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Carbon exchange between forest ecosystems and the atmosphere play an important role in global carbon cycle, which is difficult to be accurately quantified due to the large uncertainties in scaling up site-scale observations or filling-up measurement gaps. A process-oriented model equipped with comprehensive processes to explicitly simulating coupled carbon, nitrogen and water cycling, is hypothesized to reduce the uncertainties in quantification of forest carbon fluxes. To test this hypothesis, the Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC), as a hydro-biogeochemical model that dynamically couples the carbon, nitrogen, phosphorous and water cycling processes, was updated in this study by incorporating a new forest growth module derived from the Biome-BGC model and validating the updates using multiple-year continuous observations of carbon and water fluxes at the site scale. The updated model has improved the processes of photosynthesis, litter decomposition, allocation, respiration and mortality to more effectively capture the transformation and transportation of nutrients in plant-soil-water continuum. The observed gross primary productivity (GPP), ecosystem respiration (ER), net ecosystem carbon dioxide exchange (NEE) and evapotranspiration (ET) of three typical forest sites subject to subtropical and temperate climates in eastern Asia (2003–2010) were used for the model calibration and validation. Compared with the original model in validation, the updated model showed significant improvements in simulating the daily dynamics and inter-annual variations of each variable, with the NRMSE values decreased by 46 % and 54 %, 65 % and 37 %, 4 % and -6 %, and 38 % and -3 % for GPP, ER, NEE, and ET on daily and annual scales, respectively. The comparable performances of both model versions for annual NEE emphasizes the importance of validating each component of carbon fluxes to avoid the offsetting of model errors. The canopy average specific leaf area, fraction of leaf nitrogen in Rubisco, annual leaf and fine root turnover fraction, maximum stomatal conductance and the ratio of carbon to nitrogen in leaves and fine roots were identified as the sensitive eco-physiological parameters affecting the simulations of GPP and ER. In addition, the meteorological variables of solar radiation, humidity and air temperature also showed strong influences on the simulated GPP and ER. The relatively satisfactory performances demonstrated that the modified model has the ability to capture the daily dynamics and inter-annual variations of carbon fluxes for forests in temperate and subtropical zones, which is essential for estimating the emissions of greenhouse gases at the regional or global scales. [ABSTRACT FROM AUTHOR]

Maintaining or even increasing crop yields while reducing nitrous oxide (N2O) emissions is necessary to reconcile food security and climate change, while the metric of yield‐scaled N2O emission (i.e., N2O emissions per unit of crop yield) is at present poorly understood. Here we conducted a global meta‐analysis with more than 6000 observations to explore the variation patterns and controlling factors of yield‐scaled N2O emissions for maize, wheat and rice and associated potential mitigation options. Our results showed that the average yield‐scaled N2O emissions across all available data followed the order wheat (322 g N Mg−1, with the 95% confidence interval [CI]: 301–346) > maize (211 g N Mg−1, CI: 198–225) > rice (153 g N Mg−1, CI: 144–163). Yield‐scaled N2O emissions for individual crops were generally higher in tropical or subtropical zones than in temperate zones, and also showed a trend towards lower intensities from low to high latitudes. This global variation was better explained by climatic and edaphic factors than by N fertilizer management, while their combined effect predicted more than 70% of the variance. Furthermore, our analysis showed a significant decrease in yield‐scaled N2O emissions with increasing N use efficiency or in N2O emissions for production systems with cereal yields >10 Mg ha−1 (maize), 6.6 Mg ha−1 (wheat) or 6.8 Mg ha−1 (rice), respectively. This highlights that N use efficiency indicators can be used as valuable proxies for reconciling trade‐offs between crop production and N2O mitigation. For all three major staple crops, reducing N fertilization by up to 30%, optimizing the timing and placement of fertilizer application or using enhanced‐efficiency N fertilizers significantly reduced yield‐scaled N2O emissions at similar or even higher cereal yields. Our data‐driven assessment provides some key guidance for developing effective and targeted mitigation and adaptation strategies for the sustainable intensification of cereal production. [ABSTRACT FROM AUTHOR]

Anthropogenic nitrogen (N) loading alters soil ammonia‐oxidizing archaea (AOA) and bacteria (AOB) abundances, likely leading to substantial changes in soil nitrification. However, the factors and mechanisms determining the responses of soil AOA:AOB and nitrification to N loading are still unclear, making it difficult to predict future changes in soil nitrification. Herein, we synthesize 68 field studies around the world to evaluate the impacts of N loading on soil ammonia oxidizers and nitrification. Across a wide range of biotic and abiotic factors, climate is the most important driver of the responses of AOA:AOB to N loading. Climate does not directly affect the N‐stimulation of nitrification, but does so via climate‐related shifts in AOA:AOB. Specifically, climate modulates the responses of AOA:AOB to N loading by affecting soil pH, N‐availability and moisture. AOB play a dominant role in affecting nitrification in dry climates, while the impacts from AOA can exceed AOB in humid climates. Together, these results suggest that climate‐related shifts in soil ammonia‐oxidizing community maintain the N‐stimulation of nitrification, highlighting the importance of microbial community composition in mediating the responses of the soil N cycle to N loading. [ABSTRACT FROM AUTHOR]

Arable soil continues to be the dominant anthropogenic source of nitrous oxide (N2O) emissions owing to application of nitrogen (N) fertilizers and manures across the world. Using laboratory and in situ studies to elucidate the key factors controlling soil N2O emissions remains challenging due to the potential importance of multiple complex processes. We examined soil surface N2O fluxes in an arable soil, combined with in situ high‐frequency measurements of soil matrix oxygen (O2) and N2O concentrations, in situ 15N labeling, and N2O 15N site preference (SP). The in situ O2 concentration and further microcosm visualized spatiotemporal distribution of O2 both suggested that O2 dynamics were the proximal determining factor to matrix N2O concentration and fluxes due to quick O2 depletion after N fertilization. Further SP analysis and in situ 15N labeling experiment revealed that the main source for N2O emissions was bacterial denitrification during the hot‐wet summer with lower soil O2 concentration, while nitrification or fungal denitrification contributed about 50.0% to total emissions during the cold‐dry winter with higher soil O2 concentration. The robust positive correlation between O2 concentration and SP values underpinned that the O2 dynamics were the key factor to differentiate the composite processes of N2O production in in situ structured soil. Our findings deciphered the complexity of N2O production processes in real field conditions, and suggest that O2 dynamics rather than stimulation of functional gene abundances play a key role in controlling soil N2O production processes in undisturbed structure soils. Our results help to develop targeted N2O mitigation measures and to improve process models for constraining global N2O budget. [ABSTRACT FROM AUTHOR]

Water-induced erosion and associated particulate carbon (PC), particulate nitrogen (PN) and particulate phosphorus (PP) nutrient losses are vital parts of biogeochemical cycling. Identifying their intensity and distribution characteristics is of great significance for the control of soil and water loss and nitrogen/phosphorus nonpoint source pollution. This study incorporated modules of physical soil erosion and associated PC, PN and PP losses into a process-oriented hydro-biogeochemical model (Catchment Nutrients Management Model coupled with DeNitrification–DeComposition, CNMM-DNDC) to enable it to predict soil and water loss. The results indicated that the upgraded CNMM-DNDC (i) performed well in simulating the observed temporal dynamics and magnitudes of surface runoff, sediment and PN/PP yields in the lysimetric plot of the Jieliu catchment in Sichuan Province and (ii) successfully predicted the observed monthly dynamics and magnitudes of stream flow, sediment yield and PN yields at the catchment outlet, with significant univariate linear regressions and acceptable Nash–Sutcliffe indices higher than 0.74. The upgraded CNMM-DNDC demonstrated that a greater proportion of PN to total nitrogen (TN) during the period with large precipitation events and amounts than that during the drought period (16.2 %–26.6 % versus 2.3 %–12.4 %). The intensities of soil erosion and particulate nutrient yields in the Jieliu catchment were closely related to land use type in the following order: sloping cultivated upland (SU) > residential areas (RA) > forest land (FL). The scenario analysis demonstrated that high greenhouse gas (GHG) emissions scenarios provided a greater risk of soil erosion than did low GHG emissions scenarios and that land use change (i.e., from SU to FL) could help to mitigate soil and water loss accelerated by climate change in the future. The upgraded model was demonstrated to have the ability of predicting ecosystem productivity, hydrologic nitrogen loads, emissions of GHGs and pollutant gases, soil erosion and particulate nutrient yields, which renders it a potential decision support tool for soil erosion and nonpoint source pollution control coordinated with increasing production and reducing GHG and pollutant gases emissions in a catchment. [ABSTRACT FROM AUTHOR]