Testing DNDC model for simulating soil respiration and assessing the effects of climate change on the CO2 gas flux from Irish agriculture

Abstract

Simulation models can be valuable to investigate potential effects of climate change on greenhouse gas emissions from terrestrial ecosystems. DNDC (the DeNitrification- Change (IPCC) A1B emission scenario. The aims of this study were to use measured soil respiration rates to validate the DNDC model for estimating CO 2 efflux from these key Irish soils, investigate the effects of future climate change on CO 2 efflux and estimate the efflux uncertainties due to using different future climate projections.The results indicate that the DNDC model can reliably estimate soil respiration from the two fields examined. The model underestimated annual measured CO 2 efflux from the pasture by only13% (model efficiency: ME = 0.6; root mean square error: RMSE =1.9 and mean absolute error: MAE = 6.3) and that from the arable conventional and A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT3 reduced tillage by 9% (ME = 0.6; RMSE = 1.6 and MAE = 2.4) and 8% (ME = 0.23; RMSE = 1.8 and MAE = 2.9), respectively. Short-term land use change had no significant effects on CO 2 effluxes from soil. Using the high temperature sensitive scenario, future C effluxes would increase by 15% for the pasture and 14 and 16% for the arable conventional and reduced tillage systems, respectively. However, under the low temperature sensitive scenario, lower increases in the C efflux of 6% for the pasture and 5% for the arable field were predicted. The calculated annual CO 2 efflux uncertainties for using the high and low temperature sensitivity scenarios were 9% for the pasture and 8% for the arable field.

Assessment of Global Carbon Dioxide Concentration Using MODIS and GOSAT Data

“…The increased atmospheric CO 2 emissions from the burning of fossil fuels [8,9] and land-use changes [10–12] are such that terrestrial and marine environments are able to absorb approximately one-half to three-quarters of the emitted CO 2 [13,14]. To understand the relationship between land-cover changes and GHG concentration, great efforts have been made to measure the GHG emissions from forests and agricultural systems in recent years [11,15–17], and numerous data from field measurements and laboratory studies have been accumulated.…”

The development of the DNDC plant growth sub-model and the application of DNDC in agriculture: A review

“…Several studies have investigated the effectiveness of the DNDC model to access and predict GHG emissions and crop yields under different management practices and emissions scenarios in wheat fields and have demonstrated that the simulated results of DNDC are helpful in choosing best management practices to decrease nitrate leaching and N 2 O and NO emissions (Ludwig et al, 2011;Smith et al, 2013;Cui et al, 2014;Sansoulet et al, 2014). In addition, DNDC is also widely used and compared with other models to investigate the influence of future climate change and the application of advanced agricultural management measures to achieve good application results in barley fields (Abdalla et al, 2011;Smith et al, 2012;Cardenas et al, 2013;Balashov et al, 2014;Deng et al, 2015).…”

“…Improvements to the soil hydrology framework of the model should be considered for further studies. (5) The predicted N 2 O emissions from organic manure in the absence of any additional N fertilization are often too low (Abdalla et al, 2009(Abdalla et al, , 2011. To fix this error, a portion of the N in manure is allocated to various N pools in Manure-DNDC and the other most recent DNDC models, with a sizable amount going directly to the NH 3 pool.…”

Soil respiration and carbon loss relationship with temperature and land use conversion in freeze–thaw agricultural area

“…Soil respiration (R s ) can discharge carbon dioxide when soil organisms respired, which is the primary source for greenhouse gas (Abdalla et al, 2011;Mangalassery et al, 2015). The R s is the metabolic ecology process with the biophysical feature and is the sensitive indicator for SOC dynamics assessment in agro-landscapes (López-López et al, 2012).…”