Search Results (326)

Lignin, an organic compound with a complex structure, is formed through the polymerization of structural units linked by carbon–carbon bonds and ether bonds. The question of whether lignin is labile or resistant to biological and chemical degradation in soil, particularly in alpine ecosystems, remains unresolved. To address this knowledge gap, we analyzed the relationship between phospholipid fatty acid biomarkers and the abundance of lignin components in grassland soils from North Tibet, China. Soil samples were collected from alpine grasslands, including alpine meadows and alpine steppes. The relative abundance of lignin in these alpine grassland soils before and after a 210-day incubation period was measured. Our results indicate that the relative abundance of lignin in the alpine grassland soils decreased during the incubation period. Significant relationships were found between the phospholipid fatty acid biomarkers of bacteria, fungi, Gram-positive bacteria, and Gram-negative bacteria and the relative abundance of lignin components. This research was conducted under laboratory conditions that are optimal for the development of microorganisms but significantly different from the conditions in Tibet. Furthermore, this study contributes to the understanding of soil organic matter degradation and the dynamics of microbial communities in alpine grassland soils in the context of future global warming. Full article

Climate change poses great challenges to the survival of plants. Plant endophytes play important roles in improving plant adaptability. However, our knowledge of the effects of climate change on endophytic community structures is limited. Relying on a field experimental platform simulating climate warming, precipitation increases, and their combination in an alpine grassland, the root endophytic bacterial community structures and assembly processes of three coexisting plant species (Elymus nutans, Kobresia humilis, and Melissilus ruthenicus) were measured. The results indicated that Proteobacteria was the dominant phylum, with a relative abundance ranging from 50% to 80%, followed by Actinobacteria and Bacteroidetes. Bacterial diversity decreased significantly under the combined treatment for all three plant species, with the largest reduction observed in E. nutans. The climate manipulation treatments had a minimal effect on the endophytic bacterial community structures. The relative abundance of Burkholderiaceae increased significantly under the combined treatment for the three plant species. Moreover, the endophytic community assembly processes changed from stochastic dominated under control plots to deterministic dominated under the combined plots for E. nutans, while this shift was reversed for M. ruthenicus. The root endophytic bacterial community was affected by the soil’s available nitrogen and stoichiometric ratio. These results revealed that the sensitivity of endophyte community structures to climate change varies with host plant species, which has implications for plant fitness differences. Full article

Glomalin-related soil protein (GRSP) is an important component of soil organic carbon (SOC), which can promote long-term SOC sequestration. However, GRSP distribution characteristics and its contribution to the SOC pool among different grassland types remain poorly understood. Therefore, six grassland types (alpine meadow, mountain meadow, temperate meadow steppe, temperate steppe, temperate desert steppe, and temperate desert) were chosen to evaluate the contribution of GRSP to the SOC pool and the factors that influence GRSP accumulation in the Irtysh River Basin in China. The results revealed that GRSP (EE-GRSP, T-GRSP) accumulated more in the 0–10 cm soil layer than in the 10–20 cm soil layer (p < 0.05). GRSP content was higher in alpine grasslands (15.69 mg·g⁻¹) than in desert grasslands (5.45 mg·g⁻¹). However, their contribution to the SOC pool exhibited an opposite trend, whereas GRSP-C/SOC even accounted for 11.88% in the desert grasslands. The redundancy analysis (RDA) showed that SOC was the top important positive regulator for GRSP accumulation both in the two layers (explanatory rate > 80%). Besides the SOC factor, the two soil layers had different factors in regulating GRSP accumulation. Changes in GRSP content in the 0–10 cm soil layer were more strongly associated with mean annual temperature (MAT), sand content, soil water content (SWC), and silt content. In contrast, in the 10–20 cm soil layer, GRSP content was more influenced by SWC, electrical conductivity (EC), and pH (p < 0.05). Additionally, the main factor in the GRSP content variation was the interaction between climate and soil in the two soil layers (explanatory rate > 80%). Our findings underscore the critical role of GRSP in facilitating SOC sequestration within desert grasslands and elucidate the primary factors driving GRSP distribution across varying soil depths. Full article

The gut microbiota is a diverse and complex population, and it has a key role in the host’s health and adaptability to the environment. The present study investigated the fecal bacterial community of wild grazing (WG) and domestic grazing (DG) yaks on natural grazing pastures, analyzing the gut microbiota using 16S rRNA sequencing to assess bacterial diversity. A total of 48 yak fecal samples were selected from two different grazing habitats. The DG group had more crude proteins and non-fiber carbohydrates. The WG group had more OM, insoluble dietary fiber such as NDF, ADF, ether extract, and TC. There were 165 and 142 unique operational taxonomic units (OTUs) in the WG and DG groups, respectively. Shannon index analysis revealed a higher bacterial diversity in the WG group than in the DG group. At the phylum level, Firmicutes were the dominant bacterial taxa in both groups. The relative abundance of Firmicutes in the WG group was higher than in the DG group. At the family level, the WG group had a significantly higher abundance of Ruminococcaceae (p < 0.001) and Rikenellaceae (p < 0.001) than the DG group. The abundances of Alloprevotella and Succinivibrio were more pronounced in the DG group than in the WG group at the genus level. This study presents a novel understanding of the bacterial communities of ruminants and their potential applications for livestock production. Full article

The Tarim River Basin is one of the most ecologically fragile regions around the world in the arid areas of Northwest China. The study of natural vegetation ecological water requirement (EWR) is the basis for the promotion of regional ecological conservation and sustainable development of ecosystems when extreme environmental events occur frequently, which is of great significance for the formulation of scientific and rational ecological conservation strategies. In the study, we improved the vegetation EWR calculation method by introducing a dynamic soil moisture limitation coefficient (K_S) and a dynamic vegetation coefficient (K_C) that is coupled with a resistance correction factor (F_r) based on the Penman-Monteith method and analyzed its spatio-temporal variation characteristics. Additionally, this study utilized the latitude of ecosystem resilience (LER) to clarify the thresholds for vegetation EWR throughout the growing season in the study area and to analyze the water surplus and deficit (WSD) at different threshold levels. The results of the study show that: (1) Over the past 21 years, the EWR for vegetation has shown a downward trend, with the change in EWR for arbor-shrub forests being more significant than that for grasslands. The average EWR for arbor-shrub forests and grasslands is 36.76 × 10⁸ m³ and 459.59 × 10⁸ m³, respectively. (2) The minimum ecological water requirement (EWR_min) and optimal ecological water requirement (EWR_opt) for natural vegetation were 360.45 × 10⁸ m³ and 550.10 × 10⁸ m³, respectively. (3) In EWR_min conditions, the alpine plateau area as a whole showed a water surplus, and the plains area as a whole was in a state of water scarcity, but the precipitation in the study area as a whole could meet the basic survival needs of the vegetation. (4) In EWR_opt conditions, the plains and local alpine plateau areas are in a state of water scarcity, the area of water scarcity is gradually increasing, and the regional precipitation is unable to fully realize the objectives of ecological conservation and vegetation restoration. Full article

Bedrock geology is crucial in structuring alpine plant communities. Old studies mainly focused on the compositional differences between alpine plant communities on carbonate rocks and crystalline rocks, i.e., calcareous vs. siliceous vegetation. Increasing attention is being paid to bedrock types other than calcareous or siliceous ones, viz. those which have intermediate geochemical characteristics between pure calcareous and pure siliceous ones. Among these types of ‘intermediate’ bedrocks, calc-schists and serpentines are generally characterized by vegetation comprised of a mixture of basiphilous and acidophilous species. We selected several sites in alpine grasslands in the Western Italian Alps, on calc-schist and serpentine bedrocks, located at 2500 ± 100 m above sea level. X-ray fluorescence quantification of major and trace elements, combined with stereomicroscopic examination of bedrock samples with a petrographic approach, revealed a much broader range of bedrock types than recognized by inspection of geological maps. The vegetation investigated in our study was mostly composed of a set of species found more or less frequently in alpine silicicolous or calcicolous plant communities of the Alps and other European mountains. The carbonate content in the bedrock was one of the main drivers of variation in grassland vegetation, not necessarily related to soil pH. There were no distinctive species uniquely characterizing grassland vegetation on serpentines or calc-schists. Full article

Understanding the roles of core bacterial taxa in forage production is crucial for developing sustainable fertilization practices that enhance the soil bacteria and forage yield. This study aims to investigate the impact of different fertilization regimes on soil bacterial community structure and function, with a particular focus on the role of core bacterial taxa in contributing to soil nutrient content and enhancing forage yield. Field experiments and high-throughput sequencing techniques were used to analyze the soil bacterial community structure and function under various fertilization regimes, including six treatments, control with no amendment (CK), double the standard rate of organic manure (T01), the standard rate of organic manure with nitrogen input equal to T04 (T02), half the standard rate of inorganic fertilizer plus half the standard rate of organic manure (T03), the standard rate of inorganic fertilizer reflecting local practice (T04), and double the standard rate of inorganic fertilizer (T05). The results demonstrated that organic manure treatments, particularly T01, significantly increased the forage yield and the diversity of core bacterial taxa. Core taxa from the Actinomycetota, Alphaproteobacteria, and Gammaproteobacteria classes were crucial in enhancing the soil nutrient content, directly correlating with forage yield. Fertilization significantly influenced functions relating to carbon and nitrogen cycling, with core taxa playing central roles. The diversity of core microbiota and soil nutrient levels were key determinants of forage yield variations across treatments. These findings underscore the critical role of core bacterial taxa in agroecosystem productivity and advocate for their consideration in fertilization strategies to optimize forage yield, supporting the shift towards sustainable agricultural practices. Full article

Drought has broad and deep influences on ecosystem dynamics and functions, particularly considering the lagged and cumulative effects of drought. Yet the individual role of climate variables in mediating such drought effects on vegetation remains largely unknown. Based on the Normalized Difference Vegetation Index (NDVI) and the standard precipitation evapotranspiration index (SPEI), here, we investigated the patterns and mechanisms of drought effects on alpine grasslands in the Qinghai–Tibetan Plateau (QTP) from 1982 to 2015. Drought imposed widespread lagged and cumulative impacts on alpine grasslands with notable spatial heterogeneity, showing that the southwestern and northeastern parts of the plateau were more sensitive and responded quickly to drought. Further, drought effects showed an evident elevation dependence across different grassland types, which could be explained by altitudinal shifts in climatic factors, including temperature and precipitation. Precipitation was the dominant factor in drought effects on alpine meadows, while temperature dominated the drought impacts on the alpine steppes. Such a divergent dominant factor implied that there would be different vegetation responses to future climate change among diverse types of alpine grasslands. To maintain the sustainability of alpine grassland, more effort should be applied to alpine steppes regarding pasture management, particularly in response to extreme drought due to warmer climates in the future. Full article

The construction of mountain tunnels can lead to groundwater loss and severely impact plant growth. In order to study the limited discharge of groundwater in mountain tunnels for the normal growth of typical herbaceous plants, a tunnel in the alpine meadow area of Qinghai Province was taken as the research objective. Based on transplant experiments, numerical simulations, and the empirical calculation of tunnel discharge limits, the minimum water level required for the normal growth of herbaceous plants, groundwater changes, and grouting parameters during tunnel construction, as well as limited discharge values of groundwater based on the normal growth requirements of plants, were studied. The results indicate that when the groundwater level declined by 0.6–0.8 m, herbaceous plants were able to normally grow. Generally, tunnel excavation lowered the groundwater level so that the normal growth of herbaceous plants was significantly affected. The reasonable grouting parameters were obtained by numerical simulation. They were able to ensure that the groundwater level decline was less than 0.8 m and ultimately recovered to over 90% of the pre-construction level. The herbaceous plants in Qinghai’s alpine grasslands were able to normally grow when the groundwater discharge limit was 0.2~4.0 m³/(m·d). This research offers guidance and support for managing groundwater discharge during tunnel construction in ecologically fragile areas, such as the Three Rivers Source in Qinghai. Full article

The accurate identification of different restoration stages of degraded alpine meadow patches is essential to effectively curb the deterioration trend of ‘Heitutan’ (areas of severely degraded alpine meadows in western China). In this study, hyperspectral imaging (HSI) and machine learning techniques were used to develop a method for accurately distinguishing the different restoration stages of alpine meadow patches. First, hyperspectral images representing the four restoration stages of degraded alpine meadow patches were collected, and spectral reflectance, vegetation indexes (VIs), color features (CFs), and texture features (TFs) were extracted. Secondly, valid features were selected by competitive adaptive reweighted sampling (CARS), ReliefF, recursive feature elimination (RFE), and F-test algorithms. Finally, four machine learning models, including the support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and extreme gradient boosting (XGBoost), were constructed. The results demonstrated that the SVM model based on the optimal wavelengths (OWs) and prominent VIs achieved the best value of accuracy (0.9320), precision (0.9369), recall (0.9308), and F1 score (0.9299). In addition, the models that combine multiple sets of preferred features showed a significant performance improvement over the models that relied only on a single set of preferred features. Overall, the method combined with HSI and machine learning technology showed excellent reliability and effectiveness in identifying the restoration stages of meadow patches, and provided an effective reference for the formulation of grassland degradation management measures. Full article

As a plant kingdom and a biodiversity hotspot, Yunnan is a key region for our understanding of modern and past global changes in biodiversity and environment. As proxies of vegetation and climate, phytoliths have become increasingly important in ecological and paleoecological studies. In this study, phytolith analysis was carried out on samples of surface sediments from 70 lakes in western Yunnan, southwest China. These lakes are surrounded by modern vegetation types including broadleaved and coniferous forests, scrubs, grasslands, meadows, and alpine vegetation. The results of this study show that modern lacustrine phytoliths in western Yunnan are dominated by herbaceous phytoliths, among which Poaceae types are the most abundant. The 70 phytolith samples used can be divided into 4 groups, reflecting the major vegetation types from which samples were collected. The principal component analysis (PCA) and redundancy analysis (RDA) of the phytolith and climatic data of the 70 lacustrine phytolith samples showed that temperature and precipitation are the climatic parameters controlling the spatial distribution of phytolith assemblages in western Yunnan. Phytolith–MAT (mean annual temperature) and phytolith–MAP (mean annual precipitation) transfer functions were developed using weighted averaging partial least squares (WA-PLS), and both the MAT and MAP functions showed good performances (MAT: R² = 0.67, RMSEP = 0.96 °C, MAP: R² = 0.64, RMSEP = 140.4 mm). Our results also reveal that phytolith analysis is a useful technique offering reliable vegetation interpretation and climate reconstruction; thus, this study provides a basis for the vegetational and climatic interpretation of fossil lacustrine phytolith records in western Yunnan. Full article

Climate change is causing permafrost in the Qinghai–Tibet Plateau to degrade, triggering thermokarst hazards and impacting the environment. Despite their ecological importance, the distribution and risks of thermokarst lakes are not well understood due to complex influencing factors. In this study, we introduced a new interpretable ensemble learning method designed to improve the global and local interpretation of susceptibility assessments for thermokarst lakes. Our primary aim was to offer scientific support for precisely evaluating areas prone to thermokarst lake formation. In the thermokarst lake susceptibility assessment, we identified ten conditioning factors related to the formation and distribution of thermokarst lakes. In this highly accurate stacking model, the primary learning units were the random forest (RF), extremely randomized trees (EXTs), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost) algorithms. Meanwhile, gradient boosted decision trees (GBDTs) were employed as the secondary learning unit. Based on the stacking model, we assessed thermokarst lake susceptibility and validated accuracy through six evaluation indices. We examined the interpretability of the stacking model using three interpretation methods: accumulated local effects (ALE), local interpretable model-agnostic explanations (LIME), and Shapley additive explanations (SHAP). The results showed that the ensemble learning stacking model demonstrated superior performance and the highest prediction accuracy. Approximately 91.20% of the total thermokarst hazard points fell within the high and very high susceptible areas, encompassing 20.08% of the permafrost expanse in the QTP. The conclusive findings revealed that slope, elevation, the topographic wetness index (TWI), and precipitation were the primary factors influencing the assessment of thermokarst lake susceptibility. This comprehensive analysis extends to the broader impacts of thermokarst hazards, with the identified high and very high susceptibility zones affecting significant stretches of railway and highway infrastructure, substantial soil organic carbon reserves, and vast alpine grasslands. This interpretable ensemble learning model, which exhibits high accuracy, offers substantial practical significance for project route selection, construction, and operation in the QTP. Full article

The carbon density of subalpine-alpine grasslands (SGs) is significantly vital to sustaining the carbon cycle in global terrestrial ecosystems. However, on the Loess Plateau of China, it remains unclear how the geographical environment and plant functional groups affect the spatial variation pattern of plant carbon density in these grasslands. Here, nine typical SGs distributed in the eastern Loess Plateau with elevations ranging from 1720 to 3045 m were investigated. The biomass indices from grassland plants of different functional groups were investigated using plot surveys. The Kriging interpolation method was used to explore the spatial variation pattern of plant carbon density along geographical gradients. We found that (1) the total plant carbon density of SGs was 2676.825 g C/m² on the eastern plateau, with 37.07%, 37.50%, and 25.43% contributed by the northern, central, and southern areas, respectively. Above- (666.338 g C/m²) and belowground (2010.488 g C/m²) carbon density accounted for 24.9% and 75.11% of the total, respectively. (2) At the horizontal scale, the plant carbon density in the northern SGs was high in the northwest and low in the southeast; in the central SGs, it was low in the northwest and high in the southeast; and in the southern SGs, it was high in the southwest and low in the northeast. At the vertical scale, plant carbon density in all SGs decreased with increasing altitude. (3) The carbon density of grasses, forbs, and sedges was 247.419 g C/m², 26.073 g C/m², and 23.471 g C/m², respectively. With increased latitude, the carbon density of all functional groups (grasses, forbs, and sedges) decreased; the carbon density of forbs and grasses increased with increased longitude, while that of sedges decreased; and with increased altitude, the carbon density of all functional groups increased. In conclusion, the spatial variation pattern of plant carbon density in the SGs was not only influenced by the geographical environment but also by the plant functional groups at the horizontal and vertical scales on the eastern Loess Plateau of China. Full article

The grasslands in high-latitude areas are sensitive to climate warming and drought. However, the drought stress effect on the long-term variability of grassland productivity at the continental scale still hinders our understanding. Based on aboveground net primary production (ANPP) surveys, satellite remote sensing Normalized Difference Vegetation Index (NDVI), and meteorological data, we comprehensively analyzed three Aridity metrics and their effect on ANPP in Eurasian grassland from 1982 to 2020. Our results showed that the ANPP had an overall uptrend from 1982 to 2020, increasing most in the Tibetan Plateau alpine steppe subregion (TPSSR). Among three Aridity indicators, vapor pressure deficit (VPD) had an overall uptrend, while the trend of Aridity and soil moisture (SM) was insignificant from 1982 to 2020. Soil drought had negative effects on ANPP for all Eurasian grassland, while the atmospheric VPD had a positive effect on ANPP for TPSSR and the Mongolian Plateau steppe subregion (MPSSR), but a negative effect for the Black Sea–Kazakhstan steppe subregion (BKSSR) which was the driest subregion. SM had been the predominant driving factor for the interannual variability of ANPP in MPSSR since 1997. The increasing VPD had facilitated grassland productivity in alpine grasslands due to its cascading effect with an increasing temperature after 2000. The cascading effects networks of climate factors—drought factors (VPD, Aridity, and SM)—ANPP (CDA–CENet) indicated that SM was the predominant driving factor of the interannual variability of ANPP in MPSSR and BKSSR, and the dominance of SM had enhanced after the year 1997. The inhibitory effect of VPD on ANPP transformed into a facilitating effect after 1997, and the facilitating effect of SM is weakening in TPSSR. Full article

Changes to land use carbon emissions (LUCEs) have become significant contributors to increasingly severe climate issues. Land use change is one of the crucial factors that affect carbon emissions. Alpine meadows regions are sensitive to climate change and human activities. However, current research on LUCEs mainly focuses on analyzing present land use status and spatial patterns. To reveal and forecast future LUCEs in the alpine region, the Upper Yellow River of Gannan (UYRG) was used as a case study. Based on the land use data from 1990 to 2020, we used the multi-scenario PLUS model to predict the land use types in 2030 and analyzed the spatial and temporal dynamic trends of LUCEs from 1990 to 2030. The results showed a strong correlation between the predicted and actual land use types, with a Kappa value of 0.93, indicating the applicability of the PLUS model in predicting land use in the UYRG. Over the study period, construction land expanded, while woodland and grassland diminished. Carbon emissions (CEs) increased by 516.4% from −200,541.43 Mg CO₂e in 1990 to 835,054.08 Mg CO₂e in 2020, with construction land being the main contributor. In the Natural Development scenario for 2030, construction land expanded most rapidly, resulting in the highest LUCEs. In the Ecological Protection scenario, woodland and grassland expanded, while construction land decreased, leading to an expansion in carbon sinks. In the Cropland Protection scenario, cropland expanded, with CEs falling between the other two scenarios. These findings lay a theoretical groundwork for formulating policies addressing LUCEs in alpine meadows, providing valuable insights for further studies. Full article