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Can we improve interpolation of N2O emission measurements by using environmental factors?
Chiba, M.K., Cichota, R., Vogeler, I. (2012). Can we improve interpolation of N2O emission measurements by using environmental factors? In: Advanced Nutrient Management: Gains from the Past - Goals for the Future. (Eds L.D. Currie and C L. Christensen).
Determining nitrous oxide (N2O) emissions is highly uncertain due to their large spatial and temporal variability. This variability is caused by the many biological processes involved, each responding in a different way to environmental conditions. Also the various processes are often associated with non-linear relationships to gaseous emissions. The objective of this study was to analyse N2O emission from a recently compiled New Zealand N2O database and to verify the possibility of using environmental factors to improve the currently used linear interpolation of measurements. The database comprises a collection of data from 21 trials carried out in New Zealand since 2000, under different climates, with different soils and N loads and sources. Gaseous and soil data collection were performed according to NZ’s Ministry of Agriculture and Forest (MAF) protocols. In this work, we analyzed all data from urine patches treatments (N application ranging from 49 – 1,000 kg/ha) using stepwise multiple regression to select significant variables and to determine their relationship with N2O emissions. Daily measurements of soil water-filled pore space, volumetric water content, soil porosity, sum of rain recorded in the two previous days of gas measurement, soil temperature, air temperature, solar radiation as well as soil organic carbon content and inorganic soil N content were used as environmental variables. Prediction of N2O emissions using environmental parameters resulted in a poor agreement when fitting was done using the whole dataset (R2 =0.16). Improvement of fitting (R2 =0.39) was achieved after filtering the data according to the soil’s nitrate content (soil NO3 content higher than 70% of total inorganic N). This separates the N2O values obtained when denitrification was the dominating process on the production of N2O. For the remaining data, the emissions come from both nitrification and denitrification, and could not be related to environmental factors in a more precise way. Next the data were analysed region specific. For the Waikato region, stepwise regression indicated four variables as significant: rainfall, air temperature, radiation, soil’s clay content, and NO3 amount; while for Otago only rainfall and NO3 amount were significant. Predictive functions based on these variables were used to interpolate N2O emissions and these were compared with the Intergovernmental Panel on Climate Change (IPCC) interpolation approach. Preliminary results suggest that the above procedure is promising and specific tests will be carried out in the future. The relationship between estimated gaseous emissions and environmental factors at the time of high ammonium contents also need to be further investigated.
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