Cropland phosphorus (P) is essential for global food security, yet its management remains challenging owing to low phosphorus use efficiency (PUE), leading to resource depletion and nutrient loss from agricultural fields. Although a range of management practices can improve PUE, their effectiveness varies across environmental and socioeconomic contexts, and the absence of a predictive framework has hindered global assessments of their potential. Here we develop a machine learning model to map global PUE geospatial variations for maize, rice and wheat and quantify potential gains under a feasibility-constrained scenario. Our results reveal global average PUEs of 25.1% for maize, 25.0% for rice and 24.2% for wheat. Under three-layer feasibility constraints, management interventions could yield absolute PUE gains of 5.2-6.0%, with adoption barriers as the dominant limiting factor. Changes in cropping system and fertilizer type are the two largest management contributors across all three crops. Our spatially explicit framework evaluates the feasible PUE improvement potential, providing a foundation for regionally differentiated phosphorus management that supports sustainable intensification and food security.

Climate warming-induced disruptions to soil microbial communities have been shown to affect the stability of soil carbon pools within terrestrial ecosystems, yet how these shifts regulate changes in soil organic carbon (SOC) and microbial assembly remains poorly understood. Here, we collected paddy soil samples during the drained fallow phase from thirteen regions across China, and incubated them under five temperature regimens, to investigate how temperature shapes the assembly of bacterial generalists and specialists and its consequences for SOC changes. Our findings revealed a contrasting response to different thermal regimens between generalists and specialists in paddy soils. Generalists showed reduced diversity at higher static incubation temperatures, whereas specialists displayed the opposite trend. Simultaneously, a temperature-dependent divergence in assembly mechanisms between bacterial specialists and generalists, with 15 °C representing the point of maximum deterministic selection for specialists but maximum stochastic processes for generalists. Habitat generalists demonstrated greater network robustness than specialists, while functional capacities related to carbon metabolism were enhanced for both groups under different incubation temperatures. Among the bacterial properties examined, network interactions and diversity of specialists were the strongest biotic predictors of short-term SOC changes, while soil type and nutrients remained the dominant overall drivers. This study provides a mechanistic underpinning for the process of bacterial community assembly in soil carbon metabolism.

Understanding the apparent temperature dependence of wetland methane emissions (EM) is critical for predicting climate-carbon feedbacks, yet current estimates remain constrained by observational limitations and methodological inconsistencies. The inherent biogeographic heterogeneity of wetland ecosystems combined with sparse, unevenly distributed flux measurements introduces substantial uncertainty in characterizing spatial patterns of EM. This knowledge gap impedes accurate projections of wetland methane contributions under climate warming scenarios. Here, we develop a framework that integrates mixed-effects models with artificial intelligence techniques to resolve scale-dependent patterns in methane emission thermodynamics across global wetlands. Our unified framework demonstrates that only 73.6% (5th-95th quantiles: 71.8%-75.4%) of the global wetland area conforms to classical Arrhenius-type temperature dependence. This framework can predict 69.5% (67.9%-71.1%) of the global wetlands with high confidence using the Mahalanobis distance and area of applicability tests. We quantify the weighted mean EM across high-confidence predictable areas of 0.694 eV, with latitudinal differentiation: tropical (0.634 eV), temperate (0.678 eV), and boreal (0.745 eV) wetlands exhibit progressively stronger temperature responses. Ignoring these biogeographic variations could result in underestimation of projected end-century methane emissions by 4.2%-13.3% across selected socioeconomic pathway scenarios. Our study refined the temperature sensitivity parameter in coupled climate-carbon cycle models, thereby enhancing predictive accuracy of future global warming trends and informing strategic responses to climate change mitigation.

Farmland soils are currently experiencing severe degradation, with a significant decline in soil organic carbon (SOC) content. Nitrogen-fixing cyanobacteria, known for their efficient green manure properties, have considerable potential to improve soil quality. However, the underlying mechanisms driving their effects remain unclear. In this study, we utilized a nitrogen-fixing cyanobacterial strain (Anabaena azotica SJ-1), isolated from local Mollisol soil, to assess its impact on rice plant growth and to elucidate the associated mechanisms. The results indicated that Anabaena azotica SJ-1 significantly enhanced rice plant growth, particularly in low-yielding soils (dry weight of rice spikes increased by 38-74 % in high-yielding soils and 107-157 % in low-yielding soils). Soil pH, available nitrogen content, and activities of soil acid phosphatase and N-acetyl-beta-glucosaminidase were all increased with the application of Anabaena azotica SJ-1. Additionally, SOC content increased, characterized by an increase in alkyl C and a decrease in amid/carbonyl C. Moreover, the metabolic activity of live microbes in the soil was enhanced. Genome sequencing revealed that Anabaena azotica SJ-1 has a genome consisting of 6,115,153 bp nucleotides, eight plasmids, and 5367 protein-coding genes. Carbohydrate metabolism was identified as the primary metabolic pathway, while energy metabolism relied primarily on oxidative phosphorylation. This study underscores the significant potential of nitrogen-fixing cyanobacteria to improve the quality and efficiency of degraded Mollisol soils.

Viral diversity is essential for regulating the stability of ecosystem function by modulating the biochemical cycles via alterations in the survival and metabolic processes of host organisms. However, how viral survival strategies impact ecosystem function remains unresolved. Here, we analyzed 1824 metagenomes from soils across eight biomes, revealing that lytic viruses constituted a dominant proportion (88%) of the viral communities, with Siphoviridae (35.34%) being the most abundant lytic viral group. Viral communities significantly impacted soil organic carbon dynamics, while ecosystem multifunctionality was notably influenced by microbial necromass carbon, microbial biomass carbon, and various environmental factors. Microbial carbon use efficiency was the primary driver of ecosystem multifunctionality, with significant modulation by lytic and lysogenic viral communities, and lytic viruses contributed more directly to ecosystem multifunctionality (3%) compared to lysogenic viruses (1%). Our study underscores the pivotal role of viral communities, particularly lytic viruses, in shaping global carbon dynamics and ecosystem function, thereby providing a novel framework for future carbon management.

Soil microbes are essential for regulating carbon stocks under climate change. However, the uncertainty surrounding how microbial temperature responses control carbon losses under warming conditions highlights a significant gap in our climate change models. To address this issue, we conducted a fine-scale analysis of soil organic carbon composition under different temperature gradients and characterized the corresponding microbial growth and physiology across various paddy soils spanning 4000 km in China. Our results showed that warming altered the composition of organic matter, resulting in a reduction in carbohydrates of approximately 0.026% to 0.030% from humid subtropical regions to humid continental regions. These changes were attributed to a decrease in the proportion of cold-preferring bacteria, leading to significant soil carbon losses. Our findings suggest that intrinsic microbial temperature sensitivity plays a crucial role in determining the rate of soil organic carbon decomposition, providing insights into the temperature limitations faced by microbial activities and their impact on soil carbon-climate feedback.

Soil organic carbon (SOC) represents the largest terrestrial pool of organic carbon and is indispensable for mitigating climate change and sustaining soil fertility. As a major component of stable SOC, microbial-derived carbon (MDC) accounts for approximately half of the total SOC and has repercussions on climate feedback. However, our understanding of the spatial and temporal dynamics of MDC stocks is limited, hindering assessments of the long-term impacts of global warming on persistent SOC sequestration in the soil-atmosphere carbon cycle. Here, we compiled an extensive global dataset and employed ensemble machine learning techniques to forecast the spatial-temporal dynamics of MDC stocks across 93.4% of the total global land area from 1981 to 2018. Our findings revealed that for every 1 degrees C increase in temperature, there was a global decrease of 6.7 Pg in the soil MDC stock within the predictable areas, equivalent to 1.4% of the total MDC stock or 0.9% of the atmospheric C pool. Tropical regions experienced the most substantial declines in MDC stocks. We further projected future MDC stocks for the next century based on shared socioeconomic pathways, showing a global decline in MDC stocks with a potential 6-37 Pg reduction by 2100 depending on future pathways. We recommend integrating the response of MDC stocks to warming into socioeconomic models to enhance confidence in selecting sustainable pathways.

Soil acidification due to climate and anthropogenic changes persistently threatens biodiversity and biomass, the essential drivers of ecosystem multifunctionality. However, the influence of a sustained reduction in soil pH on the regulatory role of microbial communities in ecosystem multifunctionality has not yet been assessed. Here, we investigated the critical pH thresholds at which microbial biomass becomes a key determinant of soil multi- functionality (SMF) based on a large-scale paddy field study (n n = 429) and a global dataset (n n = 35,641). We found that when the soil pH was <5, microbial biomass (i.e., bacterial or fungal) was significantly positively correlated with the soil SMF, representing a critical threshold for microbial biomass regulation of ecosystem multifunctionality. We further predicted the global pattern of the microbial drivers of SMF under soil acidification scenarios over the next 50 years. Our results indicate that as soil acidification continues, the global area of biomass-mediated SMF will increase by approximately 14 % by 2070. Our results highlight that due to ongoing acidification, biomass reduction will cause accelerated losses in global SMF.

Compelling evidence has shown that wetland methane emissions are more temperature dependent than carbon dioxide emissions across diverse hydrologic conditions. However, the availability of carbon substrates, which ultimately determines microbial carbon metabolism, has not been adequately accounted for. By combining a global database and a continental-scale experimental study, we showed that differences in the temperature dependence of global wetland methane and carbon dioxide emissions ( E M/C ) were dependent on soil carbon-to-nitrogen stoichiometry. This can be explained mainly by the positive relationship between soil organic matter decomposability and E M/C . Our study indicates that only 23% of global wetlands will decrease methane relative to carbon dioxide emissions under future warming scenarios when soil organic matter decomposability is considered. Our findings highlight the importance of incorporating soil organic matter biodegradability into model predictions of wetland carbon–climate feedback.

Global warming poses an unprecedented threat to agroecosystems. Although temperature increases are more pronounced during winter than in other seasons, the impact of winter warming on crop biomass carbon has not been elucidated. Here we integrate global observational data with a decade-long field experiment to uncover a significant negative correlation between winter soil temperature and crop biomass carbon. For every degree Celsius increase in winter soil temperature, straw and grain biomass carbon decreased by 6.6 ( ± 1.7) g kg-1 and 10.2 ( ± 2.3) g kg-1, respectively. This decline is primarily attributed to the loss of soil organic matter and micronutrients induced by warming. Ignoring the adverse effects of winter warming on crop biomass carbon could result in an overestimation of total food production by 4% to 19% under future warming scenarios. Our research highlights the critical need to incorporate winter warming into agricultural productivity models for more effective climate adaptation strategies.

Arbuscular mycorrhizal fungi (AMF), playing critical roles in carbon cycling, are vulnerable to climate change. However, the responses of AM fungal abundance to climate change are unclear. A global-scale meta-analysis was conducted to investigate the response patterns of AM fungal abundance to warming, elevated CO2 concentration (eCO(2)), and N addition. Both warming and eCO(2) significantly stimulated AM fungal abundance by 18.6% (95%CI: 5.9%-32.8%) and 21.4% (15.1%-28.1%) on a global scale, respectively. However, the response ratios (RR) of AM fungal abundance decreased with the degree of warming while increased with the degree of eCO(2). Furthermore, in warming experiments, as long as the warming exceeded 4 degrees C, its effects on AM fungal abundance changed from positive to negative regardless of the experimental durations, methods, periods, and ecosystem types. The effects of N addition on AM fungal abundance are -5.4% (-10.6%-0.2%), and related to the nitrogen fertilizer input rate and ecosystem type. The RR of AM fungal abundance is negative in grasslands and farmlands when the degree of N addition exceeds 33.85 and 67.64 kg N ha(-1) yr(-1), respectively; however, N addition decreases AM fungal abundance in forests only when the degree of N addition exceeds 871.31 kg N ha(-1) yr(-1). The above results provide an insight into predicting ecological functions of AM fungal abundance under global changes. (C) 2021 Elsevier B.V. All rights reserved.

森林土壤碳库对全球变暖的响应是气候变暖下预测CO2不确定性的潜在主要来源.然而,不同植被带上各粒径团聚体的SOC矿化的温度敏感性(Q10)及机理尚不明确.收集了中国太白山4个不同海拔的植被带的土壤,将土壤按粒径大小筛分为大、中、小3类团聚体,并进行了100天的土壤培养实验,以监测在3个恒定温度(5℃、15℃和25℃)下土壤呼吸速率、微生物量碳和胞外酶活性等指标.研究表明(1)团聚体占全土比例随粒径增大而增大,而有机碳含量随粒径的增大而减小.(2)随着海拔的升高,大团聚体、中团聚体、小团聚体的惰性碳库比例分别从45.11％、36.37％、64.72％升高到45.71％、38.11％、67.12％,缓效碳库比例分别从28.81％、37.20％、14.54％下降到28.41％、36.16％、13.78％,活性碳库比例从26.06％、26.42％、20.73％下降到25.35％、25.72％、19.09％.(3)各团聚体温度敏感性(Q10)表现出随海拔升高而增加,随温度升高而降低(T1Q10＞T2Q10),并且具有惰性碳库Q10＞缓效碳库Q10＞活性碳库Q10的规律.(4)团聚体的微生物量碳(MBC)随着培养时间,各海拔、各温度下均呈现先升高后下降的趋势.(5)影响碳库和Q10的环境因素包括植被类型、土壤特性、土壤环境、土壤底物,其中植被表现较其他更强.

为探究森林土壤微生物呼吸对温度的敏感性及其影响因素,在太白山选取典型的4个不同海拔的林带(锐齿栎林、辽东栎林、红桦林、牛皮桦林)的0-10 cm表层土壤为对象,分别在15、25、35℃下进行控温培养实验并测量其土壤呼吸速率、微生物量和胞外酶活性等指标.结果表明:1)在1-20 d与20-72 d时的微生物呼吸速率分别呈现波动下降趋势与缓慢下降趋势,相比于其初始速率平均下降了68％与90％;表明高温在短期内促进土壤呼吸;2)太白山地区土壤温度敏感系数(Q10)随温度的升高而降低;3)在培养过程中,出现15℃和25℃下微生物量先增多后减少,35℃下微生物量一直减少的现象,并且胞外酶是影响土壤微生物呼吸的重要因素,其中BG(β-葡萄糖苷酶)是胞外酶中最重要的影响因子;4)培养72 d以后,BG已无法为微生物生长繁殖提供充足的碳,在25℃和35℃下,由BX(β-木糖苷酶)提供的碳已成为微生物生长繁殖的重要碳源之一.在15℃和25℃下,N是培养前期限制土壤呼吸的因素,C是后期限制因素;在35℃下,N一直是限制土壤呼吸的因素.在15℃和35℃下,土壤呼吸不存在P限制;在25℃的培养前期,P是限制土壤呼吸的因子,而在培养后期不存在P限制.本研究结果阐明抑制土壤碳排放的关键在于抑制土壤微生物呼吸,揭示了在胞外酶驱动下的土壤碳循环特征,为准确预测全球未来气候变化的趋势提供理论基础.

To explore changes in soil aggregate stability along an elevation gradient, and its regulating factors, soil samples were taken from the 0-10 cm surface layer at 3 different elevations on Taibai Mountain. We measured and analyzed the distribution of soil aggregates, physical and chemical properties, microbial biomass, and extracellular enzymes. The results showed that: ① the soil aggregates from the 3 elevations had mean weight diameters (MWD) of 2.17 mm, 1.83 mm, and 1.82 mm (increasing elevation), and geometric mean diameters (GMD) of 1.66 mm, 1.39 mm, and 1.32 mm, respectively. ② The change in soil aggregate stability along an elevation gradient was regulated by extracellular enzymes in the soil, in particular, the LAP in soil meso-aggregate and the BG in soil micro-aggregate. ③ Microorganisms can alleviate the N limitation at high elevations by adjusting the relative production of extracellular enzymes and altering nutrient utilization efficiency, which also changes soil aggregate stability along an elevation gradient. The results of this study have important scientific significance for soil quality evaluation and ecological environment protection in Taibai Mountain.

Aims The dynamics and driving factors of soil enzyme activities and stoichiometry in the micro-scale elevation gradient is of great significance in the study of nutrient cycling processes. Methods In the present study, the Quercus aliena var. acuteserrata forest belts at the elevation of 1 308, 1 403, 1 503, 1 603, 1 694 and 1 803 m in Taibai Mountain were sampled to determine the contents of carbon (C), nitrogen (N), and phosphorus (P) in leaves, litters, roots and soils, and the activities of alkaline phosphatase (AKP), β -1,4-glucosidase ( β G), cellobiohydrolase (CBH), β -1,4-xylosidase ( β X) and β -1,4-N-acetylgluco-saminidase (NAG). Our results showed that altitude had a great impact on the activities of five soil enzymes. CBH and β G increased first and then decreased with the altitude, while β X showed the opposite trend. The NAG and AKP activity showed a downward trend from 1 408 to 1 694 m and increased with elevation since 1 803 m. The total enzyme activity index exhibited a decreasing trend with altitudes increases. The correlation analysis results indicated that soil enzyme activities and their stoichiometry were controlled by plant, soil C, N, P resources, and soil water and heat conditions. Among these factors, the content of soil organic carbon had high correlation with these parameters and was the main factor affecting the change of soil enzyme activities in the Quercus aliena var. acuteserrata forest. In short, the soil enzyme activities and stoichiometry were different along the micro-scale elevation gradient, affected by the C, N, and P resources of plant and soil. N, nitrogen; P, phosphorus; SMC, soil moisture content; SOC, soil organic carbon; ST, soil temperature; TN, total nitrogen; TP, total phosphorus.

为探究不同海拔森林土壤氮组分对土壤-植物-凋落物化学计量特征的响应规律,选取太白山1300 ～ 2600 m海拔范围内4种典型森林——锐齿栎林(Quercus aliena var.acuteserrata)、辽东栎林(Quercus liaotungensis)、红桦林(Betula albo-sinensis)、牛皮桦林(Betula albo-sinensis var.septen-trionalis)为研究对象,测定土壤、叶片、凋落物、根的碳(C)、氮(N)、磷(P)及土壤铵态氮、硝态氮、微生物生物量氮,分析不同森林土壤、植物、凋落物的化学计量比值的变化特征及其对氮组分的影响.结果 表明:1)4种森林土壤C、N、P含量的变化范围分别为36.77～59.80、2.91～4.76、0.13～0.80 g·kg-1.C、N含量在不同森林间变化趋势基本一致,均表现为牛皮桦林＞红桦林＞辽东栎林＞锐齿栎林;P含量的变化趋势表现为辽东栎林＞牛皮桦林＞红桦林＞锐齿栎林;2)锐齿栎林叶片N∶P＜14,表明锐齿栎林生长较大程度受N限制;辽东栎林、红桦林、牛皮桦林叶片N∶P＞16,表明辽东栎林、红桦林、牛皮桦林生长较大程度受P限制;3)不同森林间微生物量氮差异显著(P＜0.05),铵态氮含量无显著差异,硝态氮含量表现为锐齿栎林(0.33 mg·kg-1)＞牛皮桦林(0.28 mg·kg-1)＞辽东栎林(0.27 mg·kg-1)＞红桦林(0.17 mg·kg-1);4)冗余分析结果表明,土壤-植物-凋落物N∶P值是影响土壤微生物量氮的重要因子,土壤C∶N是影响铵态氮、硝态氮含量的重要因子.本研究结果为太白山森林生态系统的保护和氮循环研究奠定基础.