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Global potent greenhouse gas nitrous oxide (N2O) emissions from soil are accelerating, with increases in the proportion of reactive nitrogen emitted as N2O, i.e., N2O emission factor (EF). Yet, the primary controls and underlying mechanisms of EFs remain unresolved. Based on two independent but complementary global syntheses, and three field studies determining effects of acidity on N2O EFs and soil denitrifying microorganisms, we show that soil pH predominantly controls N2O EFs and emissions by affecting the denitrifier community composition. Analysis of 5438 paired data points of N2O emission fluxes revealed a hump-shaped relationship between soil pH and EFs, with the highest EFs occurring in moderately acidic soils that favored N2O-producing over N2O-consuming microorganisms, and induced high N2O emissions. Our results illustrate that soil pH has a unimodal relationship with soil denitrifiers and EFs, and the net N2O emission depends on both the N2O/(N2O + N2) ratio and overall denitrification rate. These findings can inform strategies to predict and mitigate soil N2O emissions under future nitrogen input scenarios.

Global spatial patterns of vascular plant diversity have been mapped at coarse grain based on climate‐dominated environment–diversity relationships and, where possible, at finer grain using remote sensing. However, for grasslands with their small plant sizes, the limited availability of vegetation plot data has caused large uncertainties in fine‐grained mapping of species diversity. Here we used vegetation survey data from 1,609 field sites (>4,000 plots of 1 m2), remotely sensed data (ecosystem productivity and phenology, habitat heterogeneity, functional traits and spectral diversity), and abiotic data (water‐ and energy‐related, characterizing climate‐dominated environment) together with machine learning and spatial autoregressive models to predict and map grassland species richness per 100 m2 across the Mongolian Plateau at 500 m resolution. Combining all variables yielded a predictive accuracy of 69% compared with 64% using remotely sensed variables or 65% using abiotic variables alone. Among remotely sensed variables, functional traits showed the highest predictive power (55%) in species richness estimation, followed by productivity and phenology (48%), spectral diversity (48%) and habitat heterogeneity (48%). When considering spatial autocorrelation, remotely sensed variables explained 52% and abiotic variables explained 41%. Moreover, Remotely sensed variables provided better prediction at smaller grain size (<∼1,000 km), while water‐ and energy‐dominated macro‐environment variables were the most important drivers and dominated the effects of remotely sensed variables on diversity patterns at macro‐scale (>∼1,000 km). These findings indicate that while remotely sensed vegetation characteristics and climate‐dominated macro‐environment provide similar predictions for mapping grassland plant species richness, they offer complementary explanations across broad spatial scales. Plain Language Summary: Mapping spatial patterns of plant distributions and diversity is critical for biogeography and macroecology. In this study, we map grassland plant species richness across the Mongolian Plateau using data from over 1,600 sample sites and remote sensing and investigate the synergistic relationship of multiple diversity‐related hypotheses and underlying drivers in model predictions. We show that remotely sensed vegetation characteristics are good predictors of fine‐grained and water‐ and energy‐related variables of coarse‐grained diversity patterns. This work demonstrates how newly available high‐resolution satellite data can improve the prediction and explanation of large‐scale plant diversity in grassland. These findings hold particular significance for advancing the development and application of essential biodiversity variables (EBVs) in large‐scale plant diversity assessments in the face of rapidly changing environments. Key Points: Multiple diversity‐related hypotheses and underlying drivers are examined in the context of predicting grassland plant diversityVegetation variables obtained through remote sensing help explain how macro‐environments affect grassland plant diversityRemotely sensed vegetation variables offer more accurate diversity predictions at smaller spatial scales (less than 1000 km) [ABSTRACT FROM AUTHOR]

Livestock grazing has been shown to alter the structure and functions of grassland ecosystems. It is well acknowledged that grazing pressure is one of the strongest drivers of ecosystem-level effects of grazing, but few studies have assessed how grazing pressure impacts grassland biodiversity and ecosystem multifunctionality (EMF). Here, we assessed how different metrics of biodiversity (i.e., plants and soil microbes) and EMF responded to seven different grazing treatments based on an 11-year field experiment in semi-arid Inner Mongolian steppe. We found that soil organic carbon, plant-available nitrogen and plant functional diversity all decreased even at low grazing pressure, while above-ground primary production and bacterial abundance decreased only at high levels of grazing pressure. Structural equation models revealed that EMF was driven by direct effects of grazing, rather than the effects of grazing on plant or microbial community composition. Grazing effects on plant functional diversity and soil microbial abundance did have moderate effects on EMF, while plant richness did not. Synthesis. Our results showed ecosystem functions differ in their sensitivity to grazing pressure, requiring a low grazing threshold to achieve multiple goals in the Eurasian steppe. A plain language summary is available for this article.

Grazing and topography have drastic effects on plant communities and soil properties. These effects are thought to influence arbuscular mycorrhizal (AM) fungi. However, the simultaneous impacts of grazing pressure (sheep ha-1) and topography on plant and soil factors and their relationship to the production of extra-radical AM hyphae are not well understood. Our 10-year study assessed relationships between grazing, plant species richness, aboveground plant productivity, soil nutrients, edaphic properties, and AM hyphal length density (HLD) in different topographic areas (flat or sloped). We found HLD linearly declined with increasing grazing pressure (1.5-9.0 sheep ha-1) in sloped areas, but HLD was greatest at moderate grazing pressure (4.5 sheep ha-1) in flat areas. Structural equation modeling indicates grazing reduces HLD by altering soil nutrient dynamics in sloped areas, but non-linearly influences HLD through plant community and edaphic changes in flat areas. Our findings highlight how topography influences key plant and soil factors, thus regulating the effects of grazing pressure on extra-radical hyphal production of AM fungi in grasslands. Understanding how grazing and topography influence AM fungi in semi-arid grasslands is vital, as globally, severe human population pressure and increasing demand for food aggravate the grazing intensity in grasslands.

The intricate mechanisms controlling plant diversity and community composition are cornerstone of ecological understanding. Yet, the role of mycorrhizal symbiosis in influencing community composition has often been underestimated. Here, we use extensive species survey data from 1315 grassland sites in China to elucidate the influence of mycorrhizal symbiosis on plant phylogenetic diversity and community assembly. We show that increasing mycorrhizal symbiotic potential leads to greater phylogenetic dispersion within plant communities. Mycorrhizal species predominantly influence deterministic processes, suggesting a role in niche‐based community assembly. Conversely, non‐mycorrhizal species exert a stronger influence on stochastic processes, highlighting the importance of random events in shaping community structure. These results underscore the crucial but often hidden role of mycorrhizal symbiosis in driving plant community diversity and assembly. This study provides valuable insights into the mechanisms shaping ecological communities and the way for more informed conservation that acknowledges the complex interplay between symbiosis and community dynamics. [ABSTRACT FROM AUTHOR]

The role of plant biodiversity in stabilizing ecosystem multifunctionality has been extensively studied; however, the impact of soil biota biodiversity on ecosystem multifunctional stability, particularly under multiple environmental changes, remains unexplored. By conducting an experiment with environmental changes (adding water and nitrogen to a long‐term grazing experiment) and an experiment without environmental changes (an undisturbed site) in semi‐arid grasslands, our research revealed that environmental changes‐induced changes in temporal stability of both above‐ and belowground multifunctionality were mainly impacted by plant and soil biota asynchrony, rather than by species diversity. Furthermore, changes in temporal stability of above‐ and belowground multifunctionality, under both experiments with and without environmental changes, were mainly associated with plant and soil biota asynchrony, respectively, suggesting that the temporal asynchrony of plant and soil biota has independent and non‐substitutable effects on multifunctional stability. Our findings emphasize the importance of considering both above‐ and belowground biodiversity or functions when evaluating the stabilizing effects of biodiversity on ecosystem functions. [ABSTRACT FROM AUTHOR]