Ammonia emissions from cattle urine and dung excreted on pasture

Twelve cattle were kept for three days in a circular area of 16 m radius on short pasture and fed with freshly-cut pasture. Ammonia (NH<sub>3</sub>) emissions from the urine and dung excreted by the cattle were measured with a micrometeorological mass-balance method, during the cattle presence and for 10 subsequent days. Daily-integrated emission rates peaked on Day 3 of the experiment (last day of cattle presence) and declined steadily for five days thereafter. Urine patches were the dominant sources for these emissions. On Day 9, a secondary emissions peak occurred, with dung pats likely to be the main sources. This interpretation is based on simultaneous observations of the pH evolution in urine patches and dung pats created next to the circular plot. Feed and dung samples were analysed to estimate the amounts of nitrogen (N) ingested and excreted. Total N volatilised as NH<sub>3</sub> was 19.8 (± 0.9)% of N intake and 22.4 (± 1.3)% of N excreted. The bimodal shape of the emissions time series allowed to infer separate estimates for volatilisation from urine and dung, respectively, with the result that urine accounted for 88.6 (± 2.6)% of the total NH<sub>3</sub> emissions. The emissions from urine represented 25.5 (± 2.0)% of the excreted urine-N, while the emissions from dung amounted to 11.6 (± 2.7)% of the deposited dung-N. Emissions from dung may have continued after Day 13 but were not resolved by the measurement technique. A simple resistance model shows that the magnitude of the emissions from dung is controlled by the resistance of the dung crust

Ammonia emissions from cattle urine and dung excreted on pasture

Twelve cattle were kept for three days in a circular area of 16 m radius on short pasture and fed with freshly-cut pasture. Ammonia (NH₃) emissions from the urine and dung excreted by the cattle were measured with a micrometeorological mass-balance method, during the cattle presence and for 10 subsequent days. Daily-integrated emission rates peaked on Day 3 of the experiment (last day of cattle presence) and declined steadily for five days thereafter. Urine patches were the dominant sources for these emissions. On Day 9, a secondary emissions peak occurred, with dung pats likely to be the main sources. This interpretation is based on simultaneous observations of the pH evolution in urine patches and dung pats created next to the circular plot. Feed and dung samples were analysed to estimate the amounts of nitrogen (N) ingested and excreted. Total N volatilised as NH₃ was 19.8 (± 0.9)% of N intake and 22.4 (± 1.3)% of N excreted. The bimodal shape of the emissions time series allowed to infer separate estimates for volatilisation from urine and dung, respectively, with the result that urine accounted for 88.6 (± 2.6)% of the total NH₃ emissions. The emissions from urine represented 25.5 (± 2.0)% of the excreted urine-N, while the emissions from dung amounted to 11.6 (± 2.7)% of the deposited dung-N. Emissions from dung may have continued after Day 13 but were not resolved by the measurement technique. A simple resistance model shows that the magnitude of the emissions from dung is controlled by the resistance of the dung crust. © Author(s) 2013

Consolidating soil carbon turnover models by improved estimates of belowground carbon input

World soil carbon (C) stocks are third only to those in the ocean and earth crust, and represent twice the amount currently present in the atmosphere. Therefore, any small change in the amount of soil organic C (SOC) may affect carbon dioxide (CO2) concentrations in the atmosphere. Dynamic models of SOC help reveal the interaction among soil carbon systems, climate and land management, and they are also frequently used to help assess SOC dynamics. Those models often use allometric functions to calculate soil C inputs in which the amount of C in both above and below ground crop residues are assumed to be proportional to crop harvest yield. Here we argue that simulating changes in SOC stocks based on C input that are proportional to crop yield is not supported by data from long-term experiments with measured SOC changes. Rather, there is evidence that root C inputs are largely independent of crop yield, but crop specific. We discuss implications of applying fixed below ground C input regardless of crop yield on agricultural greenhouse gas mitigation and accounting

A process-based model for ammonia emission from urine patches, GAG (Generation of Ammonia from Grazing): description, validation and sensitivity analysis

In this paper a new process-based, weather-driven model for ammonia (NH3) emission from a urine patch has been developed and its sensitivity to various factors assessed. The GAG model (Generation of Ammonia from Grazing) is capable of simulating the TAN (total ammoniacal nitrogen) and the water content of the soil under a urine patch and also soil pH dynamics. The model tests suggest that ammonia volatilization from a urine patch can be affected by the possible restart of urea hydrolysis after a rain event as well as CO2 emission from the soil. The vital role of temperature in NH3 exchange is supported by our model results; however, the GAG model provides only a modest overall temperature dependence in total NH3 emission compared with the literature. This, according to our findings, can be explained by the higher sensitivity to temperature close to urine application than in the later stages and may depend on interactions with other nitrogen cycling processes. In addition, we found that wind speed and relative humidity are also significant influencing factors. Considering that all the input parameters can be obtained for larger scales, GAG is potentially suitable for field and regional scale application, serving as a tool for further investigation of the effects of climate change on ammonia emissions and deposition

C-TOOL: a simple model for simulating whole-profile carbon storage in temperate agricultural soils

Soil organic carbon (SOC) is a significant component of the global carbon (C) cycle. Changes in SOC storage affect atmospheric CO2 concentrations on decadal to centennial timescales. The C-TOOL model was developed to simulate farm- and regional-scale effects of management on medium- to long-term SOC storage in the profile of well-drained agricultural mineral soils. C-TOOL uses three SOC pools for both the topsoil (0–25 cm) and the subsoil (25–100 cm), and applies temperature-dependent first order kinetics to regulate C turnover. C-TOOL also enables the simulation of 14C turnover. The simple model structure facilitates calibration and requires few inputs (mean monthly air temperature, soil clay content, soil C/N ratio and C in organic inputs). The model was parameterised using data from 19 treatments drawn from seven long-term field experiments in the United Kingdom, Sweden and Denmark. It was found that the initial SOC content had to be optimised for each experiment, but also that one set of values for other model parameters could be applied at all sites. With this set of parameters, C-TOOL can be applied more widely to evaluate effects of management options on SOC storage in temperate agricultural soils. C-TOOL simulates observed losses of SOC in soils under intensive agricultural use and the gain in SOC derived from large inputs of animal manure and inclusion of perennial grassland. The model simulates changes in SOC for the entire profile, but lack of data on subsoil SOC storage hampers a proper model evaluation. Experimental verification of management effects on subsoil C storage, subsoil C inputs from roots, and vertical transport of C in the soil profile remains prioritised research areas

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N2O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N2O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N2O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N2O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N2O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N2O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N2O emissions

Challenges of accounting nitrous oxide emissions from agricultural crop residues

Crop residues are important inputs of carbon (C) and nitrogen (N) to soils and thus directly and indirectly affect nitrous oxide (N$_2$O) emissions. As the current inventory methodology considers N inputs by crop residues as the sole determining factor for N$_2$O emissions, it fails to consider other underlying factors and processes. There is compelling evidence that emissions vary greatly between residues with different biochemical and physical characteristics, with the concentrations of mineralizable N and decomposable C in the residue biomass both enhancing the soil N$_2$O production potential. High concentrations of these components are associated with immature residues (e.g., cover crops, grass, legumes, and vegetables) as opposed to mature residues (e.g., straw). A more accurate estimation of the short-term (months) effects of the crop residues on N$_2$O could involve distinguishing mature and immature crop residues with distinctly different emission factors. The medium-term (years) and long-term (decades) effects relate to the effects of residue management on soil N fertility and soil physical and chemical properties, considering that these are affected by local climatic and soil conditions as well as land use and management. More targeted mitigation efforts for N$_2$O emissions, after addition of crop residues to the soil, are urgently needed and require an improved methodology for emission accounting. This work needs to be underpinned by research to (1) develop and validate N$_2$O emission factors for mature and immature crop residues, (2) assess emissions from belowground residues of terminated crops, (3) improve activity data on management of different residue types, in particular immature residues, and (4) evaluate long-term effects of residue addition on N$_2$O emissions

Enhanced wheat yield by biochar addition under different mineral fertilization levels

Climate change and global warming have worldwide adverse consequences. Biochar production and its use in agriculture can play a key role in climate change mitigation and help improve the quality and management of waste materials coming from agriculture and forestry. Biochar is a carbonaceous material obtained from thermal decomposition of residual biomass at relatively low temperature and under oxygen limited conditions (pyrolysis). Biochar is currently a subject of active research worldwide because it can constitute a viable option for sustainable agriculture due to its potential as a long-term sink for carbon in soil and benefits for crops. However, to date, the results of research studies on biochar effects on crop production show great variability, depending on the biochar type and experimental conditions. Therefore, it is important to identify the beneficial aspects of biochar addition to soil on crop yield in order to promote the adoption of this practice in agriculture. In this study, the effects of two types of biochar from agricultural wastes typical of Southern Spain: wheat straw and olive tree pruning, combined with different mineral fertilization levels on the growth and yield of wheat (Triticum durum L. cv. Vitron) were evaluated. Durum wheat was pot-grown for 2 months in a growth chamber on a soil collected from an agricultural field near Córdoba, Southern Spain. Soil properties and plant growth variables were studied in order to assess the agronomic efficiency of biochar. Our results show that biochar addition to a nutrientpoor, slightly acidic loamy sand soil had little effect on wheat yield in the absence of mineral fertilization. However, at the highest mineral fertilizer rate, addition of biochar led to about 20–30 % increase in grain yield compared with the use of the mineral fertilizer alone. Both biochars acted as a source of available P, which led to beneficial effects on crop production. In contrast, the addition of biochar resulted in decreases in available N and Mn. A maximum reduction in plant nutrient concentration of 25 and 80% compared to nonbiochar-treated soils for N and Mn, respectively, was detected. This fact was related to the own nature of biochar: low available nitrogen content, high adsorption capacity, and low mineralization rate for N; and alkaline pH and high carbonate content for Mn. Our results indicate that biochar-based soil management strategies can enhance wheat production with the environmental benefits of global warming mitigation. This can contribute positively to the viability and benefits of agricultural production systems. However, the nutrient–biochar interactions should receive special attention due to the great variability in the properties of biochar-type materials

Multi-objective calibration of RothC using measured carbon stocks and auxiliary data of a long-term experiment in Switzerland

Interactions between model parameters and low spatiotemporal resolution of available data mean that conventional soil organic carbon (SOC) models are often affected by equifinality, with consequent uncertainty in SOC forecasts. Estimation of belowground C inputs is another major source of uncertainty in SOC modelling. Models are usually calibrated on SOC stocks and fluxes from long‐term experiments (LTEs), whereas other point data are not used for constraining the model parameters. We used data from an agricultural long‐term (> 65 years) fertilization experiment to test a multi‐objective parameter estimation approach on the RothC model, combining SOC data from different fertilization treatments with microbial biomass, basal respiration and Zimmermann’s fractions data. We also compared two methods to estimate the belowground C inputs: a conventional scaling of belowground biomass from crop harvest yield and an alternative approach based on constant belowground C for cereals measured experimentally in the field. The resulting posterior parameter distributions still suffered from some equifinality; the most stable C pool kinetic constants and composition of exogenous organic matter were the most sensitive parameters. The use of fixed belowground C inputs for cereals improved the model performance, reducing the importance of treatment‐specific parameters and processes. The introduction of microbial biomass and basal respiration data was effective for increasing determination of the calibration, but also suggested a change in the model structure: the microbial biomass pool, which is proportional to the C inputs in the traditional models, could be represented by different microbial physiology functions

Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

ACKNOWLEDGEMENTS This study was supported by the project “C and N models inter-comparison and improvement to assess management options for GHG mitigation in agro-systems worldwide” (CN-MIP, 2014- 2017), which received funding by a multi-partner call on agricultural greenhouse gas research of the Joint Programming Initiative ‘FACCE’ through national financing bodies. S. Recous, R. Farina, L. Brilli, G. Bellocchi and L. Bechini received mobility funding by way of the French Italian GALILEO programme (CLIMSOC project). The authors acknowledge particularly the data holders for the Long Term Bare-Fallows, who made their data available and provided additional information on the sites: V. Romanenkov, B.T. Christensen, T. Kätterer, S. Houot, F. van Oort, A. Mc Donald, as well as P. Barré. The input of B. Guenet and C. Chenu contributes to the ANR “Investissements d’avenir” programme with the reference CLAND ANR-16-CONV-0003. The input of P. Smith and C. Chenu contributes to the CIRCASA project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774378 and the projects: DEVIL (NE/M021327/1) and Soils‐R‐GRREAT (NE/P019455/1). The input of B. Grant and W. Smith was funded by Science and Technology Branch, Agriculture and Agri-Food Canada, under the scope of project J-001793. The input of A. Taghizadeh-Toosi was funded by Ministry of Environment and Food of Denmark as part of the SINKS2 project. The input of M. Abdalla contributes to the SUPER-G project, which received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement no 774124.Peer reviewedPostprin