Modelling nitrous oxide emissions from mown-grass and grain-cropping systems: Testing and sensitivity analysis of DailyDayCent using high frequency measurements.

The DailyDayCent biogeochemical model was used to simulate nitrous oxide (N2O) emissions from two contrasting agro-ecosystems viz. a mown-grassland and a grain-cropping system in France. Model performance was tested using high frequency measurements over three years; additionally a local sensitivity analysis was performed. Annual N2O emissions of 1.97 and 1.24kgNha-1year-1 were simulated from mown-grassland and grain-cropland, respectively. Measured and simulated water filled pore space (r=0.86, ME=-2.5%) and soil temperature (r=0.96, ME=-0.63°C) at 10cm soil depth matched well in mown-grassland. The model predicted cumulative hay and crop production effectively. The model simulated soil mineral nitrogen (N) concentrations, particularly ammonium (NH4+), reasonably, but the model significantly underestimated soil nitrate (NO3-) concentration under both systems. In general, the model effectively simulated the dynamics and the magnitude of daily N2O flux over the whole experimental period in grain-cropland (r=0.16, ME=-0.81gNha-1day-1), with reasonable agreement between measured and modelled N2O fluxes for the mown-grassland (r=0.63, ME=-0.65gNha-1day-1). Our results indicate that DailyDayCent has potential for use as a tool for predicting overall N2O emissions in the study region. However, in-depth analysis shows some systematic discrepancies between measured and simulated N2O fluxes on a daily basis. The current exercise suggests that the DailyDayCent may need improvement, particularly the sub-module responsible for N transformations, for better simulating soil mineral N, especially soil NO3- concentration, and N2O flux on a daily basis. The sensitivity analysis shows that many factors such as climate change, N-fertilizer use, input uncertainty and parameter value could influence the simulation of N2O emissions. Sensitivity estimation also helped to identify critical parameters, which need careful estimation or site-specific calibration for successful modelling of N2O emissions in the study region.

Systems approaches in global change and biogeochemistry research.

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.