Reduced soil organic carbon sequestration driven by nitrogen deposition–induced increases in microbial carbon to phosphorus ratio in alpine grassland

Reduced soil organic carbon sequestration driven by nitrogen deposition–induced increases in microbial carbon to phosphorus ratio in alpine grassland | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Reduced soil organic carbon sequestration driven by nitrogen deposition–induced increases in microbial carbon to phosphorus ratio in alpine grassland Jianbo Wu, Lidong Mo, Constantin M. Zohner, Hui Zhao, Fan Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4645564/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aims Effect of nitrogen deposition on soil organic carbon and the underlying mechanisms in grassland ecosystems remains a topic of debate. Moreover, previous research has primarily concentrated on interaction between carbon and nitrogen cycles in response to nitrogen deposition, with less attention paid to how nitrogen-induced phosphorus deficits may impact soil organic carbon sequestration. Methods we applied a meta-analysis to quantify how soil organic carbon and phosphorus respond to nitrogen enrichment in grassland ecosystem. Besides, we conducted an eight-year field experiment involving nitrogen and phosphorus additions. Results the meta-analysis revealed that soil organic carbon increased below 5 g·m − 2 but decreased above 10 g·m − 2 under nitrogen addition. The field experiment also indicated that soil available phosphorus did not significantly decrease with nitrogen addition of 10 g·m − 2 , suggesting an increase in soil available phosphorus due to nitrogen addition. The microbial biomass carbon to phosphorus (MC:MP) ratio significantly decreased under any level of nitrogen addition, indicating that nitrogen enhanced phosphorus limitation of microbes. Moreover, the significant negative correlation between MC:MP ratio and soil organic carbon indicated that microbial carbon limitation increased with microbial phosphorus limitation under nitrogen enrichment. Furthermore, both microbial carbon limitation and phosphorus limitation were significantly correlated with reduced soil organic carbon, suggesting that increases in the MC:MP ratio will reduce soil organic carbon sequestration. Conclusions soil organic carbon will decrease above 10 g·m − 2 under nitrogen addition, and the nitrogen deposition-induced MC:MP imbalance may lead to decreased soil organic carbon in alpine grassland ecosystems. soil organic carbon MC:MP ratio nitrogen deposition microbial P limitation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Nitrogen (N) is the primary limiting nutrient for grassland ecosystems (Lebauer and Treseder 2008; Fay et al. 2015; Wu et al. 2022). Over the past century, the burning of fossil fuels has caused a substantial influx of active N deposition into terrestrial ecosystems (Davidson 2009; Galloway et al. 2008). This N deposition has increased the concentration of active N in the soil, leading to enhanced productivity within grassland ecosystems (Wang et al.2012; Stevens et al. 2016). However, the effects of this increased productivity on the accumulation of soil organic carbon (SOC) is still under debate, with varying effects that range from positive (Fornara et al. 2013; Cenini et al. 2015; Xu et al. 2021), non-significant (Lu et al. 2011; Crowther et al. 2019), to negative (Luo et al. 2020; Lu et al. 2021; Xiao et al. 2021). The dynamics of SOC stocks have significant implications for carbon (C) cycle feedbacks to climate change (Trumbore and Czimczik 2008; Bhattacharya et al. 2016). Given that global grassland ecosystems serve as significant C pools, it is crucial to obtain a comprehensive understanding of SOC sequestration dynamics in grasslands under N enrichment. In this respect, previous research has predominantly focused on the interaction between C and N cycles in response to N deposition (Averill and Waring 2018; Gu et al. 2018; Terrer et al. 2018; Luo et al. 2020; Xiao et al. 2021; Lu et al. 2021). In addition, phosphorus (P) also influences the C cycle (Camenzind et al. 2018; Fang et al. 2019) by constraining biomass accumulation and primary productivity in various ecosystems (Turner et al. 2018). Increasing levels of N can increase the N:P ratio in soil, with stoichiometric consequences for plant tissues and soil microbes. To maintain N:P stoichiometric homeostasis for their growth, plants and microbes must enhance their acquisition of the most limiting nutrient: either N or P (Cleveland and Liptzin 2007; Finkel et al. 2019). Specifically, plants respond by producing carboxylates to actively acquire P through absorption mechanisms (Lambers 2022), which can induce a priming effect and destabilize the SOC (Ding et al. 2021). Meanwhile, soil microbes are likely to increase their production of extracellular enzymes to obtain limiting nutrients from the decomposition of SOC (Bowles et al. 2014). Therefore, the P limitation induced by increasing N deposition could influence the physiological processes of plants and microbes, which will subsequently influence C storage in soil. Along with stoichiometric changes, N enrichment also impacts SOC by altering the balance between C gains through plant photosynthesis and C losses via microbial decomposition (Houghton 2007). The addition of N has been shown to increase both above- and belowground plant C inputs (Xu et al. 2020). More specifically, the increased input of fresh organic matter can induce a priming effect, stimulating activities of soil microbes in the short term (Kuzyakov et al. 2000; Cheng et al. 2014). Over the long term, soil microbes play a critical role in determining SOC mineralization in response to nutrient status, including N and P availability, as well as their stoichiometric ratios (Kirkby et al. 2013; Chen et al. 2014). According to the consumer-driven nutrient recycling theory, the elemental ratios of consumers and their resources dictate the ratio of C to nutrients (N or P) released through different recycling processes (Sterner and Elser, 2002). Specifically, soil microbes maintain stoichiometric homeostasis through their biomass C:N:P ratios (Cleveland and Liptzin, 2007), reallocating limiting resources (eg. C, N and P) to acquisition mechanisms rather than growth (Schimel et al. 2007). The differentiation of microbial C, N and P demands allows for predictions of C cycling dynamics under varying nutrient regimes (De Sosa et al. 2018; Hessen et al. 2013). Thus, investigating the link between microbial stoichiometric homeostasis and SOC decomposition is integral to understanding soil C dynamics under climate change. In this study, we explored the impacts of N enrichment on SOC dynamics and stoichiometry in the Qinghai–Tibet Plateau (QTP), a region that represents a substantial SOC pool (Chen et al. 2023). The QTP has been experiencing N deposition, ranging from 4.2 to 12.6 kg∙ha − 1 ∙yr − 1 (Zhu et al. 2016), which is lower than the average N deposition level in China (21.1 kg∙ha − 1 ∙yr − 1 ; Han et al. 2019). As N deposition is expected to continue increasing in the future, understanding how SOC in the QTP responds to this rising N deposition remains a poorly understood aspect (Luo et al. 2020; Xiao et al. 2021; Yang et al. 2021). The QTP is primarily composed of alpine grassland ecosystems, offering a valuable platform and resources for studying SOC responses to N deposition in these environments. We conducted this study by integrating a meta-analysis to quantify the effects of N concentration on SOC in QTP grassland ecosystems and a field experiment involving N and P additions to investigate the influence of soil microbial stoichiometry on SOC responses to N deposition. The aim of this research was to address two main questions: ( 1 ) How does N deposition affect SOC in alpine grasslands? ( 2 ) Does microbial P stoichiometry impact SOC sequestration during N deposition? Materials and methods 2.1 Meta-analysis We constructed our dataset by conducting searches on Web of Science, Google Scholar, and China National Knowledge from January 1, 2000, to December 31, 2022. The keyword combinations used were “Nitrogen/N addition”, “Nitrogen/N enrichment”, “Nitrogen/N deposition”, and “alpine” or “Tibet”. To minimize bias, we applied the following criteria to select relevant studies that included (i) both control and N-addition plots conducted in alpine grassland; (ii) measurement of soil properties such as pH, SOC, total phosphorus (TP), and available phosphorus (AP); (iii) availability of means, standard deviation (SD), standard error (SE), and sample size, either directly from the article or extractable from digitized graphs using Getdata Graph Digitizer (version 2.26, Moscow, Russia); (vi) consideration of different N-addition rates in the same experiment as multiple observations. In total, we collected 18 studies conducted in alpine grassland on the QTP (see Supplementary material 1 ). During the data collection, we applied the following criteria to choose relevant data from the papers: ( 1 ) only data from N-addition and control treatments conducted in the same ecosystems and under the same conditions were considered; ( 2 ) N-addition forms only included inorganic N (such as NH 4 NO 3 , NH 4 Cl), and organic N (such as CO(NH 2 ) 2 ) was excluded; ( 3 ) treatments involving the addition of other fertilizers (e.g. P) in addition to N were excluded; ( 4 ) soil samples taken at a depth of 0–30 cm were included; ( 5 ) N-addition experiments that lasted for at least two years were included; and ( 6 ) if a study reported SE instead of SD, we calculated the SD value by taking the square root of the SE. By applying these criteria, we ensured that the selected data met specific requirements for comparability and reliability in our analysis. Having collected the data, we then performed the meta-analysis using the methodologies described in Hedges et al. (1999) and Lu et al. (2021) to unravel the responses of the selected variables to N deposition. 2.2 N- and P-addition experiment Study site The N- and P-addition experiment was conducted at the Xainzha Alpine Steppe and Wetland Ecosystem Observation and Experiment Station, located in the northern QTP (30°57'N, 88°42'E; 4675 m a.s.l). The experiment was conducted in a Stipa purpurea steppe, dominated by S. purpurea and Carex moorcroftii , with Artemisia nanschanica as a companion species. The soil in this region is primarily composed of frigid calcic soil, with a high sand content of approximately 77% and a pH level around 8. Experimental treatments The experiment consisted of four treatments: a control treatment (CK), an N-addition experiment (N), a P-addition experiment (P), and a combination of N and P addition (N + P). A total of twelve 4 × 4 m plots were established in a Latin square design in 2013, with a separation of 1 m between plots. For the N-addition treatments, two different rates were applied: 2 g m − 2 yr − 1 (N2) and 10 g m − 2 yr − 1 (N10), using NH 4 NO 3 as the fertilizer. The P-addition treatment involved a rate of 4 g m − 2 yr − 1 , using a mixture of K 2 HPO 4 and KH 2 PO 4 , which was adjusted to maintain a pH value of 7. The N, P, and N + P amendments were applied twice, at the beginning of June and July, from 2013 to 2020. The fertilizers were dissolved in 1 L of water and evenly sprayed over each plot. Sampling In each plot (1 × 1 m quadrat), we recorded the number of plant species and collected ground litter in mid-August 2020. We also clipped and sorted all shoots within each plot according to their respective species. After clipping the aboveground biomass, we collected five soil core samples at a depth of 0–15 cm, each with a 6 cm diameter. The soil samples were then mixed to create a composite sample for each plot. To remove roots and stones, the soil samples were sieved through a 2 mm mesh. The soil samples were divided into two parts. One part was stored in an ice box and later transferred to the laboratory for soil chemical characterization and microbial analysis. The second part was air-dried for soil pH analysis. Soil properties The soil pH was measured using a pH meter (E20-FiveEasyTM pH, Mettler Toledo, Germany) with a 1:5 soil to deionized water (wt/v) ratio. SOC and dissolved organic carbon (DOC) were analyzed using a TOC analyzer (Multi N/C 3000, Analytik Jena, Germany). Soil total nitrogen (TN) was determined using an elemental analyzer (Vario Max Elementar, Germany). The available nitrogen (AN) in the soil was estimated using the alkaline hydrolysis method (Lu 1999). Soil AP was extracted using a sodium bicarbonate solution and quantified using the molybdenum blue method (Lu, 1999). Soil TP was determined using the alkali fusion Mo-Sb anti spectrophotometric method (Lu 1999) for soil TP analysis. Leaf C, N and P contents We specifically selected the dominant species ( S. purpurea and C. moorcroftii ) as well as a companion species ( A. nanschanica ) to measure their leaf C, N and P contents, which provide insights into plant nutrient status. The leaf C content was quantified using an elemental analyzer (VarioEL Cube, Elementar Corp. Germany). The leaf N content was determined using the semi-micro Kjeldahl method (Lu, 1999). The leaf P content was measured using the alkali fusion Mo-Sb anti spectrophotometric method (Lu, 1999). These analyses allowed us to assess the nutrient composition of the selected plant species. Microbial biomass C, N and P Microbial biomass C (MC), N (MN) and P (MP) concentrations were assessed using the chloroform fumigation method (Brookes et al. 1985). Subsequently, the molar ratios of MC:MN, MC:MP, and MN:MP were calculated. Enzyme activity assays The enzyme activities of β-1,4-glucosidase (BG, an enzyme involved in organic C degradation), L-leucine aminopeptidase (LAP, an enzyme involved in organic N degradation), β-N-acetylglucosaminidase (NAG, an enzyme involved in organic N degradation), and acid phosphatase (APA, an enzyme involved in organic P degradation) were measured to assess the microbial nutrient status (Sinsabaugh et al. 2009). The measurement methods used were modifications of the techniques described by Saiya-Cork et al. (2002), Steinweg et al. (2012), and Bell et al. (2013), using fluorometric techniques. Quantification of microbial metabolic limitation Microbial nutrient limitation was assessed by quantifying the vector lengths and angles of enzymatic activity based on untransformed proportional activities specifically, BG/(LAP + NAG), (LAP + NAG)/APA, and BG/APA. The vector length represents C limitation and was calculated as the square root of the sum of the power values of BG/(LAP + NAG) and BG/APA (Moorhead et al. 2013, 2016). On the other hand, the vector angle represents N or P limitation, with vector angles greater than 45° indicating microbial P limitation, and vector angles less than 45° indicating microbial N limitation. The vector angle was calculated as the arctangent of the line extending from the plot origin to the point (BG/APA, BG/(LAP + NAG)) (Moorhead et al. 2013, 2016). Statistical analysis The response ratio is a commonly used measure of experimental effect (Hedges et al. 1999). In this study, the response ratio represents the ratio of estimated biomass in the fertilized plot to the CK plot, which was used to determine the impact of N or P on soil properties. The response ratio for soil properties was calculated as the natural logarithm of the ratio between soil properties in the fertilization treatments and soil properties in CK. A structural equation model was introduced to assess the effects of N addition on aboveground biomass, leaf N:P, MC:MP, MC:MN, MC:MP, and SOC. The model was fitted using the maximum likelihood estimation method in IBM Amos 26.0 (SPSS, Chicago, IL, USA). Differences in MC:MP, MC:MN, and MC:MP among different N- and P-addition treatments were tested using one-way ANOVA, followed by a Duncan’s test ( p < 0.05). Regression analysis procedures were performed in SPSS 21.0 (SPSS, Chicago, IL, USA). Results 3.1 Meta-analysis of the change in the response ratios of soil pH, SOC, TP and AP with N addition The meta-analysis conducted on N addition in the QTP showed that pH decreased with increasing N addition (Fig. 1 A). SOC exhibited an initial increase at low N-addition levels (N < 5 g∙m − 2 ) but decreased at higher N addition levels (N ≥ 10 g∙m − 2 ) (Fig. 1 B). TP and AP decreased as N addition increased (Fig. 1 C, D). Changes in response ratios of soil C, N and P with N and P addition The response ratios of soil C, N and P varied between the N- and P-addition treatments (Fig. 2 ). The response ratio of soil pH was found to be neutral across all treatments. The response ratio of SOC was positive in the N2, N2 + P, and N10 + P treatments, but neutral in the N10 and P treatments. Conversely, the response ratio of DOC was negative in all treatments. The response ratios of TN and AN were positive in the N and N + P treatments. The response ratio of TN was neutral in the P treatment, while the response ratio of AN was negative in the P treatment. The response ratios of TP and AP were positive in the P and N + P treatments. However, the response ratios of TP and AP were neutral in the N treatment. Changes in microbial stoichiometry with N and P addition The addition of N, either alone or in combination with P, significantly decreased the MC:MN ratio, which was lower than that observed with P addition (Table 1 ). Additionally, the MC:MP ratio significantly decreased with N or N + P addition. While the MC:MP ratio under N addition was similar to that under P addition, it reached its lowest value in the N- and P-addition treatments (Table 1 ). Moreover, the MN:MP ratio significantly increased with N addition, but significantly decreased with N + P addition. The MN:MP ratio under P addition was higher than that under N + P addition (Table 1 ). Table 1 Microbial stoichiometry ratios under different N and P treatments CK N2 N2 + P N10 N10 + P P MC:MN 15.56 ± 1.56a 5.37 ± 0.19c 6.52 ± 0.33c 7.37 ± 1.23c 6.15 ± 0.57c 11.61 ± 0.56b MC:MP 22.63 ± 2.64a 12.03 ± 0.05b 3.51 ± 0.26c 15.16 ± 1.44b 3.19 ± 0.28c 10.70 ± 1.78b MN:MP 1.45 ± 0.03c 2.24 ± 0.19b 0.55 ± 0.07e 2.84 ± 0.13a 0.52 ± 0.01e 0.92 ± 0.14d Note: lowercase letters indicate significant differences in the results of the one-way ANOVA. Effects of microbial stoichiometry on SOC Changes in microbial stoichiometry had a significant effect on SOC and DOC. The MC:MP ratio showed a significant negative correlation with SOC (Fig. 3 B), whereas the MC:MN and MN:MP ratios did not exhibit a significant correlation with SOC (Fig. 3 A, C). The MC:MN ratio showed a significant negative correlation with DOC (Fig. 3 E), whereas the MC:MP and MN:MP ratios did not show a significant correlation with DOC (Fig. 3 D, F). Relationships between microbial metabolic limitation and SOC Microbial C limitation exhibited a significant negative correlation with SOC content, but it was not significantly correlated with soil DOC (Fig. 4 A, B). Microbial P limitation showed a significant negative correlation with SOC (Fig. 4 C). Additionally, microbial P limitation displayed a significant positive correlation with microbial C limitation (Fig. 4 D). Relationships between plant leaf and microbial stoichiometry Significant relationships were observed between plant leaf and soil microbial stoichiometry (Fig. 5 ). The MC:MN ratios showed significant differences among plant species, with S. purpurea ( R 2 = 0.79, p < 0.05), C. moorcroftii ( R 2 = 0.75, p < 0.05), and A. nanschanica ( R 2 = 0.69, p < 0.05) displaying distinct patterns. Similarly, the MC:MP ratios exhibited significant variations across plant species, including S. purpurea ( R 2 = 0.63, p < 0.05), C. moorcroftii ( R 2 = 0.70, p < 0.05), and A. nanschanica ( R 2 = 0.49, p < 0.05). Furthermore, the MN:MP ratios were significantly different among plant species, with S. purpurea ( R 2 = 0.79, p < 0.05), C. moorcroftii ( R 2 = 0.87, p < 0.05), and A. nanschanica ( R 2 = 0.84, p < 0.05) displaying distinct relationships. Mechanism by which soil microbial stoichiometry influences SOC sequestration. The effects of N addition on plants, soil microbial stoichiometry, and SOC were investigated using structural equation modeling (Fig. 6 ). The model results revealed that N addition accounted for a substantial amount of variation, explaining 90% of the variation in above-ground biomass, 95% of the variation in plant leaf N:P, 58% of the variation in soil MC:MN, 36% of the variation in soil MC:MP, and 98% of the variation in soil MN:MP (Fig. 6 ). N addition had significant positive effects on above-ground biomass and plant leaf N:P (Fig. 6 ). However, there was no significant impact of N addition on soil microbial stoichiometry. Notably, only plant leaf N:P showed a significant effect on MN:MP. Moreover, above-ground biomass, MC:MN, and MN:MP had significant positive effects on SOC, while plant leaf N:P and MC:MP had significant negative effects on SOC (Fig. 6 ). Discussion N deposition affects SOC sequestration in alpine grassland ecosystems In grassland ecosystems, N deposition has been observed to increase soil N availability and alleviate N limitation, leading to increased plant productivity (Stevens et al. 2016; Liang et al. 2020). In general, plants significantly augment the input of organic matter into the soil, consequently fostering an elevation in soil organic matter content (Bhattacharya et al. 2016; Rüegg et al. 2019). However, our results indicate that SOC increases at low N-addition levels (N < 5 g∙m − 2 ) but decreases at high N-addition levels (N ≥ 10 g∙m − 2 ). Neff et al. (2002) stated that the responses of alpine ecosystems to fertilization involve both increased productivity and increased decomposition of SOC. Similarly, Xiao et al. (2021) reported the existence of SOC sequestration thresholds in response to N addition in alpine meadows on the QTP. Hence, it is plausible that alpine grassland ecosystems may experience reductions in SOC due to rising N deposition in the future. N deposition affects SOC sequestration by influencing the MC:MP ratio P is an essential nutrient for the growth of plants and microbes (Hawkesford et al. 2023). The combined results of meta-analyses and experiments revealed a negative response of available P to high N levels (N ≥ 10 g∙m − 2 ), indicating a significant decrease in available P due to increased N availability. We also observed significant correlations between the stoichiometry of plant elements (C:N, N:P, and C:P) and microbial stoichiometry (Fig. 5 ). Furthermore, structural equation modeling also demonstrated a positive and significant relationship between the plant leaf N:P ratio and the MN:MP ratio (Fig. 6 ). These findings support the notion that plant and microbial stoichiometry align with N addition (Zechmeister-Boltenstern et al. 2016; Yuan et al. 2019). The increase in soil available N resulting from N deposition can exacerbate the deficiency of P for both plants and microbes (Wu et al. 2022). To maintain N:P stoichiometric homeostasis for their growth, plants and microbes must enhance their acquisition of the most limiting nutrient (Cleveland and Liptzin 2007; Schimel et al. 2007; Finkel et al. 2019). Furthermore, the results of microbial eco-enzymatic stoichiometry indicate that microbial growth is limited by P at the N10 level (Fig. 4 D), consistent with the findings of the meta-analysis conducted by Xu et al. (2022). Therefore, we can conclude that both plants and microbes require more P at higher levels of N addition. The significant negative correlation between plant leaf N:P ratio and SOC (Fig. 6 ) indicates that N addition accelerated the decomposition of SOC. The structural equation model revealed that N addition significantly increased plant biomass and the N:P ratio, which supports the suggestion that N is a primary limiting nutrient for plant growth (Fay et al. 2015; Wu et al. 2022). To acquire more available P, plants promote the growth of fine roots (Li et al. 2015), which results in an increase in root biomass (Lambers, 2020). Specifically, under low-P conditions, roots produce more carboxylates, which can release P that is complexed with Fe and Al (Tomasi et al. 2008; Cesco et al. 2012). Simultaneously, carboxylates also release C that is compounded minerals and aggregates, thereby accelerating SOC decomposition (Ding et al. 2021). Therefore, the increased production of carboxylates can stimulate a priming effect, activating microbes to decompose SOC (Cheng et al. 2014; Xu et al. 2019). As N addition increases the microbial demand for P (Cleveland and Liptzin, 2007), and MC:MP ratios follow stoichiometric homeostasis, this accelerates the mineralization of SOC, releasing P (Camenzind et al. 2018) due to inadequate inorganic P availability (Zheng et al. 2015). In this study, the MC:MP ratio decreased significantly with N addition and was lower than that in the P-addition treatment (Table 1 ), suggesting an increased acquisition of P by microbes ( Supplementary material 2, Table S1 ). When soil available P decreases, organic P and P bound to rocks and minerals become the dominant P pools (Oliverio et al. 2020), which induces microbes to produce more extracellular phosphatase to obtain P (Olander and Vitousek 2000, Supplementary material 2, Table S2 ). At the same time, microbial P limitation also intensifies microbial C limitation (Fig. 4 D). Specifically, microbial C decreases significantly with N addition, while microbial P remains relatively stable ( Supplementary material 2, Table S1 ). This is because microbes acquire more C as an energy source to fulfill their increased demand for P to maintain stoichiometric homeostasis (Zechmeister-Boltenstern et al. 2016; Finn et al. 2016; Dai et al. 2019). These results suggest that microbial C limitation increases due to N addition, consequently accelerating SOC decomposition (Xu et al. 2022). Furthermore, we found no significant relationship betweenMC:MP and plant leaf N:P under N addition (Fig. 6 ), indicating that soil microbial stoichiometry is not associated with litter stoichiometry (Fanin et al. 2013; Zechmeister-Boltenstern et al. 2015). In conclusion, these findings demonstrate that microbial stoichiometric homeostasis of MC:MP enhances SOC decomposition with increasing N addition, supporting the idea that consumer-driven nutrient recycling shapes the dynamics of SOC. Conclusion This study revealed that the SOC content tends to increase at low levels of N deposition but decrease at high levels of N deposition (> 10 g∙m − 2 ) in alpine grassland ecosystems. While the increases in SOC may be directly associated with increased plant C inputs, the reduced SOC storage at high concentrations can be explained by the enhancement of plant and microbial P limitation under higher N deposition scenarios, which place pressures on plants and microbes to maintain stoichiometric homeostasis. However, due to the limited availability of P in the soil, this can result in an increase in organic C input by plants, and then acceleration of SOC decomposition through priming effects. Furthermore, we discovered that microbes respond to P limitation by increasing the production of extracellular phosphatase to activate organic P, thus alleviating P limitation and maintaining stoichiometric MC:MP homeostasis. As a consequence, microbes require more C as an energy resource, resulting in increased SOC decomposition. Overall, our study highlights the importance of the MC:MP ratio in mediating SOC sequestration and implies that SOC in the QTP will decrease with the increasing deposition of N in the future. This implication highlights the challenge we face in increasing C sequestration in terrestrial ecosystems to mitigate climate change. Declarations Declaration of Interest Statement: The author(s) declared no potential conflicts of interest with respect to the research, author- ship, and/or publication of this article. Author contributions: Jianbo Wu and Lidong Mo conceived the ideas and designed the methodology; Jianbo Wu, Lidong Mo and Hui Zhao collected and analyzed the data; Jianbo Wu, Lidong Mo, Constantin M. Zohner, Fan Chen and Xiaodan Wang led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. Acknowledgements This study was financially supported by the Second Tibetan Plateau Scientific Expedition and Research (2019QZKK04040102), the Science and Technology Research Program of the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (IMHE-ZDRW-04), the Optimization and Integration of Vegetation Restoration Techniques for Hydropower Stations in Alpine Regions (HNKJ20-H23) and the Nation Natural Science Foundation of China (41401072) References Averill C, Waring B (2018) Nitrogen limitation of decomposition and decay: how can it occur? Global Change Bio 24:1417–1427. https://doi.org/10.1111/gcb.13980 Bhattacharya SS, Kim K-H, Das S et al (2016) A review on the role of organic inputs in maintaining the soil carbon pool of the terrestrial ecosystem. 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Eur J Soil Biol 68:77–84. https://doi.org/10.1016/j.ejsobi.2015.03.010 Zhu J, Wang Q, He N et al (2016) Imbalanced atmospheric nitrogen and phosphorus depositions in China: Implications for nutrient limitation. J Geophys Res Biogeo 121:1605–1616. https://doi.org/10.1002/2016JG003393 Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4645564","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324244859,"identity":"48e6f195-d582-41bf-98da-94abe3ea2909","order_by":0,"name":"Jianbo Wu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jianbo","middleName":"","lastName":"Wu","suffix":""},{"id":324244860,"identity":"72cf566a-9619-463c-ae3f-bad7254746dd","order_by":1,"name":"Lidong Mo","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Lidong","middleName":"","lastName":"Mo","suffix":""},{"id":324244861,"identity":"d6dbb627-53de-4d11-a551-651ba3543349","order_by":2,"name":"Constantin M. Zohner","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Constantin","middleName":"M.","lastName":"Zohner","suffix":""},{"id":324244862,"identity":"b38863cb-8b6e-43eb-be22-ee2b5b73a852","order_by":3,"name":"Hui Zhao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Zhao","suffix":""},{"id":324244863,"identity":"bcac82ac-19cc-4f7b-8936-0c47df01a8c5","order_by":4,"name":"Fan Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIie3QIQvCQBTA8TcOZjlcvaHMr/BEUESbX2SHoEVhcWGgY3IGFes+xqJ1DJZmN04MVm0Gg9cVbzbD/fL9ee8dgKb9IdOK0ssDh45VC8PS9QN1Umf5uAPepGNvswjLIlcnDsy6DbhlPImnwj6vSIXFQE7xMDMS4MLnSxOs9cb9nhB5S4xT0oNUnPihCaw4JsopSHFg9sNQJoUJyOaqZNZlFAmVuwmPC1ItaVAcMcwNAdUS+cntGCdob42IuUVOlbe09lFa3p7Dxb51Pd8ffuBY69335A397bmmaZr20QsSkUwJKhoX5AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0001-8972-793X","institution":"Powerchina Guiyang Engineering corporation limited","correspondingAuthor":true,"prefix":"","firstName":"Fan","middleName":"","lastName":"Chen","suffix":""},{"id":324244864,"identity":"04d443de-849f-4d69-ad44-0dca9f5e39e6","order_by":5,"name":"Xiaodan Wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Xiaodan","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-06-27 02:50:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4645564/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4645564/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61549194,"identity":"970e8b46-27d2-416a-ac69-c63fe73b58f1","added_by":"auto","created_at":"2024-08-01 05:55:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3171212,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of N addition on soil pH (A), SOC (B), TP (C) and AP (D) using meta-analysis. \u003c/strong\u003eThe bars in the graph represent 95% confidence intervals, while the numbers displayed next to the bars and in brackets indicate the corresponding sample and study counts. The \u003cem\u003ey-\u003c/em\u003eaxis indicates the N-addition amount (g∙m\u003csup\u003e−2\u003c/sup\u003e).\u003c/p\u003e","description":"","filename":"fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/bcc8de52c865cf72c2056c7b.png"},{"id":61549195,"identity":"0bcf9d04-ba32-4962-bda9-b944c310430d","added_by":"auto","created_at":"2024-08-01 05:55:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1444014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResponse ratios of soil C, N and P with N and P addition\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/fab175b6cb39ec80340ae47e.png"},{"id":61549953,"identity":"35a95136-a72a-4f61-b264-99a285c8d912","added_by":"auto","created_at":"2024-08-01 06:11:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1643038,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationships of microbial stoichiometry ratios with SOC and DOC. \u003c/strong\u003eThe red lines in panels \u003cstrong\u003eB\u003c/strong\u003e and \u003cstrong\u003eD\u003c/strong\u003e indicate significant linear model fits, while in the other panels, no significant linear model fitting has been detected.\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/6a3fae9306fe9d73391fd2d9.png"},{"id":61549200,"identity":"e88742d3-493f-41e7-8545-ff50c376498a","added_by":"auto","created_at":"2024-08-01 05:55:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3175075,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationships of microbial C and P(N) limitation with SOC and DOC. \u003c/strong\u003eThe red line indicates the linear model fits significantly. Microbial C limitation is represented by the vector length (\u003cem\u003ey\u003c/em\u003e-axis); microbial C limitation increases as the value increases. Microbial P(N) limitations are represented by the vector angle (\u003cem\u003ex\u003c/em\u003e-axis); angles \u0026gt;45° represent microbial P limitation, and angles \u0026lt;45° represent N limitation. Open diamonds and triangles denote the N10 treatment.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/eed247e31da29fed222dd8b4.png"},{"id":61549468,"identity":"0f9f07a1-1ea5-49b2-a6a0-993dd462b570","added_by":"auto","created_at":"2024-08-01 06:03:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2505782,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationships between plant leaf and soil microbial stoichiometry.\u003c/strong\u003e Black lines and squares indicate the plant leaf and soil microbial stoichiometry relationship of \u003cem\u003eS. purpurea\u003c/em\u003e. Red lines and circles indicate the plant leaf and soil microbial stoichiometry relationship of \u003cem\u003eC. moorcroftii\u003c/em\u003e. Blue lines and triangles indicate the plant leaf and soil microbial stoichiometry relationship of \u003cem\u003eA. nanschanica\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/3eb558b663ae70ea191e5282.png"},{"id":61549466,"identity":"1173039e-f390-4fd6-b32d-0bcd09f74581","added_by":"auto","created_at":"2024-08-01 06:03:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":197172,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural equation model explaining how N addition influenced the above ground biomass, plant leaf N:P, soil MC:MN, MC:MP and MN:MP, and SOC.\u003c/strong\u003e The percentage values close to the variables indicate the percentage of the variation in those variables accounted for by the model (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e). Adjacent values near the arrows indicate path coefficients. Red solid arrows represent significantly positive relationships (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) and blue solid arrows represent significantly negative relationships (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). Black dashed arrows represent the nonsignificant relationships between different variables (\u003cem\u003ep\u003c/em\u003e\u0026gt;0.05).\u003c/p\u003e","description":"","filename":"fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/a9d7f15bd3c3bbb3f1321cbb.png"},{"id":62794871,"identity":"5fbcb450-4861-4d70-8cb8-cb89ab2aa102","added_by":"auto","created_at":"2024-08-19 15:01:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13252484,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/a47d58d8-0835-49cd-b6d8-ee5bef33c6fe.pdf"},{"id":61549196,"identity":"b1e0400a-adad-4f3c-9152-e4d360560b27","added_by":"auto","created_at":"2024-08-01 05:55:36","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":23576,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4645564/v1/99bfbc36afb694f29eeb9bd6.docx"}],"financialInterests":"","formattedTitle":"Reduced soil organic carbon sequestration driven by nitrogen deposition–induced increases in microbial carbon to phosphorus ratio in alpine grassland","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNitrogen (N) is the primary limiting nutrient for grassland ecosystems (Lebauer and Treseder 2008; Fay et al. 2015; Wu et al. 2022). Over the past century, the burning of fossil fuels has caused a substantial influx of active N deposition into terrestrial ecosystems (Davidson 2009; Galloway et al. 2008). This N deposition has increased the concentration of active N in the soil, leading to enhanced productivity within grassland ecosystems (Wang et al.2012; Stevens et al. 2016). However, the effects of this increased productivity on the accumulation of soil organic carbon (SOC) is still under debate, with varying effects that range from positive (Fornara et al. 2013; Cenini et al. 2015; Xu et al. 2021), non-significant (Lu et al. 2011; Crowther et al. 2019), to negative (Luo et al. 2020; Lu et al. 2021; Xiao et al. 2021). The dynamics of SOC stocks have significant implications for carbon (C) cycle feedbacks to climate change (Trumbore and Czimczik 2008; Bhattacharya et al. 2016). Given that global grassland ecosystems serve as significant C pools, it is crucial to obtain a comprehensive understanding of SOC sequestration dynamics in grasslands under N enrichment.\u003c/p\u003e \u003cp\u003eIn this respect, previous research has predominantly focused on the interaction between C and N cycles in response to N deposition (Averill and Waring 2018; Gu et al. 2018; Terrer et al. 2018; Luo et al. 2020; Xiao et al. 2021; Lu et al. 2021). In addition, phosphorus (P) also influences the C cycle (Camenzind et al. 2018; Fang et al. 2019) by constraining biomass accumulation and primary productivity in various ecosystems (Turner et al. 2018). Increasing levels of N can increase the N:P ratio in soil, with stoichiometric consequences for plant tissues and soil microbes. To maintain N:P stoichiometric homeostasis for their growth, plants and microbes must enhance their acquisition of the most limiting nutrient: either N or P (Cleveland and Liptzin 2007; Finkel et al. 2019). Specifically, plants respond by producing carboxylates to actively acquire P through absorption mechanisms (Lambers 2022), which can induce a priming effect and destabilize the SOC (Ding et al. 2021). Meanwhile, soil microbes are likely to increase their production of extracellular enzymes to obtain limiting nutrients from the decomposition of SOC (Bowles et al. 2014). Therefore, the P limitation induced by increasing N deposition could influence the physiological processes of plants and microbes, which will subsequently influence C storage in soil.\u003c/p\u003e \u003cp\u003eAlong with stoichiometric changes, N enrichment also impacts SOC by altering the balance between C gains through plant photosynthesis and C losses via microbial decomposition (Houghton 2007). The addition of N has been shown to increase both above- and belowground plant C inputs (Xu et al. 2020). More specifically, the increased input of fresh organic matter can induce a priming effect, stimulating activities of soil microbes in the short term (Kuzyakov et al. 2000; Cheng et al. 2014). Over the long term, soil microbes play a critical role in determining SOC mineralization in response to nutrient status, including N and P availability, as well as their stoichiometric ratios (Kirkby et al. 2013; Chen et al. 2014). According to the consumer-driven nutrient recycling theory, the elemental ratios of consumers and their resources dictate the ratio of C to nutrients (N or P) released through different recycling processes (Sterner and Elser, 2002). Specifically, soil microbes maintain stoichiometric homeostasis through their biomass C:N:P ratios (Cleveland and Liptzin, 2007), reallocating limiting resources (eg. C, N and P) to acquisition mechanisms rather than growth (Schimel et al. 2007). The differentiation of microbial C, N and P demands allows for predictions of C cycling dynamics under varying nutrient regimes (De Sosa et al. 2018; Hessen et al. 2013). Thus, investigating the link between microbial stoichiometric homeostasis and SOC decomposition is integral to understanding soil C dynamics under climate change.\u003c/p\u003e \u003cp\u003eIn this study, we explored the impacts of N enrichment on SOC dynamics and stoichiometry in the Qinghai\u0026ndash;Tibet Plateau (QTP), a region that represents a substantial SOC pool (Chen et al. 2023). The QTP has been experiencing N deposition, ranging from 4.2 to 12.6 kg∙ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e∙yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Zhu et al. 2016), which is lower than the average N deposition level in China (21.1 kg∙ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e∙yr\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e; Han et al. 2019). As N deposition is expected to continue increasing in the future, understanding how SOC in the QTP responds to this rising N deposition remains a poorly understood aspect (Luo et al. 2020; Xiao et al. 2021; Yang et al. 2021). The QTP is primarily composed of alpine grassland ecosystems, offering a valuable platform and resources for studying SOC responses to N deposition in these environments. We conducted this study by integrating a meta-analysis to quantify the effects of N concentration on SOC in QTP grassland ecosystems and a field experiment involving N and P additions to investigate the influence of soil microbial stoichiometry on SOC responses to N deposition. The aim of this research was to address two main questions: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) How does N deposition affect SOC in alpine grasslands? (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Does microbial P stoichiometry impact SOC sequestration during N deposition?\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Meta-analysis\u003c/h2\u003e \u003cp\u003eWe constructed our dataset by conducting searches on Web of Science, Google Scholar, and China National Knowledge from January 1, 2000, to December 31, 2022. The keyword combinations used were “Nitrogen/N addition”, “Nitrogen/N enrichment”, “Nitrogen/N deposition”, and “alpine” or “Tibet”. To minimize bias, we applied the following criteria to select relevant studies that included (i) both control and N-addition plots conducted in alpine grassland; (ii) measurement of soil properties such as pH, SOC, total phosphorus (TP), and available phosphorus (AP); (iii) availability of means, standard deviation (SD), standard error (SE), and sample size, either directly from the article or extractable from digitized graphs using Getdata Graph Digitizer (version 2.26, Moscow, Russia); (vi) consideration of different N-addition rates in the same experiment as multiple observations. In total, we collected 18 studies conducted in alpine grassland on the QTP (see \u003cb\u003eSupplementary material 1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eDuring the data collection, we applied the following criteria to choose relevant data from the papers: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) only data from N-addition and control treatments conducted in the same ecosystems and under the same conditions were considered; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) N-addition forms only included inorganic N (such as NH\u003csub\u003e4\u003c/sub\u003eNO\u003csub\u003e3\u003c/sub\u003e, NH\u003csub\u003e4\u003c/sub\u003eCl), and organic N (such as CO(NH\u003csub\u003e2\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e) was excluded; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) treatments involving the addition of other fertilizers (e.g. P) in addition to N were excluded; (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) soil samples taken at a depth of 0–30 cm were included; (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) N-addition experiments that lasted for at least two years were included; and (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) if a study reported SE instead of SD, we calculated the SD value by taking the square root of the SE. By applying these criteria, we ensured that the selected data met specific requirements for comparability and reliability in our analysis.\u003c/p\u003e \u003cp\u003eHaving collected the data, we then performed the meta-analysis using the methodologies described in Hedges et al. (1999) and Lu et al. (2021) to unravel the responses of the selected variables to N deposition.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 N- and P-addition experiment\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eStudy site\u003c/h2\u003e \u003cp\u003eThe N- and P-addition experiment was conducted at the Xainzha Alpine Steppe and Wetland Ecosystem Observation and Experiment Station, located in the northern QTP (30°57'N, 88°42'E; 4675 m a.s.l). The experiment was conducted in a \u003cem\u003eStipa purpurea\u003c/em\u003e steppe, dominated by \u003cem\u003eS. purpurea\u003c/em\u003e and \u003cem\u003eCarex moorcroftii\u003c/em\u003e, with \u003cem\u003eArtemisia nanschanica\u003c/em\u003e as a companion species. The soil in this region is primarily composed of frigid calcic soil, with a high sand content of approximately 77% and a pH level around 8.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eExperimental treatments\u003c/h2\u003e \u003cp\u003eThe experiment consisted of four treatments: a control treatment (CK), an N-addition experiment (N), a P-addition experiment (P), and a combination of N and P addition (N + P). A total of twelve 4 × 4 m plots were established in a Latin square design in 2013, with a separation of 1 m between plots. For the N-addition treatments, two different rates were applied: 2 g m\u003csup\u003e− 2\u003c/sup\u003e yr\u003csup\u003e− 1\u003c/sup\u003e (N2) and 10 g m\u003csup\u003e− 2\u003c/sup\u003e yr\u003csup\u003e− 1\u003c/sup\u003e (N10), using NH\u003csub\u003e4\u003c/sub\u003eNO\u003csub\u003e3\u003c/sub\u003e as the fertilizer. The P-addition treatment involved a rate of 4 g m\u003csup\u003e− 2\u003c/sup\u003e yr\u003csup\u003e− 1\u003c/sup\u003e, using a mixture of K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e and KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, which was adjusted to maintain a pH value of 7. The N, P, and N + P amendments were applied twice, at the beginning of June and July, from 2013 to 2020. The fertilizers were dissolved in 1 L of water and evenly sprayed over each plot.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSampling\u003c/h2\u003e \u003cp\u003eIn each plot (1 × 1 m quadrat), we recorded the number of plant species and collected ground litter in mid-August 2020. We also clipped and sorted all shoots within each plot according to their respective species. After clipping the aboveground biomass, we collected five soil core samples at a depth of 0–15 cm, each with a 6 cm diameter. The soil samples were then mixed to create a composite sample for each plot. To remove roots and stones, the soil samples were sieved through a 2 mm mesh. The soil samples were divided into two parts. One part was stored in an ice box and later transferred to the laboratory for soil chemical characterization and microbial analysis. The second part was air-dried for soil pH analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSoil properties\u003c/h2\u003e \u003cp\u003eThe soil pH was measured using a pH meter (E20-FiveEasyTM pH, Mettler Toledo, Germany) with a 1:5 soil to deionized water (wt/v) ratio. SOC and dissolved organic carbon (DOC) were analyzed using a TOC analyzer (Multi N/C 3000, Analytik Jena, Germany). Soil total nitrogen (TN) was determined using an elemental analyzer (Vario Max Elementar, Germany). The available nitrogen (AN) in the soil was estimated using the alkaline hydrolysis method (Lu 1999). Soil AP was extracted using a sodium bicarbonate solution and quantified using the molybdenum blue method (Lu, 1999). Soil TP was determined using the alkali fusion Mo-Sb anti spectrophotometric method (Lu 1999) for soil TP analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLeaf C, N and P contents\u003c/h2\u003e \u003cp\u003eWe specifically selected the dominant species (\u003cem\u003eS. purpurea\u003c/em\u003e and \u003cem\u003eC. moorcroftii\u003c/em\u003e) as well as a companion species (\u003cem\u003eA. nanschanica\u003c/em\u003e) to measure their leaf C, N and P contents, which provide insights into plant nutrient status. The leaf C content was quantified using an elemental analyzer (VarioEL Cube, Elementar Corp. Germany). The leaf N content was determined using the semi-micro Kjeldahl method (Lu, 1999). The leaf P content was measured using the alkali fusion Mo-Sb anti spectrophotometric method (Lu, 1999). These analyses allowed us to assess the nutrient composition of the selected plant species.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial biomass C, N and P\u003c/h2\u003e \u003cp\u003eMicrobial biomass C (MC), N (MN) and P (MP) concentrations were assessed using the chloroform fumigation method (Brookes et al. 1985). Subsequently, the molar ratios of MC:MN, MC:MP, and MN:MP were calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEnzyme activity assays\u003c/h2\u003e \u003cp\u003eThe enzyme activities of β-1,4-glucosidase (BG, an enzyme involved in organic C degradation), L-leucine aminopeptidase (LAP, an enzyme involved in organic N degradation), β-N-acetylglucosaminidase (NAG, an enzyme involved in organic N degradation), and acid phosphatase (APA, an enzyme involved in organic P degradation) were measured to assess the microbial nutrient status (Sinsabaugh et al. 2009). The measurement methods used were modifications of the techniques described by Saiya-Cork et al. (2002), Steinweg et al. (2012), and Bell et al. (2013), using fluorometric techniques.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eQuantification of microbial metabolic limitation\u003c/h2\u003e \u003cp\u003eMicrobial nutrient limitation was assessed by quantifying the vector lengths and angles of enzymatic activity based on untransformed proportional activities specifically, BG/(LAP + NAG), (LAP + NAG)/APA, and BG/APA. The vector length represents C limitation and was calculated as the square root of the sum of the power values of BG/(LAP + NAG) and BG/APA (Moorhead et al. 2013, 2016). On the other hand, the vector angle represents N or P limitation, with vector angles greater than 45° indicating microbial P limitation, and vector angles less than 45° indicating microbial N limitation. The vector angle was calculated as the arctangent of the line extending from the plot origin to the point (BG/APA, BG/(LAP + NAG)) (Moorhead et al. 2013, 2016).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe response ratio is a commonly used measure of experimental effect (Hedges et al. 1999). In this study, the response ratio represents the ratio of estimated biomass in the fertilized plot to the CK plot, which was used to determine the impact of N or P on soil properties. The response ratio for soil properties was calculated as the natural logarithm of the ratio between soil properties in the fertilization treatments and soil properties in CK.\u003c/p\u003e \u003cp\u003eA structural equation model was introduced to assess the effects of N addition on aboveground biomass, leaf N:P, MC:MP, MC:MN, MC:MP, and SOC. The model was fitted using the maximum likelihood estimation method in IBM Amos 26.0 (SPSS, Chicago, IL, USA). Differences in MC:MP, MC:MN, and MC:MP among different N- and P-addition treatments were tested using one-way ANOVA, followed by a Duncan’s test (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Regression analysis procedures were performed in SPSS 21.0 (SPSS, Chicago, IL, USA).\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003e \u003cb\u003e3.1\u003c/b\u003e \u003cb\u003eMeta-analysis of the change in the response ratios of soil pH, SOC, TP and AP with N addition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe meta-analysis conducted on N addition in the QTP showed that pH decreased with increasing N addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). SOC exhibited an initial increase at low N-addition levels (N \u0026lt; 5 g∙m\u003csup\u003e− 2\u003c/sup\u003e) but decreased at higher N addition levels (N ≥ 10 g∙m\u003csup\u003e− 2\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). TP and AP decreased as N addition increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC, D).\u003c/p\u003e\u003ch2\u003eChanges in response ratios of soil C, N and P with N and P addition\u003c/h2\u003e\u003cp\u003eThe response ratios of soil C, N and P varied between the N- and P-addition treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The response ratio of soil pH was found to be neutral across all treatments. The response ratio of SOC was positive in the N2, N2 + P, and N10 + P treatments, but neutral in the N10 and P treatments. Conversely, the response ratio of DOC was negative in all treatments. The response ratios of TN and AN were positive in the N and N + P treatments. The response ratio of TN was neutral in the P treatment, while the response ratio of AN was negative in the P treatment. The response ratios of TP and AP were positive in the P and N + P treatments. However, the response ratios of TP and AP were neutral in the N treatment.\u003c/p\u003e\u003ch2\u003eChanges in microbial stoichiometry with N and P addition\u003c/h2\u003e\u003cp\u003eThe addition of N, either alone or in combination with P, significantly decreased the MC:MN ratio, which was lower than that observed with P addition (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, the MC:MP ratio significantly decreased with N or N + P addition. While the MC:MP ratio under N addition was similar to that under P addition, it reached its lowest value in the N- and P-addition treatments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Moreover, the MN:MP ratio significantly increased with N addition, but significantly decreased with N + P addition. The MN:MP ratio under P addition was higher than that under N + P addition (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMicrobial stoichiometry ratios under different N and P treatments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCK\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN2 + P\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN10\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN10 + P\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMC:MN\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.56 ± 1.56a\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.37 ± 0.19c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.52 ± 0.33c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.37 ± 1.23c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.15 ± 0.57c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.61 ± 0.56b\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMC:MP\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.63 ± 2.64a\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.03 ± 0.05b\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.51 ± 0.26c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.16 ± 1.44b\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.19 ± 0.28c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.70 ± 1.78b\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMN:MP\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45 ± 0.03c\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.24 ± 0.19b\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55 ± 0.07e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.84 ± 0.13a\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52 ± 0.01e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92 ± 0.14d\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: lowercase letters indicate significant differences in the results of the one-way ANOVA.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003ch2\u003eEffects of microbial stoichiometry on SOC\u003c/h2\u003e\u003cp\u003eChanges in microbial stoichiometry had a significant effect on SOC and DOC. The MC:MP ratio showed a significant negative correlation with SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), whereas the MC:MN and MN:MP ratios did not exhibit a significant correlation with SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, C). The MC:MN ratio showed a significant negative correlation with DOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE), whereas the MC:MP and MN:MP ratios did not show a significant correlation with DOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, F).\u003c/p\u003e\u003ch2\u003eRelationships between microbial metabolic limitation and SOC\u003c/h2\u003e\u003cp\u003eMicrobial C limitation exhibited a significant negative correlation with SOC content, but it was not significantly correlated with soil DOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B). Microbial P limitation showed a significant negative correlation with SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Additionally, microbial P limitation displayed a significant positive correlation with microbial C limitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\u003ch2\u003eRelationships between plant leaf and microbial stoichiometry\u003c/h2\u003e\u003cp\u003eSignificant relationships were observed between plant leaf and soil microbial stoichiometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The MC:MN ratios showed significant differences among plant species, with \u003cem\u003eS. purpurea\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.79, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), \u003cem\u003eC. moorcroftii\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.75, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), and \u003cem\u003eA. nanschanica\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.69, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) displaying distinct patterns. Similarly, the MC:MP ratios exhibited significant variations across plant species, including \u003cem\u003eS. purpurea\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.63, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), \u003cem\u003eC. moorcroftii\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.70, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), and \u003cem\u003eA. nanschanica\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.49, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Furthermore, the MN:MP ratios were significantly different among plant species, with \u003cem\u003eS. purpurea\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.79, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), \u003cem\u003eC. moorcroftii\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.87, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05), and \u003cem\u003eA. nanschanica\u003c/em\u003e (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e = 0.84, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) displaying distinct relationships.\u003c/p\u003e\u003cp\u003e \u003cb\u003eMechanism by which soil microbial stoichiometry influences SOC sequestration.\u003c/b\u003e \u003c/p\u003e\u003cp\u003eThe effects of N addition on plants, soil microbial stoichiometry, and SOC were investigated using structural equation modeling (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The model results revealed that N addition accounted for a substantial amount of variation, explaining 90% of the variation in above-ground biomass, 95% of the variation in plant leaf N:P, 58% of the variation in soil MC:MN, 36% of the variation in soil MC:MP, and 98% of the variation in soil MN:MP (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eN addition had significant positive effects on above-ground biomass and plant leaf N:P (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). However, there was no significant impact of N addition on soil microbial stoichiometry. Notably, only plant leaf N:P showed a significant effect on MN:MP. Moreover, above-ground biomass, MC:MN, and MN:MP had significant positive effects on SOC, while plant leaf N:P and MC:MP had significant negative effects on SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eN deposition affects SOC sequestration in alpine grassland ecosystems\u003c/h2\u003e \u003cp\u003eIn grassland ecosystems, N deposition has been observed to increase soil N availability and alleviate N limitation, leading to increased plant productivity (Stevens et al. 2016; Liang et al. 2020). In general, plants significantly augment the input of organic matter into the soil, consequently fostering an elevation in soil organic matter content (Bhattacharya et al. 2016; R\u0026uuml;egg et al. 2019). However, our results indicate that SOC increases at low N-addition levels (N\u0026thinsp;\u0026lt;\u0026thinsp;5 g∙m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) but decreases at high N-addition levels (N\u0026thinsp;\u0026ge;\u0026thinsp;10 g∙m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e). Neff et al. (2002) stated that the responses of alpine ecosystems to fertilization involve both increased productivity and increased decomposition of SOC. Similarly, Xiao et al. (2021) reported the existence of SOC sequestration thresholds in response to N addition in alpine meadows on the QTP. Hence, it is plausible that alpine grassland ecosystems may experience reductions in SOC due to rising N deposition in the future.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eN deposition affects SOC sequestration by influencing the MC:MP ratio\u003c/h2\u003e \u003cp\u003eP is an essential nutrient for the growth of plants and microbes (Hawkesford et al. 2023). The combined results of meta-analyses and experiments revealed a negative response of available P to high N levels (N\u0026thinsp;\u0026ge;\u0026thinsp;10 g∙m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e), indicating a significant decrease in available P due to increased N availability. We also observed significant correlations between the stoichiometry of plant elements (C:N, N:P, and C:P) and microbial stoichiometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, structural equation modeling also demonstrated a positive and significant relationship between the plant leaf N:P ratio and the MN:MP ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). These findings support the notion that plant and microbial stoichiometry align with N addition (Zechmeister-Boltenstern et al. 2016; Yuan et al. 2019). The increase in soil available N resulting from N deposition can exacerbate the deficiency of P for both plants and microbes (Wu et al. 2022). To maintain N:P stoichiometric homeostasis for their growth, plants and microbes must enhance their acquisition of the most limiting nutrient (Cleveland and Liptzin 2007; Schimel et al. 2007; Finkel et al. 2019). Furthermore, the results of microbial eco-enzymatic stoichiometry indicate that microbial growth is limited by P at the N10 level (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), consistent with the findings of the meta-analysis conducted by Xu et al. (2022). Therefore, we can conclude that both plants and microbes require more P at higher levels of N addition.\u003c/p\u003e \u003cp\u003eThe significant negative correlation between plant leaf N:P ratio and SOC (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) indicates that N addition accelerated the decomposition of SOC. The structural equation model revealed that N addition significantly increased plant biomass and the N:P ratio, which supports the suggestion that N is a primary limiting nutrient for plant growth (Fay et al. 2015; Wu et al. 2022). To acquire more available P, plants promote the growth of fine roots (Li et al. 2015), which results in an increase in root biomass (Lambers, 2020). Specifically, under low-P conditions, roots produce more carboxylates, which can release P that is complexed with Fe and Al (Tomasi et al. 2008; Cesco et al. 2012). Simultaneously, carboxylates also release C that is compounded minerals and aggregates, thereby accelerating SOC decomposition (Ding et al. 2021). Therefore, the increased production of carboxylates can stimulate a priming effect, activating microbes to decompose SOC (Cheng et al. 2014; Xu et al. 2019).\u003c/p\u003e \u003cp\u003eAs N addition increases the microbial demand for P (Cleveland and Liptzin, 2007), and MC:MP ratios follow stoichiometric homeostasis, this accelerates the mineralization of SOC, releasing P (Camenzind et al. 2018) due to inadequate inorganic P availability (Zheng et al. 2015). In this study, the MC:MP ratio decreased significantly with N addition and was lower than that in the P-addition treatment (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), suggesting an increased acquisition of P by microbes (\u003cb\u003eSupplementary material 2, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). When soil available P decreases, organic P and P bound to rocks and minerals become the dominant P pools (Oliverio et al. 2020), which induces microbes to produce more extracellular phosphatase to obtain P (Olander and Vitousek 2000, \u003cb\u003eSupplementary material 2, Table S2\u003c/b\u003e). At the same time, microbial P limitation also intensifies microbial C limitation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). Specifically, microbial C decreases significantly with N addition, while microbial P remains relatively stable (\u003cb\u003eSupplementary material 2, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). This is because microbes acquire more C as an energy source to fulfill their increased demand for P to maintain stoichiometric homeostasis (Zechmeister-Boltenstern et al. 2016; Finn et al. 2016; Dai et al. 2019). These results suggest that microbial C limitation increases due to N addition, consequently accelerating SOC decomposition (Xu et al. 2022). Furthermore, we found no significant relationship betweenMC:MP and plant leaf N:P under N addition (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), indicating that soil microbial stoichiometry is not associated with litter stoichiometry (Fanin et al. 2013; Zechmeister-Boltenstern et al. 2015). In conclusion, these findings demonstrate that microbial stoichiometric homeostasis of MC:MP enhances SOC decomposition with increasing N addition, supporting the idea that consumer-driven nutrient recycling shapes the dynamics of SOC.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that the SOC content tends to increase at low levels of N deposition but decrease at high levels of N deposition (\u0026gt;\u0026thinsp;10 g∙m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e) in alpine grassland ecosystems. While the increases in SOC may be directly associated with increased plant C inputs, the reduced SOC storage at high concentrations can be explained by the enhancement of plant and microbial P limitation under higher N deposition scenarios, which place pressures on plants and microbes to maintain stoichiometric homeostasis. However, due to the limited availability of P in the soil, this can result in an increase in organic C input by plants, and then acceleration of SOC decomposition through priming effects. Furthermore, we discovered that microbes respond to P limitation by increasing the production of extracellular phosphatase to activate organic P, thus alleviating P limitation and maintaining stoichiometric MC:MP homeostasis. As a consequence, microbes require more C as an energy resource, resulting in increased SOC decomposition. Overall, our study highlights the importance of the MC:MP ratio in mediating SOC sequestration and implies that SOC in the QTP will decrease with the increasing deposition of N in the future. This implication highlights the challenge we face in increasing C sequestration in terrestrial ecosystems to mitigate climate change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement:\u0026nbsp;\u003c/strong\u003eThe author(s) declared no potential conflicts of interest with respect to the research, author- ship, and/or publication of this article.\u003c/p\u003e\u003ch2\u003eAuthor contributions:\u003c/h2\u003e \u003cp\u003eJianbo Wu and Lidong Mo conceived the ideas and designed the methodology; Jianbo Wu, Lidong Mo and Hui Zhao collected and analyzed the data; Jianbo Wu, Lidong Mo, Constantin M. Zohner, Fan Chen and Xiaodan Wang led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis study was financially supported by the Second Tibetan Plateau Scientific Expedition and Research (2019QZKK04040102), the Science and Technology Research Program of the Institute of Mountain Hazards and Environment, Chinese Academy of Sciences (IMHE-ZDRW-04), the Optimization and Integration of Vegetation Restoration Techniques for Hydropower Stations in Alpine Regions (HNKJ20-H23) and the Nation Natural Science Foundation of China (41401072)\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAverill C, Waring B (2018) Nitrogen limitation of decomposition and decay: how can it occur? 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J Geophys Res Biogeo 121:1605\u0026ndash;1616. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/2016JG003393\u003c/span\u003e\u003cspan address=\"10.1002/2016JG003393\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"soil organic carbon, MC:MP ratio, nitrogen deposition, microbial P limitation","lastPublishedDoi":"10.21203/rs.3.rs-4645564/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4645564/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eEffect of nitrogen deposition on soil organic carbon and the underlying mechanisms in grassland ecosystems remains a topic of debate. Moreover, previous research has primarily concentrated on interaction between carbon and nitrogen cycles in response to nitrogen deposition, with less attention paid to how nitrogen-induced phosphorus deficits may impact soil organic carbon sequestration.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ewe applied a meta-analysis to quantify how soil organic carbon and phosphorus respond to nitrogen enrichment in grassland ecosystem. Besides, we conducted an eight-year field experiment involving nitrogen and phosphorus additions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ethe meta-analysis revealed that soil organic carbon increased below 5 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e but decreased above 10 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e under nitrogen addition. The field experiment also indicated that soil available phosphorus did not significantly decrease with nitrogen addition of 10 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, suggesting an increase in soil available phosphorus due to nitrogen addition. The microbial biomass carbon to phosphorus (MC:MP) ratio significantly decreased under any level of nitrogen addition, indicating that nitrogen enhanced phosphorus limitation of microbes. Moreover, the significant negative correlation between MC:MP ratio and soil organic carbon indicated that microbial carbon limitation increased with microbial phosphorus limitation under nitrogen enrichment. Furthermore, both microbial carbon limitation and phosphorus limitation were significantly correlated with reduced soil organic carbon, suggesting that increases in the MC:MP ratio will reduce soil organic carbon sequestration.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003esoil organic carbon will decrease above 10 g\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e under nitrogen addition, and the nitrogen deposition-induced MC:MP imbalance may lead to decreased soil organic carbon in alpine grassland ecosystems.\u003c/p\u003e","manuscriptTitle":"Reduced soil organic carbon sequestration driven by nitrogen deposition–induced increases in microbial carbon to phosphorus ratio in alpine grassland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-01 05:55:31","doi":"10.21203/rs.3.rs-4645564/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e887df7e-0208-41bc-863f-4af520285a45","owner":[],"postedDate":"August 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-19T14:52:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-01 05:55:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4645564","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4645564","identity":"rs-4645564","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}