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Inhibitors are widely considered an efficient tool for reducing nitrogen (N) loss and improving N use efficiency, but their effectiveness is highly variable across agroecosystems. In this study, we synthesized 182 studies (222 sites) worldwide to evaluate the impacts of inhibitors (urease inhibitors [UI], nitrification inhibitors [NI] and combined inhibitors) on crop yields and gaseous N loss (ammonia [NH3] and nitrous oxide [N2O] emissions) and explored their responses to different management and environmental factors including inhibitor application timing, fertilization regime, cropping system, water management, soil properties and climatic conditions using subgroup meta‐analysis, meta‐regression and multivariate analyses. The UI were most effective in enhancing crop yields (by 5%) and reducing NH3 volatilization (by 51%), whereas NI were most effective at reducing N2O emissions (by 49%). The application of UI mitigates NH3 loss and increases crop yields especially in high NH3‐N loss scenarios, whereas NI application would minimize the net N2O emissions and the resultant environmental impacts especially in low NH3‐N loss scenarios. Alternatively, the combined application of UI and NI enables producers to balance crop production and environmental conservation goals without pollution tradeoffs. The inhibitor efficacy for decreasing gaseous N loss was dependent upon soil and climatic conditions and management practices. Notably, both meta‐regression and multivariate analyses suggest that inhibitors provide a greater opportunity for reducing fertilizer N inputs in high‐N‐surplus systems and presumably favor crop yield enhancement under soil N deficiency situations. The pursuit of an improved understanding of the interactions between plant‐soil‐climate‐management systems and different types of inhibitors should continue to optimize the effectiveness of inhibitors for reducing environmental losses while increasing productivity. [ABSTRACT FROM AUTHOR]

Maize (Zea mays L.) production in Northeast China is vulnerable to climate change. Thus, exploring future adaptation measures for maize is crucial to developing sustainable agriculture to ensure food security. The current study was undertaken to evaluate the impacts of climate change on maize yield and partial factor productivity of nitrogen (PFPN) and explore potential adaptation strategies in Northeast China. The Decision Support System for Agrotechnology Transfer (DSSAT) model was calibrated and validated using the measurements from nine maize experiments. DSSAT performed well in simulating maize yield, biomass and N uptake for both calibration and validation periods (normalized root mean square error (nRMSE) < 10%, −5% < normalized average relative error (nARE) < 5% and index of agreement (d) > 0.8). Compared to the baseline (1980–2010), the average maize yields and PFPN would decrease by 7.6–32.1% and 3.6–14.0 kg N kg−1 respectively under future climate scenarios (2041–2070 and 2071–2100) without adaptation. Optimizing N application rate and timing, establishing rotation system with legumes, adjusting planting dates and breeding long-season cultivars could be effective adaptation strategies to climate change. This study demonstrated that optimizing agronomic crop management practices would assist to make policy development on mitigating the negative impacts of future climate change on maize production. [ABSTRACT FROM AUTHOR]

The impact of climate change on agricultural systems is a major concern as it can have a significant effect on the world food supply. The objective of this study was to evaluate climate change impacts on crop production and nitrate leaching in two distinct climatic zones in Canada. Spring wheat (Triticum aestivum L.) was selected for the semiarid regions of Western Canada (Swift Current, SK) and maize (Zea mays L.) was chosen for the more humid regions of central Canada (Woodslee, ON). Climate scenarios were based upon simulations from a Canadian Regional Climate Model (CanRCM4) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) and crop simulations were conducted using the Decision Support System for Agrotechnology Transfer (DSSAT) model. Compared to the baseline climate scenario, wheat yields increased by 8, 8, 11, 15%, whereas maize yields decreased by 15, 25, 22, 41% under RCP4.5 2050s (2041–2070), RCP4.5 2080s (2071–2100), RCP8.5 2050s and RCP8.5 2080s scenarios, respectively. Annual nitrate leaching increased by 19, 57, 73, 129% at Swift Current and by 84, 117, 208, 317% at Woodslee under the four scenarios, respectively. Adaptation measures suggested that fertilizer N rate for spring wheat should be increased to 80–100 kg N ha-1 to obtain optimal yields although this will result in an additional risk of 5–8 kg N ha-1 nitrate leaching at Swift Current. The fertilizer N rate of 150 kg N ha-1 was found to be suitable for high maize yields at Woodslee. New wheat and maize cultivars with long growing seasons would enable crop growth to match the phenological stage and hence maintain high crop yields to adapt to increased temperatures in the future. [ABSTRACT FROM AUTHOR]

Abstract Estimating regional soil nitrogen (N) balance in croplands is critical to improve management practices, reduce environmental risks and develop sustainable agriculture. In this study, spatial and temporal variations of soil N balance were evaluated from 1984 to 2014 in China's croplands. Results indicated that the total soil N balance was in surplus and increased by 7.3 Tg N (130.4%) between 1984 and 2014, which was attributed to the increased N input of 29.3 Tg N, compared with the increased N output of 22.1 Tg N. Soil N balance continually increased from the 1980s (1984–1989) to the 2000s (2000–2009), and then decreased in the 2010s (2010–2014). Meanwhile, N use efficiency decreased gradually from the 1980s to the 2000s, but it increased in the 2010s. The N loss (N 2 , N 2 O, NO, NH 3 , NO 3 − leaching and runoff) increased significantly from the 1980s to the 1990s, while the increasing trend gradually reduced from the 1990s to the 2010s. The spatial-temporal distribution of the N balance at the regional scale showed that the total highest and lowest N balance was in the middle and lower reaches of Yangtze River (2.1–3.7 Tg N) and northeast of China (0.3–1.0 Tg N), but the highest and lowest N balance per cropping area was in the southeast (93.4–129.7 kg N ha−1) and northeast (19.6–43.9 kg N ha−1) regions respectively from the 1980s to the 2010s. The N balance decreased for all regions from the 2000s to the 2010s, excluding the southeast and southwest of China due to higher increased rate of N input than the lower increased rate of N output. Reducing the use of chemical fertilizer N would improve cop productivity, decrease soil surplus N and environmental risks of N gas emissions, nitrate leaching and runoff. Highlights • Spatial and temporal variations of soil N balance were evaluated in China's croplands. • Total soil N balance was in surplus and increased by 7.3 Tg N between 1984 and 2014. • N use efficiency decreased from the 1980s to the 2000s which then increased in the 2010s. • The total highest and lowest N balances were in the MLYR and NE regions, respectively. [ABSTRACT FROM AUTHOR]

Understanding the transformation of accumulated phosphorus (P) is vital for P management. However, previous studies are limited to a few sites in Chinese agroecosystems. In this study, to investigate the temporal-spatial differences of transformation from accumulated P to available P (determined by the Olsen method), a dataset was assembled based on 91 national long-term experimental sites across China in the recent 31 years (1988–2018). A boosted regression tree (BRT) and a structural equation model (SEM) were used to analyze the factors influencing the transformation. The results showed that the transformation from accumulated P to available P in South China (1.97 mg kg−1) was significantly higher than that in other regions (0.69–1.22 mg kg−1). Soil properties were the main driving factors with a relative contribution of 81.8%, while climate and management practices explained 7.8% and 10.4% of the variations, respectively. Furthermore, SEM analysis revealed that the soil organic matter (SOM) could positively and directly affect the transformation, whereas the soil pH, soil silt content, and P fertilizer had negative and direct effects on it. For the first time, this study analyzed the transformation from soil accumulated P to available P at a national scale and at multiple sites and quantified the contribution of the main influencing factors. These results help to predict the soil available P content across different agroecosystems based on the input amount of P fertilizer, contributing to the regional precise management of P fertilizer application. [ABSTRACT FROM AUTHOR]

Tillage and crop residue management can have large impacts on soil organic carbon (SOC) sequestration, as well as additional feedbacks on crop productivity and agricultural sustainability. The objectives of this study were to (i) evaluate the effects of summer fallow, legume green manure, pea or canola in rotation with spring wheat on crop yields, biomass production and SOC dynamics (0–15 cm) from six long-term cropping systems under semiarid conditions in western Canada, (ii) calibrate and validate three process-based models (DNDC, DayCent and DSSAT) using experimental data, and (iii) investigate the long-term impacts of tillage (no-tillage (NT) vs. conventional tillage (CT)) and straw residue (returned vs. removal) on SOC changes from diverse rotation systems. Over the experimental period from 1987 to 2015, the average wheat yields in Wheat (W)-Canola (C)–W-Pea (P) and legume green manure (LGM)-W-W rotations increased by 33.5 and 10.8%, respectively, compared to the continuous wheat (ContW) cropping systems. Higher SOC sequestration rates were found under ContW, LGM-W-W and W–C–W–P cropping systems mainly due to higher residue C input and larger nitrogen (N) inputs/fixation when compared to fallow-wheat systems. All three models performed "fair" to "good" in simulating crop yield, biomass and SOC content over time across all treatments. DSSAT had the lowest errors of prediction for yields (e.g., normalized RMSE (nRMSE) ≤ 27.2%, index of agreement (d) ≥ 0.79), while DNDC had better estimates of SOC content (e.g., nRMSE ≤ 4.5%, d ≥ 0.74). Long-term scenario analysis demonstrated that the mean annual changes in SOC across rotations based on model ensemble ranged from 0.03 Mg C ha−1 y−1 under CT with straw removal to 0.31 Mg C ha−1 y−1 under NT with straw returned. Predicted SOC sequestration potential of NT was relatively small compared to crop straw return for all rotation systems. This study suggests that diverse crop rotations which include canola and legume crops have the potential to store more SOC than traditional wheat-based cropping (e.g., fallow-wheat, ContW) for the semiarid prairies of Canada. These diverse rotations are already becoming more common and can help to enhance crop yields and maximize SOC sequestration when they are coupled with NT and residue management. • DNDC, DayCent and DSSAT well predicted grain yield and SOC for diverse rotations. • Wheat (W) yield and SOC increased when in rotation with canola and legumes. • DNDC more accurately simulated SOC in comparison to DSSAT and DayCent. • Higher SOC sequestration rates were estimated for straw return than for no-tillage. • Long-term rotations W–C (canola)-W-C and C–C–C–P (pea) had the largest increases in SOC. [ABSTRACT FROM AUTHOR]

Excessive nitrogen (N) application rate led to low N use efficiency and environmental risks in a potato (Solanum tuberosum L.) production system in northwest China. Process-based models are effective tools in agroecosystems that can be used to optimize integrated management practices for improving potato yield and N use efficiency. The objectives of this study were (1) to calibrate and evaluate the DeNitrification-DeComposition (DNDC) and soil Water Heat Carbon Nitrogen Simulator of Vegetable (WHCNS_Veg) models using the measurements of potato yield, above-ground biomass, N uptake, soil moisture and temperature, and soil inorganic N based on a field experiment in northwest China (2017–2020) and (2) to explore optimal management practices for improving yield and N use efficiency under long-term climate variability (1981–2020). Both models overall performed well in simulating potato tuber yield (normalized root mean square error (NRMSE) = 5.4–14.9%), above-ground biomass (NRMSE = 6.0–14.7%), N uptake (NRMSE = 18.1–25.6%), daily soil temperature (index of agreement (d) > 0.9 and Nash–Sutcliffe efficiency (EF) > 0.8), and acceptable in-soil moisture and inorganic N content (d > 0.6 and EF > ‒1) for N-applied treatments. However, the two models underestimated tuber yield and soil N content for no N fertilization treatment which was partially attributed to the underestimated soil N mineralization rate under N stress conditions. The sensitivity analysis showed that the greatest tuber yield and N use efficiency were achieved at the N rate of 150–180 kg ha−1 with 2–3 splits, fertilization depth of 15–25 cm, and planting date of 25 April to 10 May in both models. This study highlights the importance of integrated management strategies in obtaining high N use efficiency and crop yield in potato production systems. [ABSTRACT FROM AUTHOR]

It is currently uncertain whether process-based models are capable of assessing crop yield and nitrogen (N) losses while helping to investigate best management practices from vegetable cropping systems. The objectives of this study were to (1) calibrate and evaluate the Denitrification-Decomposition (DNDC) model in simulating crop growth and nitrate leaching in a typical field radish system; (2) optimize management practices to improve radish yield and mitigate nitrate leaching under 20-year climate variability. A five-season in-situ field experiment of spring and autumn radish in northern China was established in the autumn of 2017 and measurements of radish yield, N uptake, soil temperature, soil moisture, drainage, and nitrate leaching were obtained under different N usage. DNDC overall demonstrated "good" to "excellent" performance in simulating radish yield, total biomass, N uptake, and soil temperature across all treatments (6.4% ≤ normalized root mean square error (nRMSE) ≤ 15.5%; 0.12 ≤ Nash-Sutcliffe efficiency (NSE) ≤ 0.88; 0.80 ≤ index of agreement (d) ≤ 0.97). DNDC generally exhibited "fair" performance in estimating soil moisture and drainage (10.9% ≤ nRMSE ≤ 27.2%; −0.18 ≤ NSE ≤ 0.37; 0.69 ≤ d ≤ 0.82) and "good" performance when predicting nitrate leaching (12.4% ≤ nRMSE ≤ 26.7%; −0.59 ≤ NSE ≤ 0.51; 0.68 ≤ d ≤ 0.90). Sensitivity analyses demonstrated that optimized management practices (planting dates, irrigation amount, fertilization rate and timing) could substantially reduce N usage by 40%–50%, irrigation amount by 33%–50%, and nitrate leaching by 86%–95% compared to farmers' practice in radish planting system. This study indicated that a modelling method is helpful for evaluating the biogeochemical effects of management alternatives and identifying optimal management practices in radish production systems of China. [Display omitted] • Denitrification-Decomposition (DNDC) was applied to simulate field radish systems. • DNDC well simulated radish yield, nitrogen (N) uptake, and nitrate leaching. • DNDC showed acceptable performance in simulating soil moisture and drainage. • Modelled critical agronomic and environmental N rates were 150–180 kg N ha−1. • Optimized planting dates and irrigation rates improved yields and reduced N losses. [ABSTRACT FROM AUTHOR]

Accurate estimates of soil organic carbon (SOC) are critical for evaluating the impacts of crop and nutrient management practices on soil sustainability and global climate change. Temporal and spatial variations in topsoil (0–0.20 m) SOC were analyzed using 43,743 soil samples in China's croplands. The soil database in our study was collected from the International Plant Nutrition Institute (IPNI) China Program. The results showed an increasing trend in SOC density (SOCD) for both grain and cash crops from 1991 to 2012. The average SOCD increased by 16.8, 17.4, 11.8 and 8.7% in the north central, northwest, southeast and southwest regions, respectively, whereas average SOCD decreased by 1.3% for the northeast region between the 1991–2001 and 2002–2012 periods. For both grain and cash crops, the SOCD frequency distribution (%) increased in the ranges of 10–20, 20–30 and 30–40 Mg C ha−1 from the 1991–2001 to the 2002–2012, but decreased in the ranges of 0–10 and 50–60 Mg C ha−1. Additionally, SOCD increased in most major soil types across China's cropland regions, except in phaeozems, chernozems and umbrisols, where it decreased by 8.6–18.7% mainly due to water runoff, soil erosion, and low C input. The overall SOC stock (SOCS) in China's cropland increased by 260 Tg C (23.7 Tg C yr−1) from 1991–2001 to 2002–2012, which was partially due to the increased crop residue return, improved fertilization and adopted conservation tillage over the period. This SOC increase represents a potential offset in carbon dioxide (CO2) emissions that could help reduce the overall net CO2 emissions in China. [ABSTRACT FROM AUTHOR]

• Above-ground biomass and soil temperature were well simulated using DNDC across sites. • DNDC showed reasonable performances in estimating soil water and inorganic N contents. • DNDC captured the manure application timing and rate impacts on total N 2 O emissions. • Daily N 2 O simulations may be improved by integrating N 2 O diffusivity and consumption. It is uncertain whether process-based models are currently capable of simulating the complex soil, plant, climate, manure management interactions that influence soil nitrous oxide (N 2 O) emissions from perennial cropping systems. The objectives of this study were (1) to calibrate and evaluate the DeNitrification DeComposition (DNDC) model using multi-year datasets of measured nitrous oxide (N 2 O) fluxes, soil moisture, soil inorganic nitrogen, biomass and soil temperature from managed grasslands applied with manure slurry in contrasting climates of Canada, and (2) to simulate the impact of different manure management practices on N 2 O emissions including slurry application i) rates (for both single vs. split); and ii) timing (e.g., early vs. late spring). DNDC showed "fair" to "excellent" performance in simulating biomass (4.7% ≤ normalized root mean square error (NRMSE) ≤ 29.8%; −9.5% ≤ normalized average relative error (NARE) ≤ 16.1%) and "good" performance in simulating soil temperature (13.2% ≤ NRMSE ≤ 18.1%; −0.7% ≤ NARE ≤ 10.8%) across all treatments and sites. However, the model only showed "acceptable" performances in estimating soil water and inorganic N contents which was partially attributed to the limitation of a cascade water sub-model and inaccuracies in simulating root development/uptake. Although, the DNDC model only demonstrated "fair" performance in simulating daily N 2 O fluxes, it generally captured the impact of the timing and rate of slurry application and soil texture (loam vs. sandy loam) on total N 2 O emissions. The DNDC model simulated N 2 O emissions from spring better than split manure application (fall and spring) at the Manitoba site partially due to the overestimation of available substrates for microbial denitrification from fall application during the wet spring periods. Although DNDC performed adequately for simulating most of the manure management impacts considered in this study we recommend improvements in the simulation of soil freeze-thaw cycles, manure decomposition dynamics, soil water storage, rainfall canopy interception, and microbial denitrification and nitrification activities in grasslands. [ABSTRACT FROM AUTHOR]

The DeNitrification-DeComposition (DNDC) model was developed to better simulate alfalfa (Medicago sativa L.) production with winterkill effects in eastern Canada. The pre-development DNDC produced "fair" simulations of alfalfa yield and biomass (index of agreement (d) > 0.7, Nash-Sutcliffe efficiency (NSE) > 0) but normalized root mean square error (nRMSE) was > 30% whereas the improved model indicated "good" to "excellent" performance (nRMSE = 3.9–29%; d = 0.93–0.99; NSE = 0.76–0.99). Under future RCP4.5 and 8.5 scenarios, average annual yields increased by 60.3% and 81.8% respectively due to earlier planting/spring regrowth with additional cuttings, increased C assimilation and reduced water stress under higher CO 2 concentrations. For locations at Ottawa and Quebec City there could be an increased incidence of winterkill under future climate due to reduced snow cover which leads to colder soil/crown temperatures as well as reduced fall hardening. This study indicated that the use of winter hardy cultivars could mitigate winterkill effects and increase production. • Alfalfa biomass and yield were used to develop improved alfalfa growth functions in DNDC. • Integrated winterkill effects including hardening and dehardening with cultivar specificity. • Improved DNDC model showed lower bias in biomass than pre-development version. • Yields increased notably under future climate due to early planting and more cuts. • Winterkill incidence remained a problem under future scenarios due to less snow cover. [ABSTRACT FROM AUTHOR]

• Both DNDC and DSSAT simulated maize yield, above-ground biomass and N uptake well. • DNDC showed lower bias than DSSAT in SOC and mineral N under N-fertilized treatments. • Modelled optimum fertilizer nitrogen rate was at 180–210 kg N ha−1 with two splits. • Suggested planting date was from late April to early May and density was 7 seeds m−2. Process-based models are valuable tools for simulating crop production, estimating agronomic efficiency and developing optimum management practices to achieve sustainable agriculture. However, a comparison of the DeNitrification-DeComposition (DNDC) and Decision Support System for Agrotechnology Transfer (DSSAT) models has not been previously used to optimize management practices for spring maize in northeast China. The objectives of this study were to evaluate the performance of the DSSAT and DNDC models in simulating maize growth and soil C & N dynamics and analyse their weaknesses and strengths based on a 7-year spring maize study in northeast China; and to explore the optimal management practices for improving maize production and nitrogen use efficiency under 20-year climate variability. Both DNDC and DSSAT exhibited "good" to "excellent" performance in simulating maize yield, above-ground biomass and plant N uptake for ecological intensification with N fertilizer (EI-N) and farmers' practice with N fertilizer (FP-N) treatments based on percent bias (PBIAS) of −10.5–4.2%, a normalized root mean squared error (nRMSE) of 7.5–17.2%, a Nash-Sutcliffe efficiency (NSE) of 0.17–0.77 and a d index of agreement (d) of 0.81–0.94. Both models showed "fair" to "good" performance in the same simulation for EI without N fertilizer (EI-N0) and FP without N fertilizer (FP-N0) treatments, but the maize yield simulation was better for the DSSAT model. In addition, the two models provided "fair" performance for N-fertilized treatments to "poor" performance for N-unfertilized treatments in simulations of soil organic carbon (0–0.20 m) and mineral N (0–0.30 m), but the simulations were better for the DNDC model. Sensitivity analyses indicated that the optimum yield and agronomic efficiency were achieved at a planting date of late April to early May, a fertilizer N application rate of 180–210 kg N ha−1 with two timing splits in the DNDC and DSSAT model and a planting density of 7 seeds m−2 in the DSSAT model. This study suggests that comparing the management scenarios of multiple dynamic models is more beneficial to develop best management practices for improving crop production and fertilizer use efficiency. [ABSTRACT FROM AUTHOR]

Abating ammonia (NH 3) volatilization from intensive cropping system is of great importance for preventing the pollution of atmospheric environment and sustainable agriculture. Urea, a common nitrogen fertilizer, can convert to an unstable carbamate and further releases NH 3 from the fields. However, few investigations of NH 3 volatilization loss following fertilizer application to agricultural soils have been done using process-based models. In this study, a two-year field study was conducted to calibrate and evaluate the DeNitrification-DeComposition (DNDC) model for simulating NH 3 volatilizations and crop production for the rice-wheat rotation system under four fertilizer regimes: control group without N fertilizer (CK), chemical fertilizer (CF), mixed application of inorganic and organic fertilizer (MF), and organic fertilizer (OF) treatments. The calibrated and modified DNDC performed effectively in simulating cumulative NH 3 volatilization (coefficient of determination (R2) = 0.96 for rice and 0.92 for wheat field, relative deviation (RD) = −6.3% - 2.1% for rice and −22.5 to −4.6% for wheat) and grain yields for both crops (R2 = 0.94 for rice and 0.91 for wheat, RD of rice: 4.94%–9.59%; wheat: −1.84%–11.51%). The sensitivity analysis demonstrated that NH 3 volatilization from rice-wheat rotation field was most sensitive to N application rate. Compared to CF and OF, MF treatments significantly mitigated NH 3 volatilization and improved crop yield. Therefore, scenario simulation was conducted to confirm the optimal N application rate under MF. The results revealed that 250 kg N ha−1 and 112.5 kg N ha−1 in MF were recommended for rice- and wheat-growing, respectively. Compared to the current N fertilizer rate, the recommended rate saved 50 kg N ha−1 and mitigated NH 3 volatilization loss by 28.31% from rice field and saved 37.5 kg N ha−1 and mitigated NH 3 volatilization loss by 19.29% from wheat field. Overall, the calibrated DNDC model proved to be an effective tool to simulate NH 3 volatilization from the rice-wheat rotation system and provides a promising fertilizer management strategy to decrease N input and mitigate NH 3 volatilization. [Display omitted] • DNDC model simulates NH 3 emission and crop yield for rice-wheat rotation system. • Coefficient of determination for NH 3 emission by DNDC ranged from 0.92 to 0.96 • Sensitivity analysis showed NH 3 emission was most sensitive to N application rate. • Scenario simulation was conducted to confirm the optimal N application rate. • Optimized N application rate reduces N input and mitigates NH 3 volatilization. [ABSTRACT FROM AUTHOR]

Optimizing management practices is essential to guarantee crop yield and reduce greenhouse gas emissions for the sustainable agricultural production under climate change. The objectives of this study were to i) calibrate and evaluate the Denitrification-Decomposition (DNDC) model using the measurements of maize yield, nitrogen (N) uptake, soil temperature, soil moisture, soil inorganic N and nitrous oxide (N 2 O) emissions from a 5-year maize field experiment in Northeast China (NEC) and ii) simulate the impacts of climate change on maize yield and N 2 O emissions and explore adaptation strategies based on DNDC modelling. For N-fertilized treatments (farmers' practice, FP-N; current optimized management, OPT-N), the DNDC model overall showed "good" performance in simulating maize yield, aboveground biomass, N uptake and soil inorganic N based on the average statistical values. The model also performed well in simulating soil moisture, soil temperature and N 2 O emissions. For N-unfertilized treatments, however, the DNDC model overestimated crop yield and N uptake mainly due to the overestimation of crop growth under low-temperature stress conditions, and the underestimation of soil inorganic N resulted from the underestimated N mineralization and N availability from the dissolved inorganic N pools under continuous N deficiency. The DNDC model showed that compared to the baseline scenario, future climate change would improve the maize yield (1.4–8.8%) while increasing the N 2 O emissions (37.6–83.4%) without adaptation measures in NEC. Compared to OPT-N management, solely adjusting N fertilization rate (200–220 kg N ha−1) would concurrently increase maize yield (5.0–8.7%) and N 2 O emissions (0.9–18.6%), while the adoption of optimized planting dates (April 27th to May 18th), new cultivars (with thermal degree days ranging from 2550 to 2700 °C), and the implementation of no-tillage and maize-soybean rotation would increase the maize yield by 1.8–8.9% and reduce the N 2 O emissions by 0.7–26.5% under future climate change scenarios. This study provided insights into the adaptive management strategies for the sustainable maize production under climate change in NEC. • Maize yield and N 2 O emissions for N-fertilized treatments were well simulated by DNDC. • DNDC overestimated maize yield and biomass under N-deficiency stress conditions. • Climate change would increase maize yield and N 2 O loss without adaptation measures. • Adjusting planting dates, no-tillage and rotation are effective in N 2 O reduction. [ABSTRACT FROM AUTHOR]

Potato is the largest non-cereal food crop in the world, and its sustainable production is critical for global food security. Enhanced-efficiency fertilizers (EEFs), when used in potato cropping systems, improve nitrogen use efficiency (NUE) and reduce nutrient losses, although the effectiveness of EEFs varies considerably with different management and environmental conditions. In this context, a meta-analysis of 56 studies (including 65 experimental sites) reported from across the world was conducted to evaluate the effects of EEFs (polymer-coated urea [PCU], nitrification inhibitor [NI], urease inhibitor [UI], and urease and nitrification inhibitors combined [NIUI]) on the yield, N uptake, NUE, and N losses (via nitrate [NO 3 −] leaching, ammonia [NH 3 ] volatilization, and nitrous oxide [N 2 O] emissions) in potato fields. The yield responses to EEF application under different management and environmental conditions, including the N application rate, planting density, climatic conditions, and soil properties, were comprehensively analyzed. It was observed that, compared to the traditional fertilizer, EEFs reduced the N 2 O emissions by 0.3 kg N ha–1 (32.2%), NO 3 − leaching by 15.6 kg N ha–1 (35.1%), and N application rates by 32.8 kg N ha–1 (16.8%), without any yield loss. The UIs were the most effective in increasing the potato yield, N uptake, and NUE (by 7.6%, 12.1%, and 34.6%, respectively), while the NIs were most effective in reducing the N 2 O emissions (by 49.4%). In addition, PCU was most effective in reducing NO 3 − leaching and NH 3 emissions, with an average reduction of 18.5% and 74.3%, respectively. Tradeoffs were observed between N 2 O reduction and potato yield improvement with the use of NI and UI. However, the potato yield did not improve significantly with the use of NI fertilizers. The agronomic benefits of EEFs were mainly dependent on potato yield, soil pH, N application rate, soil organic carbon content, soil total N, and soil texture. Therefore, it was inferred that the selection of an appropriate EEF application strategy based on the environmental conditions and implementing it with the corresponding N application rate was important. [Display omitted] • Efficacy of enhanced-efficiency fertilizers (EEFs) was assessed using meta-analysis. • Maximum potato yield was obtained under the application of urease inhibitor. • Nitrification inhibitor favored nitrous oxide mitigation compared with other EEFs. • Polymer-coated urea was optimal for reducing nitrate leaching and ammonia emissions. • Agronomic benefit of EEFs depend on management practices and environmental conditions. [ABSTRACT FROM AUTHOR]

Linking potassium (K) balance to soil fertility creates a valuable indicator for sustainability assessment in agricultural land-use systems. It is crucial for the efficient use of K resources, food security and resource sustainability to realize soil K balance status in China. Therefore, temporal and spatial changes of K balance for farmland in China from 1980 to 2015 were analyzed at national and regional levels using statistical data and related parameters. At the national scale, K input increased from 6.78 Mt K2O in 1980 to 23.44 Mt K2O in 2015 with an average annual increment of 0.48 Mt K2O, and output changed from 8.10 Mt in 1980 to 21.31 Mt in 2015 with an average annual increment of 0.38 Mt K2O as well. On average, K balance was -24.17, -5.92, 21.31 and 19.50 kg K2O ha-1 in 1980s, 1990s, 2000s and 2010s, respectively. Moreover, the average balance of six regions was considerably different which were -21.37, 1.25, 13.70, -22.79, 99.22 and 7.18 kg K2O ha-1 from 1980 to 2015. The potassium use efficiency (KUE) decreased with time which were 127.09, 104.35, 87.69 and 89.69% in 1980s, 1990s, 2000s and 2010s, respectively, and the decline of slope could also reflect the variation tendency of KUE. Great variation of K balance across different regions demonstrated that fertilizer application and management practices need to be adjusted to local conditions. [ABSTRACT FROM AUTHOR]

Application of urease and nitrification inhibitors is an effective strategy for decreasing nitrogen (N) losses without negatively impacting yields, but the long-term impacts of inhibitors and N placement on N dynamics remains unclear. The objectives of this study were to 1) use a 3-year maize experiment in southwestern Ontario to evaluate the Denitrification-DeComposition (DNDC) model fitted with default and enhanced urea hydrolysis mechanisms, 2) determine the impacts of climate variability (30-year) on inhibitor performance on maize yield and N losses under a range of N treatments, and 3) estimate the optimal N application rates for maintaining high yield and minimizing N losses. The experiment treatments included a factorial arrangement of two N sources (urea, urea ammonium nitrate [UAN]), three N placement methods (broadcast urea [B-Urea], broadcast incorporated urea [BInc-Urea], injected UAN [Inj-UAN]), and three inhibitors (no inhibitor, urease inhibitor [UI], urease plus nitrification inhibitor [UI&NI]). Although both the default and improved model provided "fair" to "good" simulations of maize yield, N uptake, soil temperature, soil moisture, soil inorganic N content and nitrous oxide (N 2 O) emissions across treatments, more accurate simulations were obtained using the improved model. The default DNDC model indicated "poor" simulations of ammonia (NH 3) volatilization according to the Nash-Sutcliffe efficiency (NSE <0) and index of agreement (d ≤ 0.38), whereas the improved DNDC produced "good" simulations (NSE = 0.22–0.39, d = 0.65–0.84) because of improved estimates of urea diffusion, hydrolysis and inhibitor efficiency. The 30-year simulation based upon 95% of the maximum yield resulted in annual NH 3 losses of 35.4 kg N ha−1 for B-Urea and these losses were reduced by 40.1% with BInc-Urea and by 92.7% with Inj-UAN. When UI was added to either B-Urea or BInc-Urea, NH 3 losses were reduced by 61.8–66.4%, whereas when UI&NI was added, losses were reduced by 41.0–49.4%. The Inj-UAN reduced annual N 2 O losses by 18.8% compared to B-Urea whereas two inhibitor treatments of B-Urea + UI&NI and BInc-Urea + UI&NI reduced N 2 O losses by 11.5–11.8% compared to B-Urea and BInc-Urea. Simulated annual N losses from Inj-UAN + UI&NI were reduced relative to Inj-UAN + UI because of decreased NO 3 − leaching. Simulated long-term average percentage of annual total N losses at the optimal N rate were 36.8, 30.8 and 22.0% from B-Urea, BInc-Urea and Inj-UAN, respectively, which reduced to 25.9–28.1, 24.9–25.5 and 21.2–21.9%, when inhibitors were added. Our study suggests that the DNDC model can be used to investigate the impacts of climate variability on inhibitor performance and determine the optimum range of N application rates for different inhibitor treatments. [Display omitted] • Model was developed with enhanced representations of urea diffusion and hydrolysis. • The improved model performed better in estimating daily ammonia volatilization. • Both models demonstrated good simulations of maize growth and soil nitrogen dynamics. • The long-term climate variability impacts on inhibitor performance were simulated. • Inhibitors allowed high maize yields with a reduction of 15–28 kg N ha−1 for urea. [ABSTRACT FROM AUTHOR]

Optimized fertilization is an effective strategy for improving nitrogen (N) use efficiency and maintaining high crop yield, but its long-term impacts on soil organic carbon (C) and inorganic N dynamics remain unclear. The objectives of this study were to 1) explore the economic optimum N rate and evaluate the DSSAT CERES-Maize model using the measurements from three 3-year maize (Zea mays L.) field experiments, in Gongzhuling and Yushu County, Northeast China, and 2) assess the long-term impacts of farmers' N rate (N250), optimum N rate (N180) and organic-inorganic combined N rate (MN180) on maize yields, soil N and C changes from 1985 to 2020. Results showed that similar maize yields of 8000–11,000 kg ha−1 were achieved under the average economic optimum N rate of 170 kg N ha−1 relative to N250 in both counties. Good agreements were observed between the simulated and measured maize yield, above-ground biomass, N uptake and soil nitrate (NO 3 −-N). Long-term simulation confirmed that N180 and MN180 can achieve the same yield as N250 in both counties. The lowest annual soil inorganic N balance, NO 3 −-N leaching, and nitrous oxide (N 2 O) and ammonia (NH 3) emissions were achieved under MN180, followed by N180 in both sites. Higher NO 3 −-N leaching was found in sandy clay loam soil than silt clay loam and clay loam soils. Average soil organic C (SOC, 0–0.2 m) increased from 1.3 to 2.4% in Gongzhuling and from 2.2 to 2.4% in Yushu under MN180 during the 35-year period, but it showed declining trends under N180 and N250. We concluded that the economic optimum N rate could be an option to replace current farmers' N rate for the continuous maize. Substitution of inorganic fertilizer by 20–30% manure under the optimum N rate showed advantage on maintaining high yield, reducing soil inorganic N losses as well as increasing SOC stock for sustainable agriculture. • Economic optimum N rate saved 23–76 kg N ha−1 compared with the maximum N rate. • DSSAT well simulated maize growth and soil N dynamics under multiple sites. • Soil N balance and SOC were simulated under long-term fertilization scenarios. • Substitution with 20–30% manure under optimum N rate maintained maize yields with high SOC and low N losses. [ABSTRACT FROM AUTHOR]

The excessive and inappropriate application of nitrogen (N) fertilizer in open vegetable fields is a major anthropogenic source of gaseous N losses including nitrous oxide (N 2 O) and ammonia (NH 3) emissions in China. A 2-yr Chinese cabbage (Brassica pekinensis L.) experiment was carried out to explore the impacts of optimized N management (reduced N application rate, controlled-release urea [CRF] and nitrification inhibitor [NI]) on cabbage yield, soil inorganic N, and N 2 O and NH 3 emissions, and to assess their economic benefits by a cost-benefit analysis. Six treatments including i) no N fertilizer (CK), ii) conventional urea fertilizer at 400 kg N ha−1 based on farmers' practices (CN), iii) conventional urea at 320 kg N ha−1 (RN), iv) conventional urea (320 kg N ha−1) with the addition of NI (RN + NI), v) CRF at 320 kg N ha−1 (CR) and vi) CRF (320 kg N ha−1) with the addition of NI (CR + NI) were implemented in an open Chinese cabbage field. No significant differences were found in the cabbage yields and soil NH 4 +–N contents under different N fertilization treatments. Only CR + NI treatment had significantly lower soil NO 3 −–N contents than CN by 17.6%–34.6% at the early growing stages of cabbage in both years. Compared with CN, the N 2 O emissions were significantly decreased by 8.61%, 34.4%, 37.8% and 46.6% under RN, RN + NI, CR and CR + NI, respectively, indicating that CR + NI favors N 2 O abatement especially when NH 3 has been suppressed by other 4 R practices. Meanwhile, the NH 3 volatilization was 20.6% higher under RN + NI and 30.8% and 17.3% lower under CR and CR + NI compared to CN, respectively, which implied that CR was the most effective treatment in reducing the NH 3 volatilization and total gaseous N loss in high NH 3 –N loss scenarios. Moreover, the net benefit of RN decreased by $945 USD ha−1 and those of RN + NI, CR and CR + NI treatments increased by $855, $930 and $1004 USD ha−1 compared to CN, respectively. This study recommends CR + NI as the optimal N fertilizer management for the sustainable production of vegetables with the lowest environmental risks and the greatest economic benefits. • Optimizing nitrogen (N) rate and source decreased N 2 O and NH 3 without yield loss. • Controlled-release N fertilizer (CRF) was optimal for reducing NH 3 loss by 30.8%. • N 2 O emission was mitigated by 46.6% under CRF with nitrification inhibitor (NI). • The net economic benefit of cabbage was increased by $1004 USD ha−1 under CRF + NI. • CRF + NI was cost-effective in achieving agronomical and environmental sustainability. [ABSTRACT FROM AUTHOR]

Mineral fertilizers have played a critical role in increasing cereal crop production in China. However, the use of fertilizer at rates in excess of crop removal or to support soil health has resulted in serious environmental problems, this hindering sustainable agriculture development. In order to support crop production and reduce potential environmental risks, it is essential that every effort is made to promote an efficient and effective use of phosphorus (P) resources. In this paper, the temporal and spatial changes of soil available P was analyzed using 59,956 soil samples, combined with the results of 4837 field experiments compiled from the International Plant Nutrient Institute (IPNI) China program database from 1990 to 2012. The results demonstrated that soil available P content showed an increasing trend with a slope of 1.51 from 1990 to 2012. However, this trend for all samples was separated into cash crops (with a slope of 2.75) and grain crops (with a slope of 0.76) revealing that it was cash crops that were primarily responsible for the increasing trend. Field trail results revealed that it was the high P fertilizer application rates to cash crops that resulted in the increase of soil available P. On average, for all crops, the soil analysis data showed that soil available P increased from 17.09 mg L −1 in the 1990s (from 1990 to 2000) to 33.28 mg L −1 in the 2000s (from 2001 to 2012), again mainly due to the large increase in cash crop area in China. For relative yield, there was little to no variation across regions (with mean values of 87.8%, 87.8%, 84.4%, 88.1% and 86.0% for the NE, NC, NW, SE and SW regions, respectively), but the trend of variation showed great differences in those same regions from the 1990s to the 2000s. The relative yield for grain crops in the NE, NC, SE and SW increased by 2.6%, 7.9%, 6.9% and 8.6%, but decreased by 4.9% in the NW from the 1990s to the 2000s. The relative yield for cash crops decreased by 6.7%, 6.0% and 1.6% for the NE, SE and SW regions, but increased by 8.3% and remained unchanged for the NC and NW regions, respectively. The great variation observed in soil available P across the different regions in China demonstrated the urgent need for site-specific P nutrient management. In conclusion, while P fertilizer application should meet the requirements for all types of crops, it must be managed to avoid the potential for negative environmental impacts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Nutrient Expert (NE), is designed through adoption of 4R nutrient stewardship. • Results show that NE achieved higher yields, higher profitability, and lower environmental risks. • An outstanding advantage of NE is user-friendly and can be easily acquired by all farmers with smartphones. Fertilizer has revolutionized crop production, but a lack of evidence-based fertilizer usage has resulted in negative economic and environmental ramifications, particularly for smallholder farmers. This study aimed at developing an innovative nutrient recommendation approach, Nutrient Expert (NE), for improving yields of maize, wheat, and rice while optimizing fertilizer input through adoption of 4R (applying the right source of nutrients at the right rate, time and place) nutrient stewardship technologies, and evaluating the large-scale performance on crop productivity and the environmental impact of cropping systems. Thus, we compared NE to current farmers' practice (FP) and soil test-based fertilizer application (ST) for 1,534 farm field experiments in order to validate the benefits of NE on both crop productivity and environmental protection in the main cereal production areas in China. Overall, the NE treatment achieved 4.4 % higher grain yield and 5.8 % more profit over FP, more yield for rice, but no differences for maize and wheat over ST. Nutrient Expert required 29.0 % and 14.7 % less fertilizer N than FP and ST, respectively. The NE recommendations improved the nitrogen (N) recovery efficiency by 10.8–13.4 percent points over FP across the 1,534 sites. Using the NE approach, on average, reactive N losses and greenhouse gas (GHG) emissions were reduced by 36.2 % and 21.5 % over FP, 16.0 % and 9.9 % over ST, respectively. The NE, as a user-friendly tool, is widely applicable across farm types and climatic regions. It could be beneficial for improving fertilizer use efficiency and maintaining strategic food security for smallholder production areas in China where N fertilizer is inappropriate and usually over applied. This approach could potentially be expanded to help reduce N losses and GHG emissions in other regions globally. [ABSTRACT FROM AUTHOR]

Process-based models are effective tools for assessing the sustainability of agricultural productivity and environmental health under various management practices and rotation systems. The objectives of this study were to (1) calibrate and evaluate the DeNitrification-DeComposition (DNDC) model using measurements of yields, nitrogen (N) uptake, soil inorganic N, soil temperature, soil moisture and nitrous oxide (N 2 O) emissions under long-term fertilized continuous corn (CC) and corn-oats-alfalfa-alfalfa (COAA) rotation systems in southwest Ontario from 1959 to 2015, Canada, and (2) explore the impacts of four diverse rotation systems (CC, COAA, corn-soybean-corn-soybean (CSCS) and corn-soybean-winter wheat (CSW)) on corn yields and annual N 2 O emissions under long-term climate variability. DNDC demonstrated "good" performance in simulating corn, oats and alfalfa yield (normalized root mean square error (nRMSE) < 20%, Nash-Sutcliffe efficiency (NSE) > 0.5 and index of agreement (d) > 0.8). The model provided "fair" to "good" simulations for corn N uptake and soil inorganic N (NSE > 0.2 and d > 0.8), and also daily soil temperature and soil moisture (nRMSE <30% and d > 0.7) for both calibration and validation periods. The model demonstrated "good" performance in estimating daily and cumulative N 2 O emissions from both the continuous and rotational corn, whereas it produced "poor" to "good" predictions for N 2 O emissions from the rotational oats and alfalfa crops, however, the emissions from these crops were very low and the relative magnitude of these emissions between all crops investigated were well predicted. The lowest N 2 O emissions were from COAA followed by CSCS, CSW then CC. The highest corn yields were from COAA, followed by CSW, CSCS, then CC. This study highlights how modelling approaches can help improve the understanding of the impacts of diversified rotations on crop production and greenhouse gas emissions and contribute towards developing policies aimed at improving the sustainability and resiliency of cropping systems. Unlabelled Image • Crop yields were well simulated under both monoculture and rotation systems using DNDC. • Suggest model development for excess water stress on crops and rainfall interception. • N 2 O emissions from corn were predicted more accurately than from oats and alfalfa crops. • DNDC predicted benefits to corn growth when in rotation with a legume crop. • Long-term simulations showed higher yield and lower N 2 O in corn rotation than in monoculture. [ABSTRACT FROM AUTHOR]

Assessment of the impact of climate change on agricultural sustainability requires a robust full system estimation of the interdependent soil-plant-atmospheric processes coupled with dynamic farm management. The simplification or exclusion of major feedback mechanisms in modelling approaches can significantly affect model outcomes. Using a biogeochemical model, DNDCv.CAN, at three case-study locations in Canada, we quantified the impact of using commonly employed simplified modelling approaches on model estimates of crop yields, soil organic carbon (SOC) change and nitrogen (N) losses across 4 time periods (1981–2010, 2011–2040, 2041–2070, and 2071–2100). These approaches included using climate with only temperature and precipitation data, annual re-initialization of soil status, fixed fertilizer application rates, and fixed planting dates. These simplified approaches were compared to a more comprehensive reference approach that used detailed climate drivers, dynamic planting dates, dynamic fertilizer rates, and had a continuous estimation of SOC, N and water budgets. Alternative cultivars and rotational impacts were also investigated. At the semi-arid location, the fixed fertilizer, fixed planting date, and soil re-initialization approaches reduced spring wheat (Triticum aestivum L.) yield estimates by 40%, 25%, and 29%, respectively, in the 2071–2100 period relative to the comprehensive reference approach. At both sub-humid locations, the re-initialization of soil status significantly altered SOC levels, N leaching and N runoff in all three time periods from 2011 to 2100. At all locations, SOC levels were impacted when using simplified approaches relative to the reference approach, except for the fixed fertilizer approach at the sub-humid locations. Results indicate that simplified approaches often lack the necessary characterization of the feedbacks between climate, soil, crop and management that are critical for accurately assessing crop system behavior under future climate. We recommend that modellers improve their capabilities of simulating expected changes in agronomy over time and employ tools that consider robust soil-plant-atmospheric processes. Unlabelled Image • Assess approaches for modelling climate change impact on cropping systems at 3 sites. • Simplified approaches were compared to a comprehensive reference approach. • At semi-arid site simplified approaches differed from reference for yield simulation. • Differences in N losses occurred between each approach and the reference approach. • Simplified approaches frequently could not capture soil-climate-crop feedbacks. [ABSTRACT FROM AUTHOR]

• Phenol, PNP and p-DHB removals were investigated in MABR over 184 days. • Phenolic compounds were degraded at 8.9 g/m2 d under the salinity of 32 g NaCl/L. • The phenolic-degrading genes were explored deeply through metagenomic sequencing. • Pseudomonas and Rhodococcus were the key contributor for phenolic degradation. • Various relation modules of bacteria ensured efficient phenolic removal in MABR. High saline phenolic wastewater is a typical toxic and refractory industrial wastewater. A single membrane–aerated biofilm reactor (MABR) was used to treat wastewater containing phenol, p –nitrophenol and hydroquinone under increasing phenolic loading and salinity conditions. More than 95 % of phenolic compounds were removed, and a removal efficiency of 8.9 g/m2 d for total phenolic (TP) contents was achieved under conditions with 32 g/L of salt and 763 mg/L of influent TP contents. The microbial diversity, structure and function of a biofilm exposed to different conditions were investigated by high–throughput 16S rRNA gene sequencing and metagenomics. Salinity and specific TP loading substantially affected the bacterial community. Gammaproteobacteria, Actinobacteria and Betaproteobacteria contributed more to initial phenolic compound degradation than other classes, with Pseudomonas and Rhodococcus as the main contributing genera. The key phenolic–degrading genes of different metabolic pathways were explored, and their relative abundance was strengthened with increasing phenolic loading and salinity. The diverse cooperation and competition patterns of these microorganisms further promoted the high removal efficiency of multiple phenolic contaminants in the biofilms. These results demonstrate the feasibility of MABR for degrading multiple phenolic compounds in high saline wastewater. [ABSTRACT FROM AUTHOR]

• Using estimated temperatures under snow cover is required for the simulation of alfalfa regrowth in eastern Canada with DSSAT. • The simulated values of aboveground biomass across all sites and years in the six experimental datasets were acceptable. • Additional model functions may be required to further improve the simulation of alfalfa regrowth for climate change. • Functions on reduced plant density by freezing and snow insulation are needed for modelling in northern regions. Alfalfa (Medicago sativa L.) is the predominant forage legume species in Canada and is considered a prioritized option for sustainable cropping under climate change. Crop growth models provide an opportunity to explore the potential impacts of climate change on alfalfa and for evaluating potential adaptation options. For this study, six experimental datasets in eastern Canada were used to parameterize the newly adapted CSM-CROPGRO-Perennial Forage Model (CSM-CROGRO-PFM) in simulating alfalfa regrowth and to identify areas for further model improvement needed for climate change assessments in the northern agricultural regions of North America. Estimated air temperatures under snow cover were used successfully to drive the CSM-CROPGRO-PFM model for simulating alfalfa regrowth in eastern Canada. The simulated values of aboveground biomass across all sites and years were acceptable with a root mean square error (RMSE) of 936 kg dry matter (DM) ha−1 and a normalized RMSE of 24%. A sensitivity analysis of the model revealed that with no change in the number of harvests per year, the simulated annual herbage yield (harvestable biomass) declined with increasing temperature, increased with elevated atmospheric CO 2 concentration, and changed little with increased precipitation. However, the increase in the number of harvests made possible by warmer temperatures may increase the simulated annual herbage yield. Although most alfalfa physiological processes were successfully simulated, some additional model functions may be required to further improve the simulation of alfalfa regrowth for climate change studies conducted in Canada. These functions include quantifying plant density decline and its relationship with biomass in post-seeding years, estimating temperatures surrounding alfalfa crowns during the overwintering period, and simulating herbage nutritive attributes. [ABSTRACT FROM AUTHOR]