Soil organic carbon (SOC) accumulation is influenced by multiple interacting processes, yet how long-term nitrogen (N) enrichment alters their relative importance and whether species-level trait divergence leads to differentiated SOC-regulatory pathways remain unclear. A long-term N-addition experiment was conducted in a temperate mixed forest. We quantified soil chemical and structural properties together with species-specific fine-root and mycorrhizal morphological traits. N enrichment significantly altered soil chemical conditions, with soil pH decreasing (6.18-5.00) and NO3--N increasing (12.11-36.89 & micro;g g-1), while SOC also increased across treatments (22.88-27.46 g kg-1). Although soil aggregate stability increased under N addition, multivariate and random forest analyses identified soil pH and NO3--N as the dominant predictors of SOC, whereas aggregate indices and biotic traits contributed secondarily. Mycorrhizal morphological traits declined with increasing N inputs, and fineroot traits varied among species, root orders, and treatments; however, these biotic differences did not improve SOC prediction beyond plot-scale soil chemical variables, indicating that SOC variation under long-term N enrichment was associated mainly with soil chemical conditions.

Anthropogenic nitrogen (N) deposition has intensified globally, yet its impact on root trait plasticity across mycorrhizal associations and root types remains poorly understood. To test how N addition differentially modulates fine-root traits via nutrient pathways and root functional differentiation, we conducted a field experiment. The study was conducted in a temperate mixed forest in northeastern China, where four nitrogen treatments (0, 25, 50, and 75 kg N ha⁻¹ yr⁻¹) were applied to long-term experimental plots containing both arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) tree species. N addition significantly increased root N and phosphorus (P) concentrations, decreased root carbon (C)/N and C/P ratios, and enhanced specific root length and specific root surface area in absorptive and transport roots, particularly under high-N treatments. ECM roots exhibited greater plasticity and higher nutrient contents than AM roots. Soil dissolved organic N and soil total P were key drivers of AM root traits, whereas root C concentration, soil total N, and root P concentration were dominant predictors for ECM roots. Root responses were function-dependent, with contrasting regulation patterns between absorptive and transport roots. These findings demonstrate that ECM species achieve superior adaptability to N enrichment via enhanced morphological and chemical plasticity, and that root trait responses are strongly shaped by nutrient form and root functional role. This study provides a mechanistic basis for predicting forest belowground responses to N deposition under global change scenarios.

Motivation Specific leaf area (SLA) is a key plant functional trait linked to plant structural, physiological and resource-use strategies. Despite its importance, spatially continuous data sets capturing SLA variation across global biomes remain scarce, particularly under future climate scenarios. Here, we compile and model a comprehensive global dataset of SLA to assess its current distribution and project responses to climate change. This resource provides critical support for exploring trait-environment relationships, plant community assembly and vegetation-climate feedbacks at broad spatial and temporal scales. Main Types of Variables Contained The dataset consists of a single standardised table containing 24,237 SLA measurements, each linked to geographic coordinates. Observations span 5687 vascular plant species across 282 families and were compiled from peer-reviewed literature, the TRY database and new field collections. Spatial Location and Grain The dataset has global coverage, with SLA predictions provided at a spatial resolution of 1 km(2). Spatial layers include both present-day environmental conditions and projections under future climate scenarios. Time Period and Grain The data represent current climatic conditions and future projections for the following intervals: 2020-2040, 2040-2060, 2060-2080 and 2080-2100 under multiple emissions scenarios. Major Taxa and Level of Measurement Trait data were collected at the species level for vascular plants, with particular emphasis on grasses and trees. These SLA values were measured excluding petioles and were georeferenced to 2437 sampling sites worldwide, enabling consistent cross-biome analyses of functional trait variation. Software Format The raw trait data are provided in comma-separated value (.csv) format. Model outputs, including global SLA predictions, are available as Geotiff (.tif) files suitable for integration into GIS platforms and Earth system models.

Although the effects of nitrogen (N) and water addition on carbon (C) and nutrient dynamics have been extensively investigated in surface soils of grassland ecosystems, the responses of different fractions of soil organic matter in subsoils —the primary reservoirs of elemental storage—to N and water inputs remain poorly understood. We evaluated organic C and six mineral elements (N, K, Ca, Mg, Fe, Mn) in bulk soil, particulate organic matter (POM), and mineral-associated organic matter (MAOM) at 0–10 cm (topsoil), 30–40 cm (upper subsoil), and 60–80 cm (deep subsoil) in a Eurasian steppe after long-term N and water addition. Although soil organic carbon (SOC) and total nitrogen (TN) concentrations were 3–4 times higher in POM (including free and occluded forms) than in MAOM, over 70

CONTEXT: Major cropping systems in China are facing grand challenges to promote food production while reducing water consumption, nitrogen losses, and greenhouse gas (GHG) emissions. Optimizing agricultural management is a key pathway to address these challenges. However, an advanced multi-objective optimization system for combined management practices that explicitly accounts for Genotype & times; Environment & times; Management interactions across spatially heterogeneous regions is still lacking. OBJECTIVE: This study aims to develop and apply a multi-objective optimization system at the county scale for joint water and nitrogen management in wheat and maize systems across China. The goal is to maintain grain yield while substantially reducing resource use and environmental impacts. METHODS: We coupled a multi-objective optimization algorithm with the DSSAT crop model to optimize combined management practices. The system was applied to each county in China, considering distinct dry, normal, and wet years. RESULTS AND CONCLUSIONS: The optimized practices reduced the combined irrigation water use, total national nitrogen fertilizer use, and GHG emissions for both crops by 35% f 2%, 29% f 1%, and 32% f 0.4%, respectively, with uncertainty values representing the standard deviation across the three hydrological year types. These correspond to reductions of 33 +/- 5 km(3) yr(-1) in irrigation water, 3.4 +/- 0.1 Tg in nitrogen fertilizer, and 80 +/- 1 Tg CO2-eq yr(-1) in GHG emissions, without compromising grain yield. The reductions mainly resulted from decreases in non-productive water and nitrogen losses, whereas crop nitrogen uptake and transpiration changed only slightly.

Context: Climate warming disrupts source-sink relationships that coordinate carbon acquisition and utilization in wheat. However, whether no-tillage practices can mitigate this warming-induced disruption, and how to modify source-sink coordination, remains poorly understood. Objectives: We conducted a five-year field warming experiment, and systematically examined warming-induced alterations in source-sink coordination between conventional and no-tillage wheat systems. Results: Principal component analysis revealed that source-sink relationships exhibited distinct physiological trade-offs, with significant correlations between carbon acquisition efficiency and reproductive structure traits, as well as between gas exchange and carbon allocation and yield components. Under ambient temperature conditions, source and sink processes contributed nearly equally to yield (44-47 % vs. 53-56 %, respectively). However, warming significantly shifted this balance towards source-domination (60 % vs. 40 %, respectively). Structural equation modeling indicated that yield responses to warming were negative under conventional tillage but positive under no-tillage, suggesting no-tillage practices modify resource allocation by maintaining photosynthetic activity under warming. Conclusions: The negative effect of warming on source-sink regulation in wheat yield formation was reversed under no-tillage through flexible temperature responses and integrated regulatory networks. Significance: The findings deepen impact and adaptation physiological mechanisms of climate warming on wheat systems, accelerating the development of climate-resilient agricultural practices.

Atmospheric nitrogen (N) deposition is increasing globally, yet it remains unclear how soil organic carbon (SOC) responds across levels of N enrichment and whether the associated root, soil, and microbial relationships differ between arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) systems. We conducted a long-term N-addition experiment (0–75 kg N ha−1 yr−1) in a temperate mixed forest in northeastern China. We measured soil pH and N pools, microbial biomass and basal respiration, potential extracellular enzyme activities, and morphological and chemical traits of absorptive and transport roots in AM and ECM systems. SOC peaked under medium N addition at 39.56 and 44.29 mg g−1 in AM and ECM soils, respectively, with values 15.1–15.5% lower under high N addition. Labile C and total organic N also peaked under medium N, whereas dissolved organic N decreased progressively. Microbial biomass and basal respiration were higher under low and medium N but lower under high N. AM roots showed more acquisitive morphology than ECM roots, whereas N effects on root traits depended on root functional type. SOC was positively associated with soil pH, total organic N, microbial biomass C, and β-glucosidase activity, but negatively associated with specific root length. The SEMs showed that C pool composition was directly associated with soil pH, absorptive root traits, and enzyme activities in AM, but with soil pH alone in ECM. These findings indicate that SOC responses across the N-addition gradient were associated with different root–soil–microbial relationships in AM and ECM systems.

Rice cultivation stands out as a major greenhouse gas source, emitting 10-20% of global CH4 emissions. How to accurately estimate CH4 emissions from paddy rice and their mitigation potential has been key concerns. Agroecosystem models have unique advantages in understanding CH4 processes, simulating CH4 emissions dynamics, optimizing management practices, and quantifying mitigation potentials. However, current agroecosystem models need to be substantially improved for these purposes. In this study, we develop a comprehensive agroecosystem model, MCWLA-Rice 2.0, to better depict the production, oxidation, and emission processes of CH4 and improve the simulation of root exudates, the effect of nitrate fertilizer on CH4 emissions, and the decomposition of external organic carbon. We calibrate and validate the model and demonstrate its performance in simulating the rice cultivation system under different fertilizer and irrigation treatments at seven sites across Asia. Elaborating on both aboveground and belowground carbon-nitrogen coupling processes, MCWLA-Rice 2.0 is a valuable tool for simulating rice productivity and CH4 emissions under various environments and managements, effectively supporting the development of climate-smart agriculture.

Rising temperatures accelerate wheat development and shorten grain-filling duration (GFD), thereby constraining yield formation. We hypothesized that harnessing wheat germplasm could sustain GFD and/or increase grain-filling rate (GFR) and enhance resilience to warming through optimized source-sink dynamics. Here, we first conducted genome-wide association studies on 163 diverse cultivars to identify stable loci associated with GFD and GFR. We then developed a gene-based modelling framework by deriving cultivar-specific parameters of the CERES-Wheat model from the identified stable loci using Random Forest (RF). Finally, we applied the framework across 45 global sites under current and future climates. Pyramiding favorable alleles could extend GFD by 11.4% and increase GFR by 14.8%, resulting in yield gains of up to 9.5% under irrigated conditions and 2.3% under rainfed conditions in mid-century RCP8.5 scenarios. GFR enhancement was most effective in high-rainfall environments, whereas GFD extension was more beneficial at water-limited sites. This gene-based modelling framework reveals how genetic control of grain-filling traits mediates genotype × environment × management (G×E × M) responses under climate change, providing a tool to test marker-assisted strategies toward climate-resilient cultivars.

Nitrogen fertilizer application to staple crops such as maize and wheat farmland has surged dramatically, leading to substantial losses of soil nitrogen in various forms. However, the nitrogen losses, controlling factors, and mitigation potential of global maize and wheat production have been far from clear. Here, we develop machine learning models to account for more key factors than before to investigate the spatial distribution, key controlling factors, and mitigation potential of soil reactive nitrogen losses in maize and wheat fields worldwide at a 5-arcmin resolution. We estimate the annual global soil nitrogen losses from synthetic nitrogen fertilizer use in 2020, including emissions of nitrous oxide (N2O), ammonia (NH3), nitrogen oxides (NO), nitrogen leaching, and runoff. These losses amounted to 0.21, 2.36, 0.13, 2.50, and 1.21 million tons of nitrogen, respectively, for maize; and 0.19, 1.21, 0.10, 2.74, and 1.09 million tons of nitrogen, respectively, for wheat. The hydrological pathway contributed over 55% of total losses and is more susceptible to extreme precipitation events, while gaseous losses are more influenced by climate and soil texture. Mitigation primarily relies on improving nitrogen use efficiency (NUE) and replacing fertilizer types. The most effective approach involves raising NUE to 60% while fully adopting efficient nitrogen fertilizers, achieving emission reductions of 80.6% for wheat and approximately 23.9% for maize. These findings not only hold scientific value for precise modeling of agricultural nitrogen cycling but also provide critical scientific basis for developing regionally differentiated, crop-specific nitrogen fertilizer management and emission mitigation strategies.

Terrestrial plants on Earth have been drastically affected by climate change and anthropogenic disturbances since the Industrial Revolution. The global patterns of the relationships between various plant functional traits determine the distribution and productivity of plant species worldwide. Although many studies have confirmed the importance of key traits and their relationships in the adaptation and evolution of plant species, comprehensive analyses of trait relationships within and across global biomes and biogeographical realms remain limited. In this study, we investigated the spectrum of plant functional traits and their relationships by combining functional trait data spanning 5633 species and 2342 sites across global biomes and biogeographical realms. We found that plant functional traits varied greatly and were highly specific to biomes and realms. The slopes of the standardized major axis regressions between bivariate traits reflected the resource-use strategies of each biome and realm. Multidimensional traits were highly coordinated with trade-offs but depended particularly on plant functional types. Climatic factors played a critical role in determining the composition of plant species across biomes and realms by modulating a set of essential trait combinations, namely the coordination and trade-offs of plant functional traits, which enhanced the adaptability of plants to their environments. Therefore, we propose that future studies must focus on investigating the relationships between the local habitat specificity of traits, as well as their relationships with environmental changes. Additionally, we suggest improving models that predict changes in vegetation based on continuous variations in plant functioning across global flora.

Soil structural stability underpins ecosystem function, yet how nitrogen (N) enrichment and precipitation reduction jointly regulate glomalin-related soil proteins (GRSP) and aggregate formation in temperate forests remains poorly understood. This knowledge gap limits predictions of soil carbon persistence under global change. A factorial field experiment was conducted in an old-growth temperate forest with four treatments (CK, + N, -P, + N-P) across three dominant tree species. Rhizosphere soils were analyzed for total and easily extractable GRSP (T-GRSP, EE-GRSP), aggregate-size distribution, and physicochemical properties. Random forest modeling and structural equation modeling (SEM) were used to identify key regulatory pathways. N addition significantly increased EE-GRSP (3.92-5.74 mg g ⁻ ¹) and macroaggregates (4-8 mm: 21.6%-34.8%), while precipitation reduction reduced EE-GRSP (by 36.5%) and increased microaggregates (0.053-0.25 mm: + 29.3%). soil organic carbon (SOC) was strongly and positively correlated with EE-GRSP (R² = 0.69-0.63), T-GRSP (R² = 0.82-0.77), MWD (R² = 0.85-0.67), and GMD (R² = 0.84-0.72). Random forest identified EE-GRSP and SOC as dominant predictors of aggregate stability. SEM revealed that SOC regulated GRSP and MWD through NH₄ ⁺ -N and SWC (Fig. 2-5). Our findings highlight a coupled "carbon-protein-structure" pathway in regulating soil aggregation. The regulatory effects of N and water are both species-specific and pathway-integrated, emphasizing the role of SOC-mediated GRSP dynamics in sustaining soil physical integrity under climate perturbations.

Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q10) vary with depth and plant litter input under these stressors remains poorly understood. We incubated peat from two depths with different degrees of decomposition, either alone or incubated with Sphagnum divinum shoots or Betula ovalifolia leaves, under five temperature levels and two moisture conditions in growth chambers. We found that drought and Betula addition increased CO2 emissions in both peat layers, while Sphagnum affected only shallow peat. Deep peat alone or with Betula exhibited higher Q10 than pure shallow peat. Drought increased the Q10 of both depths’ peat, but this effect disappeared with fresh litter addition. The CO2 production rate showed a positive but marginal correlation with microbial biomass carbon, and it displayed a rather similar responsive trend to warming as the microbial metabolism quotient. These results indicate that both deep and dry peat are more sensitive to warming, highlighting the importance of keeping deep peat buried and waterlogged to conserve existing carbon storage. Additionally, they further emphasize the necessity of Sphagnum moss recovery following vascular plant encroachment in restoring carbon sink function in peatlands.

Plant functional traits and their interrelationships are critical in shaping the evolutionary and adaptive trajectories of plant species, as well as their responses to environmental changes. Grassland ecosystems serve as a natural laboratory for exploring plant trait coordination, given their high biodiversity, environmental heterogeneity and intricate species interactions. However, the patterns of trait covariation across grasslands-the largest terrestrial ecosystems globally-and their environmental dependencies remain poorly understood. In this study, we compiled a newly updated dataset for grassland ecosystems to analyse global patterns of leaf traits across grassland species and to identify their key climatic drivers. A global database comprising 9158 site-level observations was used. We found that leaf traits and their relationships varied significantly across climatic zones and plant functional types. Globally, C4 plants, forbs and annuals exhibited a resource acquisition strategy. Plants in temperate climates tended to adopt a conservative strategy, whereas those in boreal, subtropical, tropical and Mediterranean climates were more likely to employ a resource acquisition strategy. A clear conservative-acquisitive trade-off axis among functional traits was observed across global grasslands. Precipitation primarily drove the first axis of trait variation, which largely reflected a resource-acquisition strategy. In contrast, temperature predominantly influenced the second axis, which was associated with leaf nitrogen status. Synthesis. Our findings underscore the strong global associations among plant functional traits, the pivotal role of plant functional types in mediating trait coordination and trade-offs and their dependencies on climatic zones and environmental factors. These findings provide valuable insights into the coordination and trade-offs of trait relationships at a global scale.

Climate change and anthropogenic nitrogen (N) deposition are altering terrestrial nutrient cycles, but their integrative effects on depth-resolved soil–microbe–plant N cycling remain poorly understood. This study aimed to disentangle how reduced precipitation and N enrichment influence soil N retention, microbial 15N assimilation, and plant N uptake across soil depths and plant species. A field experiment was conducted in a temperate forest in northeastern China using four treatments (control, N addition, precipitation reduction, and combined treatment), where N addition was applied at 50 kg N·ha⁻1·yr⁻1 and precipitation reduction excluded 30

Nitrogen deposition is a critical driver of plant-soil interactions in forest ecosystems. However, the species-specific coordination of nitrogen uptake and carbon assimilation—traced using 15N- and 13C-labeled compounds—under varying nitrogen forms, depths, and time points remains poorly understood. We conducted a dual-isotope (15NH4Cl, K15NO3, and Na213CO3) labeling experiment in a temperate secondary forest to investigate nutrient uptake and carbon assimilation in three understory species—Carex siderosticta, Maianthemum bifolium, and Oxalis acetosella—across three nitrogen treatments (control, low N, and high N), two soil depths (0–5 cm and 5–15 cm), and two post-labeling time points (24 h and 72 h). We quantified 15N uptake and 13C assimilation in above- and belowground plant tissues, as well as 15N and 13C retention in soils. C. siderosticta exhibited the highest total 15N uptake (2.2–6.9 μg N m−2 aboveground; 1.4–4.1 μg N m−2 belowground) and 13C assimilation (58.4–111.2 mg C m−2 aboveground; 17.6–39.2 mg C m−2 belowground) under high ammonium at 72 h. High nitrogen input significantly enhanced the coupling between plant biomass and nutrient assimilation (R2 > 0.9), and increased 15N-TN and 13C-SOC retention in the surface soil layer (13,200–17,400 μg N kg−1; 30,000–44,000 μg C kg−1). Multifactorial analysis revealed significant interactions among nitrogen treatment, form, depth, and time. These findings demonstrate that ammonium-based enrichment promotes nutrient acquisition and carbon assimilation in responsive species and enhances surface soil C—N retention, highlighting the integrative effects of nitrogen form, species traits, and spatial–temporal dynamics on forest biogeochemistry.

Peatlands play a crucial role in global carbon (C) sequestration, but their response to long-term nitrogen (N) deposition remains uncertain. This study investigates the effects of 12 years of simulated N addition on CO2 and CH4 fluxes in a temperate peatland through in situ monitoring. The results demonstrate that long-term N addition significantly reduces net ecosystem exchange (NEE), shifting the peatland from a C sink to a C source. This transition is primarily driven by a decline in aboveground plant productivity, as Sphagnum mosses were suppressed and even experienced mortality, while graminoid plants thrived under elevated N conditions. Although graminoid cover increased, it did not compensate for the GPP loss caused by Sphagnum decline. Instead, it further increased CH4 emissions. These findings suggest that sustained N input may diminish the C sequestration function of peatlands, significantly weakening their global cooling effect.

Agricultural total factor productivity (ATFP) is a crucial measure that determines the aggregate agricultural output per unit of aggregate input. ATFP is sensitive to climate change; however, the impacts of climate change on ATFP have rarely been investigated despite its significance. In this study, we employ the Malmquist index methods to calculate the ATFP from 1981 to 2019 based on detailed census data at the prefecture level across China. Furthermore, we project the ATFP in the period of 2020–2060 under the Societal Development Pathway (SSP) 1–2.6 and SSP3-7.0. The results showed that, during 1981–2019, the ATFP of China increased significantly, ranging from 0.74 to 38.95. The joint changes in temperature and precipitation benefited ATFP growth in some prefectures in northwestern, northeastern and southern China but reduced it in the Huang-Huai-Hai Region. During 2031–2060, ATFP is projected to be more positively affected by climate change in northern China than in southern China. Some regions such as the Northwest Arid Region, most of the Northeast China and Southwest China Region will benefit from climate change. However, some major agricultural production areas including the Huang-Huai-Hai Region and southeast China are expected to be negatively affected by climate change. Our findings highlight the need to consider the impacts of climate change on ATFP when developing climate adaptation strategies in agriculture.