Do cover crops enhance N2O, CO2 or CH4 emissions from soil in Mediterranean arable systems?

This study evaluates the effect of planting three cover crops (CCs) (barley, Hordeum vulgare L.; vetch, Vicia villosa L.; rape, Brassica napus L.) on the direct emission of N2O, CO2 and CH4 in the intercrop period and the impact of incorporating these CCs on the emission of greenhouse gas (GHG) from the forthcoming irrigated maize (Zea mays L.) crop. Vetch and barley were the CCs with the highest N2O and CO2 losses (75 and 47% increase compared with the control, respectively) in the fallow period. In all cases, fluxes of N2O were increased through N fertilization and the incorporation of barley and rape residues (40 and 17% increase, respectively). The combination of a high C:N ratio with the addition of an external source of mineral N increased the fluxes of N2O compared with − Ba and − Rp. The direct emissions of N2O were lower than expected for a fertilized crop (0.10% emission factor, EF) compared with other studies and the IPCC EF. These results are believed to be associated with a decreased NO3− pool due to highly denitrifying conditions and increased drainage. The fluxes of CO2 were in the range of other fertilized crops (i.e., 1118.71–1736.52 kg CO2–C ha− 1). The incorporation of CC residues enhanced soil respiration in the range of 21–28% for barley and rape although no significant differences between treatments were detected. Negative CH4 fluxes were measured and displayed an overall sink effect for all incorporated CC (mean values of − 0.12 and − 0.10 kg CH4–C ha− 1 for plots with and without incorporated CCs, respectively).

Spatiotemporal modelling in estimation of nitrous oxide emissions from soil

Nitrous oxide is a major greenhouse gas emission. The aim of this research was to develop and apply statistical models to characterize the complex spatial and temporal variation in nitrous oxide emissions from soils under different land use conditions. This is critical when developing site-specific management plans to reduce nitrous oxide emissions. These studies can improve predictions and increase our understanding of environmental factors that influence nitrous oxide emissions. They also help to identify areas for future research, which can further improve the prediction of nitrous oxide in practice.

A novel 15N tracer approach for the quantification of N2 and N2O emissions from soil incubations in a completely automated laboratory set up

The microbial mediated production of nitrous oxide (N2O) and its reduction to dinitrogen (N2) via denitrification represents a loss of nitrogen (N) from fertilised agro-ecosystems to the atmosphere. Although denitrification has received great interest by biogeochemists in the last decades, the magnitude of N2lossesand related N2:N2O ratios from soils still are largely unknown due to methodical constraints. We present a novel 15N tracer approach, based on a previous developed tracer method to study denitrification in pure bacterial cultures which was modified for the use on soil incubations in a completely automated laboratory set up. The method uses a background air in the incubation vessels that is replaced with a helium-oxygen gas mixture with a 50-fold reduced N2 background (2 % v/v). This method allows for a direct and sensitive quantification of the N2 and N2O emissions from the soil with isotope-ratio mass spectrometry after 15N labelling of denitrification N substrates and minimises the sensitivity to the intrusion of atmospheric N2 at the same time. The incubation set up was used to determine the influence of different soil moisture levels on N2 and N2O emissions from a sub-tropical pasture soil in Queensland/Australia. The soil was labelled with an equivalent of 50 μg-N per gram dry soil by broadcast application of KNO3solution (4 at.% 15N) and incubated for 3 days at 80% and 100% water filled pore space (WFPS), respectively. The headspace of the incubation vessel was sampled automatically over 12hrs each day and 3 samples (0, 6, and 12 hrs after incubation start) of headspace gas analysed for N2 and N2O with an isotope-ratio mass spectrometer (DELTA V Plus, Thermo Fisher Scientific, Bremen, Germany(. In addition, the soil was analysed for 15N NO3- and NH4+ using the 15N diffusion method, which enabled us to obtain a complete N balance. The method proved to be highly sensitive for N2 and N2O emissions detecting N2O emissions ranging from 20 to 627 μN kg-1soil-1hr-1and N2 emissions ranging from 4.2 to 43 μN kg-1soil-1hr-1for the different treatments. The main end-product of denitrification was N2O for both water contents with N2 accounting for 9% and 13% of the total denitrification losses at 80% and 100%WFPS, respectively. Between 95-100% of the added 15N fertiliser could be recovered. Gross nitrification over the 3 days amounted to 8.6 μN g-1 soil-1 and 4.7 μN g-1 soil-1, denitrification to 4.1 μN g-1 soil-1 and 11.8 μN g-1 soil-1at 80% and 100%WFPS, respectively. The results confirm that the tested method allows for a direct and highly sensitive detection of N2 and N2O fluxes from soils and hence offers a sensitive tool to study denitrification and N turnover in terrestrial agro-ecosystems.

Short-term CO2-C emissions from soil prior to sugarcane (Saccharum spp.) replanting in southern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Methane emission from soil under long-term no-till cropping systems

Methane (CH4) emission from agricultural soils increases dramatically as a result of deleterious effect of soil disturbance and nitrogen fertilization on methanotrophic organisms; however, few studies have attempted to evaluate the potential of long-term conservation management systems to mitigate CH4 emissions in tropical and subtropical soils. This study aimed to evaluate the long-term effect (>19 years) of no-till grass- and legume-based cropping systems on annual soil CH4 fluxes in a formerly degraded Acrisol in Southern Brazil. Air sampling was carried out using static chambers and CH4 analysis by gas chromatography. Analysis of historical data set of the experiment evidenced a remarkable effect of high C- and N-input cropping systems on the improvement of biological, chemical, and physical characteristics of this no-tilled soil. Soil CH4 fluxes, which represent a net balance between consumption (-) and production (+) of CH4 in soil, varied from -40 +/- 2 to +62 +/- 78 mu g C m(-2) h(-1). Mean weighted contents of ammonium (NH4+-N) and dissolved organic carbon (DOC) in soil had a positive relationship with accumulated soil CH4 fluxes in the post-management period (r(2) = 0.95, p = 0.05), suggesting an additive effect of these nutrients in suppressing CH4 oxidation and stimulating methanogenesis, respectively, in legume-based cropping systems with high biomass input. Annual CH4 fluxes ranged from -50 +/- 610 to +994 +/- 105 g C ha(-1), which were inversely related to annual biomass-C input (r(2) = 0.99, p = 0.003), with the exception of the cropping system containing pigeon pea, a summer legume that had the highest biologically fixed N input (>300 kg ha(-1) yr(-1)). Our results evidenced a small effect of conservation management systems on decreasing CH4 emissions from soil, despite their significant effect restoring soil quality. We hypothesized that soil CH4 uptake strength has been off-set by an injurious effect of biologically fixed N in legume-based cropping systems on soil methanotrophic microbiota, and by the methanogenesis increase as a result of the O-2 depletion in niches of high biological activity in the surface layer of the no-tillage soil. (C) 2012 Elsevier B.V. All rights reserved.

Soybean rotation and crop residue management to reduce nitrous oxide emissions from sugarcane soils

NITROUS OXIDE (N2O) IS a potent greenhouse gas and the predominant ozone-depleting substance in the atmosphere. Agricultural nitrogenous fertiliser use is the major source of human-induced N2O emissions. A field experiment was conducted at Bundaberg from October 2012 to September 2014 to examine the impacts of legume crop (soybean) rotation as an alternative nitrogen (N) source on N2O emissions during the fallow period and to investigate low-emission soybean residue management practices. An automatic monitoring system and manual gas sampling chambers were used to measure greenhouse gas emissions from soil. Soybean cropping during the fallow period reduced N2O emissions compared to the bare fallow. Based on the N content in the soybean crop residues, the fertiliser N application rate was reduced by about 120 kg N/ha for the subsequent sugarcane crop. Consequently, emissions of N2O during the sugarcane cropping season were significantly lower from the soybean cropped soil than those from the conventionally fertilised (145 kg N/ha) soil following bare fallow. However, tillage that incorporated the soybean crop residues into soil promoted N2O emissions in the first two months. Spraying a nitrification inhibitor (DMPP) onto the soybean crop residues before tillage effectively prevented the N2O emission spikes. Compared to conventional tillage, practising no-till with or without growing a nitrogen catch crop during the time after soybean harvest and before cane planting also reduced N2O emissions substantially. These results demonstrated that soybean rotation during the fallow period followed with N conservation management practices could offer a promising N2O mitigation strategy in sugarcane farming. Further investigation is required to provide guidance on N and water management following soybean fallow to maintain sugar productivity.

Spatial Variability of CO2 Emissions from Newly Exposed Paraglacial Soils at a Glacier Retreat Zone on King George Island, Maritime Antarctica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Greenhouse gas emissions and N2o mitigation in beef cattle production on tropical pasture

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Decision strategies for policy decisions under uncertainties: The case of mitigation measures addressing methane emissions from ruminants

Decision strategies aim at enabling reasonable decisions in cases of uncertain policy decision problems which do not meet the conditions for applying standard decision theory. This paper focuses on decision strategies that account for uncertainties by deciding whether a proposed list of policy options should be accepted or revised (scope strategies) and whether to decide now or later (timing strategies). They can be used in participatory approaches to structure the decision process. As a basis, we propose to classify the broad range of uncertainties affecting policy decision problems along two dimensions, source of uncertainty (incomplete information, inherent indeterminacy and unreliable information) and location of uncertainty (information about policy options, outcomes and values). Decision strategies encompass multiple and vague criteria to be deliberated in application. As an example, we discuss which decision strategies may account for the uncertainties related to nutritive technologies that aim at reducing methane (CH4) emissions from ruminants as a means of mitigating climate change, limiting our discussion to published scientific information. These considerations not only speak in favour of revising rather than accepting the discussed list of options, but also in favour of active postponement or semi-closure of decision-making rather than closure or passive postponement.

Quantifying nitrous oxide emissions from sugarcane cropping systems : Optimum sampling time and frequency

Nitrous oxide (N2O) emissions from soil are often measured using the manual static chamber method. Manual gas sampling is labour intensive, so a minimal sampling frequency that maintains the accuracy of measurements would be desirable. However, the high temporal (diurnal, daily and seasonal) variabilities of N2O emissions can compromise the accuracy of measurements if not addressed adequately when formulating a sampling schedule. Assessments of sampling strategies to date have focussed on relatively low emission systems with high episodicity, where a small number of the highest emission peaks can be critically important in the measurement of whole season cumulative emissions. Using year-long, automated sub-daily N2O measurements from three fertilised sugarcane fields, we undertook an evaluation of the optimum gas sampling strategies in high emission systems with relatively long emission episodes. The results indicated that sampling in the morning between 09:00–12:00, when soil temperature was generally close to the daily average, best approximated the daily mean N2O emission within 4–7% of the ‘actual’ daily emissions measured by automated sampling. Weekly sampling with biweekly sampling for one week after >20 mm of rainfall was the recommended sampling regime. It resulted in no extreme (>20%) deviations from the ‘actuals’, had a high probability of estimating the annual cumulative emissions within 10% precision, with practicable sampling numbers in comparison to other sampling regimes. This provides robust and useful guidance for manual gas sampling in sugarcane cropping systems, although further adjustments by the operators in terms of expected measurement accuracy and resource availability are encouraged. By implementing these sampling strategies together, labour inputs and errors in measured cumulative N2O emissions can be minimised. Further research is needed to quantify the spatial variability of N2O emissions within sugarcane cropping and to develop techniques for effectively addressing both spatial and temporal variabilities simultaneously.