumulative duration of 1–4 months [12]. Temperature has a significant dual effect on the C sink function of forests. On the one hand, a certain range of temperature increase can enhance productivity through enhanced plant photosynthesis, thus enhancing the C sink function [4,7,13,14]. On the other hand, sustained temperature increases may exceed the optimal temperature threshold for plant photosynthesis [15,16], which may negatively affect the C sink function of vegetation. Increased precipitation within a certain range can effectively promote vegetation growth and C sequestration in forests [13,17]. The areas that are affected by precipitation are mainly distributed in arid regions, especially in cold temperate and cold climate zones [18]. These results highlight the complexity and regional characteristics of forest’s C sink response in the context of climate change.
In small-scale studies, due to the relative consistency of climatic and topographic conditions and the large variation in microenvironments, studies have focused on the effects of internal factors such as vegetation characteristics (e.g., the vegetation type, species diversity, and litter quality) and soil characteristics (e.g., the soil type, texture, pH, organic matter content, and microbial activity) [19,20,21,22]. One study found that in northeast China, the C stock in coniferous forest ecosystems is significantly higher than that in broadleaf forests [23]. The C sink intensity of terrestrial ecosystems in China is positively correlated with the soil clay, silt, and nitrogen (N) contents, and negatively correlated with its sand content and bulk density [24]. These internal influences may exhibit different strengths and directions of action in forest ecosystems, which in combination drive the dynamics of ecosystem C intensity. However, although research on the internal drivers of the forest C sinks has made some progress, previous studies mostly focused on analyzing whether these factors affect forest C sinks, while neglecting in-depth exploration of the key issue of the impact intensity of each factor.
The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and C reservoir in China [25]. It is one of the most sensitive and fragile regions in the world due to its geographical features of high altitude and low temperature, where ecological thresholds are often in a critical state; and at the same time, the area is facing the dual pressure of climate warming and human activities [26,27]. Studies have shown that the dominant vegetation types in the transition zone between the Qinghai–Tibet and Loess Plateaus are undergoing rapid alternate succession in spatial patterns that are driven by climate change and human activities [28], and this succession process plays an important role in enhancing the function of forest C sinks [29]. Xinglong Mountain is located in the transition zone, which is an important water conservation area in the upper reaches of the Yellow River, with an ecologically crucial location. This study selected four stand types in different succession stages on Xinglong Mountain, using the space-for-time substitution method to estimate the C densities of vegetations, plant debris, soils, and ecosystems of the different stand types and to measure the relevant influencing factors. The aim of this study was to reveal the influencing strength of selected internal driving factors on changes in the C density of forest ecosystems during different succession stages on Xinglong Mountain. This study provides new insights for understanding the C cycle mechanism in ecologically fragile areas and further improves our theoretical understanding of the C sink function of forest ecosystems.

2. Materials and Methods

2.1. Study Site

The study sample site, Xinglong Mountain (35°38′ N–35°58′ N, 103°50′ E–104°10′ E), is located in the westernmost part of China’s Loess Plateau (Figure 1), which is part of the eastward-extending remnants of the Qilian Mountains and is known as a green rocky island on the Loess Plateau. The region has a temperate semi-humid to semi-arid climate zone, with an average annual temperature of 4.5 °C and an average annual precipitation of 625 mm [30]. The forest vegetation is mainly distributed at an altitude of 2200–3000 m, with large areas of pure Picea wilsonii Mast. forests, which are of great ecological importance as the climax community of forest succession in this region. The P. wilsonii forest improves key ecological functions such as water conservation, water quality, C sequestration, and soil fertility maintenance [31,32]. The main stand types include mixed Populus davidiana Dode–Betula platyphylla Sukaczev forest, mixed B. platyphylla–P. wilsonii forest, and pure P. wilsonii forest. The understory vegetation is dominated by shrubs, and common species include Berberis kansuensis C.K. Schneid., Sorbus koehneana Schneid., Fargesia nitida (Mitford) Keng f., and Eleutherococcus giraldii (Harms) Nakai; in addition, there is a rich variety of herbs, including Gymnocarpium disjunctum Ching, Phlomis umbrosa Turcz., Pyrola rotundifolia L., and Thalictrum L.; bryophytes such as Hygrohypnum sp. and Entodon sp. are also distributed in the understory.
Based on the forest succession data on Xinglong Mountain [33,34], this study proposed to divide the forest succession process on Xinglong Mountain into four stages, i.e., mixed P. davidiana–B. platyphylla forest (S1), mixed B. platyphylla–P. wilsonii forest (S2), middle-aged P. wilsonii forest (S3), and near-mature P. wilsonii forest (S4). The basic information of the stand types at each succession stages is shown in Table 1.

2.2. Field Investigation and Sample Collection

Four stand types were selected for this study, and three random plots (20 m × 20 m) within each of the four stand types were set up, totaling twelve sample plots. The first field investigation was carried out from 2019 to 2022. The biomass of trees, shrubs, herbs, litters, and woody debris were investigated, and plant and soil samples were collected. The second field investigation was carried out in July 2024, during which the biomass of trees and woody debris was investigated, and plant samples were collected. The main purpose of the second investigation was to calculate the C sink of the trees/woody debris.

2.2.1. Investigation of Tree Layer and Determination of Forest Age

All trees with a diameter at breast height (DBH) and height (m) at 4 cm DBH in the plot were investigated. Three to five sample trees in the mixed broadleaf forest, mixed coniferous–broadleaf forest, and middle-aged forest of P. wilsonii were selected according to the following scales of diameter classes: from 8 to 12 cm, from 20 to 24 cm, and from 32 to 36 cm, respectively. In the near-mature P. wilsonii forest, the scales of diameter classes were from 19 to 23 cm, from 39 to 43 cm, and from 57 to 61 cm. Each sample tree was divided into stems, branches, and leaves to collect at least 300 g of samples to be taken to the laboratory for analysis. When collecting samples (branches and leaves) from representative trees, we took samples from the upper, middle, and lower layers of the crown, while also considering the four cardinal directions (east, south, west, and north) to ensure the comprehensiveness and representativeness of the samples. The ages of the ten trees with the largest DBH were determined by means of tree-round analysis, and the age average of these ten trees was used as the age of the natural stand represented by the plot.

2.2.2. Investigation of Shrubs, Herbs, Litters, and Woody Debris

Three 5 m × 5 m shrub sample plots were set up diagonally within each tree plot, the total number and coverage of each shrub within the sample plot were recorded, and one standard strain was harvested for each shrub. A 1 m × 1 m herb plot was randomly set up and nested within each shrub plot for herb investigation, the total number and coverage of each species were recorded, and all species that were found in the small plot were harvested after the investigation. Meanwhile, three litter collection sample squares (0.5 m × 0.5 m) were randomly set up within the sample plots to collect all undecomposed and semi-decomposed litter material above the soil surface and to take a quarter of the sample back to the laboratory. Woody debris in this study only included coarse woody residues, as fine woody residues were rare and negligible in the sample plots. The DBH and height of all dead standing trees in the plot were investigated, and the diameters and lengths of the two ends and middle of the fallen trees as well as the degree of decay were recorded [35]. Samples of dead fallen wood at different levels of decay were collected and brought back to the laboratory for drying to a constant mass, and the dry mass was measured, ground, and sieved to determine the C content. The relationship between the volume and dry mass of sampled dead wood was calculated, and the dry mass and C density of the dead wood in the plot were estimated [36].
Five fresh litter collection frames were set up in each plot, located in the corners and center of the plot. The area of a litter collection frame was 1 m2 (length 1 m, width 1 m), and the distance from the ground was 0.2 m. Litter collection started in 2022, and litters were collected in the second half of March, April, May, June, July, August, September, and October; litters in winter were collected in late March of the following year, because the forest had more snow in winter than is convenient for collecting litters.

2.2.3. Soil Sampling

Five soil sampling points were randomly set up in each plot; soil samples were taken using auger, stratified by 0–20, 20–40, 40–60, 60–80, and 80–100 cm. Soil samples were mixed at the same level in the same plot, and samples were taken back to the laboratory for determining organic C content. At the same time, a representative lot was selected in each plot dug soil profile, with a ring knife (100 cm3), taking the original soil of each soil layer, 3 replicates, and bringing back to the laboratory at 105 °C to dry to a constant weight in order to calculate the bulk density.

2.3. Determination of C and N Content

Samples of trees, shrubs, herbs, litters, and woody debris collected in the field were placed in an oven at 65 °C and baked to a constant weight, after which we recorded the dry weight of the samples. For the determination of the plant C and N contents of the dried samples, they were crushed and sieved through a 100-mesh sieve. Soil samples were naturally air-dried, ground, and passed through a 2 mm sieve (collecting gravel larger than 2 mm and weighing it), and a portion of the soil sample was ground through a 100-mesh sieve to be measured for total C (TC) and total N (TN) contents. The C and N contents of the plant and soil samples were determined using an elemental analyzer (Flash 2000 HT, Thermo Fisher Scientific, Waltham, MA, USA).

2.4. Biomass Calculation

According to the study region and tree species, we used the corresponding allometric Equation (1) for different tree components (leaf, branch, stem, and root) to calculate the biomass of each component [36]. The individual tree biomass is the sum of all component biomasses, and the stand biomass is the sum of all tree biomasses within a plot. The biomass of shrubs, herbs, and litters per unit area in the sample plot was based on the dry weight of the collected samples:
W = a D B H 2 H b
where W is the biomass of tree; DBH is the diameter at breast height; H is the tree height; a and b are the coefficients of the function.

2.5. C Density Calculation

The organic C densities of different soil layers (0–20, 20–40, 40–60, 60–80, and 80–100 cm) were calculated according to the soil organic C content, bulk density, and corresponding soil layer thickness. Soil profiles less than 100 cm thick were calculated at actual depth. Soil organic C density was calculated by summing the C density of each soil layer [37] as in Equation (2) below:
S C D = ∑ i − 1 n B D i − S T i × h i × S C i × 10
where SCD is the soil C density (g C m−2); BDi is the soil bulk density of layer i (g cm−3); STi is the soil gravel content of layer i (g cm−3); hi is the soil depth of layer i (cm); and SCi is the soil C content of layer i (g kg−1).
Ecosystem C density was calculated by summing the C densities of vegetations (trees, shrubs, and herbs), plant debris (litters and woody debris), and soils. Vegetation C density is the sum of the C densities of trees, shrubs, and herbs. Plant debris C density is the sum of the C densities of litters and woody debris. The C density of each component of trees, shrubs, herbs, litters, and woody debris is the biomass of the corresponding component multiplied by the C content.
The C sink (Mg/(hm2∙a)) of trees/woody debris calculation formula was as follows in Equation (3):
C   s i n k = C   d e n s i t y t 2 − C   d e n s i t y t 1 t 2 − t 1
where t1 represents the year of the first investigation; t2 represents the year of the second investigation.

2.6. Data Statistics and Analysis

Data were statistically analyzed using SPSS 20.0 (IBM, Armonk, NY, USA) software, and normality and variance chi-square tests were performed before statistical analysis. One-way ANOVA was used to assess the significant differences in vegetation C density, soil C density, litter C density, woody debris C density, ecosystem C density, and C sink (trees/woody debris) among different succession stages of the forest. The Duncan post hoc test was used if the data satisfied normality and the variance chi-square test; the Kruskal–Wallis H (K) test was used if the data did not satisfy normal distribution; and the Games–Howell test was used if the data did not satisfy the variance chi-square test. Relationships among the C densities of ecosystem, soil, vegetation, tree, and internal factors (vegetation characteristics and soil characteristics) were analyzed using the Spearman correlation analysis. Variation partitioning analysis (VPA) (“vegan” package in R 4.3.0) was used to assess the contribution of individual influencing factors to the ecosystem C density as well as the vegetation C density.

3. Results

3.1. Ecosystem C Density and Its Distribution Pattern

The ecosystem C density of the forests on Xinglong Mountain gradually increased with the succession stages (S1–S4), as did the vegetation C density, while the soil C density did not exhibit a significant trend (Figure 2). The C densities of the ecosystem and vegetation differed significantly among the different succession stages. The ecosystem C densities in each succession stage (S1–S4) were 381.23, 432.10, 437.74, and 466.88 Mg/hm2 (Figure 2a), which were mainly contributed to by the soil C density and vegetation C density, which accounted for 76.85% and 19.46%, respectively, while the C density of the plant debris accounted for 3.69% (litters accounted for 3.58%; woody debris accounted for 0.11%). As the forest succession stage (S1–S4) progressed, the proportion of soil C density gradually decreased, while the proportion of vegetation C density gradually increased (Figure 2).

3.2. C Density of Forest Ecosystem Components and Their Distribution Patterns

3.2.1. Vegetation C Density and Its Distribution Pattern

With the natural succession of forests (S1–S4), the vegetation C density increased significantly, among which the tree C density increased significantly with the succession stages, while the C densities of shrub and herb layer did not change significantly (Figure 3). The vegetation C densities during different succession stages were 48.87, 70.06, 89.65, and 130.78 Mg/hm2, respectively. The tree C density accounted for the highest proportion of the vegetation C density, followed by the shrub layer, while the herb layer accounted for the smallest proportion, with the mean values of 97.19%, 2.78%, and 0.03%, respectively (Figure 3).

3.2.2. Plant Debris C Density and Its Distribution Pattern

The C density of the plant debris (litters and woody debris) showed no significant change trend with the succession stages of the forests (S1–S4) (Figure 4a). The litter C density was highest in S1 (18.60 Mg/hm2) and lowest in S2 (10.14 Mg/hm2) (Figure 4a). The woody debris C density was highest in S3 (1.57 Mg/hm2), with a value that was significantly higher than those of other stands (Figure 4a). The proportion of the litter C density in plant debris was significantly higher than that of woody debris, with values of 97.02% and 2.98%, respectively (Figure 4b).

3.2.3. Soil C Density and Its Distribution Pattern

The soil C density did not change significantly with the succession stages of the forests (S1–S4) (Figure 2a). In the vertical gradient of soils, the soil C density of the surface layer (0–20 cm) changed significantly in the different succession stages; that is, it first increased and then decreased with the succession stages (the highest in S3), while the C density of other soil layers did not change significantly (Figure 5a). The proportion of the soil C density in the different soil layers gradually decreased with the increase in depth, and the average proportion of the soil C density at 0–20 cm, 20–40 cm, 40–60 cm, 60–80 cm, and 80–100 cm was 32.54%, 23.27%, 17.46%, 13.40%, and 13.32%, respectively (Figure 5b).

3.3. C Sink of Tree and Woody Debris

The sum of the C sinks of tree and woody debris, as well as the C sink of trees, increased significantly with the succession stages of the forests, with the sum of C sinks increasing from 0.16 Mg/(hm2·a) to 2.60 Mg/(hm2·a) and the C sink of trees increasing from 0.13 Mg/(hm2·a) to 2.60 Mg/(hm2·a) (Figure 6). The C sink of woody debris first increased and then decreased with the succession stages, with its maximum occurring in the S2 stage (0.44 Mg/(hm2·a)) (Figure 6).

3.4. Driving Factors of Ecosystem C Density

The results of this study showed that the mean DBH, mean tree height, litter C/N, and surface soil0–20cm C/N increased gradually with the succession stages, among which the mean DBH, mean tree height, and surface soil0–20cm C/N in the near-mature Picea wilsonii forest (S4) were significantly higher than those of other forests; the litter C/N in the P. wilsonii forest (S3 and S4) was significantly higher than that of the mixed forest (S1 and S2) (Table 2).
Plant, litter, and surface soil0–20cm characteristics could influence significantly the C density of forest ecosystem components (Figure 7). The forest ecosystem C density was significantly and positively correlated with the vegetation C density, soil C density, C sink (trees + woody debris), mean DBH, litter C/N, and surface soil0–20cm C/N (Figure 7). The C density of vegetation/tree was significantly and positively correlated with the C sink (trees + woody debris), mean DBH, mean tree height, litter C/N, and surface soil0–20cm C/N (Figure 7). The soil C density was not significantly correlated with these influencing factors. The C sink (trees + woody debris) was significantly positively correlated with the mean DBH, mean tree height, litter C/N, and surface soil0–20cm C/N, while it was significantly negatively correlated with the surface soil0–20cm TN (Figure 7).
Based on the results of the correlation analysis (Figure 7), this study further used variation partitioning analysis (VPA) to quantify the explanation degree of the C densities of vegetation and soil in the variance of the ecosystem C density as well as the explanation degree of significant influencing factors in the variance of the vegetation C density (Figure 8). Since the soil C density did not change significantly with the succession stages, the driving factors of this change were not further analyzed. The results of the VPA showed that 98.9% of the variation in the ecosystem C density during different succession stages on Xinglong Mountain forests was explained by the C densities of vegetation and soil, as the net effect of the vegetation C density was 55.7% and that of the soil C density was 60.3% (Figure 8a), with the net effect of the two being comparable. The results showed that 95.1% of the variation in the vegetation C density was explained by vegetation characteristics (C sink, mean DBH, mean tree height), litter C/N, and soil0–20cm C/N, with the highest net effect being that of the vegetation characteristics (13.9%) (Figure 8b).

4. Discussion

4.1. Impact of Forest Succession on Stand C Density and Its Distribution

The results of this study show that, with the natural succession of the forests on Xinglong Mountain, the forest C densities of the ecosystem and vegetation gradually increased, while the soil C density did not exhibit a significant trend of change (Figure 2a), indicating that the P. wilsonii forest, which is the climax community, has a strong C absorbing capacity. Therefore, the natural forest succession on Xinglong Mountain is progressive in terms of C sink function, which ultimately contributes to the stabilization of the ecosystems and the conservation of biodiversity in this region. The ecosystem C density increased gradually (381.23–466.88 Mg/hm2) during the natural succession of the forests (Figure 2a), indicating that the ecosystem has a high potential for C sequestration with progressive succession of the forests. The change in the ecosystem C density is consistent with the results of previous studies [38,39,40,41]. However, our results were higher than those for other temperate forests in China (186.9–356.2 Mg/hm2) [42,43]. On the one hand, this is due to the fact that the forest ecosystem on Xinglong Mountain is dominated by natural forests with well-grown vegetation; on the other hand, it has benefited from China’s ecological conservation projects in recent years.
The ecosystem C density in each succession stage of forests on Xinglong Mountain were mainly constituted of the C densities of the vegetation and soil, and the proportion of the vegetation C density (19.46%) in that of the ecosystem was significantly lower than that of the soil (76.85%) (Figure 2b). This finding was similar to the results of a study on the proportions of C density of each component of global boreal and temperate forests, since the proportion of the vegetation C density in boreal forests was 20% and that of soil was 64%. In temperate forests, it was 38% for vegetation and 54% for soil [44]. Although the proportion of the vegetation C density in ecosystem C density was significantly lower than that of the soil (Figure 2b), the explanation degree of the variance in the ecosystem C density by the vegetation C density was comparable to that of the soil (Figure 8a), and with the progressive succession (S1–S4), the proportion of the vegetation C density gradually increased, while the proportion of the soil C density gradually decreased (Figure 2b). The above results indicated that the increase in the ecosystem C density during the natural succession of the forests on Xinglong Mountain was mainly caused by the vegetation C density, which was consistent with the results of previous studies [40,45,46,47]. The reason for this is that the forest age gradually increases during progressive succession, and some studies have shown that a forest vegetation C density increases rapidly with the increase in stand age (succession stage), after which the growth rate is slow and gradually reaches a stable state [7,48,49].
With the progressive succession of the forests on Xinglong Mountain, the vegetation C density gradually increased, in which the tree layer accounted for the highest proportion, followed by the shrub layer, while the herb layer accounted for the smallest proportion; the proportions were 97.19%, 2.78%, and 0.03%, respectively (Figure 2a and Figure 3). The tree C density increased significantly with forest succession, and the proportion of the tree C density in the ecosystem C density also increased gradually (Figure 2), which was consistent with the results of previous studies [38,46,50]. The C density of the understory vegetation (shrub and herb layers) accounted for a small proportion of the ecosystem C density, and that did not change significantly with succession stages. The understory biomass is closely related to the tree closure and usually decreases with increasing closure [51]. In this study, the forest closures at different succession stages were similar (Table 1); thus, there was no significant difference in C density between the shrub and herb layer.
With the progressive succession in this study, although the proportion of the soil C density gradually decreased (Figure 2b), there was no significant difference in this variable at each succession stage. However, this may be related to the land use history of the study’s sample plots. The mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, and middle-aged P. wilsonii forest were all secondary forests after felling, and the primary vegetation in these plots may have been older previously and have accumulated more C; therefore, the soil C density was higher in these plots. Although disturbances such as logging usually reduce the soil C stocks, especially in topsoil, they can be restored after a certain period of time [52,53]. Therefore, in this study, the soil C density of the younger secondary forest was comparable to that of the older primary forest (near-mature P. wilsonii forest). On the vertical gradient of the soil C density, the soil0–20cm C density increased and then decreased with succession stages, and it was highest in the middle-aged P. wilsonii forest (S3) (Figure 5a). Compared with the deeper mineral soil, the surface soil is more susceptible to disturbance and other factors and, therefore, has greater variability [46,52,53]. In our study, the change trend of C density in the soil0–20cm with the succession stage was consistent with the litter input (Table 2; Figure 5a). This result was consistent with a study that used a meta-analysis (with 712 sets of data) to elucidate how litter input increases soil organic C [54]. The balance between litter accumulation and decomposition regulates C sequestration in soil [55]; thus, the significant difference in the C density of the surface soil0–20cm in our study may be mainly related to the litter input.

4.2. Driving Factors of Stand C Density During Forest Succession

The results of this study showed that the increase in ecosystem C density during the natural succession of the forests on Xinglong Mountain is mainly impacted by the vegetation C density (Figure 2 and Figure 8); thus, this study further revealed the main internal driving factors of the change in the vegetation C density.
Generally, the large-scale studies mainly analyze the effects of climatic factors (temperature and precipitation) on C stocks in forests [4,5,6,56]. However, in small-scale studies, the climatic conditions are essentially the same, and the microenvironment is highly variable. Therefore, the focus is on the effects of internal driving factors such as vegetation and soil characteristics. Our study belongs to a small-scale study, with small differences in climatic conditions, and the results of correlation analysis showed that the C sink (trees + woody debris), mean DBH, mean tree height, litter C/N, and surface soil0–20cm C/N were the main driving factors influencing the vegetation C density (Figure 7). The results of the VPA showed that 98.9% of the variance in the vegetation C density was explained jointly by the vegetation characteristics (C sink, mean DBH, mean tree height), litter C/N, and surface soil0–20cm C/N, of which the net effect of the vegetation characteristics was the highest (Figure 8b). This result was consistent with previous studies [20,57,58], which showed that the vegetation C density is positively correlated with the DBH. In general, the vegetation C density is mainly affected by the tree biomass, which is mainly affected by the mean DBH and tree height [58]; thus, the mean DBH and tree height indirectly affect the vegetation C density by affecting the biomass [20,57,58]. In this study, the C sink (trees + woody debris), especially the tree C sink, increased significantly with succession stages (Figure 6), indicating that the growth rate of each tree species gradually accelerated during succession stages, and that more organic matter was accumulated (e.g., trunks, branches, leaves, and roots) [39,59,60,61]. The C sink of woody debris increased and then decreased with succession stages, reaching a maximum in the mixed B. platyphylla–P. wilsonii forests (S2) (Figure 6), which indicated that the pioneer tree species were degraded and died due to increased competition during the succession process (which is consistent with the results of a previous study [62]), and that nutrients that are released from the decomposition of woody debris can significantly promote the growth of vegetation. Therefore, the increase in the total C sink (trees + woody debris) contributed to the increase in vegetation C density. The results of this study showed that the increase in the vegetation C density was significantly and positively correlated with the increase in litter C/N (Figure 7), mainly due to the slower decomposition of litter with high C/N, which on the one hand allows for a sustainable input of litter nutrients, and on the other hand may indirectly promote sustainable vegetation growth through increasing the soil organic C content [63]. Although it has been suggested that the litter with high C/N is not easily and rapidly degraded by soil microorganisms—leading to a decrease in the available plant N and thus limiting the increase in vegetation biomass and C density [64]—the soil in this study site is nutrient-rich, and the vegetation growth is not limited by nutrients. Our study found that the litter C/N increased with the succession stage (Table 2), which was contrary to the result of a different study. The other study was conducted in coniferous to broad-leaved forests during succession [65], whereas our study site was the opposite. This difference in successional direction results in a different trend in the litter C/N. The change in soil0–20cm C/N is mainly affected by the litter C/N [66], and the slower decomposition of litter with high C/N may lead to temporary fixation of N, thus increasing the soil C/N [63]. Therefore, the impact of the surface soil0–20cm C/N on the vegetation C density was consistent with that of the litter.
This study used the space-for-time substitution method; its theory basis is that spatial differences can effectively simulate temporal succession processes under specific environmental conditions. While this method offers distinct advantages in terms of data collection and presenting succession processes, it also has certain limitations, particularly in large-scale studies. First, the inherent spatial heterogeneity of forest ecosystems (e.g., variations in environmental factors such as soil, topography, and light conditions) makes it difficult to accurately infer temporal evolution patterns. Second, the lack of a standard for classifying forest succession stages means that research results from different regions, forest types, and study objectives are not fully comparable, universal, or reliable. Therefore, when interpreting research results obtained using this method, it is essential to consider these constraints fully and to clearly define the applicable conditions and regional limitations, thereby enhancing the reliability of the conclusions.
In summary, the vegetation C density was jointly affected by the vegetation characteristics (C sink, mean DBH, mean tree height), litter C/N, and surface soil0–20cm C/N. These factors explained 95.1% of the variation in the vegetation C density, with the net effect of the vegetation characteristics being the strongest (13.9%) (Figure 8b). In our study, the increase in the ecosystem C density during the natural succession of the forests was mainly caused by the vegetation C density (Figure 2 and Figure 8b); thus, the above factors were also the main driving factors influencing the variation in the ecosystem C density during the natural progressive succession of forests on Xinglong Mountain. Our study revealed the strength of the influence of certain internal factors on changes in the C density of forest ecosystems during succession in the transition zone between the Qinghai–Tibet and Loess Plateaus, thus contributing key research findings that were overlooked in previous studies. The results of this study provide new insights for similar studies in other regions or forest types.

5. Conclusions

The results of this study suggested that the forest ecosystem of Xinglong Mountain in the transition zone between the Qinghai–Tibet and Loess Plateaus shows a significant trend of an increasing C sink function during the natural progressive succession process. Specifically, the forest ecosystem C density, vegetation C density, and total C sink showed a continuous increase trend with the natural succession process, while the soil C density remained relatively stable. These findings confirmed that the forest ecosystems on Xinglong Mountain have significant C sequestration potential. Further analysis showed that the increase in the ecosystem C density was mainly due to the contribution of the vegetation C density, which was jointly affected by the vegetation characteristics (C sink, mean DBH, mean tree height), litter C/N, and surface soil0–20cm C/N, among which the influence of vegetation characteristics was the strongest. The above factors were also the main factors influencing the change in the ecosystem C density in the region. Our study revealed the influence strength of certain internal driving factors on changes in the C density of forest ecosystems during succession in the transition zone between the Qinghai–Tibet and Loess Plateaus, thus contributing key research findings that were overlooked in previous studies. This study provides a new insight for understanding the C cycle mechanism in an ecological transition zone and further improves our theoretical understanding of the C sink function of forest ecosystems.

Author Contributions

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

Funding

This study was funded by the Youth Science and Technology Foundation of Gansu Provence, China (No. 25JRRA759), the Key Research and Development Special Funds for Ecological Civilization Construction of Gansu Provence, China (No. 25YFFA075), Joint Funds of the National Natural Science Foundation of China (No. U21A2005), the National Key Research and Development Program of China (No. 2024YFD2201100), the Key Research and Development Special Funds of Gansu Provence, China (No. 24YFFA040), the Self-Listed Science and Technology Projects of Gansu Forestry and Grassland Bureau (No. 2024kj021) and the Carbon Special Program for forestry, grassland, wetland, and desert of Gansu Forestry and Grassland Bureau.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

We are grateful to Q.M. and Z.C. for the study conception and design. Field investigation, sample collection, and data analysis were performed by W.Z., L.L. and Y.Z. The first draft of the manuscript was written by W.Z. and all authors commented on previous versions of the manuscript. This study was completed at Gansu Xinglong Mountain Forest Ecosystem Positioning Research Station.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

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Atmosphere 16 00890 g001
Figure 1. A map of the locality of the study area. The four sampling plots (S1, S2, S3, and S4) were set up. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest and near-mature P. wilsonii forest, respectively.
Figure 1. A map of the locality of the study area. The four sampling plots (S1, S2, S3, and S4) were set up. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest and near-mature P. wilsonii forest, respectively.
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Figure 2. Ecosystem C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. Vegetation C density is the sum of C densities of trees, shrubs, and herbs. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different uppercase letters indicate significant differences (p < 0.05) in ecosystem C density among the four succession stages. Different lowercase letters indicate significant differences (p < 0.05) in C densities of ecosystem components among the four succession stages.
Figure 2. Ecosystem C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. Vegetation C density is the sum of C densities of trees, shrubs, and herbs. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different uppercase letters indicate significant differences (p < 0.05) in ecosystem C density among the four succession stages. Different lowercase letters indicate significant differences (p < 0.05) in C densities of ecosystem components among the four succession stages.
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Figure 3. Vegetation C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in trees/shrubs/herbs among the four succession stages.
Figure 3. Vegetation C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in trees/shrubs/herbs among the four succession stages.
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Figure 4. Plant debris C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in litters or woody debris among the four succession stages.
Figure 4. Plant debris C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in litters or woody debris among the four succession stages.
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Figure 5. Soil C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in the C density of each soil layer among the four succession stages.
Figure 5. Soil C density (a) and its distribution pattern (b) during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) in the C density of each soil layer among the four succession stages.
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Figure 6. C sinks of the tree layer and woody debris during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different uppercase letters indicate significant differences (p < 0.05) in total C sink (trees + woody debris) among the four succession stages. Different lowercase letters indicate significant differences (p < 0.05) in C sink of trees/woody debris among the four succession stages.
Figure 6. C sinks of the tree layer and woody debris during the different succession stages of the forests on Xinglong Mountain. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different uppercase letters indicate significant differences (p < 0.05) in total C sink (trees + woody debris) among the four succession stages. Different lowercase letters indicate significant differences (p < 0.05) in C sink of trees/woody debris among the four succession stages.
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Figure 7. Heat map of the correlation between C density of ecosystems and their components and the characteristics of trees and soils during the different succession stages of the forests on Xinglong Mountain. Ecosystems, vegetations, trees, and soils represent their corresponding C density; DBH represents mean diameter at breast height; H represents mean tree height; TC represents total carbon; TN represents total nitrogen. Significance markers (*) are shown. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
Figure 7. Heat map of the correlation between C density of ecosystems and their components and the characteristics of trees and soils during the different succession stages of the forests on Xinglong Mountain. Ecosystems, vegetations, trees, and soils represent their corresponding C density; DBH represents mean diameter at breast height; H represents mean tree height; TC represents total carbon; TN represents total nitrogen. Significance markers (*) are shown. *, p < 0.05; **, p < 0.01; ***, p < 0.001.
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Figure 8. Variation partitioning analysis (VPA) revealed the explanation degree of the C densities of the vegetation and soil in the variance of the ecosystem C density (a); the explanation degree of each driving factor in the variance of the vegetation C density (b). Plant characteristics include C sink (trees + woody debris), mean diameter at breast height (DBH), and mean tree height.
Figure 8. Variation partitioning analysis (VPA) revealed the explanation degree of the C densities of the vegetation and soil in the variance of the ecosystem C density (a); the explanation degree of each driving factor in the variance of the vegetation C density (b). Plant characteristics include C sink (trees + woody debris), mean diameter at breast height (DBH), and mean tree height.
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Table 1. Stand characteristics of forest communities during the different succession stages on Xinglong Mountain.
Table 1. Stand characteristics of forest communities during the different succession stages on Xinglong Mountain.
Succession StageStand TypesDominant SpeciesMean DBH (cm)Mean Tree Height (m)Stand Age (a)Stand Density (No. hm−2)Canopy DensityAltitude (m)
S1Broadleaf mixed forestP. davidiana,
B. platyphylla		15.5811.92719700.852285
S2Coniferous–broadleaf mixed forestB. platyphylla,
P. wilsonii		17.6710.19639200.852376
S3Middle-aged P. wilsonii forestP. wilsonii17.0012.678612860.92406
S4Near-mature P. wilsonii forestP. wilsonii36.4722.091453770.652440
Note: DBH represents diameter at breast height.
Table 2. Driving factors of the ecosystem C density during the different succession stages of the forests on Xinglong Mountain.
Table 2. Driving factors of the ecosystem C density during the different succession stages of the forests on Xinglong Mountain.
Driving FactorsThe Succession Stages of Forests
S1S2S3S4
Mean DBH (cm)15.58 ± 0.19 b17.67 ± 0.81 b17.00 ± 0.88 b36.47 ± 0.71 a
Mean height (m)11.72 ± 0.15 b10.19 ± 0.38 c12.67 ± 0.65 b22.09 ± 0.43 a
Litter input (g/(m2 a))465.18 ± 2.90 b494.07 ± 12.78 b612.24 ± 58.99 a475.63 ± 21.78 b
Litter C/N29.03 ± 1.04 c34.18 ± 1.00 b39.34 ± 1.19 a41.25 ± 1.68 a
Soil0–20cm C/N10.87 ± 0.43 b11.02 ± 0.10 b11.90 ± 0.38 b12.96 ± 0.19 a
Soil20–100cm C/N10.67 ± 0.2011.48 ± 0.7610.48 ± 0.7511.41 ± 0.70
Soil0–20cm TC (%)8.39 ± 0.919.50 ± 0.628.95 ± 0.597.55 ± 0.69
Soil20–100cm TC (%)3.31 ± 0.28 ab2.89 ± 0.41 ab2.12 ± 0.41 b4.09 ± 0.82 a
Soil0–20cm TN (%)0.76 ± 0.05 a0.86 ± 0.05 a0.75 ± 0.03 a0.58 ± 0.05 b
Soil20–100cm TN (%)0.31 ± 0.02 ab0.26 ± 0.04 ab0.20 ± 0.04 b0.35 ± 0.05 a
Note: DBH represents mean diameter at breast height; TC represents total C; TN represents total nitrogen. S1, S2, S3, and S4 represent mixed P. davidiana–B. platyphylla forest, mixed B. platyphylla–P. wilsonii forest, middle-aged P. wilsonii forest, and near-mature P. wilsonii forest, respectively. Different lowercase letters indicate significant differences (p < 0.05) among the four succession stages.
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Zong, W.; Chen, Z.; Ma, Q.; Ling, L.; Zhong, Y. Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus. Atmosphere 2025, 16, 890. https://doi.org/10.3390/atmos16070890

AMA Style

Zong W, Chen Z, Ma Q, Ling L, Zhong Y. Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus. Atmosphere. 2025; 16(7):890. https://doi.org/10.3390/atmos16070890

Chicago/Turabian Style

Zong, Wenzhen, Zhengni Chen, Quanlin Ma, Lei Ling, and Yiming Zhong. 2025. "Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus" Atmosphere 16, no. 7: 890. https://doi.org/10.3390/atmos16070890

APA Style

Zong, W., Chen, Z., Ma, Q., Ling, L., & Zhong, Y. (2025). Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus. Atmosphere, 16(7), 890. https://doi.org/10.3390/atmos16070890

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