Increasing grazing intensity enhances vegetation elemental coupling but reduces soil elemental coupling in alpine meadows

Increasing grazing intensity enhances vegetation elemental coupling but reduces soil elemental coupling in alpine meadows | 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 Increasing grazing intensity enhances vegetation elemental coupling but reduces soil elemental coupling in alpine meadows yihe zhao, Jingyi Dong, Yuhan Liu, Yinghui Liu, Jiaqi Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6607637/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 Background Grazing alters the biogeochemical cycles in grassland ecosystems, with the elemental coupling serving as an effective measure of this impact. The concept of elemental coupling allows for the inclusion of various mineral elements, offering new insights into the effects of grazing on the material cycling. Methods This study focused on a typical alpine meadow in the eastern Qinghai-Tibet Plateau, where we measured the total elemental content of dominant vegetation, soil exchangeable ions, and soil physicochemical properties. We analysed the changes in soil and plant elemental coupling and used a Structural Equation Modeling (SEM) approach to investigate the mechanisms driving these changes. Results With increasing grazing intensity, the concentrations of heavy metals such as copper (Cu²⁺), zinc (Zn²⁺), manganese (Mn²⁺), and iron (Fe³⁺) significantly increased in the soil, while the contents of essential nutrients such as Mg, Ca, and Na decreased in the vegetation. Increasing grazing intensity enhanced vegetation element coupling but reduced soil element coupling, with increases of 52.8% and decreases of 16.8% under heavy grazing, respectively. SEM analysis revealed significant direct effects of grazing intensity on the changes in coupling. Conclusion This study investigated how grazing affects elemental coupling in an alpine meadow on the eastern Qinghai-Tibet Plateau. While grazing intensity enhances vegetation element coupling, it reduces soil element coupling.This study provides new perspectives and scientific basis for rational grazing management and sustainable grassland use. Qinghai-Tibet Plateau elemental coupling alpine meadow biogeochemical cycles Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction The Qinghai–Tibet Plateau encompasses the largest grassland area in Eurasia, where the fragile grassland ecosystems are extremely sensitive to global changes and anthropogenic disturbances(Dong et al., 2022 ; Liu et al., 2024 ). Globally, grazing is the predominant form of grassland utilization. It influences the structure, function, and processes of grassland ecosystems primarily through three pathways: herbivory, trampling, and excretion (Kohler et al., 2005 ). Overgrazing often leads to degradation in both vegetation and soil quality(LI Yu-qin & ZHAO Jing-bo, 2005), indicating a disruption in biogeochemical cycling within these ecosystems(Wang Changting et al., 2013). To understand how grassland material cycles respond to grazing gradients, previous studies have primarily focused on the effects of grazing on the contents and stoichiometric ratios of essential nutrients—namely, carbon, nitrogen, phosphorus, and potassium—in soils and plants(McSherry & Ritchie, 2013 ; He et al., 2015 ; Yu et al., 2021 ).These studies pay less attention to the mineral elements. However, mineral elements in soils also play critical roles in sustaining plant physiological functions, conserving soil nutrients, and buffering soil acidification (Bowman et al., 2008 ). For instance, the contents of Ca²⁺, Mg²⁺, K⁺, and Na⁺ are commonly used to evaluate soil quality, nutrient retention capacity, and acid-buffering potential. In contrast, elements such as Al³⁺, Mn²⁺, and Fe³⁺ serve as important indicators of soil acidification due to their phytotoxicity and interference with nutrient uptake. Xu et al. observed that the contents of Fe, Mn, Cu, and Zn decreased with increasing grazing intensity (XU Yue-fei et al., 2012 ), while Zhang et al. reported opposite trends(Zhang Hong-qin et al., 2015 ). These conflicting results highlight the importance of mineral elements as indicators of soil condition and their crucial influence on plant growth, though the patterns of their response to grazing gradients remain unclear. Plants exhibit selectivity in absorbing mineral elements from soils, and the efficiency of uptake varies among elements(Desjardins et al., 2018 ). Whether grazing directly or indirectly alters plant mineral composition via soil mediation, and whether plants adopt specific strategies in mineral acquisition under grazing pressure, are questions that require empirical data on the elemental content of plants and soils across grazing gradients. Changes in elemental contents and their ratios are classic concerns in ecological stoichiometry(Elser et al., 2000 ). Typically, element coupling or decoupling refers to variations in nutrient ratios(Liu et al., 2024 ; Rumpel & Chabbi, 2019 ). Rumpel et al. argued that stronger coupling occurs when multiple soil elements undergo synchronized biological and abiotic processes, whereas asynchrony leads to decoupling(Rumpel et al., 2015 ).Recent frameworks proposed by Ochoa-Hueso et al. redefine elemental coupling as the covariation of chemical elements within ecosystems(Ochoa-Hueso et al., 2021 ). This perspective enables the inclusion of a broader suite of elements in coupling analysis and offers elemental coupling degree as a sensitive indicator of ecosystem status. Under nitrogen addition treatments, Caetano-Sánchez et al. observed no significant changes in the absolute concentrations of available elements, yet the degree of elemental coupling varied—emphasizing the utility of coupling degree in detecting subtle environmental changes(Ochoa-Hueso et al., 2024 ). This conceptual advancement provides both methodological and analytical tools for evaluating the responses of plant–soil systems to grazing. Investigating the variation in nutrients and their interactions between plants and soils under grazing conditions enhances our understanding of plant–soil nutrient dynamics and informs sustainable grassland management. This study focuses on less-explored mineral elements and adopts the coupling degree framework to characterize the response patterns of key plant and soil elements to grazing intensity in an alpine meadow on the Qinghai–Tibet Plateau. We quantified the elemental concentrations in both vegetation and soils across a grazing gradient, and calculated soil elemental coupling as the mean absolute Spearman’s rank correlation coefficient among all element pairs. Additionally, we applied structural equation modelling (SEM) to explore the underlying mechanisms through which grazing affects elemental concentrations and their coupling. This study aims to address the following key questions: (1) How do elemental concentrations in vegetation and exchangeable soil elements respond to varying grazing intensities? (2) How does the degree of elemental coupling within and between vegetation and soil respond to grazing intensity? (3) What mechanisms drive the response of elemental coupling degree to different grazing intensities? 2. Materials and methods 2.1. Study area and experimental design This study was conducted in a typical alpine meadow located in the eastern part of the Qinghai‒Tibet Plateau (102°33′E, 32°48′N, 3500 m) within the Qinghai‒Tibet Plateau Research Base of Southwest Minzu University, which is located in Hongyuan County, Aba Tibetan Prefecture and Qiang Autonomous Prefecture, Sichuan Province, as shown in Fig. 1 . The site has a mean annual temperature of 1.5°C, with monthly mean temperatures ranging from − 9.7°C in January to 11.1°C in July. The mean annual precipitation is 747 mm, with 80% of the rainfall occurring in the summer season. The climate is cold and humid, and the soil is frequently waterlogged. The surface soil is peat soil, with a bulk density of 0.89 g·cm⁻³ and a soil pH of 5.89. The dominant plant species at the experimental site include Kobresia pygmaea , Kobresia humilis , Saussurea nigrescens , Elymus nutans , and Deschampsia cespitosa . On the basis of the average grazing intensity in the region, four treatments were established: ungrazed control (UG), light grazing (LG, 1 yak/ha), moderate grazing (MG, 2 yaks/ha), and heavy grazing (HG, 3 yaks/ha). Each treatment was replicated in three plots. The average body weight of each yak was approximately 200 kg. Each plot covered an area of approximately 1 ha, with the total area of the ungrazed control plots being 1 ha and the total experimental area spanning 10 ha. The grazing experiment was conducted each year from late May to late September. 2.2. Sampling and elemental analysis Sample collection was carried out in August 2021. Within each plot, six small quadrats (0.5 m × 0.5 m) were randomly selected, while avoiding the edges of the plots. Owing to the smaller area of the UG treatment plots, only three quadrats were sampled in these areas. The vegetation distribution within each quadrat was relatively uniform, and an appropriate spatial distance was maintained between quadrats. To estimate the aboveground biomass (AGB) and belowground biomass (BGB) of the vegetation, we harvested all green vegetation within each small plot. The samples were cleaned to remove adhering soil and gravel, then subjected to heat treatment at 105℃ for 30 minutes to terminate plant respiration and other physiological activities. Subsequently, the oven temperature was adjusted to 65℃, and the samples were dried until reaching constant weight before being weighed to determine AGB. For BGB estimation, we collected root samples using a root auger with a diameter of 7 cm and a sampling depth of 10 cm within each small plot. The roots were washed in a net bag to remove debris, dried at 65℃ until constant weight, and weighed to obtain BGB. It should be noted that during the calculation of belowground biomass, no distinction was made between live and dead roots. The elemental content of plant leaves was determined using the microwave digestion method. Leaf samples were collected from the dominant plant species within the quadrats, including Kobresia pygmaea , Elymus nutans , and Kobresia humilis . The contents of elements, including Ca, Mg, Na, Cu, Zn, Al, Mn, and Fe, were analysed using an inductively coupled plasma optical emission spectrometer (Optima 8000, PerkinElmer, USA). Soil elements primarily originate from soil solution, exchange sites, "chelated" forms bound to organic matter, and mineral crystals. Except for elements in mineral crystals, which are difficult for plants and microorganisms to utilize, the soil elements consist of exchangeable ions that can be absorbed by plants. Exchangeable Cu²⁺, Zn²⁺, Mn²⁺, and Fe³⁺ in the soil were extracted using 10 mL of extractant (5 mM DTPA + 10 mM CaCl₂ + 0.1 M TEA). Exchangeable Al³⁺ was extracted using 15 mL of 0.1 M BaCl₂, whereas Ca²⁺, Mg²⁺, and Na⁺ were extracted using 10 mL of 1 M NH₄OAc. The concentrations of all elements were determined using an inductively coupled plasma optical emission spectrometer (Optima 8000, PerkinElmer, USA). A series of soil physicochemical properties were also measured. Soil pH was determined using a pH meter (S210-K, Mettler Toledo, Switzerland). The soil water content (SWC) and redox potential were measured in situ using a portable soil moisture meter (SM150 Kit, Delta-T, UK). For total carbon (TC) and total nitrogen (TN) determination, air-dried and sieved soil samples were analysed using an elemental analyser (CN802, VELP, Germany) with the combustion method. For total organic carbon (TOC) and total organic nitrogen (TON), inorganic carbon and nitrogen were first removed from the soil samples, which were then dried and sieved before analysis. The soil samples were shaken and filtered with 0.05 mol/L K₂SO₄ solution to obtain a clear filtrate. Dissolved organic carbon was measured using a TOC analyser (TOC-LCPN, Shimadzu, Japan), whereas ammonium nitrogen and nitrate nitrogen were determined using a continuous flow analyser (AutoAnalyzer3, Bran + Luebbe, Germany).We also determined the amount of available inorganic nitrogen in the soil, that is, the sum of NH 4 + -N and NO 3 − -N content. We use 0.5 M K 2 SO 4 (40 mL) to leach per 10g of soil sample, and the contents of NH 4 + -N and NO 3 − -N in the soil were determined by using a flow injection analyzer (Auto analyzer 3, Bran + Luebbe, Hamburg, Germany). 2.3. Statistical analysis For vegetation and soil elements, the coupling value was calculated as the average of the absolute value of the Spearman rank correlation coefficient between different elements under different grazing intensities. Elemental coupling = \(\:\frac{\sum\:_{\text{i}=1}^{\text{n}}\left|\rho\:i\right|}{n}\) where n is the number of paired Spearman’s correlation coefficients and 𝜌𝑖 is the Spearman rank correlation coefficient between two elements. We used a zero-model approach to measure the extent to which the degree of coupling is detached from purely random associations between elements. Accordingly, 999 zero-model randomizations were run at each grazing intensity, and the degree of coupling was calculated for each randomization. Based on comparisons, the measured degree of coupling was divided into three types: (i) coupling, where the observed value fell outside the envelope of the 97.5% quantile; (ii) decoupling, where the observed value fell within the quantile envelope of 2.5–97.5%; and (iii) coupling, where the observed value was less than 2.5% of the random observation quantile. With the use of the FactoMineR package in R, the elemental contents of vegetation and soil were analysed via principal component analysis (PCA), with the elements studied in terms of dimension, and the comprehensive scores of the different elements on the axes of the two principal components were also added to the SEM analysis. Data analysis and mapping were performed in R Studio, SPSS, and GraphPad Prism 10.1.2, and the SEM was run using IBM SPSS Amos 26. 3. Results 3.1. Effects of grazing intensity on the contents of elements in soil and vegetation In the alpine meadow soils of the Qinghai‒Tibet Plateau subjected to disturbances from long-term grazing, the responses of various elements in soil to different intensities of grazing significantly differed. As shown in Fig. 2 , the concentrations of nutrient elements essential for plant growth, such as Mg²⁺ and Ca²⁺, were relatively high in the control and light grazing treatments. However, the concentrations of essential nutrient elements significantly decreased with increasing grazing intensity, reaching their lowest levels under heavy grazing. The soil Na⁺ content did not significantly respond to changes in the external environment. Compared with the control, grazing significantly reduced the content of Cu²⁺, which was associated with enzymatic reactions in the nitrogen cycle, with reductions of 38.04%, 11.64%, and 19.22% under the light, moderate, and heavy grazing treatments, respectively. Moreover, although light and moderate grazing reduced the soil Zn²⁺ content, heavy grazing significantly increased it, with an 89.13% increase compared with that of the control. As important indicator ions for severe soil acidification, the concentrations of soil Fe³⁺ and Mn²⁺ were highest under heavy grazing, increasing by 99.80% and 74.41%, respectively, compared with those in the control. In contrast, the soil Al³⁺ content significantly decreased with increasing grazing intensity, reaching its lowest level under heavy grazing, with a 54.75% reduction compared with that of the control. The effects of grazing intensity on the elemental composition of leaves from dominant plant species in the alpine meadows of the Qinghai‒Tibet Plateau were significantly different, as shown in Fig. 3 . The concentrations of nutrient elements essential for plant growth, such as Mg, Ca, and Na, significantly decreased with increasing grazing intensity, with reductions of 23.82%, 29.45%, and 26.80%, respectively, compared with those in the control, reaching their lowest levels under heavy grazing. Grazing at different intensities also altered the contents of elements associated with enzymatic reactions in the nitrogen cycle, such as Cu and Zn, in the leaves of the dominant plant species. Compared with those in the control treatment, the Cu concentrations in the light and moderate grazing treatments increased by 49.68% and 40.06%, respectively. The Zn concentration was highest under moderate grazing, with a 26.47% increase compared with that of the control. The leaf Fe concentration under moderate grazing was significantly greater than that under the other three treatments, with a 44.97% increase compared with the control, but it was lowest under light grazing, decreasing by 16.61% compared with the control. Similarly, the leaf Mn and Al concentrations were highest under moderate grazing, increasing by 0.70% and 49.65%, respectively, compared with those in the control, and were lowest under light grazing. 3.2. Effects of grazing intensity on the degree of coupling between soil and vegetation elements As shown in Fig. 4 , the overall degree of soil elemental coupling under the UG, LG, and MG treatments corresponded to a coupled state (above the null model region), indicating that at grazing intensities less than that corresponding to heavy grazing, the overall degree of soil coupling was not significantly altered, and spatial associations remained relatively stable. However, under the heavy grazing (HG) treatment, the overall degree of soil coupling decreased and became uncoupled, suggesting that heavy grazing disrupted the stability of spatial covariation among soil ions. The responses of different elements to grazing intensity varied significantly and could be categorized into three types of trends. The first trend involved Mn, Zn, Fe, and Ca, in which the degree of coupling initially increased and then decreased after reaching a threshold. Specifically, the degrees of coupling of Mn and Ca under LG were lower than those under UG, and these two elements were in an uncoupled state, whereas under MG, the degrees of coupling of Mn, Ca, and Fe reached their maximum values. Zn was coupled with other elements only under LG. In the first trend, the degrees of coupling of all the elements reached their lowest values under HG, and the elements were in an uncoupled state. The second trend, involving Na and Cu, showed a significant increase in coupling with increased grazing, with the highest degree of coupling observed under HG. The third trend, involving Mg and Al, exhibited a general decline in the degree of coupling with increasing grazing intensity. The degree of coupling of Al with other elements reached its lowest value under MG, whereas the degree of coupling of Mg showed a fluctuating trend, with its lowest value observed under HG. Additionally, N showed no clear trend under the grazing treatments. Overall, the degrees of coupling of multiple soil elements responded inconsistently to grazing pressure. In addition to grazing, other factors, such as soil properties and vegetation type, likely played a coregulatory role in influencing the degree of coupling. Using undirected network diagrams (Fig. 5 ) to visualize the degree of coupling between elements, it was observed that under the four grazing intensities, changes in the degree of elemental coupling did not exhibit a significant trend, with elemental associations decreasing under HG. As shown in Fig. 6 , the overall degree of coupling among plant elements generally tended to increase with increasing grazing intensity. It remained in an uncoupled state under the UG, LG, and MG treatments but showed coupling under HG. The trends in the degrees of coupling of different elements were generally similar, all displaying an increasing pattern with the intensity of grazing. The degrees of coupling of five elements—Mg, Al, Mn, Fe, and Zn—initially decreased but then increased along the grazing gradient. Except for Mg, the highest degrees coupling of the elements occurred under HG. The degree of Mg coupling reached a threshold under moderate grazing, indicating a coupled state, but decreased under HG. Both Na and Cu were in a decoupled state under grazing intensities less than that in HG, but their degree of coupling significantly increased under HG, indicating significant coupling. The degree of coupling of Ca progressively increased with grazing intensity, exhibiting a coupled state under MG and HG. Figure 7 also presents similar results, showing that under HG, the associations among plant elements clearly increased, all of which were positively correlated. 3.3. Mechanism by which grazing intensity affects the degree of coupling between soil and vegetation To further explore how grazing intensity influences the degree of coupling between soil and vegetation, structural equation modelling (SEM) was used to analyse the mechanisms driving the effects of grazing intensity. Principal component analysis (PCA) was employed to reduce the dimensionality of vegetation and soil elements, which were then incorporated into the SEM, as shown in Fig. 8 . In the PCA of the soil and vegetation elements, the first two principal components explained 67.2% and 57.7% of the variance, respectively. Under heavy grazing (HG) conditions, soil elements were characterized primarily by relatively high contents of the heavy metal elements Zn, Mn, and Fe, which significantly differed from the characteristics under UG conditions, where the Na, Al, and N contents were relatively high. The vegetation elements under UG and MG presented similar characteristics, with relatively high contents of elements such as Na, Ca, Mn, and Mg. In contrast, under HG and LG, vegetation elements presented the opposite pattern, with lower contents of Na, Ca, Mn, Mg, and other elements compared with those in the other treatments. In this study, we employed structural equation modelling (SEM) to quantify the mechanisms by which grazing intensity influenced soil and vegetation elemental contents and their degree of coupling. We calculated the scores of the first two principal components from the PCA for each element as the response variables. Figure 9 − 1 shows that grazing intensity had the strongest direct negative effect on the degree of soil elemental coupling. Additionally, the introduced element scores also exerted a direct negative effect on soil elemental coupling. Grazing intensity had the strongest positive effect on the element scores. Furthermore, NH₄⁺, soil water content (SWC), total carbon (TC), and total nitrogen (TN) played indirect roles in this process. Figure 9 − 2 shows that grazing intensity had a significant negative effect on vegetation elemental coupling. Additionally, the negative effect of grazing intensity on aboveground biomass (AGB) directly contributed to the negative effect on vegetation elemental coupling. Notably, the path coefficient of AGB on vegetation elemental coupling reached a value of -1.07, indicating that the presence of unexplained latent variables affected the degree of vegetation elemental coupling. Additionally, variables such as NH₄⁺, SWC, total organic nitrogen (TON), and others played indirect, nonsignificant roles in vegetation elemental coupling. Figure 9 − 3 shows that grazing intensity had significant direct positive effects on both the vegetation and soil element scores. Furthermore, we observed a certain association between element scores and the degrees of coupling for vegetation and soil. Specifically, the degree of soil coupling had a positive effect on the vegetation element score, whereas the soil element score had a negative effect on the degree of soil coupling and a positive effect on the degree of vegetation elemental coupling. Notably, the degree of soil coupling had a significant negative effect on the degree of vegetation elemental coupling. 4. Discussion 4.1. Exchangeable soil ions are affected by grazing intensity In alpine meadow soils subjected to long-term grazing disturbances, the responses of various elements to different intensities of grazing significantly differed. The content of nutrient elements essential for plant growth, Mg²⁺ and Ca²⁺, significantly decreased with increasing intensity of grazing. Studies have shown that an increase in soil organic matter content can increase the soil cation exchange capacity to retain Mg²⁺ and Ca²⁺. However, in the study area, the total soil organic carbon and dissolved organic carbon levels did not significantly change, and with relatively high precipitation, the soil water content increased with grazing intensity, promoting leaching processes. This accelerated the loss of Mg²⁺ and Ca²⁺ and the leaching of these cations to deeper soil layers (Zhang et al., 2002). Additionally, with increasing grazing intensity, the soil Mn²⁺ and Fe³⁺ contents increased, and these cations displaced Ca²⁺ and Mg²⁺ from binding sites into the soil solution, leading to Ca²⁺ and Mg²⁺ leaching (Gundersen et al., 2006; Skyllberg, 1999), which interfered with plant uptake of Mg²⁺ and Ca²⁺ (Blake et al., 1999; Horswill et al., 2008). Mn has high chemical activity in soil, and in this study, the soil Mn²⁺ content increased with increasing soil water content along the grazing gradient. Research has shown that the soil Mn²⁺ content in grazing areas is relatively high during seasons and in regions with abundant rainfall(JIAO Ting et al., 2014). Furthermore, the soil Cu²⁺, Zn²⁺, Fe³⁺, and Mn²⁺ contents all increased with increasing grazing intensity, reaching relatively high levels under heavy grazing. This may have occurred because the yaks trampled the ground, facilitating litter decomposition, and organic matter and nutrients were transferred to the soil(Zhang Hong-qin et al., 2015). Organic matter can form organomineral complexes with soil Cu²⁺, Zn²⁺, Fe³⁺, and Mn²⁺ (Rahman et al., 1996), having some capacity to retain these trace elements and significantly reducing their leaching losses(XIN Guo-sheng et al., 2012). In contrast, the soil Al³⁺ content significantly decreased with increasing grazing intensity. This may have occurred because, within a certain pH range, Fe³⁺, Mn²⁺, and Al³⁺ play similar roles in buffering soil acidity, and an increase in Fe³⁺ and Mn²⁺ suppressed the increase in Al³⁺ solubility in the soil. 4.2. Grazing intensity affects the leaf elemental content of dominant species The effects of grazing on the elemental composition of leaves from dominant plant species in the alpine meadows were significantly different. Among the nutrients, the contents of those essential for plant growth, i.e., Mg, Ca, and Na, significantly decreased with increasing intensity of grazing. Correlation analysis revealed that the reductions in the Mg, Ca, and Na contents in the leaves of dominant species were positively correlated with the decrease in aboveground biomass, suggesting that the reductions in these three elements may be related to the loss of aboveground biomass due to trampling by yaks. Additionally, the availability of Mg, Ca, and Na in grassland ecosystems is influenced by nitrogen-related factors, such as atmospheric nitrogen deposition, nitrate leaching, and plant nitrogen uptake, which affect the content of alkaline cations in soil and their storage in plants (Elvir et al., 2006). In this study, the leaf Ca and Na contents were positively correlated with the soil ammonium nitrogen content. This may have occurred because increased ammonium nitrogen availability stimulates plant growth, enhancing the uptake of Mg, Ca, and Na by plants(Vitousek & Howarth, 1991). Furthermore, the leaf Mg and Ca contents were negatively correlated with soil Al³⁺. Studies have shown that an increase in leaf Al content indicates increased toxicity effects from aluminium on plants (Bowman et al., 2008), which may reduce the contents of nutrient elements such as Mg, Ca, and Na. Cu, Zn, Mn, and Fe are important components of enzymes involved in the nitrogen cycle. This study revealed that the leaf Cu content in dominant species under the grazing treatments was generally greater than that in the control group but decreased with increasing intensity of grazing, which was opposite to the increasing trend observed in soil Cu²⁺. Generally, during the summer, when both rainfall levels and temperature are high, forage grasses grow rapidly, and plants absorb nutrients from the soil to meet their growth needs(JIAO Ting et al., 2014), with forage grasses primarily obtaining Cu from the soil. However, in this study, the decrease in leaf Cu content with increasing grazing intensity suggested that, during the peak growth season in summer, increasing grazing may have interfered with plant uptake of Cu from the soil. Additionally, leaf Cu was negatively regulated by soil Zn²⁺, Mn²⁺, and Fe³⁺, indicating that increases in soil Zn²⁺, Mn²⁺, and Fe³⁺ may have suppressed plant uptake of Cu from the soil. This hypothesis was also supported by Li et al., but further investigation is required to elucidate the specific mechanisms involved. As an essential trace element for plant growth, Mn plays important roles in plant physiological activities, such as regulating metabolism, promoting growth, enhancing disease resistance, and increasing forage yield(JIAO Ting et al., 2014). The response of leaf Mn to the grazing gradient was similar to that of leaf Cu, possibly due to the combined effects of grazing and other mineral elements. The leaf Fe and Al contents were significantly positively correlated with pH, possibly because the solubility of Fe and Al in the soil increased with a decrease in soil pH, increasing their toxic effects on plants. Under such conditions, plants reduce their Fe and Al contents to mitigate the toxic effects of these elements. 4.3. How the grazing intensity affects the coupling of leaf elements and soil elements，and the mechanism behind it Our study demonstrates that grazing intensity in alpine meadows exerts contrasting effects on soil and vegetation elemental dynamics. Specifically, increased grazing intensity results in a significant rise in soil heavy metal ions, such as Fe³⁺ and Zn²⁺ (Fig. 2), which, according to Structural Equation Modeling (SEM), indirectly diminishes soil elemental coupling. This phenomenon is likely due to livestock introducing heavy metals into the soil through their excreta, especially when consuming contaminated feed or water. The accumulation of these heavy metals may lead to competition with essential nutrients like Ca²⁺ and Mg²⁺ for adsorption sites(LIN Qing & XU Shao-hui, 2008) and exert toxic effects on microorganisms involved in elemental cycling(Abdu et al., 2017), thereby disrupting normal elemental interactions and reducing soil elemental coupling. At a localized scale, the accumulation of excreta contributes to elemental imbalances, which may further reduce soil elemental coupling. Furthermore, intensive grazing coupled with significant livestock trampling leads to increased soil bulk density and decreased porosity, permeability, and aeration(HOU Fu-Jiang et al., 2004). These changes restrict microbial activity and alter microbial community composition and function. Livestock trampling both increased the soil bulk density and decreased the aboveground biomass of vegetation, and these two effects decreased the number of fungi and bacteria, respectively(Yang et al., 2022).Under the same experimental location and setup as ours, Dong et al. found that soil microbial biomass increased under light grazing compared to the control group (CK) but decreased with higher grazing intensities(Dong et al., 2022). Given that microorganisms are pivotal in driving and maintaining soil elemental cycling(Spohn, 2016) , their decline can weaken soil elemental associations presumably, thereby diminishing soil elemental coupling. Although we have not further investigated the impact of microbial community changes on the mineral elemental coupling, Dong et al. found by this experiment that the concentration of ammonia-oxidizing archaea (AOA) increased significantly under heavy grazing, driving nitrification, a key process in the nitrogen cycle, to increase significantly as well(Dong et al., 2022). Similarly, Zhou et al. reached the same conclusion regarding the impact of grazing on the nitrogen cycle through a meta-analysis(Zhou et al., 2017). In biogeochemical cycling theory, the movement of various elements is coupled(Schlesinger et al., 2011). The relationship between mineral elements and the nitrogen cycle, through inter-elemental connections, may require further exploration. Existing literature indicates that under heavy grazing stress, plant populations may undergo collective miniaturization through positive interactions to defend against excessive herbivory(Wang et al., 2014; Wang X T et al., 2015). This is consistent with our findings that both aboveground and belowground vegetation biomass decreased with increasing grazing intensity, and that the reduction of aboveground biomass was directly related to vegetation coupling in the SEM model. This strategy involves individual plants reducing their nutrient demands, leading to decreased community productivity. Consequently, the co-reduction of nutrient content within plant tissues may be a significant factor contributing to the observed increase in plant elemental coupling. Additionally, grazing-tolerant species, such as Kobresia pygmaea, may adopt rapid growth strategies under heavy grazing(Cruz et al., 2010), efficiently absorbing light and nutrients to enhance regenerative capacity, resulting in accelerated internal nutrient cycling and increased elemental coupling within the plants. By examining the relationships between elements in soil and plants, we observe that changes in elemental contents do not follow a simple supplier-absorber model. Under natural conditions, a plant's ability to absorb elements is constrained by its biological demands, which vary significantly across different growth stages and exhibit strong selectivity among elements. For elements with low biological utilization efficiency, the correlation between their contents in soil and vegetation is weak. Moreover, variations in soil properties, such as pH and moisture, influence the form and distribution of soil ions, complicating plant uptake mechanisms. Thus, the available ion contents for plants may differ from the measured ion contents in the soil. 5. Conclusion In this study, we examined the response of leaf element content of dominant species and soil exchangeable ion content in alpine meadows to grazing pressure and analysed the changes in the degree of soil‒vegetation elemental coupling and underlying mechanisms. The results revealed that with increasing grazing intensity, the elemental composition of both the soil and the vegetation was significantly altered. With increasing grazing intensity, the contents of essential nutrient elements such as Mg²⁺ and Ca²⁺ in the soil significantly decreased, whereas the contents of trace elements such as Cu²⁺, Zn²⁺, Fe³⁺, and Mn²⁺ increased. Furthermore, grazing reduced the degree of coupling among soil elements to some extent but increased the degree of coupling among vegetation elements. In this study, the plant elemental contents were measured in the leaves of dominant species within sampling plots, but the elemental contents of different plant species were not measured separately. However, the capacity for elemental uptake and accumulation varies significantly among different plant species, which may influence the interpretation of the overall degrees of vegetation elemental coupling. In future studies, researchers can further incorporate the elemental uptake characteristics of different functional groups of plants to analyse the impacts of grazing on nutrient cycling in grassland ecosystems more comprehensively. Soil microbes play critical roles in nutrient mineralization, organic matter decomposition, and rhizosphere environment regulation, and their responses to grazing disturbances may be key factors influencing the elemental coupling. Therefore, future research should focus on high-throughput sequencing of microbial communities to elucidate how different microbial taxa influence specific elemental correlation and its mechanisms. Here, a new theoretical framework of coupling degree was introduced to understand the complex dynamics of nutrient cycling in alpine meadows under grazing disturbance. This approach will enhance our understanding of how grazing impacts elemental balance within grassland ecosystems.The findings of this study have important implications for grassland management. On the one hand, long-term high-intensity grazing may lead to significant losses of soil nutrient elements and deterioration of the soil chemical environment, thereby reducing soil fertility and plant growth potential. Therefore, the grazing intensity should be reasonably controlled to avoid excessive loss of key soil nutrients. Measures such as rotational grazing could be appropriately implemented to improve grassland community structure and promote vegetation recovery. On the other hand, the increase in vegetation coupling indicates that grazing pressures compel plants to adopt stress-resilient strategies, which leads to a reduction in the overall productivity of plant communities. It is crucial to prioritize the protection of high-quality forage species to avoid their overexploitation under intensive grazing regimes, thereby ensuring the long-term stability and productivity of grassland ecosystems. Abbreviations N Nitrogen MG moderate grazing AL Aluminum HG heavy grazing Mg Magnesium PCA Principal component analysis Na Sodium SEM structural equation modelling Ca Calcium AGB aboveground biomass Fe Iron BGB belowground biomass Mn Manganese TC total carbon Cu Copper TN total nitrogen Zn Zinc TOC total organic carbon (TOC) CK the control group TON total organic nitrogen (TON) UG ungrazed control AOA ammonia-oxidizing archaea LG light grazing Declarations Acknowledgments ：We would like to thank the reviewers and editor for proofreading and providing helpful suggestions on the manuscript. Thanks to the Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, especially for the manager of the Yak Grazing Intensity platform, Tserang Donko Mipam. Funding This research was supported by the National Key Research and Development Program of China [grant No. 2022YFF1302803] and National Natural Science Foundation of China [grant No. 31770519]. We thank the Duolun Restoration Ecology Station for providing access to the study site. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions Yihe Zhao and Jingyi Dong developed and proposed the research question and drafted the manuscript, Yuhan Liu analyzed the data and contributed to the manuscript writing, Yinghui Liu revised the manuscript and provided guidance, and Jiaqi Zhang conducted field investigations and collected the data. All the authors contributed substantially to the writing and revision of the manuscript. Yihe Zhao and Jingyi Dong contributed equally to this work. Data Availability The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. References Abdu, N., Abdullahi, A. A., & Abdulkadir, A. (2017). Heavy metals and soil microbes. 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Introduction to coupled biogeochemical cycles. Frontiers in Ecology and the Environment , 9 (1), 5–8. https://doi.org/10.1890/090235 Skyllberg, U. (1999). pH and solubility of aluminium in acidic forest soils: A consequence of reactions between organic acidity and aluminium alkalinity. European Journal of Soil Science , 50 (1), 95–106. https://doi.org/10.1046/j.1365-2389.1999.00205.x Spohn, M. (2016). Element cycling as driven by stoichiometric homeostasis of soil microorganisms. Basic and Applied Ecology , 17 (6), 471–478. https://doi.org/10.1016/j.baae.2016.05.003 Vitousek, P. M., & Howarth, R. W. (1991). Nitrogen limitation on land and in the sea: How can it occur? Biogeochemistry , 13 (2), 87–115. https://doi.org/10.1007/BF00002772 Wang Changting, Wang Genxu, Liu Wei, & Wang Qilan. (2013). Effects of fertilization gradients on plant community structure and soil characteristics in alpine meadow. Acta Ecologica Sinica , 33 (10), 3103–3113. https://doi.org/10.5846/stxb201202200232 Wang, X., Liang, C., & Wang, W. (2014). Balance between facilitation and competition determines spatial patterns in a plant population. Chinese Science Bulletin , 59 (13), 1405–1415. https://doi.org/10.1007/s11434-014-0142-8 Wang X T, Wang W, Liang C Z, & Liu Z L. (2015). Using positive interaction ecology to explain grassland degradation induced by overgrazing (in Chinese). Chin Sci Bull , 60 (Z2), 2794–2799. XIN Guo-sheng, LONG Rui-jun, SHANG Zhan-huan, DING Lu-ming, & GUO Xu-sheng. (2012). Status of some selected major and trace elements in pasture soil from northeast of the Qinghai-Tibetan Plateau. Acta Prataculturae Sinica , 21 (2), 8–17. XU Yue-fei, Yixi-cuomu, FU Juan-juan, CHEN Hao, MIAO Yan-jun, CHEN Jun, HU Tian-ming, & SHAN Jian-guo. (2012). Response of Plant Diversity and Soil Nutrient to Grazing Intensity in Kobresia pygmaea Meadow of Qinghai-Tibet Plateau. ACTA AGRESTIA SINICA , 20 (6), 1026–1032. Yang, X., Zang, J., Feng, J., & Shen, Y. (2022). High grazing intensity suppress soil microorganisms in grasslands in China: A meta-analysis. Applied Soil Ecology , 177 , 104502. https://doi.org/10.1016/j.apsoil.2022.104502 Yu, R., Zhang, W., Fornara, D. A., & Li, L. (2021). Contrasting responses of nitrogen: Phosphorus stoichiometry in plants and soils under grazing: a global meta‐analysis. Journal of Applied Ecology , 58 (5), 964–975. https://doi.org/10.1111/1365-2664.13808 Zhang Hong-qin, ZANG Xiaolin, MA Yuandan, LIU Mengmeng, JIA Li, BAOYIN Taogetao, ZHANG Rumin, & GAO Yan. (2015). Effects of Grazing on Soil Nutrient Elements in the Rhizosphere of Artemisiafrigida Willd. Journal of Soil and Water Conservation , 29 (6), 118–123. https://doi.org/10.13870/j.cnki.stbcxb.2015.06.022 Zhang, X. P., Deng, W., & Yang, X. M. (2002). The background concentrations of 13 soil trace elements and their relationships to parent materials and vegetation in xizang (tibet), China. Journal of Asian Earth Sciences , 21 (2), 167–174. https://doi.org/10.1016/S1367-9120(02)00026-3 Zhou, G., Zhou, X., He, Y., Shao, J., Hu, Z., Liu, R., Zhou, H., & Hosseinibai, S. (2017). Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: A meta-analysis. Global Change Biology , 23 (3), 1167–1179. https://doi.org/10.1111/gcb.13431 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. 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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-6607637","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454128288,"identity":"c1637d19-1109-4f5d-b40c-38a2e31f1328","order_by":0,"name":"yihe zhao","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0009-6387-8017","institution":"Beijing Normal University","correspondingAuthor":true,"prefix":"","firstName":"yihe","middleName":"","lastName":"zhao","suffix":""},{"id":454128289,"identity":"5f975fac-d085-4c80-ad54-1b640c79e203","order_by":1,"name":"Jingyi Dong","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jingyi","middleName":"","lastName":"Dong","suffix":""},{"id":454128290,"identity":"b57f85ca-89ee-4d14-aa13-a6469e046121","order_by":2,"name":"Yuhan Liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yuhan","middleName":"","lastName":"Liu","suffix":""},{"id":454128291,"identity":"d2a52fb4-3398-4a8d-a729-61c2bc62cec6","order_by":3,"name":"Yinghui Liu","email":"","orcid":"https://orcid.org/0000-0003-2856-5241","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Yinghui","middleName":"","lastName":"Liu","suffix":""},{"id":454128292,"identity":"7f52c4bc-e2df-4c78-bda4-305d9d530de5","order_by":4,"name":"Jiaqi Zhang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jiaqi","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-05-07 03:36:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6607637/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6607637/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82644625,"identity":"c2d11a6b-79e6-4209-9cdd-1c4c4ad22b7f","added_by":"auto","created_at":"2025-05-13 15:51:44","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68504,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic of the plot layout and vegetation status in the study area\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/c159e5bb12d19c8250f7cbee.jpg"},{"id":82644623,"identity":"f45de3a6-2419-462b-a2d0-df26b2b6fd9d","added_by":"auto","created_at":"2025-05-13 15:51:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":107987,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of grazing intensity on the contents of elements in alpine meadow soils on the Qinghai‒Tibet Plateau (n=3 (UG), n=6 (LG, MG, HG))\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/9dc51cbcd53861238755da04.jpg"},{"id":82643934,"identity":"4a399796-aaba-4847-90e4-8db1bab14b9e","added_by":"auto","created_at":"2025-05-13 15:43:44","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":102462,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of grazing intensity on the leaf elemental contents of dominant species in the alpine meadow of the Qinghai‒Tibet Plateau (n=3 (UG), n=6 (LG, MG, HG))\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/9e49d72dc2d62dd37e94cffd.jpg"},{"id":82643936,"identity":"5657a546-7074-4d7e-a5b7-df8ae7d3bd8c","added_by":"auto","created_at":"2025-05-13 15:43:44","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":70607,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of grazing intensity on the soil ion coupling. The green shaded areas represent 999 randomly arranged zero models based on our dataset, and the error bars represent the standard errors of the means.Open circles denote the decoupling state, and solid circles located above the region indicates coupling, whereas the ones below the region signifies anticoupling.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/1f81a31fb4fb62518a061949.jpg"},{"id":82644626,"identity":"c1a07fe5-f73b-4400-90f6-c643740058c5","added_by":"auto","created_at":"2025-05-13 15:51:44","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":52068,"visible":true,"origin":"","legend":"\u003cp\u003eSoil ion correlation diagram under different intensities of grazing. In the figure, a green line represents a positive correlation, and a yellow line represents a negative correlation. The width of the line is proportional to the absolute value of Spearman's rank correlation coefficient; that is, the wider the line is, the stronger the elemental correlation.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/ffc19fb54a2c45c25375ed0b.jpg"},{"id":82643938,"identity":"5fa9ad70-7bb8-492e-b46a-b956a22a0ab6","added_by":"auto","created_at":"2025-05-13 15:43:44","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":83805,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of grazing intensity on the leaf elemental coupling. The yellow shaded areas represent 999 randomly arranged zero models based on our dataset, and the error bars represent the standard errors of the means.Open circles denote the decoupling state, and solid circles located above the region indicates coupling, whereas the ones below the region signifies anticoupling.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/95e614663f92d050a82e71a8.jpg"},{"id":82643942,"identity":"0059b8f9-8b97-4e8a-a9cf-a4a435d7b99a","added_by":"auto","created_at":"2025-05-13 15:43:44","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":40827,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation diagram of leaf elements under different intensities of grazing. In the figure, a green line represents a positive correlation, and a yellow line represents a negative correlation. The width of the line is proportional to the absolute value of the Spearman’s rank correlation coefficient; that is, the wider the line is, the stronger the elemental correlation.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/643160303ae3a4763744868a.jpg"},{"id":82645634,"identity":"33a6ba53-c754-46ce-af56-556f63dd03d3","added_by":"auto","created_at":"2025-05-13 15:59:44","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":67901,"visible":true,"origin":"","legend":"\u003cp\u003ePCA of soil and vegetation elements.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/1af9f8e37d1febb7be4dba18.jpg"},{"id":82643944,"identity":"e9deae02-4e09-4630-81bb-77edf40dc155","added_by":"auto","created_at":"2025-05-13 15:43:45","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":112620,"visible":true,"origin":"","legend":"\u003cp\u003eStructural equation model (SEM) of the effects of grazing intensity on the soil and vegetation elemental contents and degree of coupling. In the figure, soil elemental coupling and leaf elemental coupling represent the degrees of coupling of elements in the soil and vegetation, respectively, whereas PCA_soil and PCA_leaf represent the sums of the scores of the soil ions and vegetation elements in the PCA.\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/597389f2eb49b03545a0a6a1.jpg"},{"id":84533052,"identity":"dc4d9a8a-a231-41c2-aed4-fa61160ef169","added_by":"auto","created_at":"2025-06-13 06:32:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1464647,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6607637/v1/e609ea1d-d853-4fda-84d2-d935e401faed.pdf"}],"financialInterests":"","formattedTitle":"Increasing grazing intensity enhances vegetation elemental coupling but reduces soil elemental coupling in alpine meadows","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Qinghai\u0026ndash;Tibet Plateau encompasses the largest grassland area in Eurasia, where the fragile grassland ecosystems are extremely sensitive to global changes and anthropogenic disturbances(Dong et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Globally, grazing is the predominant form of grassland utilization. It influences the structure, function, and processes of grassland ecosystems primarily through three pathways: herbivory, trampling, and excretion (Kohler et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Overgrazing often leads to degradation in both vegetation and soil quality(LI Yu-qin \u0026amp; ZHAO Jing-bo, 2005), indicating a disruption in biogeochemical cycling within these ecosystems(Wang Changting et al., 2013). To understand how grassland material cycles respond to grazing gradients, previous studies have primarily focused on the effects of grazing on the contents and stoichiometric ratios of essential nutrients\u0026mdash;namely, carbon, nitrogen, phosphorus, and potassium\u0026mdash;in soils and plants(McSherry \u0026amp; Ritchie, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; He et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).These studies pay less attention to the mineral elements.\u003c/p\u003e \u003cp\u003eHowever, mineral elements in soils also play critical roles in sustaining plant physiological functions, conserving soil nutrients, and buffering soil acidification (Bowman et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). For instance, the contents of Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, K⁺, and Na⁺ are commonly used to evaluate soil quality, nutrient retention capacity, and acid-buffering potential. In contrast, elements such as Al\u0026sup3;⁺, Mn\u0026sup2;⁺, and Fe\u0026sup3;⁺ serve as important indicators of soil acidification due to their phytotoxicity and interference with nutrient uptake. Xu et al. observed that the contents of Fe, Mn, Cu, and Zn decreased with increasing grazing intensity (XU Yue-fei et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), while Zhang et al. reported opposite trends(Zhang Hong-qin et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These conflicting results highlight the importance of mineral elements as indicators of soil condition and their crucial influence on plant growth, though the patterns of their response to grazing gradients remain unclear. Plants exhibit selectivity in absorbing mineral elements from soils, and the efficiency of uptake varies among elements(Desjardins et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Whether grazing directly or indirectly alters plant mineral composition via soil mediation, and whether plants adopt specific strategies in mineral acquisition under grazing pressure, are questions that require empirical data on the elemental content of plants and soils across grazing gradients.\u003c/p\u003e \u003cp\u003eChanges in elemental contents and their ratios are classic concerns in ecological stoichiometry(Elser et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Typically, element coupling or decoupling refers to variations in nutrient ratios(Liu et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Rumpel \u0026amp; Chabbi, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Rumpel et al. argued that stronger coupling occurs when multiple soil elements undergo synchronized biological and abiotic processes, whereas asynchrony leads to decoupling(Rumpel et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).Recent frameworks proposed by Ochoa-Hueso et al. redefine elemental coupling as the covariation of chemical elements within ecosystems(Ochoa-Hueso et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This perspective enables the inclusion of a broader suite of elements in coupling analysis and offers elemental coupling degree as a sensitive indicator of ecosystem status. Under nitrogen addition treatments, Caetano-S\u0026aacute;nchez et al. observed no significant changes in the absolute concentrations of available elements, yet the degree of elemental coupling varied\u0026mdash;emphasizing the utility of coupling degree in detecting subtle environmental changes(Ochoa-Hueso et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This conceptual advancement provides both methodological and analytical tools for evaluating the responses of plant\u0026ndash;soil systems to grazing.\u003c/p\u003e \u003cp\u003eInvestigating the variation in nutrients and their interactions between plants and soils under grazing conditions enhances our understanding of plant\u0026ndash;soil nutrient dynamics and informs sustainable grassland management. This study focuses on less-explored mineral elements and adopts the coupling degree framework to characterize the response patterns of key plant and soil elements to grazing intensity in an alpine meadow on the Qinghai\u0026ndash;Tibet Plateau. We quantified the elemental concentrations in both vegetation and soils across a grazing gradient, and calculated soil elemental coupling as the mean absolute Spearman\u0026rsquo;s rank correlation coefficient among all element pairs. Additionally, we applied structural equation modelling (SEM) to explore the underlying mechanisms through which grazing affects elemental concentrations and their coupling. This study aims to address the following key questions: (1) How do elemental concentrations in vegetation and exchangeable soil elements respond to varying grazing intensities? (2) How does the degree of elemental coupling within and between vegetation and soil respond to grazing intensity? (3) What mechanisms drive the response of elemental coupling degree to different grazing intensities?\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study area and experimental design\u003c/h2\u003e \u003cp\u003eThis study was conducted in a typical alpine meadow located in the eastern part of the Qinghai‒Tibet Plateau (102\u0026deg;33\u0026prime;E, 32\u0026deg;48\u0026prime;N, 3500 m) within the Qinghai‒Tibet Plateau Research Base of Southwest Minzu University, which is located in Hongyuan County, Aba Tibetan Prefecture and Qiang Autonomous Prefecture, Sichuan Province, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The site has a mean annual temperature of 1.5\u0026deg;C, with monthly mean temperatures ranging from \u0026minus;\u0026thinsp;9.7\u0026deg;C in January to 11.1\u0026deg;C in July. The mean annual precipitation is 747 mm, with 80% of the rainfall occurring in the summer season. The climate is cold and humid, and the soil is frequently waterlogged. The surface soil is peat soil, with a bulk density of 0.89 g\u0026middot;cm⁻\u0026sup3; and a soil pH of 5.89. The dominant plant species at the experimental site include \u003cem\u003eKobresia pygmaea\u003c/em\u003e, \u003cem\u003eKobresia humilis\u003c/em\u003e, \u003cem\u003eSaussurea nigrescens\u003c/em\u003e, \u003cem\u003eElymus nutans\u003c/em\u003e, and \u003cem\u003eDeschampsia cespitosa\u003c/em\u003e. On the basis of the average grazing intensity in the region, four treatments were established: ungrazed control (UG), light grazing (LG, 1 yak/ha), moderate grazing (MG, 2 yaks/ha), and heavy grazing (HG, 3 yaks/ha). Each treatment was replicated in three plots. The average body weight of each yak was approximately 200 kg. Each plot covered an area of approximately 1 ha, with the total area of the ungrazed control plots being 1 ha and the total experimental area spanning 10 ha. The grazing experiment was conducted each year from late May to late September.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sampling and elemental analysis\u003c/h2\u003e \u003cp\u003eSample collection was carried out in August 2021. Within each plot, six small quadrats (0.5 m \u0026times; 0.5 m) were randomly selected, while avoiding the edges of the plots. Owing to the smaller area of the UG treatment plots, only three quadrats were sampled in these areas. The vegetation distribution within each quadrat was relatively uniform, and an appropriate spatial distance was maintained between quadrats.\u003c/p\u003e \u003cp\u003eTo estimate the aboveground biomass (AGB) and belowground biomass (BGB) of the vegetation, we harvested all green vegetation within each small plot. The samples were cleaned to remove adhering soil and gravel, then subjected to heat treatment at 105℃ for 30 minutes to terminate plant respiration and other physiological activities. Subsequently, the oven temperature was adjusted to 65℃, and the samples were dried until reaching constant weight before being weighed to determine AGB. For BGB estimation, we collected root samples using a root auger with a diameter of 7 cm and a sampling depth of 10 cm within each small plot. The roots were washed in a net bag to remove debris, dried at 65℃ until constant weight, and weighed to obtain BGB. It should be noted that during the calculation of belowground biomass, no distinction was made between live and dead roots.\u003c/p\u003e \u003cp\u003eThe elemental content of plant leaves was determined using the microwave digestion method. Leaf samples were collected from the dominant plant species within the quadrats, including \u003cem\u003eKobresia pygmaea\u003c/em\u003e, \u003cem\u003eElymus nutans\u003c/em\u003e, and \u003cem\u003eKobresia humilis\u003c/em\u003e. The contents of elements, including Ca, Mg, Na, Cu, Zn, Al, Mn, and Fe, were analysed using an inductively coupled plasma optical emission spectrometer (Optima 8000, PerkinElmer, USA). Soil elements primarily originate from soil solution, exchange sites, \"chelated\" forms bound to organic matter, and mineral crystals. Except for elements in mineral crystals, which are difficult for plants and microorganisms to utilize, the soil elements consist of exchangeable ions that can be absorbed by plants. Exchangeable Cu\u0026sup2;⁺, Zn\u0026sup2;⁺, Mn\u0026sup2;⁺, and Fe\u0026sup3;⁺ in the soil were extracted using 10 mL of extractant (5 mM DTPA\u0026thinsp;+\u0026thinsp;10 mM CaCl₂ + 0.1 M TEA). Exchangeable Al\u0026sup3;⁺ was extracted using 15 mL of 0.1 M BaCl₂, whereas Ca\u0026sup2;⁺, Mg\u0026sup2;⁺, and Na⁺ were extracted using 10 mL of 1 M NH₄OAc. The concentrations of all elements were determined using an inductively coupled plasma optical emission spectrometer (Optima 8000, PerkinElmer, USA).\u003c/p\u003e \u003cp\u003eA series of soil physicochemical properties were also measured. Soil pH was determined using a pH meter (S210-K, Mettler Toledo, Switzerland). The soil water content (SWC) and redox potential were measured in situ using a portable soil moisture meter (SM150 Kit, Delta-T, UK). For total carbon (TC) and total nitrogen (TN) determination, air-dried and sieved soil samples were analysed using an elemental analyser (CN802, VELP, Germany) with the combustion method. For total organic carbon (TOC) and total organic nitrogen (TON), inorganic carbon and nitrogen were first removed from the soil samples, which were then dried and sieved before analysis. The soil samples were shaken and filtered with 0.05 mol/L K₂SO₄ solution to obtain a clear filtrate. Dissolved organic carbon was measured using a TOC analyser (TOC-LCPN, Shimadzu, Japan), whereas ammonium nitrogen and nitrate nitrogen were determined using a continuous flow analyser (AutoAnalyzer3, Bran\u0026thinsp;+\u0026thinsp;Luebbe, Germany).We also determined the amount of available inorganic nitrogen in the soil, that is, the sum of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content. We use 0.5 M K\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e (40 mL) to leach per 10g of soil sample, and the contents of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e -N in the soil were determined by using a flow injection analyzer (Auto analyzer 3, Bran\u0026thinsp;+\u0026thinsp;Luebbe, Hamburg, Germany).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Statistical analysis\u003c/h2\u003e \u003cp\u003eFor vegetation and soil elements, the coupling value was calculated as the average of the absolute value of the Spearman rank correlation coefficient between different elements under different grazing intensities.\u003c/p\u003e \u003cp\u003eElemental coupling = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{\\sum\\:_{\\text{i}=1}^{\\text{n}}\\left|\\rho\\:i\\right|}{n}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere n is the number of paired Spearman\u0026rsquo;s correlation coefficients and \u0026#120588;\u0026#119894; is the Spearman rank correlation coefficient between two elements. We used a zero-model approach to measure the extent to which the degree of coupling is detached from purely random associations between elements. Accordingly, 999 zero-model randomizations were run at each grazing intensity, and the degree of coupling was calculated for each randomization. Based on comparisons, the measured degree of coupling was divided into three types: (i) coupling, where the observed value fell outside the envelope of the 97.5% quantile; (ii) decoupling, where the observed value fell within the quantile envelope of 2.5\u0026ndash;97.5%; and (iii) coupling, where the observed value was less than 2.5% of the random observation quantile. With the use of the FactoMineR package in R, the elemental contents of vegetation and soil were analysed via principal component analysis (PCA), with the elements studied in terms of dimension, and the comprehensive scores of the different elements on the axes of the two principal components were also added to the SEM analysis. Data analysis and mapping were performed in R Studio, SPSS, and GraphPad Prism 10.1.2, and the SEM was run using IBM SPSS Amos 26.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Effects of grazing intensity on the contents of elements in soil and vegetation\u003c/h2\u003e \u003cp\u003eIn the alpine meadow soils of the Qinghai‒Tibet Plateau subjected to disturbances from long-term grazing, the responses of various elements in soil to different intensities of grazing significantly differed. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the concentrations of nutrient elements essential for plant growth, such as Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺, were relatively high in the control and light grazing treatments. However, the concentrations of essential nutrient elements significantly decreased with increasing grazing intensity, reaching their lowest levels under heavy grazing. The soil Na⁺ content did not significantly respond to changes in the external environment. Compared with the control, grazing significantly reduced the content of Cu\u0026sup2;⁺, which was associated with enzymatic reactions in the nitrogen cycle, with reductions of 38.04%, 11.64%, and 19.22% under the light, moderate, and heavy grazing treatments, respectively. Moreover, although light and moderate grazing reduced the soil Zn\u0026sup2;⁺ content, heavy grazing significantly increased it, with an 89.13% increase compared with that of the control. As important indicator ions for severe soil acidification, the concentrations of soil Fe\u0026sup3;⁺ and Mn\u0026sup2;⁺ were highest under heavy grazing, increasing by 99.80% and 74.41%, respectively, compared with those in the control. In contrast, the soil Al\u0026sup3;⁺ content significantly decreased with increasing grazing intensity, reaching its lowest level under heavy grazing, with a 54.75% reduction compared with that of the control.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe effects of grazing intensity on the elemental composition of leaves from dominant plant species in the alpine meadows of the Qinghai‒Tibet Plateau were significantly different, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The concentrations of nutrient elements essential for plant growth, such as Mg, Ca, and Na, significantly decreased with increasing grazing intensity, with reductions of 23.82%, 29.45%, and 26.80%, respectively, compared with those in the control, reaching their lowest levels under heavy grazing. Grazing at different intensities also altered the contents of elements associated with enzymatic reactions in the nitrogen cycle, such as Cu and Zn, in the leaves of the dominant plant species. Compared with those in the control treatment, the Cu concentrations in the light and moderate grazing treatments increased by 49.68% and 40.06%, respectively. The Zn concentration was highest under moderate grazing, with a 26.47% increase compared with that of the control. The leaf Fe concentration under moderate grazing was significantly greater than that under the other three treatments, with a 44.97% increase compared with the control, but it was lowest under light grazing, decreasing by 16.61% compared with the control. Similarly, the leaf Mn and Al concentrations were highest under moderate grazing, increasing by 0.70% and 49.65%, respectively, compared with those in the control, and were lowest under light grazing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Effects of grazing intensity on the degree of coupling between soil and vegetation elements\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the overall degree of soil elemental coupling under the UG, LG, and MG treatments corresponded to a coupled state (above the null model region), indicating that at grazing intensities less than that corresponding to heavy grazing, the overall degree of soil coupling was not significantly altered, and spatial associations remained relatively stable. However, under the heavy grazing (HG) treatment, the overall degree of soil coupling decreased and became uncoupled, suggesting that heavy grazing disrupted the stability of spatial covariation among soil ions. The responses of different elements to grazing intensity varied significantly and could be categorized into three types of trends. The first trend involved Mn, Zn, Fe, and Ca, in which the degree of coupling initially increased and then decreased after reaching a threshold. Specifically, the degrees of coupling of Mn and Ca under LG were lower than those under UG, and these two elements were in an uncoupled state, whereas under MG, the degrees of coupling of Mn, Ca, and Fe reached their maximum values. Zn was coupled with other elements only under LG. In the first trend, the degrees of coupling of all the elements reached their lowest values under HG, and the elements were in an uncoupled state. The second trend, involving Na and Cu, showed a significant increase in coupling with increased grazing, with the highest degree of coupling observed under HG. The third trend, involving Mg and Al, exhibited a general decline in the degree of coupling with increasing grazing intensity. The degree of coupling of Al with other elements reached its lowest value under MG, whereas the degree of coupling of Mg showed a fluctuating trend, with its lowest value observed under HG. Additionally, N showed no clear trend under the grazing treatments. Overall, the degrees of coupling of multiple soil elements responded inconsistently to grazing pressure. In addition to grazing, other factors, such as soil properties and vegetation type, likely played a coregulatory role in influencing the degree of coupling. Using undirected network diagrams (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) to visualize the degree of coupling between elements, it was observed that under the four grazing intensities, changes in the degree of elemental coupling did not exhibit a significant trend, with elemental associations decreasing under HG.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the overall degree of coupling among plant elements generally tended to increase with increasing grazing intensity. It remained in an uncoupled state under the UG, LG, and MG treatments but showed coupling under HG. The trends in the degrees of coupling of different elements were generally similar, all displaying an increasing pattern with the intensity of grazing. The degrees of coupling of five elements\u0026mdash;Mg, Al, Mn, Fe, and Zn\u0026mdash;initially decreased but then increased along the grazing gradient. Except for Mg, the highest degrees coupling of the elements occurred under HG. The degree of Mg coupling reached a threshold under moderate grazing, indicating a coupled state, but decreased under HG. Both Na and Cu were in a decoupled state under grazing intensities less than that in HG, but their degree of coupling significantly increased under HG, indicating significant coupling. The degree of coupling of Ca progressively increased with grazing intensity, exhibiting a coupled state under MG and HG. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e also presents similar results, showing that under HG, the associations among plant elements clearly increased, all of which were positively correlated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Mechanism by which grazing intensity affects the degree of coupling between soil and vegetation\u003c/h2\u003e \u003cp\u003eTo further explore how grazing intensity influences the degree of coupling between soil and vegetation, structural equation modelling (SEM) was used to analyse the mechanisms driving the effects of grazing intensity. Principal component analysis (PCA) was employed to reduce the dimensionality of vegetation and soil elements, which were then incorporated into the SEM, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. In the PCA of the soil and vegetation elements, the first two principal components explained 67.2% and 57.7% of the variance, respectively. Under heavy grazing (HG) conditions, soil elements were characterized primarily by relatively high contents of the heavy metal elements Zn, Mn, and Fe, which significantly differed from the characteristics under UG conditions, where the Na, Al, and N contents were relatively high. The vegetation elements under UG and MG presented similar characteristics, with relatively high contents of elements such as Na, Ca, Mn, and Mg. In contrast, under HG and LG, vegetation elements presented the opposite pattern, with lower contents of Na, Ca, Mn, Mg, and other elements compared with those in the other treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn this study, we employed structural equation modelling (SEM) to quantify the mechanisms by which grazing intensity influenced soil and vegetation elemental contents and their degree of coupling. We calculated the scores of the first two principal components from the PCA for each element as the response variables. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;1 shows that grazing intensity had the strongest direct negative effect on the degree of soil elemental coupling. Additionally, the introduced element scores also exerted a direct negative effect on soil elemental coupling. Grazing intensity had the strongest positive effect on the element scores. Furthermore, NH₄⁺, soil water content (SWC), total carbon (TC), and total nitrogen (TN) played indirect roles in this process. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;2 shows that grazing intensity had a significant negative effect on vegetation elemental coupling. Additionally, the negative effect of grazing intensity on aboveground biomass (AGB) directly contributed to the negative effect on vegetation elemental coupling. Notably, the path coefficient of AGB on vegetation elemental coupling reached a value of -1.07, indicating that the presence of unexplained latent variables affected the degree of vegetation elemental coupling. Additionally, variables such as NH₄⁺, SWC, total organic nitrogen (TON), and others played indirect, nonsignificant roles in vegetation elemental coupling. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e\u0026thinsp;\u0026minus;\u0026thinsp;3 shows that grazing intensity had significant direct positive effects on both the vegetation and soil element scores. Furthermore, we observed a certain association between element scores and the degrees of coupling for vegetation and soil. Specifically, the degree of soil coupling had a positive effect on the vegetation element score, whereas the soil element score had a negative effect on the degree of soil coupling and a positive effect on the degree of vegetation elemental coupling. Notably, the degree of soil coupling had a significant negative effect on the degree of vegetation elemental coupling.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e4.1.\u0026nbsp;\u0026nbsp;Exchangeable soil ions are affected by grazing intensity\u003c/p\u003e\n\u003cp\u003eIn alpine meadow soils subjected to long-term grazing disturbances, the responses of various elements to different intensities of grazing significantly differed. The content of nutrient elements essential for plant growth, Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺, significantly decreased with increasing intensity of grazing. Studies have shown that an increase in soil organic matter content can increase the soil cation exchange capacity to retain Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺. However, in the study area, the total soil organic carbon and dissolved organic carbon levels did not significantly change, and with relatively high precipitation, the soil water content increased with grazing intensity, promoting leaching processes. This accelerated the loss of Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺ and the leaching of these cations to deeper soil layers\u0026nbsp;(Zhang et al., 2002).\u0026nbsp;Additionally, with increasing grazing intensity, the soil Mn\u0026sup2;⁺ and Fe\u0026sup3;⁺ contents increased, and these cations displaced Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ from binding sites into the soil solution, leading to Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ leaching (Gundersen et al., 2006; Skyllberg, 1999), which interfered with plant uptake of Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺\u0026nbsp;(Blake et al., 1999; Horswill et al., 2008).\u003c/p\u003e\n\u003cp\u003eMn has high chemical activity in soil, and in this study, the soil Mn\u0026sup2;⁺ content increased with increasing soil water content along the grazing gradient. Research has shown that the soil Mn\u0026sup2;⁺ content in grazing areas is relatively high during seasons and in regions with abundant rainfall(JIAO Ting et al., 2014).\u0026nbsp;Furthermore, the soil Cu\u0026sup2;⁺, Zn\u0026sup2;⁺, Fe\u0026sup3;⁺, and Mn\u0026sup2;⁺ contents all increased with increasing grazing intensity, reaching relatively high levels under heavy grazing. This may have occurred because the yaks trampled the ground, facilitating litter decomposition, and organic matter and nutrients were transferred to the soil(Zhang Hong-qin et al., 2015).\u0026nbsp;Organic matter can form organomineral complexes with soil Cu\u0026sup2;⁺, Zn\u0026sup2;⁺, Fe\u0026sup3;⁺, and Mn\u0026sup2;⁺\u0026nbsp;(Rahman et al., 1996), having some capacity to retain these trace elements and significantly reducing their leaching losses(XIN Guo-sheng et al., 2012).\u0026nbsp;In contrast, the soil Al\u0026sup3;⁺ content significantly decreased with increasing grazing intensity. This may have occurred because, within a certain pH range, Fe\u0026sup3;⁺, Mn\u0026sup2;⁺, and Al\u0026sup3;⁺ play similar roles in buffering soil acidity, and an increase in Fe\u0026sup3;⁺ and Mn\u0026sup2;⁺ suppressed the increase in Al\u0026sup3;⁺ solubility in the soil.\u003c/p\u003e\n\u003cp\u003e4.2.\u0026nbsp;\u0026nbsp;Grazing intensity affects the leaf elemental content of dominant species\u003c/p\u003e\n\u003cp\u003eThe effects of grazing on the elemental composition of leaves from dominant plant species in the alpine meadows were significantly different. Among the nutrients, the contents of those essential for plant growth, i.e., Mg, Ca, and Na, significantly decreased with increasing intensity of grazing. Correlation analysis revealed that the reductions in the Mg, Ca, and Na contents in the leaves of dominant species were positively correlated with the decrease in aboveground biomass, suggesting that the reductions in these three elements may be related to the loss of aboveground biomass due to trampling by yaks. Additionally, the availability of Mg, Ca, and Na in grassland ecosystems is influenced by nitrogen-related factors, such as atmospheric nitrogen deposition, nitrate leaching, and plant nitrogen uptake, which affect the content of alkaline cations in soil and their storage in plants\u0026nbsp;(Elvir et al., 2006).\u0026nbsp;In this study,\u0026nbsp;the\u0026nbsp;leaf Ca and Na contents\u0026nbsp;were positively correlated with the\u0026nbsp;soil ammonium nitrogen\u0026nbsp;content. This may have occurred because increased ammonium nitrogen availability\u0026nbsp;stimulates\u0026nbsp;plant growth, enhancing the uptake of Mg, Ca, and Na by plants(Vitousek \u0026amp; Howarth, 1991).\u0026nbsp;Furthermore,\u0026nbsp;the\u0026nbsp;leaf Mg and Ca contents\u0026nbsp;were negatively correlated with\u0026nbsp;soil Al\u0026sup3;⁺. Studies have shown that an increase in leaf Al content indicates\u0026nbsp;increased\u0026nbsp;toxicity effects from aluminium on plants\u0026nbsp;(Bowman et al., 2008), which may reduce the contents of nutrient elements such as Mg, Ca, and Na.\u003c/p\u003e\n\u003cp\u003eCu, Zn, Mn, and Fe are important components of enzymes involved in the nitrogen cycle. This study revealed that the leaf Cu content in dominant species under the grazing treatments was generally greater than that in the control group but decreased with increasing intensity of grazing, which was opposite to the increasing trend observed in soil Cu\u0026sup2;⁺. Generally, during the summer, when both rainfall levels and temperature are high, forage grasses grow rapidly, and plants absorb nutrients from the soil to meet their growth needs(JIAO Ting et al., 2014), with forage grasses primarily obtaining Cu from the soil.\u0026nbsp;However, in this study, the decrease in leaf Cu content with increasing grazing intensity suggested that, during the peak growth season in summer, increasing grazing may have interfered with plant uptake of Cu from the soil. Additionally, leaf Cu was negatively regulated by soil Zn\u0026sup2;⁺, Mn\u0026sup2;⁺, and Fe\u0026sup3;⁺, indicating that increases in soil Zn\u0026sup2;⁺, Mn\u0026sup2;⁺, and Fe\u0026sup3;⁺ may have suppressed plant uptake of Cu from the soil. This hypothesis was also supported by Li\u0026nbsp;et al., but further investigation is required to elucidate the specific mechanisms involved.\u003c/p\u003e\n\u003cp\u003eAs an essential trace element for plant growth, Mn plays important roles in plant physiological activities, such as regulating metabolism, promoting growth, enhancing disease resistance, and increasing forage yield(JIAO Ting et al., 2014).\u0026nbsp;The response of leaf Mn to the grazing gradient was similar to that of leaf Cu, possibly due to the combined effects of grazing and other mineral elements. The leaf Fe and Al contents were significantly positively correlated with pH, possibly because the solubility of Fe and Al in the soil increased with a decrease in soil pH, increasing their toxic effects on plants. Under such conditions, plants reduce their Fe and Al contents to mitigate the toxic effects of these elements.\u003c/p\u003e\n\u003cp\u003e4.3. How the grazing intensity affects the coupling of leaf elements and soil elements，and the mechanism behind it\u003c/p\u003e\n\u003cp\u003eOur study demonstrates that grazing intensity in alpine meadows exerts contrasting effects on soil and vegetation elemental dynamics. Specifically, increased grazing intensity results in a significant rise in soil heavy metal ions, such as Fe\u0026sup3;⁺ and Zn\u0026sup2;⁺ (Fig. 2), which, according to Structural Equation Modeling (SEM), indirectly diminishes soil elemental coupling. This phenomenon is likely due to livestock introducing heavy metals into the soil through their excreta, especially when consuming contaminated feed or water. The accumulation of these heavy metals may lead to competition with essential nutrients like Ca\u0026sup2;⁺ and Mg\u0026sup2;⁺ for adsorption sites(LIN Qing \u0026amp; XU Shao-hui, 2008) and exert toxic effects on microorganisms involved in elemental cycling(Abdu et al., 2017), thereby disrupting normal elemental interactions and reducing soil elemental coupling.\u003c/p\u003e\n\u003cp\u003eAt a localized scale, the accumulation of excreta contributes to elemental imbalances, which may further reduce soil elemental coupling. Furthermore, intensive grazing coupled with significant livestock trampling leads to increased soil bulk density and decreased porosity, permeability, and aeration(HOU Fu-Jiang et al., 2004). These changes restrict microbial activity and alter microbial community composition and function. Livestock trampling both increased the soil bulk density and decreased the aboveground biomass of vegetation, and these two effects decreased the number of fungi and bacteria, respectively(Yang et al., 2022).Under the same experimental location and setup as ours, Dong et al. found that soil microbial biomass increased under light grazing compared to the control group (CK) but decreased with higher grazing intensities(Dong et al., 2022). Given that microorganisms are pivotal in driving and maintaining soil elemental cycling(Spohn, 2016) , their decline can weaken soil elemental associations presumably, thereby diminishing soil elemental coupling. Although we have not further investigated the impact of microbial community changes on the mineral elemental coupling, Dong et al. found by this experiment that the concentration of ammonia-oxidizing archaea (AOA) increased significantly under heavy grazing, driving nitrification, a key process in the nitrogen cycle, to increase significantly as well(Dong et al., 2022). Similarly, Zhou et al. reached the same conclusion regarding the impact of grazing on the nitrogen cycle through a meta-analysis(Zhou et al., 2017). In biogeochemical cycling theory, the movement of various elements is coupled(Schlesinger et al., 2011). The relationship between mineral elements and the nitrogen cycle, through inter-elemental connections, may \u0026nbsp;require further exploration.\u003c/p\u003e\n\u003cp\u003eExisting literature indicates that under heavy grazing stress, plant populations may undergo collective miniaturization through positive interactions to defend against excessive herbivory(Wang et al., 2014; Wang X T et al., 2015). This is consistent with our findings that both aboveground and belowground vegetation biomass decreased with increasing grazing intensity, and that the reduction of aboveground biomass was directly related to vegetation coupling in the SEM model. This strategy involves individual plants reducing their nutrient demands, leading to decreased community productivity. Consequently, the co-reduction of nutrient content within plant tissues may be a significant factor contributing to the observed increase in plant elemental coupling. Additionally, grazing-tolerant species, such as Kobresia pygmaea, may adopt rapid growth strategies under heavy grazing(Cruz et al., 2010), efficiently absorbing light and nutrients to enhance regenerative capacity, resulting in accelerated internal nutrient cycling and increased elemental coupling within the plants.\u003c/p\u003e\n\u003cp\u003eBy examining the relationships between elements in soil and plants, we observe that changes in elemental contents do not follow a simple supplier-absorber model. Under natural conditions, a plant\u0026apos;s ability to absorb elements is constrained by its biological demands, which vary significantly across different growth stages and exhibit strong selectivity among elements. For elements with low biological utilization efficiency, the correlation between their contents in soil and vegetation is weak. Moreover, variations in soil properties, such as pH and moisture, influence the form and distribution of soil ions, complicating plant uptake mechanisms. Thus, the available ion contents for plants may differ from the measured ion contents in the soil.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn this study, we examined the response of leaf element content of dominant species and soil exchangeable ion content in alpine meadows to grazing pressure and analysed the changes in the degree of soil‒vegetation elemental coupling and underlying mechanisms. The results revealed that with increasing grazing intensity, the elemental composition of both the soil and the vegetation was significantly altered. With increasing grazing intensity, the contents of essential nutrient elements such as Mg\u0026sup2;⁺ and Ca\u0026sup2;⁺ in the soil significantly decreased, whereas the contents of trace elements such as Cu\u0026sup2;⁺, Zn\u0026sup2;⁺, Fe\u0026sup3;⁺, and Mn\u0026sup2;⁺ increased. Furthermore, grazing reduced the degree of coupling among soil elements to some extent but increased the degree of coupling among vegetation elements.\u003c/p\u003e \u003cp\u003eIn this study, the plant elemental contents were measured in the leaves of dominant species within sampling plots, but the elemental contents of different plant species were not measured separately. However, the capacity for elemental uptake and accumulation varies significantly among different plant species, which may influence the interpretation of the overall degrees of vegetation elemental coupling. In future studies, researchers can further incorporate the elemental uptake characteristics of different functional groups of plants to analyse the impacts of grazing on nutrient cycling in grassland ecosystems more comprehensively. Soil microbes play critical roles in nutrient mineralization, organic matter decomposition, and rhizosphere environment regulation, and their responses to grazing disturbances may be key factors influencing the elemental coupling. Therefore, future research should focus on high-throughput sequencing of microbial communities to elucidate how different microbial taxa influence specific elemental correlation and its mechanisms.\u003c/p\u003e \u003cp\u003eHere, a new theoretical framework of coupling degree was introduced to understand the complex dynamics of nutrient cycling in alpine meadows under grazing disturbance. This approach will enhance our understanding of how grazing impacts elemental balance within grassland ecosystems.The findings of this study have important implications for grassland management. On the one hand, long-term high-intensity grazing may lead to significant losses of soil nutrient elements and deterioration of the soil chemical environment, thereby reducing soil fertility and plant growth potential. Therefore, the grazing intensity should be reasonably controlled to avoid excessive loss of key soil nutrients. Measures such as rotational grazing could be appropriately implemented to improve grassland community structure and promote vegetation recovery. On the other hand, the increase in vegetation coupling indicates that grazing pressures compel plants to adopt stress-resilient strategies, which leads to a reduction in the overall productivity of plant communities. It is crucial to prioritize the protection of high-quality forage species to avoid their overexploitation under intensive grazing regimes, thereby ensuring the long-term stability and productivity of grassland ecosystems.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNitrogen\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003emoderate grazing\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAL \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAluminum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eheavy grazing\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMagnesium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ePCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003ePrincipal component analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSodium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eSEM\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003estructural equation modelling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalcium\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAGB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eaboveground biomass\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIron\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eBGB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003ebelowground biomass\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eManganese\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;total carbon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCu\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCopper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003etotal nitrogen\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZinc\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003etotal organic carbon (TOC)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eCK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003ethe control group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eTON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003etotal organic nitrogen (TON)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eUG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003eungrazed control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003eammonia-oxidizing archaea\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 210px;\"\u003e\n \u003cp\u003elight grazing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e：We would like to thank the reviewers and editor for proofreading and providing helpful suggestions on the manuscript. Thanks to the Sichuan Zoige Alpine Wetland Ecosystem National Observation and Research Station, especially for the manager of the Yak Grazing Intensity platform, Tserang Donko Mipam.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis\u0026nbsp;research\u0026nbsp;was supported by the National Key Research and Development Program of China [grant No. 2022YFF1302803] and National Natural Science Foundation of China [grant No. 31770519]. We thank the Duolun Restoration Ecology Station for providing access to the study site.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYihe Zhao and Jingyi Dong developed and proposed the research question and drafted the manuscript, Yuhan Liu analyzed the data and contributed to the manuscript writing, Yinghui Liu revised the manuscript and provided guidance, and Jiaqi Zhang conducted field investigations and collected the data. All the authors contributed substantially to the writing and revision of the manuscript. Yihe Zhao and Jingyi Dong contributed equally to this work.\u003c/p\u003e\n\u003ch4\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/h4\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdu, N., Abdullahi, A. A., \u0026amp; Abdulkadir, A. (2017). Heavy metals and soil microbes. \u003cem\u003eEnvironmental Chemistry Letters\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 65\u0026ndash;84. https://doi.org/10.1007/s10311-016-0587-x\u003c/li\u003e\n\u003cli\u003eBlake, L., Goulding, K. W. T., Mott, C. J. B., \u0026amp; Johnston, A. E. (1999). 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The background concentrations of 13 soil trace elements and their relationships to parent materials and vegetation in xizang (tibet), China. \u003cem\u003eJournal of Asian Earth Sciences\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(2), 167\u0026ndash;174. https://doi.org/10.1016/S1367-9120(02)00026-3\u003c/li\u003e\n\u003cli\u003eZhou, G., Zhou, X., He, Y., Shao, J., Hu, Z., Liu, R., Zhou, H., \u0026amp; Hosseinibai, S. (2017). Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: A meta-analysis. \u003cem\u003eGlobal Change Biology\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(3), 1167\u0026ndash;1179. https://doi.org/10.1111/gcb.13431\u003c/li\u003e\n\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":"Qinghai-Tibet Plateau, elemental coupling, alpine meadow, biogeochemical cycles","lastPublishedDoi":"10.21203/rs.3.rs-6607637/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6607637/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGrazing alters the biogeochemical cycles in grassland ecosystems, with the elemental coupling serving as an effective measure of this impact. The concept of elemental coupling allows for the inclusion of various mineral elements, offering new insights into the effects of grazing on the material cycling.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study focused on a typical alpine meadow in the eastern Qinghai-Tibet Plateau, where we measured the total elemental content of dominant vegetation, soil exchangeable ions, and soil physicochemical properties. We analysed the changes in soil and plant elemental coupling and used a Structural Equation Modeling (SEM) approach to investigate the mechanisms driving these changes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWith increasing grazing intensity, the concentrations of heavy metals such as copper (Cu\u0026sup2;⁺), zinc (Zn\u0026sup2;⁺), manganese (Mn\u0026sup2;⁺), and iron (Fe\u0026sup3;⁺) significantly increased in the soil, while the contents of essential nutrients such as Mg, Ca, and Na decreased in the vegetation. Increasing grazing intensity enhanced vegetation element coupling but reduced soil element coupling, with increases of 52.8% and decreases of 16.8% under heavy grazing, respectively. SEM analysis revealed significant direct effects of grazing intensity on the changes in coupling.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study investigated how grazing affects elemental coupling in an alpine meadow on the eastern Qinghai-Tibet Plateau. While grazing intensity enhances vegetation element coupling, it reduces soil element coupling.This study provides new perspectives and scientific basis for rational grazing management and sustainable grassland use.\u003c/p\u003e","manuscriptTitle":"Increasing grazing intensity enhances vegetation elemental coupling but reduces soil elemental coupling in alpine meadows","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 15:43:40","doi":"10.21203/rs.3.rs-6607637/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":"51427a66-cd96-4f55-91b5-09edce46eafb","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-13T06:24:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 15:43:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6607637","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6607637","identity":"rs-6607637","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}