Denitrification and nitrous oxide emissions from riparian forests soils exposed to prolonged nitrogen runoff

Compared to upland forests, riparian forest soils have greater potential to remove nitrate (NO3) from agricultural run-off through denitrification. It is unclear, however, whether prolonged exposure of riparian soils to nitrogen (N) loading will affect the rate of denitrification and its end products. This research assesses the rate of denitrification and nitrous oxide (N2O) emissions from riparian forest soils exposed to prolonged nutrient run-off from plant nurseries and compares these to similar forest soils not exposed to nutrient run-off. Nursery run-off also contains high levels of phosphate (PO4). Since there are conflicting reports on the impact of PO4 on the activity of denitrifying microbes, the impact of PO4 on such activity was also investigated. Bulk and intact soil cores were collected from N-exposed and non-exposed forests to determine denitrification and N2O emission rates, whereas denitrification potential was determined using soil slurries. Compared to the non-amended treatment, denitrification rate increased 2.7- and 3.4-fold when soil cores collected from both N-exposed and non-exposed sites were amended with 30 and 60 μg NO3-N g-1 soil, respectively. Net N2O emissions were 1.5 and 1.7 times higher from the N-exposed sites compared to the non-exposed sites at 30 and 60 μg NO3-N g-1 soil amendment rates, respectively. Similarly, denitrification potential increased 17 times in response to addition of 15 μg NO3-N g-1 in soil slurries. The addition of PO4 (5 μg PO4–P g-1) to soil slurries and intact cores did not affect denitrification rates. These observations suggest that prolonged N loading did not affect the denitrification potential of the riparian forest soils; however, it did result in higher N2O emissions compared to emission rates from non-exposed forests

Mapping and linking supply- and demand-side measures in climate-smart agriculture. A review

Climate change and food security are two of humanity’s greatest challenges and are highly interlinked. On the one hand, climate change puts pressure on food security. On the other hand, farming significantly contributes to anthropogenic greenhouse gas emissions. This calls for climate-smart agriculture—agriculture that helps to mitigate and adapt to climate change. Climate-smart agriculture measures are diverse and include emission reductions, sink enhancements, and fossil fuel offsets for mitigation. Adaptation measures include technological advancements, adaptive farming practices, and financial management. Here, we review the potentials and trade-offs of climate-smart agricultural measures by producers and consumers. Our two main findings are as follows: (1) The benefits of measures are often site-dependent and differ according to agricultural practices (e.g., fertilizer use), environmental conditions (e.g., carbon sequestration potential), or the production and consumption of specific products (e.g., rice and meat). (2) Climate-smart agricultural measures on the supply side are likely to be insufficient or ineffective if not accompanied by changes in consumer behavior, as climate-smart agriculture will affect the supply of agricultural commodities and require changes on the demand side in response. Such linkages between demand and supply require simultaneous policy and market incentives. It, therefore, requires interdisciplinary cooperation to meet the twin challenge of climate change and food security. The link to consumer behavior is often neglected in research but regarded as an essential component of climate-smart agriculture. We argue for not solely focusing research and implementation on one-sided measures but designing good, site-specific combinations of both demand- and supply-side measures to use the potential of agriculture more effectively to mitigate and adapt to climate change

Nitrite accumulation and nitrogen gas production increase with decreasing temperature in urea-amended soils: Experiments and modeling

Nitrite (NO₂⁻) accumulation and associated production of nitric oxide (NO) and nitrous oxide (N₂O) gases in soils amended with nitrogen (N) fertilizers are well documented, but there remains a poor understanding of their regulation and variation among soil types. We examined responses to urea inputs in two soils at five temperatures from 5 to 30 °C and developed a process-driven model to describe the dynamics. A microcosm system was used to measure ammonia gas (NH₃), ammonium (NH₄⁺), NO₂⁻, nitrate (NO₃⁻), NO, N₂O and pH over 12 weeks. Unexpectedly, NO₂⁻, NO and N₂O production tended to increase as soil temperature declined in both soils. The maximum NO₂⁻ concentration, or compensation point (CP), differed by soil type but the time required to reach CP decreased exponentially with increasing temperature in both soils. A two-step nitrification model (’2SN’) accounted for interactions of ammonia-oxidation (AmO), nitrite oxidation (NiO), urea hydrolysis, NH₄⁺ sorption, N gas production and pH dynamics. Both steps of nitrification (AmO and NiO) were modeled using NH3 inhibition kinetics. The model adequately simulated the observed dynamics and temperature responses and showed that increased uncoupling of AmO and NiO at colder temperatures resulted from their differential temperature responses. The dynamics observed here may be important following high-rate and banded N fertilizer applications and in ruminant urine patches. The results may help explain elevated N₂O emissions observed under cold temperatures. The 2SN model can account for interactions among multiple processes and may be useful for studying the effects of management practices and climate factors, including climate change scenarios, on soil N cycling

Nitrous oxide fluxes and soil oxygen dynamics of soil treated with cow urine

Ruminant urine deposition onto pasture creates hot-spots where emissions of nitrous oxide (N₂O) are produced by aerobic and anaerobic microbial pathways. However, limited measurements of in situ soil oxygen (O₂)-N₂O relationships hinder the prediction of N₂O emissions from urine-affected soil. This study tested whether soil O₂ concentration or relative diffusivity of O₂ (Dp/DO) could explain N₂O emissions from urine patches. Using a randomized plot design, N₂O emissions were measured daily from a perennial ryegrass (Lolium perenne L.) pasture for 56 d following bovine (Bos taurus) urine deposition to an imperfectly drained silty loam soil. Soil O₂, volumetric water content, pH, conductivity, and extractable N and C were measured in urine-amended and non-amended soil. Values of water-filled pore space (WFPS) and Dp/DO were modeled. When data from treatments were pooled together, daily mean Dp/DO explained 73% of the total variance in mean daily N₂O flux, compared with 65, < 60, and < 20% for WFPS, O₂ and other measured variables, respectively. Soil pH, O₂, volumetric water content, WFPS and Dp/DO all explained more of the variance in the urineamended compared with the non-amended soil. Daily N₂O fluxes increased substantially at Dp/DO values around 0.006, which was consistent with past laboratory studies. These results demonstrate for the first time an O₂ diffusion threshold for elevated N₂O fluxes in the field, expressed as Dp/DO ≈ 0.006. Further studies should examine the consistency of this threshold under varying N and C substrates and a range of soil pH

Nitrification gene ratio and free ammonia explain nitrite and nitrous oxide production in urea-amended soils

The atmospheric concentration of nitrous oxide (N₂O), a potent greenhouse gas and ozone-depleting chemical, continues to increase, due largely to the application of nitrogen (N) fertilizers. While nitrite (NO₂⁻) is a central regulator of N₂O production in soil, NO₂⁻ and N₂O responses to fertilizer addition rates cannot be readily predicted. Our objective was to determine if quantification of multiple chemical variables and structural genes associated with ammonia (NH₃)- (AOB, encoded by amoA) and NO₂⁻ -oxidizing bacteria (NOB, encoded by nxrA and nxrB) could explain the contrasting responses of eight agricultural soils to five rates of urea addition in aerobic microcosms. Significant differences in NO₂⁻ accumulation and N₂O production by soil type could not be explained by initial soil properties. Biologically-coherent statistical models, however, accounted for 70–89% of the total variance in NO₂⁻ and N₂O. Free NH₃ concentration accounted for 50–85% of the variance in NO₂⁻ which, in turn, explained 62–82% of the variance in N₂O. By itself, the time-integrated nxrA:amoA gene ratio explained 78 and 79% of the variance in cumulative NO₂⁻ and N₂O, respectively. In all soils, nxrA abundances declined above critical urea addition rates, indicating a consistent pattern of suppression of Nitrobacter-associated NOB due to NH₃ toxicity. In contrast, Nitrospira-associated nxrB abundances exhibited a broader range of responses, and showed that long-term management practices (e.g., tillage) can induce a shift in dominant NOB populations which subsequently impacts NO₂⁻ accumulation and N₂O production. These results highlight the challenges of predicting NO₂⁻ and N₂O responses based solely on static soil properties, and suggest that models that account for dynamic processes following N addition are ultimately needed. The relationships found here provide a basis for incorporating the relevant biological and chemical processes into N cycling and N₂O emissions models

Temperature alters dicyandiamide (DCD) efficacy for multiple reactive nitrogen species in urea-amended soils: Experiments and modeling

Dicyandiamide (DCD) is a nitrification inhibitor (NI) used to reduce reactive nitrogen (N) losses from soils. While commonly used, its effectiveness varies widely. Few studies have measured DCD and temperature effects on a complete set of soil N variables, including nitrite (NO₂¯) measured separately from nitrate (NO₃‾). Here the DCD reduction efficiencies (RE) for nine N availability metrics were quantified in two soils (a loam and silt loam) using aerobic laboratory microcosms at 5–30 °C. Both regression analysis and process modeling were used to characterize the responses. Four metrics accounted for NO₃‾ production and included total mobilized N, net nitrification, maximum nitrification rate, and cumulative NO₃‾ (cNO₃‾). The REs for these NO₃‾ -associated production variables decreased linearly with temperature, and in all cases were below 60% at temperatures ≥22 °C, except for cNO₃‾ in one soil. In contrast, REs for NO₂‾ and nitric oxide (NO) gas production were less sensitive to temperature, ranging from 80 to 99% at 22 °C and 50–95% at 30 °C. Addition of DCD suppressed nitrous oxide (N₂O) production in both soils by 20–80%, but increased ammonia volatilization by 36–210%. The time at which the maximum reduction efficiency occurred decreased exponentially with increasing temperature for most variables. The two-step nitrification process model (2SN) was modified to include competitive inhibition coupled to first-order DCD decomposition. Model versus data comparisons suggested that DCD had indirect effects on NO₂‾ kinetics that contributed to the greater suppression of NO₂‾ and NO relative to NO₃‾. This study also points to the need for NIs that are more stable under increased temperature. The methods used here could help to assess the efficacy and temperature sensitivity of other NIs as well as new microbial inhibitors that may be develope