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Essay

Short-Term Effects of Tunnel Construction on Soil Organic Carbon and Enzyme Activity in Shrublands in Eastern Tibet Plateau

by
Xiaodong Wang
1,2,†,
Yang Xiao
1,2,†,
Xinrui Luo
3,
Chenyu Ye
1,
Yuzhuo Chen
1,
Jincheng Xiang
1,
Ningfei Lei
1,
Ci Song
4,
Xiangjun Pei
2,* and
Xiaolu Tang
1,2,*
1
State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
2
College of Ecology and Environment, Chengdu University of Technology, Chengdu 610059, China
3
College of Earth Science, Chengdu University of Technology, Chengdu 610059, China
4
China Railway Eryuan Engineering Group Co., Ltd., Chengdu 610031, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sustainability 2023, 15(6), 5107; https://doi.org/10.3390/su15065107
Submission received: 30 January 2023 / Revised: 6 March 2023 / Accepted: 8 March 2023 / Published: 14 March 2023
(This article belongs to the Special Issue Carbon Sequestration in Terrestrial Ecosystems)
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Abstract

:
Soil is the largest carbon pool, and our understanding of soil organic carbon (SOC) has been enhanced due to its role in mitigating climate change. However, fundamental uncertainty remains about the quantitative importance of tunnel excavation, one of the most common practices for road construction in mountainous areas, on the SOC dynamics. Therefore, the short-term effects of tunnel construction on SOC and its fraction, soil microbial carbon, and soil enzyme activity within 0–20 cm in two shrublands (dominated by Quercus aquifolioides and mixed with Q. aquifolioides, Rhododendron phaeochrysum and Betula platyphylla, respectively) in Eastern Tibet Plateau were investigated. The results showed that, regardless of vegetation type, SOC, dissolved organic carbon, and easily oxidizable carbon were 27.14 ± 2.87, 6.70 ± 0.74, and 0.29 ± 0.10 g kg−1 for tunnel-affected area of Q. aquifolioides and 47.96 ± 17.89, 11.19 ± 2.92, and 0.24 ± 0.04 g kg−1 for the mixture of Q. aquifolioides, R. phaeochrysum, and B. platyphylla, respectively. The values were not significantly different from those of tunnel unaffected areas (p > 0.05). Similarly, soil enzymes (except cellulase) were not significantly different between tunnel-affected and unaffected areas (p > 0.05), indicating that tunnel construction had a minor impact on the SOC fractions and soil enzymes in the early stage. The unchanged SOC and enzyme activities may be associated with no changes in vegetation production and soil water content in tunnel-affected areas. However, vegetation type had a significant impact on SOC and its fractions and soil enzymes (p < 0.05), demonstrating the importance of vegetation control on the SOC fraction and soil enzymes. This study would be one of the earliest studies to explore the effects of tunnel construction on soil carbon dynamics based on field experiment, which could provide a new concept on environmental sustainability during tunnel construction. However, a long-term study is encouraged to detect the effects of tunnel construction SOC and soil enzymes in the future.

1. Introduction

With the rapid development of the economy and transportation industry in China, in the past decades, more than 10,000 tunnels were built or are still being built. Since most areas in China are mountainous or hilly, tunnels are the most efficient way for road construction [1,2]. However, changes in the process of groundwater drainage caused by tunnel excavation could directly or indirectly affect soil and vegetation, such as the decrease in soil water content (SWC), destruction of vegetation root growth [3], and microbial communities [4], all of which have the potential to affect soil organic carbon (SOC) content [5]. Therefore, studying the SOC dynamics after tunnel construction has become a research focus for ecologists and can provide scientific evidence for environmental protection.
SOC represents the largest carbon reservoir of terrestrial ecosystems and plays an important role in the global carbon cycle by sequestering the carbon for long times in the soil and also releasing carbon dioxide in the atmosphere as a result of heterotrophic respiration [6,7,8]. However, SOC varies greatly due to complex terrain and climate conditions, land use, vegetation cover, and parent materials of the soil [9,10]. For example, decreasing soil water content caused by tunnel excavation may lead to a decrease in SOC and its fractions by accelerating aerobic microbial activities. Although SOC plays an important role in soil physicochemical cycling, soil labile carbon fractions, i.e., dissolved organic carbon (DOC), easily oxidized carbon (EOC) and microbial biomass carbon (MBC), are more sensitive to soil disturbance than SOC [11,12,13,14]. As one of the most important fractions of SOC, soil labile organic carbon is easily oxidized and decomposed by microorganisms [15], which can directly participate in soil biochemical transformation processes and provide energy for microbial activities [16]. Therefore, soil labile carbon fractions are considered as good predictors for SOC changes [17]. Moreover, groundwater loss caused by tunnel excavation leads to significant changes in vegetation groundwater absorption [1] and leaf morphology [18], drought and defoliation [19], and even vegetation death [20]. When subjected to anthropogenic damage, vegetation litter, as a source of SOC, may potentially affect the quantity and quality of organic matter input and the leaching of dissolved organic matter, thus regulating the SOC content [21]. Although previous studies have explored the effects of tunnel construction on soil quality [22,23], most of the studies were focused on tunnel drainage [24] and vegetation water use strategies [1,3], while less attention has been paid to exploring the effects of tunnel construction on the SOC dynamics, particularly in fragile ecosystems in the Tibetan Plateau.
Soil enzymes, produced by microorganisms, plant or animal activity, are important indicators of soil biological activity and are involved in various biological and chemical processes [5,25]. Because soil enzyme activities are sensitive to environmental changes, they are often used as an indicator to evaluate soil properties [26]. In addition, soil enzymes are closely related to the decomposition and transformation of SOC, nutrient cycling, energy transfer, and environmental quality [27]. For example, soil sucrase and cellulase are involved in the decomposition of cellulose compounds present in plant residues [28,29]. Catalase and polyphenol oxidase facilitate the degradation of lignin and release of nutrients available to plants, and thus they regulate carbon cycling [30]. Soil oxidative enzymes have been shown to be sensitive to soil pH and other soil properties [31]. In the process of tunnel construction, soil environment and groundwater circulation are greatly affected. The changes of soil structure and environmental conditions have an important influence on the dynamic changes of soil microbial activity, biomass and diversity, enzyme activity, and other microbial biochemical processes [32,33]. Kivlin and Treseder [30] found that water content had a remarkable effect on soil enzyme activities, and too high or too low soil water content would inhibit soil enzyme activities. Drainage during tunnel construction will reduce soil moisture content, which directly or indirectly affects soil enzyme activities. Although previous studies have shown that tunnel construction resulted in the decrease in soil water content and changed soil microbial community [34], few studies have focused on the effects of tunnel construction on soil enzyme activities. Therefore, studying soil enzymes could help us understand the early changes in soil environment in response to ecosystem disturbances.
The Tibetan Plateau (TP), the “third pole” of the Earth, is the highest and largest plateau in the world [35]. The TP stores 7.4 Pg SOC with an average density of 6.5 kg C m−2 in the top 1 m of the soil and plays a key role in organic carbon accumulation [35,36]. The alpine shrubland is a dominant ecosystem on the plateau [37]. Loss or degradation of vegetation due to climate change and human activities has resulted in a remarkable decline in SOC [38]. In recent years, massive, large road projects have been conducted in the Tibetan Plateau, e.g., Qinghai–Tibet Railway and Shanghai-Nyalam Road, which might lead to significant impact on soil and vegetation. However, how giant road construction affects SOC and soil enzyme activities has not received enough attention, particularly in the Tibetan Plateau. Therefore, the short-term effects of tunnel construction on SOC and its fractions and soil enzyme activities were examined in this study. Since the SOC fractions and soil enzymes are very sensitive to environmental changes [5,15], it is hypothesized that tunnel construction had a significant impact on SOC and soil enzymes because up to more than 50,000 m3 belowground water loss per day during the tunnel construction. The outcomes are expected to provide effective scientific guidelines for sustainable environmental protection in the regions affected by tunnel construction in the TP.

2. Materials and Methods

2.1. Study Area

The study was conducted in the eastern edge of the Tibetan Plateau, Southwest China (Figure 1). The regional climate is characterized by a subtropical monsoon climate with the average annual precipitation of 950 mm (over 70% of precipitation occurring during the rainy season from May to August) and the mean annual air temperature of 7 ℃. The study area is located in the southwest edge of the transition between the Sichuan Basin and the Tibetan Plateau and belongs to the alpine and very alpine tectonic denudation geomorphic area. The dominant plant species are Quercus aquifolioides, Rhododendron phaeochrysum, and Betula platyphylla and the tunnel excavation started in December 2020 and plans to finish within 10 years. The depth of the tunnel was about 80 m with up to 50,000 m3 belowground water loss per day during the tunnel construction.

2.2. Experimental Design and Soil Sampling

To investigate the impact of tunnel construction on SOC and soil enzymes, two sites were selected in tunnel-affected areas (named TA1 and TA2) between August and September in 2021 (Figure 1). Before the tunnel construction, no visual disturbance was observed according to local residents and remote sensing images. Meanwhile, two sites were also selected in non-tunnel-affected areas as the control (CK1 and CK2), which was about two kilometers away with similar site conditions, elevation, and same vegetation type. TA1 and CK1 were dominated by Q. aquifolioides, and TA2 and CK2 were mixed with Q. aquifolioides, R. phaeochrysum, and B. platyphylla. More specifically, first, a preliminary investigation of potential study sites around the tunnel was carried out. Then, to determine whether the selected sites could be representative of the geographic area, we decided which should meet the following two requirements: (a) the sites were not damaged by humans and were at least more than 100 m away from the entrance of the construction tunnel, and (b) the site community structure and species composition should be relatively homogeneous.
Three replicate plots with a radius of 5 m were set within each site, and a buffer zone at least five meters was set between two nearby plots. Soil and vegetation sampling locations were set at three directions of 0°, 120°, and 240° and were 2.5 m away from plot center within each plot to reduce the bias from human’s randomization. Within each direction, a subplot of 100 cm × 100 cm was set for vegetation and soil sampling (topsoil: 0–20 cm). The soil samples were mixed from three sampling locations within each plot and a total 300–500 g of fresh soil was placed in a sealed bag and transferred to the car refrigerator for storage at 4 ℃. At the same time, 70–100 g of soil with stones and roots removed was placed in an aluminum box, which was brought back to the laboratory and dried at 105 ℃ to a constant weight to determine soil water content (SWC). Similarly, vegetation samples were dried at 65 ℃ to a constant weight to calculate aboveground biomass. In the laboratory, soil samples were passed through a 2 mm sieve and then divided into two sub-samples: one for SOC, EOC analysis and the other one for soil enzyme analysis, DOC, and MBC analysis storing at 4 ℃. Soil physical and chemical properties are presented in Table 1 and these physical and chemical properties were not significantly different at p = 0.05.

2.3. Laboratory Analyses

SOC was determined using external heating methods (the K2Cr2O7 volumetric method) [39]. Specifically: 0.1–0.5 g air dried soil samples was digested by 5 mL K2Cr2O7 solutions with a concentration of 0.8 mol L−1 and 5 mL concentrated H2SO4 (1.84 g mL−1) at 170–180 °C for 5 min. Then the digested solution was titrated with 0.2 mol·L−1 FeSO4 solution mixed with 15 mL concentrated H2SO4 per litter to prevent oxidation.
The DOC content was measured using an automatic analyzer for the SOC samples [40]. Specifically, 10 g air—dried soil sample was added with distilled water in the ratio of water to soil 2:1 at 25 °C. After 30 min of shaking under constant temperature, the samples were filtered through a 0.45 µm filter membrane and the filtrate was measured directly. The filtrate was measured directly on a TOC—1020 A organic carbon analyzer (Elementar, Langenselbold, Germany).
EOC content was determined using 333 mmol L−1 K2SO4 oxidation-colorimetry method [41]. Three soil samples containing 15 to 30 mg of carbon were put into a 100 mL plastic bottle, and the soil suspension was obtained by shaking and reacting with 333 mmol·L−1 KMnO4 solution at 25 r·min−1 for one hour, and then centrifuged at 4000 r·min−1 for 5 min and diluted with distilled water. The 565 nm UV absorbance of the extracts was determined by ultraviolet visible spectrophotometer.
MBC was measured by chloroform fumigation as described by Vance, et al. [42]. The fresh soil samples (sieving < 2 mm, equivalent to 5 g dry weight) were fumigated with chloroform for 24 h and 40 mL L−1 K2SO4 was added and shaken for 30 min (300 r·min−1). Next, 10 μL extracted solution was transferred into the automatic total organic carbon (TOC) analyzer (enviro TOC, Langenselbold, Germany) for the MBC content.
Soil sucrase and cellulase activity were analyzed by 3, 5-dinitrosalicylic acid colorimetric method [43]. A total of 5 g fresh soil, 15 mL of 8% sucrose solution, 5 mL of phosphate buffer solution at pH 5.5, and 5 drops of toluene were used. After incubation for 24 h at 37 °C, 0.5 mL aliquot was transferred to a 50 mL volumetric bottle and soil sucrase activity was measured by spectrophotometer at 508 nm. Soil cellulase activity was analyzed by using 10 mL of 1% carboxymethyl cellulose solution, 2.5 mL of phosphate buffer solution with pH 5.5, and 0.75 mL of toluene. After incubation at 37 °C for 72 h, it was measured at 508 nm by spectrophotometer. Soil polyphenol oxidase and catalase were determined by the enzyme standard method [44]. Sample suspensions were prepared by adding 0.15 g soil to 1 mL of 50 mM, pH 5.0, acetate buffer and shaken for 1 min with a small mixer. Then 250 µL of supernatant was pipetted into the corresponding well of a clear colorimetric plate and analyzed by measuring absorbance at 450 nm.

2.4. Calculation of Soil Carbon Pool Management Index

The carbon management index (CMI) was calculated according to [41]:
C M I = C P I × L I × 100
where CPI is the carbon pool index and LI is the lability index. The CPI and the LI are calculated as follows:
C P I = S O C s a m p l e S O C r e f e r e n c e
L I = L s a m p l e L r e f e r e n c e
where L refers to C lability:
L = K M n O 4 − C S O C − K M n O 4 − C
The mean of the two control samples (No tunnel influence area) was used as the reference with a CMI defined as 100. TheKMnO4—C was considered as the portion of SOC that was oxidized by 333 mM KMnO4 in the chemical oxidation method. The concentration of non-KMnO4—C was estimated from the difference between the total organic C pool and the KMnO4—C.

2.5. Statistical Analysis

Two-way analysis of variance was used to test the effects of tunnel construction and vegetation type on SOC, its fractions and enzyme activities. The Pearson correlation analysis was conducted to determine the correlations among environmental variables. All statistical analyses were carried out using R 4.1.1.

3. Results

3.1. Effects of Tunnel Construction on SOC and Its Fractions

The SOC, EOC, and DOC contents were 27.14 ± 2.87, 6.70 ± 0.74, and 0.29 ± 0.10 g kg−1 for TA1, and 47.96 ± 17.89, 11.19 ± 2.92, and 0.24 ± 0.04 g kg−1 for TA2 (Figure 2), and tunnel construction had no significant effect on the SOC, EOC, DOC contents. The MBC contents of TA2 (0.58 ± 0.05 g kg−1) and CK2 (0.86 ± 0.06 g kg−1) were significantly different (Figure 2D, p = 0.029). In contrast, vegetation type had significant effects on SOC, EOC, and MBC except for DOC (Table 2). The SOC, EOC and MBC contents of mixed shrublands were significantly higher than those of Q. aquifolioides shrubland (Figure 2). However, the interactions of tunnel construction and vegetation type had no significant effect on the SOC, EOC, DOC and MBC contents.

3.2. Effects of Tunnel Construction on Carbon Pool Management Index

The CMI embodies the comprehensive measurement of SOC in terms of quantity and quality. The CMI can be used as a more sensitive indicator in response to changes in soil management. Consistent with SOC, the CMI did not differ from the tunnel-affected area and non-tunnel-affected area (Figure 2E). Similarly, vegetation type and the interactions of tunnel construction and vegetation type did not affect the CMI (Table 2).

3.3. Effect of Tunnel Construction on Soil Enzyme Activity

Soil cellulase content of TA1 was 0.31 ± 0.18 mg g−1 24 h−1, which was significantly lower than that of CK1 (0.70 ± 0.40 mg g−1 24 h−1, p < 0.001, Figure 3B). Tunnel construction had no significant effect on sucrase, polyphenol, and catalase. However, the sucrase, polyphenol, and catalase contents of Q. aquifolioides shrubland were 14.82, 0.06, 0.62 mg g−1 24 h−1, which is significantly lower than those of mixed shrublands (Figure 3, 48.82, 0.18 and 1.09 mg g−1 24 h−1, respectively). The interactions of tunnel construction and vegetation type did not affect sucrase, polyphenol, and catalase except for cellulase (Table 2).

3.4. Correlations between SOC Fraction and Soil Enzyme Activity

SOC significantly positively correlated with SWC, and EOC, DOC were significantly positive correlated with cellulase, catalase, SWC, and AGB (Table 3). However, no significant correlation was found for MBC and soil carbon fraction and soil enzymes. Meanwhile, EOC was positively correlated with DOC. Cellulase was significantly positively correlated with catalase, SWC, and AGB.

4. Discussion

4.1. SOC Changes

Tunnel construction had no significant effect the SOC content (p = 0.796, Table 2). Our result was different from previous reports, that forest road construction significantly reduced the SOC content in mountainous catchment [23]. Tunnel construction could affect SOC by changing vegetation production and litterfall, the main source of SOC [1,45], and cause surface water to dry up and groundwater to fall, leading to a decrease in soil moisture, which may change soil structure and reduce the decrease in SOC and nutrient content [22,46]. Furthermore, the destruction or death of vegetation roots caused by the drop of groundwater level will affect the normal growth of vegetation and litter amount, thus reducing carbon input into soil [47]. However, in this study area, the main species were Q. semicarpifolia and B. platyphylla mixed shrubland, which were typical vigorous and drought tolerant. The results showed that there was no significant difference in SWC between tunnel-affected areas and non-affected areas (Table 1). This result may be associated with the short-term effect of tunnel construction because of the tunnel construction in December 2020, which might lead to a minor impact on soil moisture and vegetation growth, and a long-term study is encouraged. In addition, the significant and positive correlation between SOC and SWC (Table 3) further support that tunnel excavation had no effect on the SOC content.

4.2. Change in SOC Fractions Content

EOC and DOC were significantly positively correlated with SWC and AGB (r = 0.71–0.85, Table 3), while SWC and AGB in the tunnel-affected areas were not significantly different from those in the non-tunnel-affected area (p > 0.05, Table 1). This was different from previous studies, which showed tunnel construction significantly affected soil organic matter. This result may be associated with the fixation and distribution process of photosynthetic carbon in plant–soil systems, which significantly affects the dynamic change of SOC pool [48]. To cope with drought stress, the closure of leaf stomata will lead to the decline of photosynthesis [49] and reduce vegetation biomass [50]. EOC and DOC mainly derive from plant residues and litters. However, this study area was located at the high altitude, where the annual sunshine can reach about 1689.9 h (the data were from weather stations stalled in the study area). The strong and abundant light also improves the photosynthetic transformation of plants, which accumulates more biomass.
MBC is considered as a current soil monitoring index because of its rapid response and high sensitivity to environmental changes [51]. However, tunnel construction significantly affected MBC. The underground root system of plants is one of the factors affecting the quantity and activity of microorganisms. For example, Ma, et al. [52] showed that root biomass was one of the reasons for MBC change. Based on the water absorption strategies of plants in two seasons (rainy season and dry season) during tunnel excavation, Liu, Shen, Wang, Duan, Wu, Peng, Wu and Jiang [3] conclude that under the condition of water shortage, plant roots would change to cope with the reduced soil water by tunnel excavation, which would change the residual input of plant roots in the upper soil, thus affecting the content of MBC. Although the results showed no significant effect of tunnel construction on SWC (Table 1), changes in MBC may be related to plant roots. In addition, microorganisms are also affected by the quantity and quality of root exudates secreted by specific species, soil physical and chemical properties, and climatic conditions [53]. Therefore, changes in MBC may be due to other factors.
Different vegetation types have different biomass and litterfall; thus, the decomposition and conversion rate of carbon input into soil are different [54], and the vegetation type had significant effect on SOC and its fractions in this study. The increase in vegetation diversity will increase the SOC input from vegetation, which will increase the SOC. Thus, the SOC and its fractions of mixed shrublands were higher than that of pure shrubland of Q. aquifolioides.

4.3. Changes in Soil Enzyme Activities

There were no significant differences in sucrase, polyphenol, and catalase at tunnel-influenced and non-tunnel-influenced (p > 0.05, Table 2), indicating that tunnel excavation had no effect on soil enzyme activities. This is contrary to the results of Wang, Jiang, He, Fan, He and Wu [34], who showed that tunnel construction affected the metabolic efficiency of soil microbial communities. Because tunnel construction affects plant growth and soil quality indirectly by reducing soil moisture, and plants can influence soil microbial communities through plant leaves and litter [55]. Soil microbial community is closely related to soil enzyme activities. The difference of litter input and decomposition rate will affect the quality and quantity of soil enzyme substrates [56]. In addition, soil moisture affects biological activities and metabolism, and it is also the main factor limiting soil enzyme activities [57]. However, in this study, we did not find that tunnel construction had an effect on soil moisture and plant biomass (Table 1); thus, the results proved that tunnel construction had no effect on soil sucrase, polyphenol, and catalase. On the other hand, SOC accumulation can significantly improve soil biological and chemical properties, which will increase the number of microbial diversity and the number of secreted enzymes [58]. Ma, Li, Wu, Xu and Wu [52] showed that the soil enzyme adhered to organic carbon and its fractions to form humus–protein complexes, thus protecting the enzymes from decomposition. Therefore, the lack of significant change in SOC can also be considered as one of the reasons that soil enzyme activities are not affected by tunnel construction.
Cellulase is a soil hydrolase that is involved in SOC decomposition and the release of reducing sugars as the end-product of the C cycle [59]. The cellulase content of TA1 was 55.32% lower than that of CK1 in this study (Figure 3B). Dodor and Tabatabai [60] found that a water deficit increased apoplankton production and stimulated soil enzyme activity. However, excessive moisture conditions can significantly inhibit soil enzyme activity by altering microbial communities and increasing the concentration of inhibitors such as Fe2+ [61]. However, our results show that there is no significant difference in SWC between the TA1 and CK1 (Table 1), and there was a significant positively correlation between cellulase and soil organic carbon fractions, SWC and AGB (Table 3). In addition, changes in soil enzyme activity are related to soil chemical properties, plant diversity, climatic topographic conditions, moisture, and aggregates [33,62,63]. These interactions are extremely complex. At present, the cause of cellulase change in the affected area of the tunnel remains unclear due to the short time of tunnel construction.
Vegetation coverage and plant diversity had important effects on enzymes [64]. Vegetation types had significant effect on soil enzyme activities (Table 2). Higher plant diversity has higher soil enzyme levels [5]. Therefore, soil enzyme activity of mixed shrublands was higher than that of Q. aquifolioides shrubland. Future studies should focus on the causes and mechanisms of changes in SOC and enzyme activities over long-term periods after tunnel excavation.

5. Conclusions

This study showed that SOC, SOC fraction, and soil enzymes were not altered by tunnel construction significantly. However, vegetation type had a significant impact on the SOC fraction and soil enzymes, highlighting the importance of vegetation control on the SOC fraction and soil enzymes. These findings can provide important scientific evidence for the sustainability of the fragile environment in the TP and also establish a closer link between human development and environment protection. However, a long-term study is still encouraged to explore the impact of tunnel construction on SOC and soil enzymes.

Author Contributions

Conceptualization, X.W., C.Y., X.P. and X.T.; formal analysis, X.W., X.L. and X.T.; investigation, X.W., Y.X., Y.C., J.X. and X.T.; methodology, X.W., Y.X., X.L., N.L. and X.T.; software, X.W., X.L., C.Y. and X.T.; validation, X.W., Y.C., J.X. and X.T.; visualization, X.W. and X.T.; writing—original draft, X.W. and X.T.; writing—review and editing, X.W., Y.X., X.L., C.Y., Y.C., J.X., N.L., C.S., X.P. and X.T.; project administration, Y.C. and J.X. supervision, Y.C. and J.X. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Everest Scientific Research Program of Chengdu University of Technology (80000-2022ZF11410); State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2018Z004, SKLGP2021K024); influence of Sichuan–Tibet railway tunnel project on typical forest ecosystem (KDNQ213070); Research on key technologies of mountain rail transit green construction in ecologically sensitive region based on mountain rail transit from Dujiangyan to Mt. Siguniang anti-poverty project (2018-ZL-08).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Figure 1. Location of the study sites. TA1: tunnel-affected areas 1, CK1: non-tunnel-affected areas 1, TA2: tunnel-affected areas 2, CK2: non-tunnel-affected areas 2.
Figure 1. Location of the study sites. TA1: tunnel-affected areas 1, CK1: non-tunnel-affected areas 1, TA2: tunnel-affected areas 2, CK2: non-tunnel-affected areas 2.
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Figure 2. Changes in soil organic carbon fractions in tunnel−affected and non−affected areas. The error bars mean standard error (n = 3). SOC (A): soil organ carbon; EOC (B): easily oxidizable carbon; DOC (C): dissolved organic carbon; MBC (D): microbial carbon. CMI (E): carbon management index. TA1: tunnel−affected areas 1, CK1: non−tunnel−affected areas 1, TA2: tunnel−affected areas 2, CK2: non−tunnel−affected areas 2. The same below.
Figure 2. Changes in soil organic carbon fractions in tunnel−affected and non−affected areas. The error bars mean standard error (n = 3). SOC (A): soil organ carbon; EOC (B): easily oxidizable carbon; DOC (C): dissolved organic carbon; MBC (D): microbial carbon. CMI (E): carbon management index. TA1: tunnel−affected areas 1, CK1: non−tunnel−affected areas 1, TA2: tunnel−affected areas 2, CK2: non−tunnel−affected areas 2. The same below.
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Figure 3. Changes in soil enzyme activities ((A): Sucrase, (B): Cellulase, (C): Polyphenol, (D): Catalase) in tunnel−affected and non−affected areas.
Figure 3. Changes in soil enzyme activities ((A): Sucrase, (B): Cellulase, (C): Polyphenol, (D): Catalase) in tunnel−affected and non−affected areas.
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Table
Table 1. Soil physical-chemical properties and aboveground biomass of study sites (n = 3).
Table 1. Soil physical-chemical properties and aboveground biomass of study sites (n = 3).
VariablespHSWC (%)TN (g kg−1)AGB (kg m−2)SBD (g cm−3)
TA14.95 ± 0.07 a0.28 ± 0.01 a1.14 ± 0.02 a1.24 ± 0.06 a0.83 ± 0.04 a
CK14.68 ± 0.07 a0.23 ± 0.03 a1.13 ± 0.29 a1.07 ± 0.14 a0.91 ± 0.05 a
TA24.55 ± 0.10 a0.31 ± 0.02 a2.02 ± 0.08 a0.57 ± 0.04 a0.72 ± 0.04 a
CK24.33 ± 0.06 a0.33 ± 0.02 a2.22 ± 0.25 a0.49 ± 0.05 a0.67 ± 0.05 a
Note: values represent mean and standard error, n = 3. SWC: soil water content; TN: total nitrogen contents; AGB: aboveground biomass, SBD: soil bulk density. TA1: tunnel-affected areas 1, CK1: non-tunnel-affected areas 1, TA2: tunnel-affected areas 2, CK2: non-tunnel-affected areas 2. Means followed by the same letter a not significantly different (p => 0.05) for TA1 and CK1, TA2 and CK2, respectively.
Table
Table 2. p-Values of two−way analysis of the tunnel construction (TC), vegetation type (VT), and their interactions on soil organ carbon (SOC), easily oxidizable carbon (EOC), dissolved organic carbon (DOC), microbial carbon (MBC), and carbon pool management index (CMI), sucrase (SC), cellulase (CL), polyphenol (PPO), and catalase (CAT).
Table 2. p-Values of two−way analysis of the tunnel construction (TC), vegetation type (VT), and their interactions on soil organ carbon (SOC), easily oxidizable carbon (EOC), dissolved organic carbon (DOC), microbial carbon (MBC), and carbon pool management index (CMI), sucrase (SC), cellulase (CL), polyphenol (PPO), and catalase (CAT).
VariablesSOCEOCDOCMBCCMISCCLPPOCAT
TC0.7960.8830.0590.0160.8890.4710.0070.0790.236
VT0.0090.0040.1510.0250.912<0.001<0.0010.0060.037
TC × VT0.8200.8650.6600.3800.8900.514<0.0010.1840.594
Table
Table 3. Correlation coefficients between soil organic carbon and soil enzymes and environmental factors (n = 12).
Table 3. Correlation coefficients between soil organic carbon and soil enzymes and environmental factors (n = 12).
VariablesSOCEOCDOCMBCCMISCCLPPOCATSWC
EOC0.53
DOC0.540.98 **
MBC−0.48−0.53−0.55
CMI−0.100.400.420.01
SC−0.12−0.08−0.02−0.39−0.24
CL0.490.70 *0.72 **−0.370.69 *−0.15
PPO−0.13−0.42−0.420.53−0.230.01−0.47
CAT0.100.75 **0.72 **−0.070.77 **−0.170.77 **−0.27
SWC0.71 **0.78 **0.71 **−0.480.19−0.200.59 *−0.400.39
AGB0.470.85 **0.80 **−0.540.33−0.180.65 *−0.530.66 *0.67 *
Note: * and ** indicate significant correlation at the 0.05 and 0.01 levels, respectively. SOC: soil organ carbon; EOC: easily oxidizable carbon; DOC: dissolved organic carbon; MBC: microbial carbon. CMI: carbon management index, SC: sucrase, CL: cellulase, PPO: polyphenol, and CAT: catalase, SWC: soil water content, AGB: aboveground biomass.
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Wang, X.; Xiao, Y.; Luo, X.; Ye, C.; Chen, Y.; Xiang, J.; Lei, N.; Song, C.; Pei, X.; Tang, X. Short-Term Effects of Tunnel Construction on Soil Organic Carbon and Enzyme Activity in Shrublands in Eastern Tibet Plateau. Sustainability 2023, 15, 5107. https://doi.org/10.3390/su15065107

AMA Style

Wang X, Xiao Y, Luo X, Ye C, Chen Y, Xiang J, Lei N, Song C, Pei X, Tang X. Short-Term Effects of Tunnel Construction on Soil Organic Carbon and Enzyme Activity in Shrublands in Eastern Tibet Plateau. Sustainability. 2023; 15(6):5107. https://doi.org/10.3390/su15065107

Chicago/Turabian Style

Wang, Xiaodong, Yang Xiao, Xinrui Luo, Chenyu Ye, Yuzhuo Chen, Jincheng Xiang, Ningfei Lei, Ci Song, Xiangjun Pei, and Xiaolu Tang. 2023. "Short-Term Effects of Tunnel Construction on Soil Organic Carbon and Enzyme Activity in Shrublands in Eastern Tibet Plateau" Sustainability 15, no. 6: 5107. https://doi.org/10.3390/su15065107

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