Nitrous oxide (N2O) is a powerful greenhouse gas and the main driver of stratospheric ozone depletion. Since soils are the largest source of N2O, predicting soil response to changes in climate or land use is central to understanding and managing N2O. Here we find that N2O flux can be predicted by models incorporating soil nitrate concentration (NO3−), water content and temperature using a global field survey of N2O emissions and potential driving factors across a wide range of organic soils. N2O emissions increase with NO3− and follow a bell-shaped distribution with water content. Combining the two functions explains 72% of N2O emission from all organic soils. Above 5 mg NO3−-N kg−1, either draining wet soils or irrigating well-drained soils increases N2O emission by orders of magnitude. As soil temperature together with NO3− explains 69% of N2O emission, tropical wetlands should be a priority for N2O management.

[1] There is widespread recognition that the groundwater-surface water interface can have significant influence on the pattern and form of the transfer of nutrient-rich groundwater to rivers. Characterizing and quantifying this influence is critical for successful management of water resources in many catchments, particularly those threatened by rising nitrate levels in groundwater. Building on previous experimental investigations in one such catchment: the River Leith, UK, we report on a multimeasurement, multiscale program aimed at developing a conceptualization of groundwater-surface water flow pathways along a 200 m reach. Key to this conceptualization is the quantification of vertical and horizontal water fluxes, which is achieved through a series of Darcian flow estimates coupled with in-stream piezometer tracer dilution tests. These data, enhanced by multilevel measurements of chloride concentration in riverbed pore water and water-borne geophysical surveying, reveal a contrast in the contribution of flow components along the reach. In the upper section of the reach, a localized connectivity to regional groundwater, that appears to suppress the hyporheic zone, is identified. Further downstream, horizontal (lateral and longitudinal) flows appear to contribute more to the total subsurface flow at the groundwater-surface water interface. Although variation in hydraulic conductivity of the riverbed is observed, localized variation that can account for the spatial variability in flow pathways is not evident. The study provides a hydrological conceptualization for the site, which is essential for future studies which address biogeochemical processes, in relation to nitrogen retention/release. Such a conceptualization would not have been possible without a multiexperimental program.Citation: Binley, A., S. Ullah, A. L. Heathwaite, C. Heppell, P. Byrne, K. Lansdown, M. Trimmer, and H. Zhang (2013), Revealing the spatial variability of water fluxes at the groundwater-surface water interface, Water Resour. Res., 49,[3978][3979][3980][3981][3982][3983][3984][3985][3986][3987][3988][3989][3990][3991][3992]

Climate change, increasing populations, competing demands on land for production of biofuels, and declining soil quality are challenging global food security. Finding sustainable solutions requires bold new approaches and integration of knowledge from diverse fields, such as materials science and informatics. The convergence of precision agriculture, whereby farmers respond in real-time to changes in crop growth, with nanotechnology and artificial intelligence offers exciting opportunities for sustainable food production. Coupling existing models for nutrient cycling and crop productivity with nanoinformatics approaches to optimize targeting, uptake, delivery nutrient capture and long term impacts on soil microbial communities will allow design of nanoscale agrochemcials that combine optimal safety and functionality profiles. bacterial community structure after just 90 days of exposure to a realistic concentration of NPs (1 mg kg −1 dry soil) 10 , while studies with Ag NMs, which are well-known for their antimicrobial activity have shown that the extent of impact on soil community composition over 90 days are affected by exposure time and physicochemical composition of soil as well as the type and coating of the NMs 11 . Thus, an important caveat at the outset of this review is that NMs represent a very broad spectrum of chemistries, compositions and physicochemical properties, which are dynamic and evolving as the NMs interact with their surroundings, and as such generalisations regarding their applications in agriculture are difficult, and predictions of long-term effects are challenging currently.However, as noted in the aforementioned reviews 3, 4, 5 , the development of nanotechnology for agricultural applications is still at an early stage and is moving forward quite slowly. Significant differences may exist between nanotechnology-based pesticides and conventional pesticides, including altered bioavailability, sensitivity, dosimetry, and pharmacokinetics 12, 13 . Challenges and barriers include limited understanding of plant-NMs interactions, limited methods for efficient delivery of NMs to plants and soil, risks of potentially hazardous effects of NMs to human health from accumulation of NMs and active ingredient residues in edible portions of plants 4 , and to long term soil quality and soil health from accumulation of NMs and their degradation products in soil and resultant potential alterations in microbial biodiversity 14 . There is an urgent need to address these barriers and achieve a true win-win scenario, whereby improved agricultural production, reduced environmental pollution from agriculture and lower costs for farmers can be achieved synergistically. A one-health approach to nano-agriculture was proposed by Lombi et al., that requires interdisciplinarity and the bridging of human and environmental health research 15 . Computational approaches including artificial intelligence (A.I.) and machine learning (M.L.) modelling will undoubtedly play critical roles in the progess of nano-enabled agric...

[1] The exchange of the important trace gases, methane (CH 4 ), nitrous oxide (N 2 O), and carbon dioxide (CO 2 ), between forested soils and the atmosphere can show great temporal and spatial variability. We measured the flux of these three gases over 2 years along catenas at two forested sites, to determine the important controls. Well-drained soils consumed atmospheric CH 4 , while poorly drained swamp soils embedded in depressions were a source. CH 4 fluxes could be predicted primarily by temperature and moisture, and tree cover exerted an influence mainly through the creation of large soil porosity, leading to increased consumption rates. In contrast, there were very poor relationships between N 2 O fluxes and environmental variables, reflecting the complex interactions of microbial, edaphic, and N cycling processes, such as nitrification in well-drained soils and denitrification in poorly drained soils, which led to N 2 O production (or consumption) in soils and hence larger variability. At the broad temporal and spatial scale, soil C:N ratio was a good predictor of N 2 O emission rates, through its influence upon N cycling processes. Soil CO 2 emission rates showed less spatial and temporal variability, and were controlled by temperature and moisture. The source strength, in global warming potential of CH 4 and N 2 O fluxes in CO 2 equivalents, was reduced markedly when trace gas fluxes from 5 to 15% poorly drained soils were included in the net global warming potential calculation of whole forested watersheds. Soils drainage class integrates many of the biogeochemical processes controlling the flux of these gases providing a framework for extrapolating results.

We investigated soil carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) exchanges in an age-sequence (4, 17, 32, 67 years old) of eastern white pine (Pinus strobus L.) forests in southern Ontario, Canada, for the period of mid-April to mid-December in 2007. For both CH 4 and N 2 O, we observed uptake and emission ranging from À160 to 245 lg CH 4 m À2 h À1 and À52 to 21 lg N 2 O m À2 h À1 , respectively (negative values indicate uptake). Mean fluxes from mid-April to mid-December across the 4, 17, 32, 67 years old stands were similar for CO 2 fluxes (259, 246, 220, and 250 mg CO 2 m À2 h À1 , respectively), without pattern for N 2 O fluxes (À3.7, 1.5, À2.2, and À7.6 lg N 2 O m À2 h À1 , respectively), whereas the uptake rates of CH 4 increased with stand age (6.4, À7.9, À10.8, and À23.3 lg CH 4 m À2 h À1 , respectively). For the same period, the combined contribution of CH 4 and N 2 O exchanges to the global warming potential (GWP) calculated from net ecosystem exchange of CO 2 and aggregated soil exchanges of CH 4 and N 2 O was on average 4%, o1%, o1%, and 2% for the 4, 17, 32, 67 years old stand, respectively. Soil CO 2 fluxes correlated positively with soil temperature but had no relationship with soil moisture. We found no control of soil temperature or soil moisture on CH 4 and N 2 O fluxes, but CH 4 emission was observed following summer rainfall events. LFH layer removal reduced CO 2 emissions by 43%, increased CH 4 uptake during dry and warm soil conditions by more than twofold, but did not affect N 2 O flux. We suggest that significant alternating sink and source potentials for both CH 4 and N 2 O may occur in N-and soil water-limited forest ecosystems, which constitute a large portion of forest cover in temperate areas.

Laboratory incubations with river-bed sediment collected from riffles and pools were used to quantify potential pathways of dissimilatory nitrate reduction in the hyporheic zone of a groundwater-fed river. Sediments collected from between 5-cm and 86-cm depth in the bed of the River Leith, Cumbria, United Kingdom, were incubated with a suite of 15 N-labeled substrates ( 15 NO { 3 , 15 NH z 4 , and 14 NO { 3 ) to quantify nitrate reduction via denitrification, dissimilatory nitrate reduction to ammonium (DNRA), and anaerobic ammonium oxidation (anammox). Denitrification was the dominant pathway of dissimilatory nitrate reduction in the hyporheic sediments, although recovery of 15 N from the ammonium pool indicated that DNRA was also active. The potential for anammox was confirmed by the production of 29 N 2 during the 15 NH z 4 and 14 NO { 3 incubation, but it was much smaller than denitrification. Potential rates of denitrification were highest in shallow sediments and decayed exponentially with depth thereafter. There were clear differences in denitrification activity between riffle and pool sediments. After the production of 15 N-N 2 had stabilized, we added a spike of bacteriological peptone to determine the effect of complex organic substrates on denitrification potential. The potential rate of denitrification increased uniformly at all sediment depths but the total amount of denitrification fueled by the organic substrates decreased markedly with depth, from 90% in the shallow sediments to 30% in the deepest sediments. In addition, a considerable fraction of the 15 NO { 3 could not be accounted for, which suggested that up to 87% of it had been assimilated in the deepest sediments.

Greenhouse gas (GHG) emissions of carbon dioxide (CO2) and methane (CH4) from streambeds are currently understudied. There is a paucity of research exploring organic matter (OM) controls on GHG production by microbial metabolic activity in streambeds, which is a major knowledge gap given the increased inputs of allochthonous carbon to streams, especially in agricultural catchments. This study aims to contribute to closing this knowledge gap by quantifying how contrasting OM contents in different sediments affect streambed GHG production and associated microbial metabolic activity. We demonstrate, by means of an incubation experiment, that streambed sediments have the potential to produce substantial amounts of GHG, controlled by sediment OM quantity and quality. We observed streambed CO2 production rates that can account for 35% of total stream evasion estimated in previous studies, ranging between 1.4 and 86% under optimal conditions. Methane production varied stronger than CO2 between different geologic backgrounds, suggesting OM quality controls between streambed sediments. Moreover, our results indicate that streambed sediments may produce much more CO2 than quantified to date, depending on the quantity and quality of the organic matter, which has direct implications for global estimates of C fluxes in stream ecosystems.

Globally, rivers and streams are important sources of carbon dioxide and methane, with small rivers contributing disproportionately relative to their size. Previous research on greenhouse gas (GHG) emissions from surface water lacks mechanistic understanding of contributions from streambed sediments. We hypothesise that streambeds, as known biogeochemical hotspots, significantly contribute to the production of GHGs. With global climate change, there is a pressing need to understand how increasing streambed temperatures will affect current and future GHG production. Current global estimates assume linear relationships between temperature and GHG emissions from surface water. Here we show non-linearity and threshold responses of streambed GHG production to warming. We reveal that temperature sensitivity varies with substrate (of variable grain size), organic matter (OM) content and geological origin. Our results confirm that streambeds, with their non-linear response to projected warming, are integral to estimating freshwater ecosystem contributions to current and future global GHG emissions.