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Coastal ecosystems are highly susceptible to salt-related problems due to their formation process and geographical location. As such ecosystems are the most accessible land resources on Earth, clarifying and quantifying the effects of salt-alkali conditions on N concentration and ammonia (NH3) volatilization are pivotal for promoting coastal agricultural productivity. The challenge in establishing this effect is to determine how salt-alkali conditions impact NH3volatilization through direct or indirect interactions. An incubation experiment using a coastal soil from a paddy farmland, combined with the structural equation modeling (SEM) method, was conducted to reveal the net effects of salt-alkali on NH3volatilization and the role of environmental and microbial factors in mutual interaction networks. The specific experimental design consisted of four salt treatments (S1, S2, S3, and S4: 1‰, 3‰, 8‰, and 15‰ NaCl by mass of soil, respectively), four alkaline treatments (A1, A2, A3, and A4: 0.5‰, 1‰, 3‰, and 8‰ NaHCO3by mass of soil, respectively) and a control without NaCl or NaHCO3addition (CK), and each treatment had three urea concentrations (N1, N2, and N3: 0.05, 0.10, and 0.15 g N kg-1soil, respectively) and three replicates. At the N1, N2, and N3 levels, NH3volatilization increased by 9.31%–34.98%, 3.07%–26.92%, and 2.99%–43.61% as the NaCl concentration increased from 1‰ to 15‰, respectively, compared with CK. With an increase in the NaHCO3concentration from 0.5‰ to 8‰, NH3volatilization increased by 8.36%–56.46%, 5.49%–30.10%, and 30.72%–73.18% at the N1, N2, and N3 levels, respectively, compared with CK. According to the SEM method, salinity and alkalinity had positive direct effects on NH3volatilization, with standardized path coefficients of 0.40 and 0.19, respectively. Considering the total effects (net positive and negative effects) in the SEM results, alkalinity had a greater influence than salinity (total standardized coefficient 0.104 > 0.086). Nitrogen concentrations in the incubation system showed a direct positive effect on NH3volatilization (standardized path coefficient = 0.78), with an obvious decrease under elevated salinity and alkalinity levels. Additionally, gene abundances of nitrogen-transforming microbes indirectly increased NH3volatilization (total indirect standardized coefficient = 0.31). Our results indicated that potential NH3emissions from coastal saline areas could be enhanced more by soil alkalization than by salinization.

The impacts of biochar addition with nitrogen fertilizer (Urea-N) on greenhouse gas (GHG) fluxes and grain yields are not comprehensively understood. Therefore, we designed a field experiment in an intensive rice–wheat cropping system located in the Taihu Lake region of China and measured CH4and N2O emissions for 2 consecutive years to examine the impacts of biochar combined with N-fertilizer on rice production and GHG flux. Three field experimental treatments were designed: (1) no N-fertilizer application (N0); (2) 270 kg N ha−1application (N270); and (3) 270 kg N-fertilizer ha−1plus 25 t ha−1biochar application (N270 + C). We found that, compared with urea application alone, biochar applied with Urea-N fertilizer increased N use efficiency (NUE) and resulted in more stable growth of rice yield. In addition, biochar addition increased CH4emissions by 0.5–37.5% on average during the two consecutive rice-growing seasons, and decreased N2O–N loss by ~ 16.7%. During the first growing season, biochar addition did not significantly affect the global warming potential (GWPt) or the greenhouse gas intensity (GHGI) of rice production (p> 0.05). By contrast, during the second rice-growing season, biochar application significantly increased GWPt and GHGI by 28.9% and 18.8%, respectively, mainly because of increased CH4emissions. Our results suggest that biochar amendment could improve grain yields and NUE, and increased soil GWPt, resulting in a higher potential environmental cost, but that biochar additions enhance exogenous carbon sequestration by the soil, which could offset the increases in GHG emissions.

Denitrification is one of the most challenging nitrogen (N)‐cycling processes to quantify due to complex interactions among influencing factors. In shallow water‐sediment systems, ubiquitous periphytic biofilms consisting of a consortium of algae, bacteria, and nutrients account for additional interactions. The challenge in improving denitrification models is to determine how each factor directly affects denitrification and how those factors indirectly impact denitrification via interactions with other factors. We combined incubation experiments and structural equation modeling to reveal the interaction networks of biotic and abiotic factors and their roles in net denitrification. The N species in the sediment exerted much greater control over net denitrification than that exerted by the N species in the water column. In addition, the relative abundances of denitrifier and nitrifier genes in the sediment showed a dominant control over net denitrification that was similar to the control by N species but was affected by abiotic factors. Periphytic biofilm increased net denitrification both directly and indirectly by altering the pH and the dissolved oxygen, dissolved organic carbon, and N concentrations in the water column and sediment. The overall contribution of periphytic biofilm to net denitrification was less than that of the sediment but greater than that of the water column. Our findings highlight the importance of incorporating bacterial denitrifier and nitrifier genes and periphytic biofilm characteristics during model construction when predicting denitrification in a shallow and stagnant water‐sediment system. SEM was used to reveal the interaction networks of biotic and abiotic factors and their roles in net denitrificationThe periphytic biofilm increased the denitrification rate directly and indirectlyWe suggest improving model precision by including periphytic and bacterial factors

Nitrate (NO3−) pollution is a serious problem worldwide, particularly in countries with intensive agricultural and population activities. Previous studies have used δ15N‐NO3−and δ18O‐NO3−to determine the NO3−sources in rivers. However, this approach is subject to substantial uncertainties and limitations because of the numerous NO3−sources, the wide isotopic ranges, and the existing isotopic fractionations. In this study, we outline a combined procedure for improving the determination of NO3−sources in a paddy agriculture‐urban gradient watershed in eastern China. First, the main sources of NO3−in the Qinhuai River were examined by the dual‐isotope biplot approach, in which we narrowed the isotope ranges using site‐specific isotopic results. Next, the bacterial groups and chemical properties of the river water were analyzed to verify these sources. Finally, we introduced a Bayesian model to apportion the spatiotemporal variations of the NO3−sources. Denitrification was first incorporated into the Bayesian model because denitrification plays an important role in the nitrogen pathway. The results showed that fertilizer contributed large amounts of NO3−to the surface water in traditional agricultural regions, whereas manure effluents were the dominant NO3−source in intensified agricultural regions, especially during the wet seasons. Sewage effluents were important in all three land uses and exhibited great differences between the dry season and the wet season. This combined analysis quantitatively delineates the proportion of NO3−sources from paddy agriculture to urban river water for both dry and wet seasons and incorporates isotopic fractionation and uncertainties in the source compositions. We outlined a combined procedure for improving the determination of NO3−sources in a paddy agriculture‐urban gradient watershedDenitrification was first incorporated into the Bayesian modelThe variation and uncertainty of different NO3−sources were quantified via SIAR

Nitrogen is an essential nutrient and a major limiting element for the ocean ecosystem. Since the preindustrial era, substantial amounts of nitrogen from terrestrial sources have entered the ocean via rivers, groundwater, and atmospheric deposition. China serves as a key hub in the global nitrogen cycle, but the pathways, sources, and potential mitigation strategies for land-ocean nitrogen transport are unclear. By combining the CHANS, WRF-Chem, and WNF models, we estimated that 8 million tonnes (Tg) of nitrogen was transferred into the ocean in 2017 in China, with atmospheric deposition contributing 1/3. About half variation of the offshore chlorophyll concentration was explained by atmospheric deposition. The Bohai Sea was the hot spot of nitrogen input, estimated at 214 kg N ha–1, while other areas were around 25–51 kg N ha–1. The largest contributors are agricultural systems (4 Tg, 55%), followed by domestic sewage (2 Tg, 21%). Abatement measures could reduce nitrogen export to the ocean by 43%, and mitigating ammonia and nitrogen oxide emissions accounts for 33% of this reduction, highlighting the importance of addressing air pollution in resolving ocean pollution. The cost-benefit analysis suggests the priority of nitrogen reduction in cropland and transport systems for the ocean environment.

Partial substitution of synthetic nitrogen with organic fertilizers (PSOF) is of great significance in improving deteriorated soil ecosystem functions caused by excessive application of chemical nitrogen fertilizer. However, existing studies typically focus on single soil functions, neglecting the fact that multiple functions occur simultaneously. How PSOF influences multiple soil functions and its relationship with soil microbial communities remain unclear. Here, we examined the impact of partial substitution (25-50%) of chemical nitrogen fertilizer with organic forms (pig manure or municipal sludge) in a vegetable field on multiple functions, involving primary production (vegetable yield and quality), nutrient cycling (soil enzyme activities, ammonia volatilization, nitrogen leaching and runoff) and climate regulation (soil organic carbon sequestration and nitrous oxide emissions). We observed that PSOF improved soil multifunctionality, with 50% substitution of pig manure being the best management practice to promote soil multifunctionality, which was strongly related to bacterial and fungal diversity and microbial network complexity. Further random forest analysis revealed that soil multifunctionality was best explained by bacterial-fungal network complexity, followed by available phosphorus levels and bacterial diversity. PSOF also shifted the composition of bacterial and fungal communities, with increased relative abundances of dominant bacteria phyla such as Bacteroidetes, Gemmatimonadetesand Myxococcota, and fungal phyla such as Basidiomycotaand Olpidiomycota. The observed increases in soil multifunctionality were consistent with significant increases in abundance of keystone taxa such as Blastocladiomycota, Chaetomiaceaeand Nocardiopsaceae. Together, these findings indicate that partial substitution of organic fertilizers can enhance interactions within and among microbial communities and has the potential to improve ecosystem multifunctionality and contribute to the development of sustainable agriculture.

Ammonia (NH3) volatilization from paddy soils is one of the main contributors to agricultural NH3emissions, however, little attention has been paid to the role of the ubiquitous periphyton in paddy soils on NH3volatilization. Considering that the composition of periphyton is dominated by autotrophs that directly affect the redox and pH conditions, it is hypothesized that the presence of periphyton may be an important factor affecting NH3emissions. In this study, NH3volatilization was determined under six periphyton biomass treatments and under treatments with six different N application rates to evaluate the contribution of periphyton to NH3volatilization in the laboratory representing the paddy soils system. Results showed that periphyton had trade‐off effects on NH3volatilization through pH and the NH4+concentration. Periphyton had net inhibition effects on NH3volatilization when the periphyton biomass was higher than 110 g·m−2. In contrast, periphyton had net promotion effects on NH3volatilization when the periphyton biomass was less than 110 g·m−2. The contribution of periphyton to NH3volatilization increased exponentially with increasing N application rates (i.e., with the increasing nitrogen concentration of the overlying water). In the low‐nitrogen treatments (≤20 kg N·ha−1), periphyton had no significant effect on NH3volatilization. In contrast, periphyton contributed as much as 47.4% of NH3volatilization at high nitrogen concentrations (100 kg N·ha−1). This study provides valuable insight into the role of periphyton on NH3volatilization, offers quantified relationship between periphyton and NH3volatilization, and improves the accuracy of NH3volatilization estimation in regional paddy soils. We first addressed the response of ammonia volatilization to periphyton in paddy soils role of periphyton on NH3volatilizationWe found a nonlinear contribution of periphyton to NH3volatilizationThis study offered implications in improving the accuracy of NH3volatilization estimation We first addressed the response of ammonia volatilization to periphyton in paddy soils role of periphyton on NH3volatilization We found a nonlinear contribution of periphyton to NH3volatilization This study offered implications in improving the accuracy of NH3volatilization estimation

Constructed wetland geography, including size and location, plays a key role in nutrient retention; it remains a challenge to isolate and quantify the contributions of wetland size and spatial location. We constructed a clear conceptual model and modeled the effects of variations in wetland size (represented as cells width in each flow path of a grid of cells) and location on the mean nutrient discharge (MD) and standard deviation of nutrient discharge (SdD). A basic comparison between a broadly and mathematically tractable Poisson distribution and a conventionally hypothesized uniform distribution showed that wetlands with a Poisson width or Poisson location distribution exhibit much greater effects on SdD than wetlands with a uniform distribution. We then compared and summarized the effects of 10,000 variations in wetlands on MD and SdD. For all kinds of wetlands, the MD was largely determined by the mean size, mean location, and evenness of location, while the SdD was closely related to the evenness and standard deviation (Sd) of both wetland size and location. Incorporating these factors into landscape models could greatly simplify the model structure and improve precision. Location was more important than size for both MD and SdD, regardless of the retention of the wetlands, which suggested that optimizing wetland location should be a high priority for water quality management and will yield greater benefits than widening wetlands elsewhere. We isolated and quantified the effects of variations in wetland size and location on nutrient dischargeLocation is more important than size for mean nutrient discharge and its variationsThe mean nutrient discharge and Sd could be predicted by simple CW variation statistics