Search Results (204)

Fertilization is a critical measure for vegetation restoration and ecological reconstruction in degraded grasslands. However, little is known about the long-term effects of different combinations of nitrogen (N), phosphorus (P), potassium (K) on plant and microbial communities in degraded grasslands. This study conducted a four-year (2017–2020) N, P, K addition experiment in the Khorchin Grassland, a degraded typical grassland located in Zhalute Banner, Tongliao City, Inner Mongolia, to investigate the effects of fertilization treatment on plant functional groups and microbial communities after grazing exclusion. Our results showed that the addition of P, NP, and NPK compound fertilizers significantly increased aboveground biomass of the plant community, which is mainly related to the improvement of nutrient availability to promote the growth of specific plant functional groups, especially annual and biennial plants and perennial bunchgrasses. However, the addition of N, P, and NP fertilizers significantly reduced the species diversity of the plant community. At the same time, the addition of N, P, and NP fertilizers and the application of N and NP significantly reduced fungal species diversity but had no significant effect on soil bacteria. Our study provides new insights into the relationships between different types of fertilization and plant community productivity and biodiversity in degraded grasslands over four years of fertilization, which is critical for evaluating the effect of fertilization on the restoration of degraded grassland. Full article

Grazing affects soil organic carbon (SOC) through plant removal, livestock trampling, and manure deposition. However, the impact of grazing on SOC is also influenced by multiple factors such as climate, soil properties, and management approaches. Despite extensive research, the mechanisms by which grazing intensity influences SOC density in grasslands remain incompletely understood. This study examines the effects of varying grazing intensities on SOC density (0–30 cm) dynamics in temperate grasslands of northern China using field surveys and experimental analyses in a typical steppe ecosystem of Inner Mongolia. Results show that moderate grazing (3.8 sheep units/ha/yr) led to substantial consumption of aboveground plant biomass. Relative to the ungrazed control (0 sheep units/ha/yr), aboveground plant biomass was reduced by 40.5%, 36.2%, and 50.6% in the years 2016, 2019, and 2020, respectively. Compensatory growth failed to fully offset biomass loss, and there were significant reductions in vegetation carbon storage and cover (p < 0.05). Reduced vegetation cover increased bare soil exposure and accelerated topsoil drying and erosion. This degradation promoted the downward migration of SOC from surface layers. Quantitative analysis revealed that moderate grazing significantly reduced surface soil (0–10 cm) organic carbon density by 13.4% compared to the ungrazed control while significantly increasing SOC density in the subsurface layer (10–30 cm). Increased precipitation could mitigate the SOC transfer and enhance overall SOC accumulation. However, it might negatively affect certain labile SOC fractions. Elucidating the mechanisms of SOC variation under different grazing intensities and precipitation regimes in semi-arid grasslands could improve our understanding of carbon dynamics in response to environmental stressors. These insights will aid in predicting how grazing systems influence grassland carbon cycling under global climate change. Full article

Climate change alters plant biomass allocation and aboveground–belowground trade-offs in grassland ecosystems, potentially affecting critical functions such as carbon sequestration. However, uncertainties persist regarding how precipitation gradients regulate (1) responses of aboveground biomass (AGB), belowground biomass (BGB), and total biomass in alpine grasslands, and (2) precipitation-mediated AGB-BGB allocation strategies. To address this, we conducted a large-scale field survey across precipitation gradients (400–700 mm/y) in the Sanjiangyuan alpine grasslands, Qinghai–Tibet Plateau. During the 2024 growing season, a total of 63 sites (including 189 plots and 945 quadrats) were sampled along five aridity classes: <400, 400–500, 500–600, 600–700, and >700 mm/y. Our findings revealed precipitation as the dominant driver of biomass dynamics: AGB exhibited equal growth rates relative to BGB within the 600–700 mm/y range, but accelerated under drier/wetter conditions. This suggests preferential allocation to aboveground parts under most precipitation regimes. Precipitation explained 31.71% of AGB–BGB trade-off variance (random forest IncMSE), surpassing contributions from AGB (17.61%), specific leaf area (SLA, 13.87%), and BGB (12.91%). Structural equation modeling confirmed precipitation’s positive effects on SLA (β = 0.28, p < 0.05), AGB (β = 0.53, p < 0.05), and BGB (β = 0.60, p < 0.05), with AGB-mediated cascades (β = 0.33, p < 0.05) dominating trade-off regulation. These results advance our understanding of mechanistic drivers governing allometric AGB–BGB relationships across climatic gradients in alpine ecosystems of the Sanjiangyuan Region on the Qinghai–Tibet Plateau. Full article

The arid-hot valleys of Sichuan Province contain extensive engineered gravel deposits, where ecological restoration has become the predominant remediation strategy. Accelerating vegetation recovery and continuously improving productivity are important prerequisites for the protection of regional biodiversity. We employed fertilization and sowing cultivation to facilitate ecological restoration. We have conducted continuous ecological experiments for two years using the following experimental treatments, covering indigenous soil, adding organic fertilizer, and applying compound fertilizer and organic fertilizer, with six types of sowing established under each soil treatment: monoculture and pairwise mixed cropping utilizing Elymus dahuricus (EDA), Dactylis glomerata (DGL), and Medicago sativa (MSA). Through the analysis of variance and the calculation of effect factors, our results indicated that compound fertilizer and organic fertilizer adding significantly improved vegetation cover and increased aboveground biomass, and the highest productivity was observed in the mixed sowing treatment of EDA and MSA. The effect coefficient model analysis further showed that the combination of EDA and MSA resulted in the highest selection and compensation effects on aboveground productivity. Two potential mechanisms drive enhanced productivity in mixed grasslands: the strengthening of the selection effect via increased legume nitrogen fixation, and the enhancement of the compensation effect through niche differentiation among species. Full article

To clarify the ecological mechanisms underlying the succession of artificial grasslands to native alpine meadows and systematically reveal the patterns of ecological restoration in artificial grasslands in the Qinghai–Tibet Plateau, this study provides a theoretical basis for alpine meadow ecological restoration. In this study, artificial grassland and degraded grassland (CK) with different restoration years (20 years, 16 years, 14 years, and 2 years) in the Qinghai–Tibet Plateau were taken as research objects. We focused on the tillering characteristics, patch number, community structure evolution, and soil properties of the dominant species, C. alatauensis, and systematically explored the ecological restoration law by comparing and analyzing ecological indicators in different restoration years. The results showed the following: (1) With the extension of restoration years, the asexual reproduction ability of C. alatauensis was enhanced, the patches became large, and aboveground/underground biomass significantly accumulated. (2) Community structure optimization meant that the coverage and biomass of Cyperaceae plants increased with restoration age, while those of Poaceae plants decreased. The diversity of four species in 20A of restored grasslands showed significant increases (10.71–19.18%) compared to 2A of restored grasslands. (3) Soil improvement effect: The contents of soil organic carbon (SOC), total phosphorus (TP), nitrate nitrogen (NN), and available phosphorus (AP) increased significantly with the restoration years (in 20A, the SOC content in the 0–10 cm soil layer increased by 57.5% compared with CK), and the soil pH gradually approached neutrality. (4) In artificial grasslands with different restoration ages (20A, 16A, and 14A), significant or highly significant correlations existed between C. alatauensis tiller characteristics and community and soil properties. In conclusion, C. alatauensis in artificial grasslands drives population enhancement, community succession, and soil improvement through patch expansion. Full article

Aboveground biomass (AGB) is a critical indicator for assessing carbon sequestration and ecosystem health in transboundary ecologically fragile areas. High-precision estimation and spatiotemporal inversion of AGB are the key to investigating transition zones. However, inadequate feature selection and complex parameter tuning limit accuracy and spatiotemporal representation in the estimation model. An AGB estimation model that integrates SHAP-based feature selection with a particle swarm optimization-enhanced random forest model (RF_PSO) was proposed. Then AGB trajectory clustering was used to characterize the grassland change pattern. The method was applied to grasslands across the China–Mongolia–Russia (CMR) border area from 2000 to 2020. The results show that (1) the SHAP-RF_PSO model achieved the highest accuracy (R² = 0.87, RMSE = 45.8 g/m²), outperforming other estimation models. (2) AGB improvements were observed in 72.13% of the area, mainly in MN_EA, MN_CE, and CN_NMG, while 27.39% showed degradation, concentrated in CN_NMG and MN_CE. The stable area accounts for 0.48%, which is scattered in RU_BU and RU_ZA.CN_NMG. (3) Four change patterns, namely Fluctuating Low, Stable Low, Fluctuating High, and Stable High, were identified, with major shifts in 2007, 2012, and 2014. (4) Projections indicate that 80% of the region may maintain current trends, 13% may reverse, and 7% remain uncertain, requiring targeted interventions. This study offers a robust tool for high-precision AGB estimation and supports dynamic monitoring in the CMR border area. Full article

The biomass allocation patterns between aboveground and belowground are an essential functional trait for plant survival under a changing environment. The effects of arbuscular mycorrhizal fungi (AMF) communities on plant biomass allocation, particularly in degraded Festuca ovina grasslands in ecologically fragile karst areas, remain unclear. Therefore, we conducted a field investigation combined with a greenhouse experiment to explore the importance of AMF compared to bacteria and fungi for plant biomass allocation. The results showed that plant biomass in degraded grasslands exhibited allometric biomass allocation, contrasting with isometric partitioning in non-degraded grasslands. AMF, not bacteria or fungi, were the primary microbial mediators of grassland degradation effects on plant biomass allocation based on structural equation modeling. The greenhouse experiment demonstrated that the selected AMF keystone species from the field study performed according to ecological network analysis, particularly multi-species combinations, enhanced the belowground biomass allocation of F. ovina under rocky desertification stress compared to single-species inoculations, through decreasing soil pH, enhancing alkaline phosphatase (ALP) activity, and increasing the expression level of AMF-inducible phosphate transporter (PT4). This study highlights the critical role of the AMF community, rather than individual species, in mediating plant survival strategies under rocky desertification stress. Full article

Grassland biomass yield reflects a complex interaction of management intensity and environmental factors, yet quantifying the relative role of practices such as mowing and fertilization remains challenging. In this study, we introduce a multi-class machine learning framework to predict above-ground biomass on 150 permanent grassland plots across eight years (2009–2016) in Germany’s Biodiversity Exploratories and to evaluate the influence of key management variables. Following rigorous data cleaning, imputation of missing nitrogen values, feature standardization, and encoding of categorical practices, we trained CatBoost classifiers optimized via Bayesian hyperparameter search and mitigated class imbalance with ADASYN oversampling. We assessed model performance under binary, three-class, four-class, and five-class quantile-based categorizations, achieving test accuracies of 0.76, 0.57, 0.42, and 0.38, respectively. Across all schemes, mowing frequency and mineral nitrogen input emerged as the dominant predictors, while secondary variables such as drainage and conditioner use contributed as well. These results demonstrate that broad biomass categories can be forecast reliably from standardized management records, whereas finer distinctions necessitate additional environmental information or automated sensing to capture nonlinear effects and reduce reporting bias. This work shows both the potential and the limits of machine learning for informing sustainable grassland management and explainability thereof. Frequent mowing and higher mineral nitrogen inputs explained most of the predictable variation, enabling a 76% accurate separation of low and high biomass categories. Predictive accuracy fell below 60% for finer class resolutions, indicating that management records alone are insufficient for detailed yield forecasts without complementary environmental data. Full article

The Qinghai–Tibet Plateau, a critical ecological barrier and major livestock region, faces deteriorating grasslands and rising forage demand under its harsh alpine climate. Oat (Avena sativa L.), valued for its cold tolerance, rapid biomass accumulation, and ability to thrive in nutrient-poor soils, can expand winter feed reserves and partly alleviate grazing pressure on native rangelands. However, genetic improvement alone has not been sufficient to address the environmental challenges. This issue is particularly severe in the Qaidam Basin, where soil salinization, characterized by high pH, poor soil structure, and low nutrient availability, significantly limits crop performance. Rhizosphere growth-promoting bacteria (PGPR) are environmentally friendly biofertilizers known to enhance crop growth, yield, and soil quality, but their application in the saline soil of the Qaidam Basin remains limited. We evaluated two PGPR application rates (B1 = 75 kg hm⁻² and B2 = 150 kg hm⁻²) on ‘Qingtian No. 1’ oat, assessing plant growth, soil physicochemical properties, and rhizosphere microbial communities. The results indicated that both treatments significantly increased oat productivity, raised the comprehensive growth index, augmented soil organic matter, and lowered soil pH; B1 chiefly enhanced above-ground biomass and fungal community stability, whereas B2 more strongly promoted root development and bacterial community stability. Structural equation modeling showed that PGPR exerted direct effects on the comprehensive growth index and indirect effects through soil and microbial pathways, with soil properties contributing slightly more than microbial factors. Notably, rhizosphere organic matter, fungal β-diversity, and overall microbial community stability emerged as positive key drivers of the comprehensive growth index. These findings provide a theoretical basis for optimizing PGPR dosage in alpine forage systems and support the sustainable deployment of microbial fertilizers under saline soil conditions in the Qaidam Basin. Full article

Research was conducted in Gannan Prefecture, China, to better understand the characteristics of carbon emissions and sequestration in areas dominated by animal husbandry. The emission factor method was used to calculate and analyze changes in carbon emissions from 2009 to 2024. The region’s average annual carbon emissions from animal husbandry are 774,286 t C-eq (2,839,049 t CO₂eq), with enteric emissions from cattle being the biggest contributor. However, as the number of locally raised cattle and sheep has decreased, carbon emissions have gradually fallen at an average annual rate of −1.0%. The annual average total carbon sequestration of vegetation in the region is 6,861,535 t C-eq, and the carbon content in underground biomass is higher than that in aboveground biomass, making it the main contributor to grassland carbon sequestration. Carbon sequestration from grassland vegetation is greater than the carbon emissions from animal husbandry, which means that the entire production system is currently a carbon sink. Meanwhile, the analysis of land-use carbon sequestration found that the annual average total sequestration by forests and grasslands over the same time period was 752,327 t C-eq, and sequestration is increasing at an annual rate of 1.4%, primarily driven by the progressive expansion of forested areas. Although the regional carbon emissions from animal husbandry are lower than the carbon sequestration, developing a science-based animal husbandry plan aligned with regional ecological thresholds, continuing to implement grass–livestock balance management measures, and preventing livestock numbers from exceeding their ecological carrying capacity remain critical to promoting sustainable coordination between livestock economies and ecological conservation. Full article

Gut microbiota “enterotypes” are strongly associated with diet and host health. For grazing animals, plant species richness and nutrient content of vegetation may alter the food supply and diet composition of animals. Understanding this relationship is critical to clarify the adaption of gut microbiota to changes in vegetation quantity and quality in grassland ecosystems. Here, we studied the relationship between dietary and gut microbiota composition of sheep (lambs) over a growing season in a grassland ecosystem in northern China. Variation in vegetation composition among grazing intensities was greatest in September: and sheep preferred forbs and Rosaceae throughout the grazing period in all grazing treatments, yet their preference for Fabaceae was reduced in HG treatments in September. Grazing intensity and seasonal variations in food resource availability influenced dietary patterns, which in turn affected gut bacterial community composition. Enterotype 1, dominated by Christensenellaceae_R_7_group and Clostridia_UCG_014_unclassified, predominated during the warm season (July) for both LG and HG treatments. In contrast, Enterotype 2, dominated by Escherichia_Shigella, prevailed during the cool season (September) in HG. Diversity of Enterotype 1 exceeded (p < 0.001) that of Enterotype 2. For MG, Enterotype 1 and Enterotype 2 were evenly distributed over the grazing period. Our results highlight the importance of regulating grazing intensity to maintain the balance and health of gut microbiota according to temporal changes in plant nutrients and aboveground biomass of grassland ecosystems. Full article

The escalation in the population of livestock coupled with inadequate precipitation has caused a reduction in pasture biomass, thereby resulting in diminished grassland carrying capacity (GCC) and pasture degradation. In this research, net primary productivity (NPP) data, sourced from the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets from 1982 to 2020, were initially transformed into aboveground biomass (AGB) estimates. These estimates were subsequently utilized to evaluate and assess the long-term trends of GCC across Mongolia. The MODIS data indicated an upward trend in AGB from 2000 to 2020, whereas the GLASS data reflected a downward trend from 1982 to 2018. Between 1982 and 2020, climatic analysis uncovered robust positive correlations between AGB and precipitation (R > 0.80) and negative correlations with temperature (R < −0.60). These climatic alterations have led to a reduction in AGB, further impairing the regenerative capacity of grasslands. Concurrently, livestock numbers have generally increased since 1982, with a decrease in certain years due to dzud and summer drought, leading to the increase in the GCC. GCC assessment found that 37.5% of grasslands experienced severe overgrazing and 31.9–40.7% was within sustainable limits. Spatially, the eastern region of Mongolia could sustainably support current livestock numbers; the western and southern regions, as well as parts of northern Mongolia, have exhibited moderate to critical levels of grassland utilization. A detailed analysis of GCC dynamics and its climatic impacts would offer scientific support for policymakers in managing grasslands in the Mongolian Plateau. Full article

Phosphorus (P) and silicon (Si) could profoundly affect the net primary productivity (ANPP) of grassland ecosystems. However, how ecosystem biomass will respond to different Si addition, especially under a concurrent increase in P fertilization, remains limited. With persistent demand for grassland utilization, there is a need to enhance and sustain the productivity of grasslands on the Qinghai–Tibet Plateau. Three P addition rates (0, 400, 800, and 1200 kg Ca(H₂PO₄)₂ ha⁻¹ yr⁻¹) without Si and with Si (14.36 kg H₄SiO₄ ha⁻¹ yr⁻¹) were applied to alpine grassland on the Qinghai–Tibet Plateau to evaluate the responses of aboveground biomass and the underlying mechanisms linking to structural carbon composition and physiological traits of grasses and forbs. Our results show that the application of Si significantly reduced the lignin, cellulose, hemicellulose, and total phenol contents of both grasses and forbs. Additionally, the addition of P, Si, and phosphorus and silicon (PSi) co-application significantly increased the net photosynthetic rate (Pn) and light use efficiency (LUE) of grasses and forbs. Moreover, Si promoted the absorption of N and P by plants, resulting in significant changes in the Si:C, Si:P, and Si:N ratios and increasing the aboveground biomass. Our findings suggest that Si can replace structural carbohydrates and regulate the absorption and utilization of N and P to optimize the photosynthetic process of leaves, thereby achieving greater biomass. In summary, Si supplementation improves ecosystem stability in alpine meadows by optimizing plant functions and increasing biomass accumulation. Full article

Above-ground biomass (AGB) is a core indicator for evaluating grassland ecosystem health and carbon storage. Traditional ground-based AGB measurements are labor-intensive and ill suited for large-scale monitoring. This study addresses this gap by developing a Multilayer Perceptron (MLP) model integrating Landsat 9 OLI/TIRS imagery acquired on 15 August 2024, with ground data from 78 sampling points (62 training, 16 testing). Incorporating fourteen multi-source features (seven vegetation indices, e.g., Modified Vegetation Index (MVI) and Green Chlorophyll Index (CIg); four meteorological variables; three soil properties), all data were standardized via z-score normalization before training. The MLP model, optimized via six-fold cross-validation, achieved an R² of 0.765 and RMSE of 38.066 g/m², outperforming XGBoost (R² = 0.723, RMSE = 41.354 g/m²) with a statistically significant 5.8% accuracy improvement (p < 0.05). Spatial analysis revealed a north-to-south AGB gradient, strongly correlated with precipitation gradients (250–350 mm/year) and soil organic carbon (R = 0.428). These findings provide a robust framework for climate-adaptive grassland management and carbon assessment in semi-arid regions. Full article

Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to significantly enhance the carbon storage capacity of ecosystems. This study evaluated ecological restoration strategies in Chongqing’s Tongluo Mountain mining area by integrating GF-6 satellite multispectral data (2 m panchromatic/8 m multispectral resolution) with ground surveys across 45 quadrats to develop a quadratic regression model based on vegetation indices and the field-measured biomass. The methodology quantified carbon storage variations among engineered restoration (ER), natural recovery (NR), and unmanaged sites (CWR) while identifying optimal vegetation configurations for karst ecosystems. The methodology combined the high-spatial-resolution satellite imagery for large-scale vegetation mapping with field-measured biomass calibration to enhance the quantitative accuracy, enabling an efficient carbon storage assessment across heterogeneous landscapes. This hybrid approach overcame the limitations of traditional plot-based methods by providing spatially explicit, cost-effective monitoring solutions for mining ecosystems. The results demonstrate that engineered restoration significantly enhances carbon sequestration, with the aboveground vegetation biomass reaching 5.07 ± 1.05 tC/ha, a value 21% higher than in natural recovery areas (4.18 ± 0.23 tC/ha) and 189% greater than at unmanaged sites (1.75 ± 1.03 tC/ha). In areas subjected to engineered restoration, both the vegetation and soil carbon storage showed an upward trend, with soil carbon sequestration being the primary form, contributing to 81% of the total carbon storage, and with engineered restoration areas exceeding natural recovery and unmanaged zones by 17.6% and 106%, respectively, in terms of their soil carbon density (40.41 ± 9.99 tC/ha). Significant variations in the carbon sequestration capacity were observed across vegetation types. Bamboo forests exhibited the highest carbon density (25.8 tC/ha), followed by tree forests (2.54 ± 0.53 tC/ha), while grasslands showed the lowest values (0.88 ± 0.52 tC/ha). For future restoration initiatives, it is advisable to select suitable vegetation types based on the local dominant species for a comprehensive approach. Full article