Urine patches and dung pats from grazing livestock create hotspots for production and emission of the greenhouse gas, nitrous oxide (N2O), and represent a large proportion of total N2O emissions in many national agricultural greenhouse gas inventories. As such, there is much interest in developing country specific N2O emission factors (EFs) for excretal nitrogen (EF3, pasture, range and paddock) deposited during gazing. The aims of this study were to generate separate N2O emissions data for cattle derived urine and dung, to provide an evidence base for the generation of a country specific EF for the UK from this nitrogen source. The experiments were also designed to determine the effects of site and timing of application on emissions, and the efficacy of the nitrification inhibitor, dicyandiamide (DCD) on N2O losses. This co-ordinated set of 15 plot-scale, year-long field experiments using static chambers was conducted at five grassland sites, typical of the soil and climatic zones of grazed grassland in the UK. We show that the average urine and dung N2O EFs were 0.69% and 0.19%, respectively, resulting in a combined excretal N2O EF (EF3), of 0.49%, which is <25% of the IPCC default EF3 for excretal returns from grazing cattle. Regression analysis suggests that urine N2O EFs were controlled more by composition than was the case for dung, whilst dung N2O EFs were more related to soil and environmental factors. The urine N2O EF was significantly greater from the site in SW England, and significantly greater from the early grazing season urine application than later applications. Dycandiamide reduced the N2O EF from urine patches by an average of 46%. The significantly lower excretal EF3 than the IPCC default has implications for the UK's national inventory and for subsequent carbon footprinting of UK ruminant livestock products.
Adequately estimating soil nitrous oxide (N2O) emissions using static chambers is challenging due to the high spatial variability and episodic nature of these fluxes. We discuss how to design experiments using static chambers to better account for this variability and reduce the uncertainty of N2O emission estimates. This paper is part of a series, each discussing different facets of N2O chamber methodology. Aspects of experimental design and sampling affected by spatial variability include site selection and chamber layout, size, and areal coverage. Where used, treatment application adds a further level of spatial variability. Time of day, frequency, and duration of sampling (both individual chamber closure and overall experiment duration) affect the temporal variability captured. We also present best practice recommendations for chamber installation and sampling protocols to reduce further uncertainty. To obtain the best N2O emission estimates, resources should be allocated to minimize the overall uncertainty in line with experiment objectives. Sometimes this will mean prioritizing individual flux measurements and increasing their accuracy and precision by, for example, collecting four or more headspace samples during each chamber closure. However, where N2O fluxes are exceptionally spatially variable (e.g., in heterogeneous agricultural landscapes, such as uneven and woody grazed pastures), using available resources to deploy more chambers with fewer headspace samples per chamber may be beneficial. Similarly, for particularly episodic N2O fluxes, generated for example by irrigation or freeze–thaw cycles, increasing chamber sampling frequency will improve the accuracy and reduce the uncertainty of temporally interpolated N2O fluxes.
Drained, lowland agricultural peatlands are greenhouse gas (GHG) emission hotspots and a large but vulnerable store of irrecoverable carbon. They exhibit soil loss rates of ~2.0 cm yr−1 and are estimated to account for 32% of global cropland emissions while producing only 1.1% of crop kilocalories. Carbon dioxide emissions account for >80% of their terrestrial GHG emissions and are largely controlled by water table depth. Reducing drainage depths is, therefore, essential for responsible peatland management. Peatland restoration can substantially reduce emissions. However, this may conflict with societal needs to maintain productive use, to protect food security and livelihoods. Wetland agriculture strategies will, therefore, be required to adapt agriculture to the wetland character of peatlands, and balance GHG mitigation against productivity, where halting emissions is not immediately possible. Paludiculture may substantially reduce GHG emissions but will not always be viable in the current economic landscape. Reduced drainage intensity systems may deliver partial reductions in the rate of emissions, with smaller modifications to existing systems. These compromise systems may face fewer hurdles to adoption and minimize environmental harm until societal conditions favour strategies that can halt emissions. Wetland agriculture will face agronomic, socio‐economic and water management challenges, and careful implementation will be required. Diversity of values and priorities among stakeholders creates the potential for conflict. Successful implementation will require participatory research approaches and co‐creation of workable solutions. Policymakers, private sector funders and researchers have key roles to play but adoption risks would fall predominantly on land managers. Development of a robust wetland agriculture paradigm is essential to deliver resilient production systems and wider environmental benefits. The challenge of responsible use presents an opportunity to rethink peatland management and create thriving, innovative and green wetland landscapes for everyone's future benefit, while making a vital contribution to global climate change mitigation.