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Article

Effects of Exogenous Silicon Addition on Nitrification and Denitrification-Derived N2O Emissions from Moso Bamboo (Phyllostachys edulis) Forest Soil

by
Jie Yang
1,2,†,
Kecheng Wang
1,2,†,
Lijun Liu
1,2,
Yongchun Li
1,2,
Jiasen Wu
1,2,
Jinhuan Zhong
1,
Rong Zheng
3,
Lili Fan
4,
Chengpeng Huang
1,2,* and
Peikun Jiang
1,2,*
1
School of Environmental and Resource Sciences, Zhejiang A & F University, Hangzhou 311300, China
2
Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration, Zhejiang A & F University, Hangzhou 311300, China
3
Fujian Academy of Forestry, Fuzhou 350012, China
4
Research 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.
Land 2025, 14(5), 1004; https://doi.org/10.3390/land14051004
Submission received: 9 April 2025 / Revised: 30 April 2025 / Accepted: 2 May 2025 / Published: 6 May 2025
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Abstract

:
It has been reported that applying silicon (Si) to agricultural soils can reduce N2O emissions. But, we do not fully understand how this might work in forest ecosystems, especially in Phyllostachys edulis plantations. This study set out to determine how exogenous Si impacts soil nitrification and denitrification. Also, it aimed to assess their separate contributions to N2O emissions. A pot incubation experiment that lasted 28 days was carried out under controlled conditions. The soil used was collected from a bamboo plantation that is intensively managed. The treatments included adding silicon. Also, 3,4-dimethylpyrazole phosphate (DMPP) and acetylene (C2H2) were applied to specifically hold back nitrification and denitrification. We measured the rates of soil N2O emissions, the cumulative fluxes, and the concentrations of NH4+-N, NO3−-N, and NO2−-N. A positive correlation that was significant (p < 0.05) was found between N2O emissions and the levels of soil NO3−-N. Adding Si continued to reduce both the emission rate and the cumulative flux in all of the treatment groups. Also worth mentioning is that the relative contribution of denitrification to N2O emissions dropped from 38.2% to 11.4%. Meanwhile, nitrification’s contribution went up from 61.8% to 88.6%. These findings show that adding Si mainly suppresses denitrification. And, by doing so, it lessens N2O emissions in bamboo plantations. This study underlines the potential of Si amendments. They could be used as an effective management strategy to reduce greenhouse-gas emissions in forest soils. It also provides a scientific basis for making Phyllostachys edulis ecosystems more sustainable.

1. Introduction

The emissions of greenhouse gases (GHGs) are on the rise. Also, the concentrations of atmospheric nitrous oxide (N2O) keep going up. These are both major factors contributing to global warming and the increasingly frequent extreme weather events. The increase in N2O concentrations is particularly concerning. Its 100-year global warming potential is about 298 times that of carbon dioxide (CO2) [1]. Also worth mentioning is that when N2O reaches the stratosphere, it can trigger photochemical reactions. These reactions can deplete ozone, which poses a further threat to the stability of the ecosystem [2,3]. By the end of 2022, the global atmospheric N2O concentration had reached 335.8 ppb. This means it had gone up by 24.4% since 1750 [4,5]. This trend will probably continue as economic development and climate change continue. What is more, the rising global temperatures may further worsen the N2O concentration. How? By speeding up soil respiration and thus making N2O release faster [2]. So, it has become very important to come up with effective strategies to reduce N2O emissions. This is crucial in the attempts to ease climate change. Terrestrial ecosystems are the main source of global N2O emissions. They account for around 70% of the total fluxes. Nitrogen (N) fertilizer application is seen as a major cause [6,7,8]. China is the world’s largest producer and user of N fertilizers. From 1978 to 2015, China’s N2O emissions went up by 140%. N2O contributes 9–20% of the nation’s GHG emissions (in CO2 equivalents), which is about 1.8 times the global average [1,9]. Land-use changes, like changing natural forests to managed land, and other strong human interventions, result in soil disturbance and N2O emissions becoming even worse [10,11]. So, forest ecosystems are very important in the global N cycle [12]. Phyllostachys edulis (Ph. edulis, also called Moso bamboo) plantations are present throughout subtropical China. That is because they can adapt well, grow fast in a clonal way, and have high economic value [13]. But, the way they are managed intensively—with a large amount of fertilization, tilling, irrigation, and removal of the understory—has made many Ph. edulis plantations become large sources of soil N2O emissions [14]. In fact, in some bamboo stands that are managed intensively, the annual N2O fluxes can reach 15.8 kg ha−1. That is more than you would see in rice paddies [15,16], soybean fields [17], and even tropical rainforests [18,19].
Silicon (Si), which is one of the most-plentiful non-metallic elements in the Earth’s crust, has drawn a lot of attention. People are interested in its potential to boost both plant growth and soil health [20,21]. As we know, Si is widely recognized for its uses in industries like electronics, construction, and medicine [21,22]. But, its physiological functions in plants are also important. Mainly, Si is absorbed as monosilicic acid (H4SiO4). Then, it is deposited as amorphous silica in plant tissues. This strengthens cell walls and improves gas exchange and nutrient uptake [23,24]. Si can enhance the root oxidative capacity. It can also lessen the uptake of toxic ions and reduce biotic or abiotic stresses [25]. Field trials, such as those in alpine meadows on the Qinghai–Tibet Plateau, have indicated that adding Si can reduce the negative effects of nitrogen fertilization on plant diversity. At the same time, it can increase crop yields [26]. This shows its potential to boost ecological stability in managed ecosystems. Recent research has also pointed out that Si might play a part in controlling soil N2O emissions. For example, when using steel slag fertilizer which contains Si and Fe3+, the N2O emissions were reduced significantly, by 166.2%. This could be because of some synergistic effects [27]. It is worth mentioning that applying Si has also been related to a drop in N2O emissions in agricultural systems [6,28]. It is likely that this happens by improving the nitrogen uptake efficiency [29]. But, it is still not clear if this kind of reduction in emissions also happens in intensively managed forest soils, especially in Ph. edulis plantations. Microbial nitrification and denitrification are usually seen as the two main ways that soil N2O is produced [30]. Nitrification is an aerobic process. It involves oxidizing ammonia to nitrate, and N2O is formed as a byproduct during this process [31]. It is also worth mentioning that denitrification is an anaerobic process. It reduces nitrate to dinitrogen gas (N2), with N2O being an intermediate [32]. Although other processes like nitrifier denitrification, co-denitrification, and dissimilatory nitrate reduction to ammonium can also create N2O [33], many studies have shown that denitrification is a major source of N loss in soils [34,35]. But, only a few studies have determined the relative contributions of these processes to N2O emissions in bamboo plantation soils. And, we do not fully understand to what extent adding Si might change the balance between nitrification and denitrification.
Firstly, this study had the aim of achieving two things: one was to determine just how much nitrification and denitrification contribute to N2O emissions in of the soils of intensively managed Ph. edulis plantations; the other was to see how exogenous Si can control these emissions. All in all, what we found provides a scientific reason for using Si fertilization as a way to reduce greenhouse-gas emissions in Ph. edulis plantations and other forest ecosystems that are under intensive management.

2. Materials and Methods

2.1. Soil Used for Cultivation

The soil used in this study was classified as red soil (Acrisols, WRB FAO taxonomy). It was collected from a Ph. edulis forest. This forest is located in the Sandiejin National Forest Park (119°9′58″ E, 26°14′56″ N), Fujian Province, Southeastern China. The site is characterized by a typical subtropical maritime monsoon climate, with an average annual temperature of 19.6 °C and annual precipitation ranging from 900 to 2100 mm. This Ph. edulis forest has been cultivated primarily for bamboo-shoot production since the 1960s. Management practices in the area include land reclamation, periodic fertilization, grass splitting, harvesting of old culms, and biennial bamboo-shoot digging. Over time, such long-term utilization has led to relatively uniform stand structure and soil characteristics across the landscape. Due to a shortage of local labor, active management was suspended for five years prior to sampling. This shift allowed for the partial recovery of understory vegetation and litter accumulation, potentially influencing soil microbial activity. These site conditions were carefully considered during soil sampling to ensure representative soil characteristics for the experiment.
To make sure that the experimental soil could be representative and the results reproducible, we used a composite sampling strategy. The bamboo plantation has a long history of traditional management. It is made up of naturally propagated Moso bamboo and is located over 50 m away from roads to minimize anthropogenic interference. We set up three sampling zones (5 × 5 m each) on the upper, middle, and lower slopes of the site. In each zone, three sampling points were evenly spread along the diagonals. From each point, about 5.0 kg of topsoil (0–20 cm) was collected. Altogether, the nine sampling points provided around 45 kg of soil. We mixed this soil well and then used it for the incubation experiments. The soil samples were taken to the experimental greenhouse at the Fujian Academy of Forestry. Then, they were split into two parts: one part was used right away for the incubation experiments (refer to Section 2.2, Section 2.3 and Section 2.4) and the other part was dried in the air indoors for storage. We removed stones, plant roots, remains of macrofauna, and other debris by hand. Afterwards, the soil was crushed. It was then passed through a 5 mm mesh to be sieved, mixed up evenly again, and stored in airtight bags for later use. The basic physicochemical properties of this soil are shown in Table 1.

2.2. Soil Incubation

The experiment was conducted using soil amended with urea [CO(NH2)2] as the nitro gen source at a rate of 80 mg kg−1. Two experimental groups were established: one without silicon addition (Si−) and one with silicon addition (Si+), each including four treatments where sodium metasilicate was added at a rate of 25.0 mg kg−1 (dry soil basis). Within each group, four treatments were set up (as detailed in Table 2): (1) control (CK), (2) nitrification inhibitor treatment (DMPP), (3) denitrification inhibitor treatment using acetylene (C2H2), and (4) combined DMPP + C2H2 treatment. Experiments with each treatment were performed in triplicate. The soil moisture was adjusted to 60% water-filled pore space (WFPS) and maintained throughout the experiment. Detailed protocols for reagent preparation, inhibitor application, and moisture control are described in the following sections.

2.3. Experimental Design

For the DMPP inhibition test in the Si− group, 50 g (on a dry weight basis) of air-dried soil was spread evenly on a plastic film. Then, a DMPP solution (1 mg mL−1) was applied uniformly. The dosage was set to correspond to 1% of the nitrogen application rate, which was 80 mg kg−1. After that, the soil was adjusted to 60% WFPS. Next, it was transferred into 500 mL glass incubation bottles with perforated caps. This was to allow gas exchange under aerobic conditions. All samples were weighed and incubated at 25 °C in a controlled incubator (model GXZ-160A, Zhongxin Medical Instrument Co., LTD., Jiaxing, China) for 28 days. Bottle weights were monitored regularly and deionized water was added using a rubber-tipped burette to maintain constant moisture. Gas samples were collected on days 1, 3, 7, 14, and 28 using a negative-pressure syringe at 2 and 6 h after sealing. Destructive soil sampling was conducted concurrently to determine the concentrations of NH4+-N, NO3−-N, and NO2−-N, and the pH. For the C2H2 inhibition test, the same procedure was followed except that, after placing the soil in the bottles, 10% of the headspace air was withdrawn and replaced with acetylene (C2H2) to achieve a partial pressure of 10 kPa; the air–C2H2 mixture was refreshed every 7 days. For the combined DMPP + C2H2 treatment, DMPP was applied in the same way as described above. And, the bottles were treated with C2H2 following the same steps as the C2H2 test.

2.4. N2O Sampling and Analyses

We collected gas samples (20 mL) from the bottle headspace. This was carried out at 2 h and also at 6 h after sealing the bottle. N2O concentrations were measured using gas chromatography (Shimadzu, GC-2014, Kyoto, Japan). Soil N2O emission fluxes (µg kg−1 h−1) were calculated using the following equation:
R = (ρV/G)·(P/P0)·(T0/T)·(dCt/dt)
where ρ is the density of N2O under standard conditions (1.293 × 106 mg m−3), G is the soil mass (g), V is the volume of the chamber headspace (mL), dCt/dt is the rate of change in N2O concentration (ppb h−1), T0 (273.15 K) and P0 (101.325 kPa) are the standard temperature and pressure, and T and P are the actual temperature (K) and atmospheric pressure (kPa) at sampling. Cumulative N2O emissions (mg kg−1) were calculated using the following equation:
Mg = Σ(i=1)n [(R(i+1) + Ri)/2 × (t(i+1) − ti) × 10−3]
where Mg is the cumulative emission, Ri is the emission flux at the ith sampling, and (t(i+1) − ti) is the time interval between consecutive samplings.

2.5. Soil Sampling and Analyses

We used the repeated-measures analysis of variance (ANOVA) to determine the differences in N2O fluxes and soil parameters among the treatments as time passed. Soil total carbon (C) was analyzed via dry combustion using an elemental analyzer (Vario EL III, Elementar, Germany). Soil pH was measured with a digital pH meter (BPH-7100, Bell Instrument Co., Zhengzhou, China) in a 1:5 (w/v) soil–water suspension after 30 min of equilibration. Total nitrogen (N) was determined by the Kjeldahl method using a digestion distillation titration procedure. Available phosphorus was measured using the Bray-1 extraction followed by colorimetric detection at 660 nm with a UV–visible spectrophotometer (TU-1810, Purkinje General Instrument Co., Beijing, China). Available potassium was extracted with 1 mol L−1 ammonium acetate and determined by flame photometry (6400A, Shanghai Yidian Instrument Co., Shanghai, China). Available silicon was extracted with an acetic acid–sodium acetate buffer and measured calorimetrically after a molybdenum blue reaction. The NO2−-N concentrations were determined using the Griess diazotization method with the absorbance measured at 540 nm.
Enzyme activities were determined as follows: urease activity was assayed by measuring NH4+ release after incubation with urea substrate at 37 °C for 2 h; amylase activity was quantified via the 3,5-dinitrosalicylic acid method using starch as a substrate; and nitrate reductase, nitrite reductase, and nitric oxide reductase activities were measured spectrophotometrically by tracking the reduction of NO3− to NO2−, NO2− to NH4+, and NO to N2O, respectively. NH4+-N and NO3−-N concentrations were determined using the indophenol blue and cadmium reduction methods, respectively, as described by Lu [36]. Pearson correlation analysis assessed the relationships between N2O fluxes and soil parameters, with statistical significance set at p < 0.05. All of the data visualizations and plots were created using the software Origin 2022.

2.6. Availability of Materials and Data

All materials, datasets, computer codes, and detailed protocols used in this study are available from the corresponding author upon reasonable request. There are no restrictions on the availability of the materials or information related to this work. If applicable, accession numbers for large datasets will be provided.

2.7. Use of Generative Artificial Intelligence

We did not use any generative artificial intelligence tools in regard to designing the study. Also, we did not rely on them for gathering data. And, for analyzing or interpreting the data, those generative artificial intelligence tools were not used either.

3. Results

3.1. Soil pH and Nitrogen Dynamics

3.1.1. Soil pH

After 28 days of incubation, the soil pH values exhibited similar increasing trends across all treatments (Figure 1). In the Si− group, pH values ranged from 4.83 to 5.08. On average, among the treatments, they ranged from 4.95 to 5.00. In the Si+ group, the pH increased. The increases were from 0.03 to 0.08. During the first 14 days, all of the treatment groups showed a significant rise in pH (p < 0.05). Si application slightly mitigated pH reductions caused by DMPP and C2H2 treatments; however, overall pH differences between Si− and Si+ groups were not statistically significant (p > 0.05).

3.1.2. NH4+-N Concentrations

The concentrations of NH4+-N went up during the first 7 days in all of the treatment groups (Figure 2). In the Si− group, the DMPP treatment resulted in NH4+-N increasing by 64.0% compared to the CK group. The C2H2 treatment resulted in an increase of 17.6%, and the DMPP + C2H2 treatment resulted in an increase of 66.3% (Figure 3a). In addition, in the Si+ group, corresponding increases were 60.0%, 0.5%, and 49.4%. The concentrations of NH4+-N in the DMPP and DMPP + C2H2 treatment groups were significantly higher than those in the CK group (p < 0.05). The addition of Si constantly resulted in a decrease in the concentrations of NH4+-N in all treatment groups by 12.6–25.4% (p < 0.05, Figure 3a). It seems that Si helped the concentrations of NH4+-N to decline.

3.1.3. NO3−-N Concentrations

In the Si− group, NO3−-N concentrations kept on increasing in the CK and C2H2 treatment groups. Then, in the DMPP + C2H2 treatment group, the levels initially rose, but later on, they actually declined (Figure 4). NO3−-N concentrations were reduced by 30.1%, 21.8%, and 58.7% for DMPP, C2H2, and DMPP + C2H2, respectively, relative to the CK group. The Si+ group showed reductions of 14.3–42.6%, with significant differences among treatment groups (p < 0.05, Figure 3b). Si addition effectively suppressed NO3−-N accumulation, particularly under conditions of denitrification inhibition.

3.1.4. NO2−-N Concentrations

NO2−-N concentrations showed variable trends. Generally, they peaked at the end of incubation. But, this was different for the C2H2 treatment, as it peaked on day 7 (Figure 5). The average NO2−-N concentrations were lower in those treatments that involved nitrification and denitrification inhibitors when compared to the CK group (Figure 3c). When Si was added, it significantly suppressed the accumulation of NO2−-N. This was the case in both the CK and C2H2 treatment groups (p < 0.05). It seems there was a selective impact under different inhibition conditions.

3.2. N2O Emission Rates

The rates of N2O emissions were different among the various treatments (Figure 6). In the Si− group, the emission rates reached their highest point between days 7 and 14. The emission rates for the CK and DMPP treatment groups reached their peaks later than those for the C2H2 and DMPP + C2H2 treatment groups. Compared to the CK treatment, the DMPP treatment managed to reduce the emission rates by 35.5%. On the other hand, the C2H2 and DMPP + C2H2 treatments actually increased the rates by 25.9% and 6.1%, respectively. In the Si+ group, the emission rates generally went down. The DMPP and DMPP + C2H2 treatment groups showed significant reductions of 47.8% and 8.0%, respectively (p < 0.05, Figure 3d). In terms of the correlation analysis, this showed that there were significant connections between the N2O emission rates and both soil pH and NH4+-N. But, there were no such significant associations with NO3−-N and NO2−-N concentrations (Figure 7).

3.3. Contributions of Nitrification and Denitrification to N2O Emissions

The cumulative N2O emissions showed quite a difference between the Si− and Si+ treatment groups (Figure 3e). In the Si− treatment group, the cumulative fluxes ranged from 2.71 to 5.62 mg kg−1. Denitrification and nitrification contributed 38.2% and 61.8%. When Si was added, it reduced the cumulative fluxes to 2.39–4.58 mg kg−1. And, it also changed the relative contributions. The contribution from denitrification became 11.4% and that from nitrification was 88.6%. This shows that applying Si strongly sup-pressed the N2O emissions that came from denitrification. It also shifted the dominant source of these emissions towards nitrification. These results have made it clear that adding Si significantly reduced N2O emissions. And, it did this mainly by suppressing denitrification.

4. Discussion

4.1. Effect of Silicon Addition on Soil Nitrogen Transformation

Nitrification and denitrification are particularly important microbial processes in the N cycle. They have a large impact on soil N availability and environmental N losses. This is especially true when it comes to NO3−-N leaching and the gaseous emissions of N2O [37,38]. These biochemical reactions are easily affected by many environmental factors. For example, factors like soil pH, temperature, oxygen availability, and the structure and activity of the microbial community can all have an impact [13,39,40,41]. In our study, the soil pH kept increasing during the incubation period for all of the treatments. There was no significant difference observed between the groups where Si was added and the control group. So, it seems that the changes in soil pH that we observed might be due to intrinsic buffering processes. They probably do not result from the effects of added N or Si.
It is worth noting that the bamboo plantation included in this study had been under less-intensive management for about five years before the soil was collected. Occasional harvesting of bamboo shoots still occurred. But, activities like fertilization and tillage, which are active interventions, had been stopped. This semi-abandonment situation probably caused surface litter and organic matter to pile up. It may also have changed the soil microclimate. How? By making the soil hold more moisture and reducing the disturbance to the soil [42]. These changes could have influenced the microbial activity and the balance between nitrification and denitrification processes, potentially increasing anaerobic microsites favorable for denitrifiers. Although our incubation experiment controlled for moisture and temperature, the legacy effects of this reduced management on the soil microbial community structure cannot be completely excluded. Further studies that incorporate field microbial assessments are warranted to fully understand the long-term ecological impacts of management cessation on bamboo plantations.
The results showed that when the nitrification inhibitor DMPP was applied, the NH4+-N concentrations became significantly elevated, increasing by around 64.0%. Meanwhile, the NO3−-N and NO2−-N concentrations significantly decreased. This was in line with the results of previous studies [42,43]. Also worth mentioning is the inhibitory effect of DMPP on ammonia oxidation processes and nitrifier microbial communities. This probably led to the observed NH4+-N accumulation. Also, it likely caused the diminished NO3−-N production, as stated in [44].
The C2H2 treatment also increased the NH4+-N concentration. At the same time, it decreased the NO3−-N concentration. This was because C2H2 had dual inhibitory effects on both bacterial and fungal nitrification processes. However, it was known to suppress the reduction of N2O to N2 during denitrification, as stated by the authors in [45,46]. The combined DMPP + C2H2 treatment further amplified NH4+-N accumulation and decreased NO3−-N and NO2−-N concentrations markedly, highlighting the dominant inhibitory impact of DMPP on nitrification relative to the partial inhibitory effect of C2H2 on denitrification [47,48].
When Si was added, we saw significant decreases in the concentrations of NH4+-N, NO3−-N, and NO2−-N in nearly all of the treatments. Previous reports have indicated that Si application enhances nitrogen uptake in Ph. edulis, thereby reducing available inorganic nitrogen [49]. However, the absence of plants in this incubation experiment implies that these decreases reflect microbial immobilization and altered N transformation processes, which is in agreement with recent findings [50,51]. Also worth mentioning is that Si’s effect was particularly obvious in the treatments where denitrification was inhibited. This shows that Si has a large impact on denitrification and the related microbial activities. It would be a good idea to carry out more studies in the future that look at the interactions between plants, soil, and microbes. That way, we can fully understand how Si affects nitrogen dynamics.

4.2. Effect of Silicon Addition on Soil N2O Emission Rate

The N2O emission rates vary considerably across different treatments. This shows that soil microbial activity can respond quite significantly to environmental and biochemical conditions [52,53]. When compared to the CK group, the DMPP treatment decreased the average N2O emission rates by a significant 41.9%. On the other hand, the C2H2 treatment caused emissions to increase. This is likely to occur because it stops N2O from being reduced to N2 during denitrification [45,52]. The treatment that caused dual inhibition (DMPP + C2H2) produced intermediate results. This shows that there are complex interactions occurring between the nitrification and denitrification pathways.
Importantly, when Si was added, there was a significant overall reduction in N2O emissions across the different treatments. This was especially obvious in the denitrification-inhibited scenarios. Initially, in the dual-inhibition treatment without Si, there was a slight emission increase of 6.1%. But then, after adding Si, there was a substantial emission decrease of 8.0%. This shows that Si has the potential to lessen N2O release by affecting both the nitrification and denitrification pathways. Also worth mentioning is that these reductions match up with previous findings. It seems that Si might change the soil microbial communities and reduce the availability of NO3−-N and NO2−-N. As a result, it restricts the substrate availability for N2O production [54]. These results highlight Si as a promising additive for reducing greenhouse-gas emissions from forest plantation soils. However, long-term field trials are still needed to confirm these laboratory observations and determine the practical implications.

4.3. Relative Contribution of Nitrification and Denitrification to Soil N2O Emissions

The relative contributions of nitrification and denitrification to soil N2O emissions differ considerably depending on the environmental conditions and ecosystems [17]. Usually, denitrification is the main process occurring in anaerobic systems like wetlands and rice paddies. Also worth mentioning is that nitrification is more common under aerobic conditions, which are typical of upland soils, such as forest plantations [9,12,41].
We found out that nitrification is the main process that produces N2O in Ph. edulis plantation soils. It accounts for around 61.8% of the total emissions under standard conditions. Furthermore, the dominance of nitrification probably indicates the soil’s usual aerobic condition and its effective drainage as well as structure. These are the typical features of these plantation ecosystems [55]. We can presume initially that the soil conditions play a role in nitrification. But, when we look deeper, it becomes clear that these characteristics are indeed what make nitrification so dominant in these ecosystems [55].
Notably, the application of Si caused the relative contribution of nitrification to N2O production to increase to around 88.4%. And, it also decreased the contributions from denitrification quite significantly. This shows that when Si is added, it suppresses denitrification much more than nitrification. A likely reason for this is that Si has different effects on microbial communities. Nitrification involves all kinds of microbial groups like bacteria and fungi. But, denitrification mainly concerns bacteria [55,56,57]. So, Si amendments might hold back bacterial denitrifiers to a greater degree. This changes the community structure and how it works more noticeably compared to what happens with nitrifiers [56,58]. Also worth mentioning is that because Si was added, there was a larger decrease in the availability of the NO3−-N substrate. This could have placed even more limits on the N2O production that comes from denitrification [59].
This study gives us some valuable insights about how silicon plays a role in regulating N2O emissions from Ph. edulis plantation soils. But, we should also note several limitations. Firstly, the experiment was carried out under controlled incubation conditions and there were no plants around. So, it might not be able to show the full complexity of how plants, soils, and microbes interact in real-world field environments. Also worth mentioning is that the composition of the microbial community and the expression of functional genes were not investigated in this study. This limits our ability to fully understand the mechanism behind the observed suppression of denitrification. Also, the study did not have a long enough duration. It did not take into account the potential long-term changes or seasonal differences [60]. Future research should involve profiling the microbial community, conducting enzyme assays, and using molecular techniques like qPCR testing of functional genes. Consequently, we can clearly determine the microbial responses mediated by Si and their mechanisms. Field-scale trials are particularly important too. Especially long-term monitoring under realistic management regimes. They are essential for confirming the practical effectiveness and sustainability of using Si amendments in forest management practices that aim to reduce greenhouse-gas emissions [61,62].

5. Conclusions

This study showed that adding Si had a significant influence on the processes of soil N transformation in the soils of Ph. edulis plantations. And, this has notable implications for how soil N behaves and for N2O emissions. Si application managed to inhibit both the nitrification and denitrification processes at the same time. As a result, the concentrations of soil NH4+-N and NO3−-N were significantly reduced. Also worth mentioning is that these effects were more obvious in the treatments that were aimed at denitrification (the acetylene treatments) compared to those that were specifically trying to inhibit nitrification (the DMPP treatments). This indicates that Si has a broader inhibitory effect on the pathways of microbial denitrification. Nitrification was found to be the main cause of N2O emissions under the kinds of experimental conditions you usually see with upland forest plantation soils. And, Si amendment managed to reduce the emissions that came from both nitrification and denitrification processes. Also worth mentioning is that the effect of Si on suppressing emissions was especially obvious when it came to the N2O emissions from denitrification. This indicates that adding Si may be more successful at targeting the microbial communities related to denitrification in a more selective way. What this selective inhibition means is that the drop in N2O emissions we saw when we added Si was mostly because the denitrification activity became weaker. But still, nitrification still represented the main cause of emissions. All in all, our findings show that the addition of Si supplementation to existing fertilization regimes may be effective in reducing greenhouse-gas emissions coming from bamboo plantations that are intensively managed. Firstly, we need to understand how this could work. Si might have an impact on certain processes within the plantation that in turn affect emissions. Future research should mainly focus on validating this on a field scale; this means going out to the fields and seeing if what we think will happen actually does. Also, future research should focus on determining exactly how microbial communities respond and quantifying this. Why is this important? Because these microbial communities can play a large role in how the plantation functions and how much gas is emitted. Lastly, long-term assessments are needed. We cannot just look at the short-term effects. We have to determine whether the addition of Si is practical and sustainable in different forestry and agricultural ecosystems over a long period of time to determine whether this strategy can succeed in the real world.

Author Contributions

Conceptualization, P.J. and J.W.; methodology, J.Y. and K.W.; validation, J.Y., K.W., Y.L., R.Z., J.Z., C.H., L.F. and L.L.; formal analysis, J.Y. and K.W.; investigation, J.Y., Y.L., J.Z., C.H. and L.F.; resources, P.J.; data curation, J.Y. and K.W.; writing—original draft preparation, J.Y. and L.L.; writing—review and editing, P.J., J.W. and K.W.; visualization, J.Y.; supervision, K.W., P.J. and C.H.; project administration, P.J. and C.H.; funding acquisition, J.Y. and K.W. contributed equally to this work. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 42177290; the Fujian Provincial Public Welfare Research Institutes Special Program, grant number 2024R1010004; and the Fujian Forestry Science and Technology Promotion Program, grant number 2024TG12. The APC was funded by the National Natural Science Foundation of China.

Data Availability Statement

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

Acknowledgments

We gratefully acknowledge Yanjiang Cai for his assistance with the sample preparation and analysis.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Temporal changes in soil pH under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil pH changes in the control treatment without and with silicon addition; (B) Soil pH changes under DMPP treatment without and with silicon addition; (C) Soil pH changes under C2H2 treatment without and with silicon addition; (D) Soil pH changes under the combined DMPP + C2H2 treatment without and with silicon addition.
Figure 1. Temporal changes in soil pH under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil pH changes in the control treatment without and with silicon addition; (B) Soil pH changes under DMPP treatment without and with silicon addition; (C) Soil pH changes under C2H2 treatment without and with silicon addition; (D) Soil pH changes under the combined DMPP + C2H2 treatment without and with silicon addition.
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Figure 2. Temporal changes in soil NH4+-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment group (p < 0.05). (A) Soil NH4+-N changes in the control treatment without and with silicon addition; (B) Soil NH4+-N changes under DMPP treatment without and with silicon addition; (C) Soil NH4+-N changes under C2H2 treatment without and with silicon addition; (D) Soil NH4+-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
Figure 2. Temporal changes in soil NH4+-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment group (p < 0.05). (A) Soil NH4+-N changes in the control treatment without and with silicon addition; (B) Soil NH4+-N changes under DMPP treatment without and with silicon addition; (C) Soil NH4+-N changes under C2H2 treatment without and with silicon addition; (D) Soil NH4+-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
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Figure 3. Effects of silicon addition on soil nitrogen transformation and N2O emissions under different treatments. (a) Soil NH4+-N concentrations; (b) soil NO3−-N concentrations; (c) soil NO2−-N concentrations; (d) soil N2O emission rate; (e) soil N2O emission flux. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among treatments (p < 0.05). * and ** indicate significant differences between the Si− and Si+ groups (* = p < 0.05, ** = p < 0.01). The symbol “&” represents the relative change rate of Si+ compared to Si− within the same treatment.
Figure 3. Effects of silicon addition on soil nitrogen transformation and N2O emissions under different treatments. (a) Soil NH4+-N concentrations; (b) soil NO3−-N concentrations; (c) soil NO2−-N concentrations; (d) soil N2O emission rate; (e) soil N2O emission flux. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among treatments (p < 0.05). * and ** indicate significant differences between the Si− and Si+ groups (* = p < 0.05, ** = p < 0.01). The symbol “&” represents the relative change rate of Si+ compared to Si− within the same treatment.
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Figure 4. Temporal changes in soil NO3−-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil NO3−-N changes in the control treatment without and with silicon addition; (B) Soil NO3−-N changes under DMPP treatment without and with silicon addition; (C) Soil NO3−-N changes under C2H2 treatment without and with silicon addition; (D) Soil NO3−-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
Figure 4. Temporal changes in soil NO3−-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil NO3−-N changes in the control treatment without and with silicon addition; (B) Soil NO3−-N changes under DMPP treatment without and with silicon addition; (C) Soil NO3−-N changes under C2H2 treatment without and with silicon addition; (D) Soil NO3−-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
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Figure 5. Temporal changes in soil NO2−-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil NO2−-N changes in the control treatment without and with silicon addition; (B) Soil NO2−-N changes under DMPP treatment without and with silicon addition; (C) Soil NO2−-N changes under C2H2 treatment without and with silicon addition; (D) Soil NO2−-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
Figure 5. Temporal changes in soil NO2−-N concentrations under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil NO2−-N changes in the control treatment without and with silicon addition; (B) Soil NO2−-N changes under DMPP treatment without and with silicon addition; (C) Soil NO2−-N changes under C2H2 treatment without and with silicon addition; (D) Soil NO2−-N changes under the combined DMPP + C2H2 treatment without and with silicon addition.
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Figure 6. Temporal changes in soil N2O emission rate under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil N2O emission rate changes in the control (CK) treatment without and with silicon addition; (B) Soil N2O emission rate changes under DMPP treatment without and with silicon addition; (C) Soil N2O emission rate changes under C2H2 treatment without and with silicon addition; (D) Soil N2O emission rate changes under the combined DMPP + C2H2 treatment without and with silicon addition.
Figure 6. Temporal changes in soil N2O emission rate under different treatments. Data are presented as means ± standard error (n = 3). Different lowercase letters indicate significant differences among incubation days within each treatment (p < 0.05). (A) Soil N2O emission rate changes in the control (CK) treatment without and with silicon addition; (B) Soil N2O emission rate changes under DMPP treatment without and with silicon addition; (C) Soil N2O emission rate changes under C2H2 treatment without and with silicon addition; (D) Soil N2O emission rate changes under the combined DMPP + C2H2 treatment without and with silicon addition.
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Figure 7. Correlations between N2O emission rate and (A) soil pH, (B) NH4+-N concentrations, (C) NO3−-N concentrations, and (D) NO2−-N concentrations. Each point represents a treatment replicate (n = 24). Linear trend lines are shown where applicable. Correlation significance levels are indicated in the figure (p < 0.05).
Figure 7. Correlations between N2O emission rate and (A) soil pH, (B) NH4+-N concentrations, (C) NO3−-N concentrations, and (D) NO2−-N concentrations. Each point represents a treatment replicate (n = 24). Linear trend lines are shown where applicable. Correlation significance levels are indicated in the figure (p < 0.05).
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Table 1. Physicochemical properties of soil.
Table 1. Physicochemical properties of soil.
Soil
Type		Total N
(g kg−1)		pHSOC
(g kg−1)		Alkali-Hydrolysable N
(mg kg−1)		Available P
(mg kg−1)		Available K
(g kg−1)		Available Si
(mg kg−1)
Red soil1.394.8023.75160.141.3784.0065.00
The data shown in the table are derived from three repetitions.
Table 2. The design of experiments related to nitrification and denitrification.
Table 2. The design of experiments related to nitrification and denitrification.
GroupTreatmentDMPPC2H2N (mg kg−1)Si (mg kg−1)
Si− *CK--800
DMPP+-800
C2H2-+800
DMPP + C2H2++800
Si+CK--8025
DMPP+-8025
C2H2-+8025
DMPP + C2H2++8025
* “Si−” indicates treatments without silicon addition, while “Si+” refers to treatments with silicon addition. The symbol “+” denotes the application of the inhibitor (DMPP or C2H2), whereas “-” indicates that no inhibitor was applied.
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Yang, J.; Wang, K.; Liu, L.; Li, Y.; Wu, J.; Zhong, J.; Zheng, R.; Fan, L.; Huang, C.; Jiang, P. Effects of Exogenous Silicon Addition on Nitrification and Denitrification-Derived N2O Emissions from Moso Bamboo (Phyllostachys edulis) Forest Soil. Land 2025, 14, 1004. https://doi.org/10.3390/land14051004

AMA Style

Yang J, Wang K, Liu L, Li Y, Wu J, Zhong J, Zheng R, Fan L, Huang C, Jiang P. Effects of Exogenous Silicon Addition on Nitrification and Denitrification-Derived N2O Emissions from Moso Bamboo (Phyllostachys edulis) Forest Soil. Land. 2025; 14(5):1004. https://doi.org/10.3390/land14051004

Chicago/Turabian Style

Yang, Jie, Kecheng Wang, Lijun Liu, Yongchun Li, Jiasen Wu, Jinhuan Zhong, Rong Zheng, Lili Fan, Chengpeng Huang, and Peikun Jiang. 2025. "Effects of Exogenous Silicon Addition on Nitrification and Denitrification-Derived N2O Emissions from Moso Bamboo (Phyllostachys edulis) Forest Soil" Land 14, no. 5: 1004. https://doi.org/10.3390/land14051004

APA Style

Yang, J., Wang, K., Liu, L., Li, Y., Wu, J., Zhong, J., Zheng, R., Fan, L., Huang, C., & Jiang, P. (2025). Effects of Exogenous Silicon Addition on Nitrification and Denitrification-Derived N2O Emissions from Moso Bamboo (Phyllostachys edulis) Forest Soil. Land, 14(5), 1004. https://doi.org/10.3390/land14051004

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