Nitrogen Addition Exacerbates the Negative Effect of Throughfall Reduction on Soil Respiration in a Bamboo Forest

Abstract

Impacts of drought events and nitrogen (N) deposition on forests are increasingly concerning in the context of global climate change, but their effects, in particular, their interactive effects on soil respiration and its components remain unclear. A two-factor random block field experiment was conducted at a subtropical Moso bamboo forest in Southwest China to explore the response of soil respiration (R_s), autotrophic respiration (R_a), and heterotrophic respiration (R_h) to throughfall re-duction and N addition. Our results showed that throughfall reduction significantly decreased R_s, which is mainly attributed to the decrease in R_a as a result of the decline in fine roots biomass. The N addition led to microbial carbon limitation hence significantly decreased R_h, and thus R_s. We also observed the negative effect of throughfall reduction on R_s was exacerbated by N addition, which is attributed to the significant reduction in R_a under the interaction between throughfall reduction N addition. Our findings suggest that R_a tended to respond more sensitively to potential drought, while R_h responds more sensitively to N deposition, and consequently, increased soil N availability caused by N deposition might aggravate the negative effect of expected drought on soil carbon cycling.

1. Introduction

As the second-largest fluxes in the global terrestrial carbon (C) cycle, soil respiration (R_s) consequently exerts a strong influence on the feedbacks between soil C pools and atmospheric CO₂ concentration [1]. Changes in R_s in response to global change scenarios [2] can have a tremendous effect on the terrestrial C cycle and subsequently global climate change. Amongst, change in precipitation patterns (intensity and frequency) results in frequent extreme droughts during the 21st century [2], which has been exerting a large impact on soil C cycling [3,4]. Nitrogen (N) deposition, another important global change feature, had been intensified due to increasing human activities, such as fossil fuel combustion and use of fertilizers [5,6,7], which were also demonstrated to affect soil C cycling [8]. The global change characterized by the concurrence of multiple environmental factors, like N deposition and drought events, and therefore, leading to large uncertainties in predicting impacts of the combined factors [9], because both N deposition and drought will be very likely to affect soil N availability and soil water availability and consequently, further impact on ecological process in future [5,10]. However, their combined effects have inadequately been addressed from the perspective of coupled relationships between N and water, which often interact together to alter the direction and magnitudes of the response of the ecological process [11,12].

R_s is composed of two components, including autotrophic respiration (R_a) and heterotrophic respiration (R_h), and their different response to environmental changes finally determine the variation of R_s [13,14]. For example, Hinko-Najera et al. [15] attributed drought-induced reductions in R_s to a decrease in R_a in a dry temperate broadleaved evergreen forest, while Zhou et al. [3] found the decreased R_a and the increased R_h contributed to the non-responsive R_s under throughfall reduction in a tropical rainforest. Contrastingly, R_a was increased by throughfall reduction and combined with the non-responsive R_h; all of them finally contributed to the increase of R_s in the temperate oak forest [16]. Moreover, soil N availability also determines the soil C cycling in response to climate changes [17]. Previous studies showed that N addition promoted R_a and R_h and subsequently triggered an increase of R_s in a temperate forest [18], while inhibited both R_a and R_h hence leading to the decline of R_s in a subtropical forest [19,20]. The highly variable effects of throughfall reduction or N addition on R_s, R_a, and R_h may be brought by the diverse plant types, natural precipitation, and nutrient status of ecosystems [18,21,22,23]. Interestingly, Yan et al. [24] found N addition had a neutral effect on R_a in dry years but a positive effect on R_a in wet years in a semi-arid temperate steppe. In other cases, throughfall exclusion promoted R_h in subtropical and temperate forests, while the positive response diminished under the combined effects of throughfall exclusion and N addition [18,25]. Thus, it is crucial to quantify the respective response of R_a and R_h to N addition and throughfall reduction to achieve a comprehensive perspective on the interactive effects of N addition and throughfall reduction on soil C cycling.

Bamboo is one of the important forest types in the subtropical area in China [26], which currently accounts for about 6.41 million hm² of forested area, of which 72.9% is dominated by Moso bamboo (Phyllostachys heterocycla) (the Ninth National Forest Resource Inventory Report). The subtropical region of China is controlled by a West Pacific Subtropical High-Pressure System, which was also subjected to a prevailing descending airflow, leading to severe drought in summer [27]. Moreover, this region is projected to experience an increasing intensity and frequency of drought events in the 21st century [28] and has been suffering N deposition since the 1980s [29,30]. The former studies implied that N addition could change the response direction and extent of R_a and R_h to drought, making the effects of throughfall reduction, N addition, and their interactions on R_s uncertain. Therefore, a two-factorial field manipulation experiment was conducted in a subtropical Moso bamboo forest, we aim to investigate the effects of throughfall reduction, N addition, and their interaction on soil respiration and its components. We hypothesized that: (1) The negative response of R_s to throughfall reduction might primarily result from the decline of R_a; (2) N addition might relieve the negative effect of throughfall reduction on R_a; thus the differential responses between components must be figured to accurately predict the total soil respiration in response to future climate change scenarios, particularly to drought.

2. Material and Methods

2.1. Site Description

The study site is located in Changning Bamboo Forest National Ecosystem Research Station, Changning country, Sichuan province of China (28°27′–28°27′ N, 105°00′–105°01′ E). The local climate is characterized by a humid mid-subtropical climate influenced largely by the southeast monsoon, with mean annual air temperature of 18.3 °C and an average annual precipitation of 1141.7 mm. The soil in the study site was Cambisols (FAO classification). The dominant tree species at the study site was Moso bamboo (Phyllostachys heterocycla). The initial stand density and diameter at breast height (DBH) are summarized in Table S1.

2.2. Experimental Design

To explore the effects of throughfall reduction and nitrogen addition and their interaction on Rs and its components, we fenced four blocks, with each block consisting of four 20 m × 20 m plots (Ambient plot: A, Throughfall reduction plot: TR, Nitrogen addition plot: N, Nitrogen addition and Throughfall reduction plot: TR + N), and a more than 5 m wide buffer strip was set between the neighboring plots. We trenched the plots to bedrock (approximately 70–80 cm), then inserted a 3 mm thick and 80 cm width polyvinyl chloride board along the trench to prevent horizontal transport of soil lateral water and clonal integration by rhizome from bamboos outside the plot. The throughfall reduction experiment was installed using plastic roofs made of agricultural polyolefin film attached to rails about 2 m above the ground, and the roofs cover about 50% area in the throughfall reduction plot. The throughfall reduction experiment was initiated in April 2017 [31]. The N addition was conducted once every two months with the total amount of 100 kg N ha⁻¹ yr⁻¹ by applying ammonium nitrate (NH₄NO₃), which was weighed and dissolved in 100 L water, and then sprayed with an automatic sprinkler system under the canopy in the plots. The ambient and through-fall reduction plots simultaneously supplied 100 L water without NH₄NO₃ additions, which was equal to 1.5 mm precipitation every year. The N addition experiment was initiated in June 2017.

2.3. Soil Respiration Measurements

Three polyvinyl chloride (PVC) collars (19.5 cm inner diameter, 8 cm deep) were randomly installed in the plots to determine soil respiration (R_s), and another three PVC collars in trenched quadrats were installed to determine soil heterotrophic respiration (R_h). A total of six PVC collars were inserted 3 cm deep into the soil and kept the position unchanged throughout the experiment. In trenched quadrat, 1 m × 1 m area to 60 cm depth (approximately the bottom of the root zone in study site) was randomly selected and trenched in April 2017, then a 3 mm thick and 80 cm width polyvinyl chloride board was inserted to avoid root growth into the quadrat [16]. All plants were removed before trench establishment, and living vegetation were kept free from trench quadrats by periodically manual removal throughout the experiment. To minimize the effect of dead roots caused by trenching, R_h was measured 4 months later after trenching. R_s and R_h were measured approximately once a month from September of 2017 to August of 2018 (14 times in the whole monitored period) by using the Li-8100 (Li-Cor Inc., Lincoln, NE, USA), respectively. The measurement time was selected before NH₄NO₃ was added or 15 days later after NH₄NO₃ added, starting from 09:00 a.m. to 3:00 p.m. Accordingly, soil autotrophic respiration (R_a) was represented as the difference between R_s and R_h. The soil temperature (T) and the soil moisture (SWC: volumetric water content, %v/v) at the 5 cm depth were monitored simultaneously by using a ProCheck (METER Group Inc., Pullman, WA, USA) and soil temperature and moisture probes (Decagon: 5TE, Pullman, WA, USA) at three measurement sites nearby the collar.

2.4. Soil Sampling and Analysis

The soil samples were collected in August of 2018, respectively. After carefully removing the litter layer from the topsoil, three soil cores from each plot were randomly sampled at a depth of 0–10 cm using a 5 cm diameter stainless steel auger for the measurement of fine root biomass (diameter ≤ 2 mm). Overall, the soil samples were separately homogenized and sieved through a 2 mm screen to obtain the final soil sample for a given plot. All the fine roots were rinsed with water and weighed to determine fine root biomass (FRB) after oven drying at 75 °C for 72 h. A portion of each soil sample was air-dried at room temperature and for pH measurement using a pH meter (PHS-3C, INESA Scientific Instrument Co. Ltd., Shanghai, China) with a 1:2.5 ratio of soil dry weight to deionized water volume. Another portion of air-dried soil sample was sieved through a 0.15 mm screen for chemical properties analysis. The soil total C (TOC) and N (TN) were measured by using Elemental Analyzer (ECS 4010 CHNSO, Costech Analytical Tecnologies Inc., Vlencia, CA, USA), and soil total phosphorus (TP) were measured colorimetrically by using Smartchem Discrete Auto Analyzer (Smartchem 300, Westco Scientific Instruments, Rome, Italy) after wet digestion with HClO₄-H₂SO₄. The other portion of each soil sample was transported to the laboratory in a 4 °C cooler for the later measurement of soil ammonium nitrogen (NH₄-N), nitrate-nitrogen (NO₃-N), soil microbial biomass, and extracellular enzyme activities (EEAs). The NH₄-N and NO₃-N were measured by using Smartchem Discrete Auto Analyzer (Smartchem 300, Westco Scientific Instruments, Rome, Italy) after extraction with 50 mL of 2M KCl solution (wet soil weight: solution volume = 1:5). Soil phospholipid fatty acid (PLFA) content was analyzed following the methods of Bossio and Scow [32]. Briefly, PLFA was extracted from soil equivalent to 8 g dry weight and measured by gas chromatography combustion mass spectrometry (Agilent N6890, Agilent Technologies, PaloAlto, CA, USA) fitted with a MIDI Sherlocks microbial identification system (Version 4.5, MIDI Inc., Newark, DE, USA). For each sample, PLFAs were quantified relative to the C19:0 internal standard and expressed as nmol PLFA g⁻¹ soil. Total PLFAs concentration has been used to represent soil total microbial biomass [33], and the sum of the PLFAs was used as an estimate of the total microbial biomass. The activities of β-Glucosidase (BG), leucine aminopeptidase (LAP), N-acetylglucosaminidase (NAG), and acid phosphatase (AP) were assayed using the modified method by Saiya-Cork et al. [34] and Wang et al. [14]. In brief, 1.25 g (wet weight) of soil (0–10 cm depth) closed to collar in trench quadrats were homogenized for one minute with 125 mL 50mM acetate buffer (pH = 4.2) in a blender. Two hundred microliters of soil slurry and 50 µL of 200 µM 4-methylumbelliferyl or l-leucine-7-amido-4-methyl substrate were added to each well on the microplate, eight replicates for one kind of EEAs. Eight control quench replicates were made for each soil (200 µL soil slurries plus 50 µL of 10 µM 4-methylumbellifferone [MUB] or 50 µL of 10 µM 7-amino-4-methylcoumarin [AMC]). Background fluorescence of soil slurry, substrates, and standard solution of MUB and AMC were also measured. The microplates were incubated in the dark at 25 °C for 3 h, and reactions were stopped with 5 µL 0.5 N NaOH. Finally, the microplates were read on a PerkinElmer LAMBDA 35 plate reader (excitation filter at 355 nm and emission filter at 460 nm). According to Sinsabaugh et al. [35] and Sistla and Schimel [36], EEAs were divided into carbon acquiring enzyme activities (BG), nitrogen acquiring enzyme activities (NAG and LAP) and phosphorus acquiring enzyme activities (AP), and EEAs are expressed as nmol h⁻¹ g⁻¹ soil.

We used the vector analysis of soil enzymatic stoichiometry proposed by Moor-head et al. [37] and Jing et al. [38] to address the clear metrics of soil microbial carbon and nutrient limitations. Vector length (relative carbon vs. nutrient limitation) were calculated as the square root of the sum of the squared values of x and y, where x represents the relative carbon vs. phosphorus acquiring enzyme activities [(BG + CB)/(BG + AP)] and y represents the relative carbon vs. nitrogen acquiring enzyme activities [(BG + CB)/(BG + CB + NAG + LAP)] (Equation (1)), and vector degree (relative phosphorus vs. nitrogen limitation) was calculated as the angles between the x-axis and the vector from the plot origin to point (x, y) (Equation (2)):

$$Vectorlength=SQRT\left(x^2+y^2\right)$$

(1)

$$Vector degree=DEGREES\left(ATAN2\left(x , y\right)\right)$$

(2)

2.5. Statistical Analyses

We used the bivariate exponential equation to describe the relationship between R and SWC and T [18]:

$$R=a.e^{bT}.SW{C}^c$$

(3)

where R represents the rate of soil respiration or its components (R_s, R_a, and R_h, μmol m⁻² s⁻¹); T represents soil temperature at 5 cm depth; SWC (% v/v) represents soil moisture at 5 cm depth; a, b and c represent model parameters.

Temperature sensitivity of R (Q₁₀) was calculated using b values in the bivariate model as follows (Equation (4)):

$$Q_{10}=e^{10b}$$

(4)

The estimation of accumulated C efflux of R_s, R_a, and R_h was calculated as follows (Equation (5)) [39]:

$$F\left(c\right)={\displaystyle \sum }\left(R_{i+1}+R_i\right)/2\times \left(t_{i+1}-t_i\right)\times 3600\times 24\times 44\times {10}^{-8}$$

(5)

where F(c) is the accumulative CO₂ emission (t CO₂ ha⁻¹ a⁻¹) of R_s, R_a, and R_h, R is the rates of R_s, R_a and R_h (μmolm⁻² s⁻¹), i is the sampling number, and t is the Julian day between two sampling time.

Three-way ANOVA was used to examine the effect of measuring time, throughfall reduction, and N addition on soil respiration (R_s, R_a, and R_h). In the general linear model, throughfall reduction and N addition were treated as fixed factors, and the block was treated as a random factor to examine throughfall reduction, N addition and their interactive effect on environmental factors (T and SWC), soil properties (pH, TOC, TN, TP, NO₃-N, and NH₄-N), FRB, Total PLFAs, vector analysis of soil enzymatic stoichiometry (vector length and vector degrees) and Q₁₀ values. Pearson analysis was used to elucidate the relationships of R_s, R_a, and R_h and soil properties, FRB, Total PLFAs, vector length, and vector degrees. For A, TR, N, and TR+N treatments, principle component analysis (PCA) for R_s, R_a, and R_h were performed by using Canoco 4.5, in which R_s, R_a, and R_h at every turn were treated as “species”. Statistical analyses were carried out using SPSS 17.0 (SPSS Inc., Chicago, IL, USA).

3. Results

3.1. Throughfall Reduction and N Addition on Soil Environment, Fine Root Biomass and Microbial Properties

Soil temperature at the 5 cm soil depth showed strong seasonal patterns with the higher soil temperatures from June to August regardless of treatments (Figure 1a). Soil temperatures ranged from 5.44 °C to 29.35 °C during the study period. The seasonal pattern of soil moisture was different from that of soil temperature, and the variation fluctuated over seasons (Figure 1c). Throughfall reduction, N addition, and their interaction did not affect soil temperature; while throughfall reduction significantly decreased soil moisture (p < 0.001) by 27.6%, respectively (Figure 1b,d).

Throughfall reduction, N addition, and their interaction neither affect soil TOC, TP, pH, NO₃-N, and NH₄-N (Figure 2). N addition significantly increased TN by 17.5% and 17.0% for the N and TR + N treatments (p = 0.01), and throughfall reduction significantly decreased FRB by 21.1% (p = 0.03, Figure 2b). In vector analysis of soil enzymatic stoichiometry, the interaction of throughfall reduction and N addition on vector degree was significant (p = 0.03), showing that the vector degree was decreased by 8.1% for TR treatment, while combined with N addition, the decline was largely offset and only decreased by 2.0% (Figure 2h). Furthermore, N addition alone significantly increased vector length by 21.3%, compared to the A treatment (p = 0.03, Figure 2i). We did not observe treatment effects on total PLFAs (Figure 2j).

3.2. Effects of Throughfall Reduction and N Addition on Soil Respiration and Its Components

Across the year, R_s was significantly influenced by throughfall reduction, N addition, and their interaction. Throughfall reduction and N addition alone significantly decreased annual cumulative R_s by 5.1% (p = 0.021) and 1.2% (p < 0.001), and their combined effect further limited R_s, leading to a decline of 18.4% in annual cumulative R_s (p = 0.034, Figure 3b and

Table 1. F-values and p-values of three-way ANOVA on the effects of measured time, throughfall reduction, N addition, and their interactions on soil respiration (R_s), soil autotrophic respiration (R_a), and soil heterotrophic respiration (R_h).

	Rs	Ra	Rh
Time	F(13,168) = 73.1 p < 0.001	F(13,168) = 29.7 p < 0.001	F(13,168) = 78.4 p < 0.001
Throughfall reduction	F(1,168) = 14.2 p < 0.001	F(1,168) = 9.9 p = 0.002	F(1,168) = 3.5 p = 0.063
N addition	F(1,168) = 5.4 p = 0.021	F(1,168) = 1.9 p = 0.174	F(1,168) = 97.2 p < 0.001
Throughfall reduction × N addition	F(1,168) = 4.5 p = 0.034	F(1,168) = 5.5 p = 0.020	F(1,168) = 0.2 p = 0.633
Throughfall reduction × Time	F(13,168) = 1.6 p = 0.090	F(13,168) = 2.1 p = 0.019	F(13,168) = 0.9 p = 0.522
N addition × Time	F(13,168) = 0.6 p = 0.858	F(13,168) = 0.2 p = 0.999	F(13,168) = 4.1 p < 0.001
Throughfall reduction × N addition × Time	F(13,168) = 0.6 p = 0.867	F(13,168) = 0.6 p = 0.845	F(13,168) = 0.6 p = 0.881

). In PCA plots, the symbols of A, TR, N, and TR + N treatments were distributed in 3 quadrants, indicating that the effect of TR and N on R_s had the same negative influence (Figure 3b and Figure 4a). The symbol of TR + N separated from the other symbols implied the effect of TR + N on R_s was different from those under A, TR, and N treatments, and the results verified the negative response of R_s to the interactive effects of throughfall reduction and N addition (Figure 3b and Table 1). The effect of throughfall reduction significantly decreased annual cumulative R_a by 5.4% (p = 0.002), while the effect of N addition on annual cumulative R_a was not significant (p = 0.174). Overall, the interaction of throughfall reduction and N addition significantly decreased annual cumulative R_a by 8.8% (p = 0.020, Figure 3d and Table 1). The symbols of A and N treatments were situated in one quadrant, while the symbols of TR and TR + N were situated in the other quadrant, which illustrated the same negative response of TR and TR + N on R_a (Figure 3d and Figure 4b). Different from R_a, throughfall reduction and the interaction combined with N addition did not affect annual cumulative R_h (p = 0.063 and p = 0.633, respectively), but N addition significantly decreased annual cumulative R_h by 25.2% (p < 0.001, Figure 3f and Table 1). The differences of R_h stood in line with the symbols of A, TR, N, and TR + N treatments in PCA plots (Figure 3f and Figure 4c).

3.3. Controls for Soil Respiration and Its Components

Across the year, the variations of R_s, R_a, and R_h mainly tracked T and combined with SWC, which explained 76–89%, 51–78%, 75–86% of the monthly variations in R_s, R_a, and R_h (Figure 3 and

Table 2. Parameter estimates of bivariate exponential models for R_s, R_a, and R_h as a function of soil temperature (T) and moisture (SWC) in the 0–10 cm soil from September 2017 to August 2018 in different treatments (mean ± SE).

	a	b	c	R2	p
Rs = a.ebT.SWCc
A	0.55 ± 0.08	0.09 ± 0.00	0.47 ± 0.23	0.89	0.000
TR	0.76 ± 0.18	0.09 ± 0.00	0.52 ± 0.23	0.87	0.000
N	0.58 ± 0.09	0.09 ± 0.00	0.43 ± 0.23	0.81	0.000
TR + N	0.73 ± 0.12	0.08 ± 0.00	0.39 ± 0.05	0.76	0.000
Ra = a.ebT.SWCc
A	0.16 ± 0.03	0.10 ± 0.01	0.03 ± 0.32	0.78	0.000
TR	0.31 ± 0.14	0.12 ± 0.02	0.54 ± 0.38	0.69	0.000
N	0.23 ± 0.09	0.11 ± 0.01	−0.08 ±0.76	0.67	0.000
TR + N	0.35 ± 0.17	0.08 ± 0.01	0.07 ± 0.33	0.51	0.000
Rh = a.ebT.SWCc
A	0.45 ± 0.03	0.09 ± 0.01	1.13 ± 0.13	0.86	0.000
TR	0.55 ± 0.08	0.07 ± 0.00	0.78 ± 0.19	0.80	0.000
N	0.51 ± 0.15	0.07 ± 0.00	1.14 ± 0.44	0.78	0.000
TR + N	0.51 ± 0.14	0.07 ± 0.00	0.85 ± 0.35	0.75	0.000

). The R_s, R_a, and R_h were not affected by soil chemical properties, but significantly and positively correlated with fine root biomass (p = 0.004, p = 0.033, and p = 0.026, respectively,

Table 3. The correlation coefficients between soil respiration and its components and soil biotic and abiotic factors.

	TOC	TN	TP	pH	NO3-N	NH4-N	Total PLFAs	FRB	Vector Degree	Vector Length
Rs	−0.141	0.009	−0.402	0.391	−0.186	0.210	0.312	0.680 **	0.377	−0.477
Ra	−0.080	0.175	−0.323	0.371	−0.125	0.197	0.165	0.534 *	0.262	−0.236
Rh	−0.188	−0.392	−0.314	0.166	−0.203	0.098	0.443	0.554 *	0.386	−0.716 **

Notes: R_s represents soil respiration; R_a represents soil autotrophic respiration; R_h represents soil heterotrophic respiration; TOC represents soil total organic carbon content; TN represents total nitrogen content; TP represents total phosphorus content; NO₃-N represents nitrate nitrogen; NH₄-N represents ammonium nitrogen; Total PLFAs represents soil microbial biomass; FRB represents fine root biomass; vector degree represents relative P vs. N limitation; vector length represents relative C vs. nutrient limitation. Data of R_s, R_a, and R_h used in Pearson analysis were calculated from the mean values from June to August; * denotes p < 0.05; ** denotes p < 0.01.

). Moreover, the R_s and R_h were not linked to total PLFAs or vector degree (Table 3), but R_h was negatively related to vector lengths (p = 0.002, Table 3).

3.4. Throughfall Reduction and N Addition on Temperature Sensitivity of Soil Respiration and Its Components

The fitted Q₁₀ values of R_s ranged from 2.17 to 2.58, the Q₁₀ values of R_a ranged from 2.35 to 3.45 and the Q₁₀ values of R_h ranged from 1.98 to 2.36 (Figure 5). Moreover, there was no significant difference in the Q₁₀ values of R_a and R_h among throughfall reduction, N addition, and their interaction (Figure 5b,c). The effects of the interaction of N addition and throughfall reduction on Q₁₀ values of R_s were significant (p = 0.02). The Q₁₀ values of Rs decreased by 1.21% under TR treatment, but when combined with N addition, it was decreased by 15.93% under TR + N treatment (Figure 5a).

4. Discussion

4.1. Effects of Throughfall Reduction on Soil Respiration and Its Components

Although the previous study had synthesized the diverse responses of R_s to simulated precipitation reduction [40], R_s showed a negative response in most ecosystems around the world [41], indicating the limitation of SWC for soil CO₂ emissions in many terrestrial ecosystems. We also found R_s responded negatively to throughfall reduction across the years (Table 1 and Figure 3a), and the result was in full agreement with the findings by Liu et al. [42] and Sun et al. [43], who found R_s was limited under drought conditions. As the two main sources of R_s, the co-response of R_a and R_h determines the responsive directions and magnitudes of R_s to throughfall reduction [16]. The bi-directional responses (positive vs. negative) of R_a and R_h could mask the response of R_s under TR treatment, respectively. Owing to the unequal sensitivities of microbes and plants to soil moisture across different ecosystems, changes in soil moisture could have different impacts on R_a and R_h [16,25]. In our study, we found R_a negatively responds to throughfall reduction (Table 1 and Figure 3d), and our findings were consistent with those of Huang et al. [25] and Zhou et al. [3], who observed R_a was inhibited in subtropical and tropical forests. This is possibly due to drought reduces plant primary productivity and the amount of C allocated to respiration [44]. We also found the decline of FRB and Ra under TR and TR + N treatments (Figure 2g and Figure 3c). It is known that the variation of R_a was correlated with fine root properties [45,46], which could be verified by the positive relationships between R_a and FRB (Table 3), and consequently, change in FRB brought about the decline of R_a under drought conditions.

Different from R_a, throughfall reduction did not affect R_h across the year (Table 1), and our results were in line with those findings in a subtropical forest in China and a Eucalyptus spp. dominating forest in Australia, who reported R_h was less suppressed than R_a during drought conditions [15,25]. Various responses in R_a and R_h to throughfall reduction might result from different responses in FRB and soil microbial biomass to throughfall reduction. Our findings were supported by the significantly negative effect of throughfall reduction on FRB and neutral effect on total PLFAs (Figure 2g,j), which agreed with the results of Huang et al. [25], who found a more pronounced negative effect of drought on FRB than on microbial biomass C. Thus, the unchanged total PLFAs could cause the neutral response of R_h to throughfall reduction. As the important substrate for soil microbes, fine roots supply C to the soil in the form of exudation [47]. Though R_h was tightly coupled with FRB and significant negative effects of throughfall reduction on FRB were obtained, R_h was nonresponsive to throughfall reduction (Table 1 and Table 3). This may be caused by a greater share of photosynthetic C was allocated to exudation, rather than biomass production, under drought conditions [48,49]. In addition to these changes in the amount of exudation, plants also could alter the composition of root exudation when trapped in drought [50]. Therefore, in the case of FRB negatively respond to throughfall reduction (Figure 2g), the labile C substrate such as root exudation, may be not changed and did not limit microbial utilization. The vector length, as an indicator of microbial C limitation [37], was not affected by throughfall reduction (Figure 2i), which further verified R_h was not constrained by C substrate under drought conditions, and thus R_h in our study (Figure 3f and Figure 4c). Therefore, our results showed that the inhibition effect of throughfall reduction on R_s was mainly the result of a decline in Ra and the non-responsive R_h, which supports our first hypothesis.

4.2. Effects of N Addition on Soil Respiration and Its Components

Nitrogen addition did not affect R_a during the observation period (Table 1). Similarly, Chen et al. [51] showed that R_a maintains relative stability by N fertilization. However, Wang et al. [20] reported that N addition alone reduced R_a from subtropical Cunninghamia lanceolata forest. The low response of R_a to N addition in our study was largely attributed to the insignificant response of FRB to N addition (Figure 2g). It has been acknowledged that R_a is driven by belowground C allocation, such as fine root biomass [16], and the close relationship between R_a and FBR was observed in our study (Table 3). Zeng and Wang [52] found that N addition significantly suppressed fine root biomass in N-limited Pinus sylvestris plantations. However, in this study, FRB did not significantly change after N addition. This may be due to the bamboo ecosystem in our study area was P limited [53], and N addition could not affect FRB according to Liebig’s law of the minimum [54] and thus respiration of roots. On the other hand, soil water status could modify the role of N addition on soil C emissions. Chen et al. [55] observed R_a was significantly increased by N fertilization in a year with much less precipitation (544 mm). Accordingly, it was speculated that excessive soil moisture conditions might inhibit the response of R_a to N addition. The precipitation in our study site was 1141 mm, which may alleviate the promoting role of N addition by leaching, hence the neutral response of R_a under N addition was found (Table 1).

Unlike R_a, N addition significantly decreased R_h (Figure 3e and Table 1), this result agreed with that in a subtropical forest, temperate forest, and grassland ecosystems [20,23]. Previous studies found N addition suppressed soil organic matter (SOM) decomposition, leading to a reduction in R_h [30,56]. The retarding effect of N addition on SOM decomposition was supported by the negative correlation between patterns of R_h and vector lengths (Table 3), and the higher value of vector length in our study indicates the more C limitation on soil microbes [37]. Furthermore, N addition may increase chemical stabilization of SOM by increasing the proportion of recalcitrant C that resists microbial decomposition [30], thus soil microbes could be limited by C and lead to the drop of R_h in our study. Consequently, we found that N addition did not affect R_a while decreased R_h by broadening the C limitation on microorganisms in this P-limited bamboo forest, thus led to the negative response of R_s to N addition.

4.3. Interactive Effects of N Addition and Throughfall Reduction on Soil Respiration and Its Components

According to hypothesis 2, N addition relieved the negative response of R_a to throughfall reduction. However, the synergistic non-additive effect of throughfall reduction and N addition on R_s was detected. Interestingly, throughfall reduction significantly decreased R_s by 5.1% and N addition significantly decreased R_s by 1.2%, while their combination further limited R_s and decreased by 18.4% (Figure 3b and Table 1). Our results were opposite to the conclusions drawn by Chen et al. [18] in a temperate forest, who observed N addition or throughfall reduction alone increased R_s, but the increment decreased under their combination. The distinct findings may be attributed to different nutrient limitations across different ecosystems. It has been proved that N addition increases R_s in N-limited ecosystems, while it decreased in N-rich ecosystems [57,58]. Our study site is suffering from P-limited but not from N-limited, thus it may have led to the negative response to N addition or throughfall reduction. As the main components in R_s, R_a contributed more proportions than R_h (Figure 3), hence the negative response of R_s may stem from R_a. Throughfall reduction significantly decreased R_a by 5.4% and N addition did not change R_a, but the combined effect of throughfall reduction and N addition significantly decreased R_a by 8.8% (Figure 3d and Table 1). A previous study showed N deposition enhanced photosynthesis and led to the increment of evapotranspiration in Moso bamboo, and the relatively high evapotranspiration of Moso bamboo may aggravate the role of SWC in regulating root activities [59,60]. Accordingly, the interactive effect of throughfall reduction and N addition may promote the limiting effect of water deficit on root activities, and therefore constrained R_a in our study. Different from the interaction of throughfall reduction and N addition on R_s and R_a, N addition significantly decreased R_h by 25.2%, but combined with throughfall reduction, the interaction had no effect on R_h (Figure 3f and Table 1). N addition alone significantly increased microbial C limitation and led to the decline of R_h [20]. Nevertheless, the vector length was not affected by the combination of N addition and throughfall reduction in our study (Figure 2i), which means drought condition had a barely negative role on microbial C limitation under N addition and thus nonresponsive R_h.

Though N addition or throughfall reduction alone changed R_h and R_a, the effect of N addition or throughfall reduction on Q₁₀ of R_h and R_a was not obvious. Furthermore, the interactive effect of N addition and throughfall reduction on Q₁₀ of R_s was significant (Table 1). The Q₁₀ values of R_s at soil depths of 5 cm ranged from 2.02 to 2.43 and were similar to the observations (2.00–2.30) in bamboo plantation, which was a little lower than that reported global median of 2.4 [39,61,62]. Mo et al. [63] and Jia et al. [64] found ammonium nitrate addition or drier soil could significantly decrease Q₁₀ values of R_s, however, the interaction of N addition and throughfall reduction on Q₁₀ of R_s was rarely reported in the field. Our observations found that N addition or throughfall reduction slightly decreased Q₁₀ values of R_s, but what is interesting is that the combined effect of N addition and throughfall reduction on Q₁₀ values of R_s was significantly decreased. The decline of Q₁₀ values of R_s may reflect variations of the metabolic activity of plant roots and soil microbes under N addition [65]. Though T was not affected by N addition, throughfall reduction, and their combination, R_a and R_h were still lowest under TR + N treatment and determined the response of R_s and Q₁₀ values to the combined effect of N addition or throughfall reduction (Figure 3d,f). Possible reasons for the decreased Q₁₀ values of R_s are: (1) the decreased FRB under TR + N treatment and contributed most in the variations of R_s and R_a; (2) such a decrease in R_h in response to TR + N treatment may be related to physiological acclimatization of microbes [66]; (3) N addition in our study exceeds a certain threshold (90 kg N ha⁻¹ yr⁻¹), and thus led to the reduced Q₁₀ values of R_s [63,67].

5. Conclusions

In this subtropical Moso bamboo forest, R_a was suppressed by throughfall reduction and contribute to the decline of R_s, all of which was governed by FRB. Furthermore, N addition reduced R_h, potentially due to microbial C limitation, leading to the decreased R_s. We also found the interaction of throughfall reduction and N addition further negatively affected R_s and R_a, and the non-additive effect was synergistic. Our findings highlight the need to account for the response to throughfall reduction, N addition, and their interaction between R_s, R_a, and R_h when accurately predicting the responses of ecosystem C cycling on the scenario of concurrence of multiple climate changes.