Testing DNDC model for simulating soil respiration and assessing the effects of climate change on the CO2 gas flux from Irish agriculture (original) (raw)
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Agricultural sciences, 2016
Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135-159 kg•N•ha −1 •yr −1 and crop residues at 3 t•ha −1 •yr −1. For surface soil nitrate (0-10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R 2 = 0.31-0.55, p < 0.05). Only the ECOSSE-simulated N2O fluxes showed a significant relationship (R 2 = 0.33, p < 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N2O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R 2 = 0.34-0.41, p < 0.05). Compared to the measured value (3624 kg•C•ha −1 •yr −1), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH4 uptake well although the ECOSSE * Corresponding author. M. I. Khalil et al. 504 prediction was closer (−29 g•C•ha −1 •yr −1) to the measured one (2.9). The site-specific results imply that the ECOSSE model performed better under Irish conditions. However, further refinement and validation of all of the models with a more extensive dataset that includes other land-use and soil types will be required to determine their suitability in providing national estimates.
Simulation of N2O fluxes from Irish arable soils: effect of climate change and management
Biology and Fertility of Soils, 2010
Emissions of nitrous oxide (N 2 O) from an Irish arable soil were simulated using the DeNitrification-DeComposition (DNDC) model. The soil chosen was a free-draining sandy loam typical of the majority of cereal growing land in Ireland, and one that has been previously used to test and validate DNDC-model. DeNitrification-DeComposition model was considered suitable to estimate N 2 O fluxes from Irish arable soils however, underestimated the flux by 24%. The objectives of this study were to estimate future N 2 O fluxes from a spring barley field under conventional (moulboard plowing) and reduced (chisel plowing) tillage and different N-fertilzer application rates. Three climate scenarios, a baseline of measured climatic data from the weather station at Kilkenny and a high-and low-temperature-sensitive scenarios predicted by the Hadley Global Climate Model (HadCM 4 ) based on the AB1 emission scenario of the Intergovernment Panel on Climate Change (IPCC) were investigated. For conventional tillage under all scenarios, three peaks of N 2 O emissions were predicted; an early spring peak coinciding mostly with soil plowing, a mid/late spring peak coinciding with fertilizer application and an early autumn peak coinciding with residue incorporation and onset of autumn rainfall. Under reduced tillage, due to the less amount of soil disturbance, the early spring peak was not predicted. In all cases, the total amount of N 2 O emitted in the late spring peak due to fertilizer application was less than the sum of the other peaks. Under climate change, using the high-temperatureincrease scenario, DNDC predicted an increase in N 2 O emissions from both conventional and reduced tillage, ranging from 58% to 88% depending upon N application rate. In contrast, annual fluxes of N 2 O either decreased or increased slightly in the low temperature increase scenario relative to N application (−26 to +16%). Outputs from the model indicate that elevated temperature and precipitation increase N mineralization and total denitrification leading to greater fluxes of N 2 O. Annual uncertainties due to the use of two different future climate scenarios were significantly high, ranging from 74% to 95% and from 71% to 90% for the conventional and reduced tillage.
2011
Greenhouse gas emissions (GHG) were simulated from commonly used crop rotations in eastern Poland for conventional and conservation tillage systems. We used denitrification-decomposition (DNDC) model baseline climate conditions and two future climate scenarios (2030 and 2050). Analyzed cropping systems included corn, rapeseed, and spring and winter wheat. It has been shown that an increase of temperature and decrease of precipitation can reduce net global warming potential (GWP) by 2% in the 2030 climate scenario and by 5% in the 2050 scenario in conventional tillage with reference to the baseline scenario. In the case of conservation tillage, a reduction of GWP by 5% and by 10% was estimated. The use of conservation tillage results decrease the GWP by 17-19% in the baseline scenario, in the 2030 scenario by 16-18%, and in the 2050 scenario by 15-17%. It also has been shown that change in climate conditions has declined biomass production of winter wheat and corn, which may suggest that a larger area would be needed for these crops to maintain production at the same level.
2015
The development of climate mitigation services partly depends on our ability to simulate, with confidence, agricultural production and greenhouse gas (GHG) emissions so as to understand the effectiveness of the mitigation approach on both gas emissions and food production. The Soil C-N Group of the Global Research Alliance (GRA) on GHG has initiated an international model benchmarking and inter-comparison that will assess GHG balance and soil C sequestration of arable crops and grasslands as affected by agricultural practices. The inter-comparison arises from collaborations between GRA, AgMIP and four FACCE-JPI projects to lead to the largest exercise in this domain. An initial stock take has been conducted, resulting in the selection of datasets from five grasslands and five crop sites worldwide. A total of 28 models used in 11countries for the prediction of GHG emissions in crop and grassland systems are contributing, ranging from process-oriented models to simpler models. The stu...
Agronomy Journal, 2015
Models of instantaneous soil-surface CO 2 e ux (SCE ins ) are critical for understanding the potential drivers of soil C loss. Several simple SCE ins models have been reported in the literature. Our objective was to compare and validate selected soil temperature (T s )and water content (q v )-based equations for modeling SCE ins among a variety of cropping systems and land management practices. Soil-surface CO 2 e uxes were measured and modeled for grain-harvested corn (Zea mays L.)-soybean [Glycine max (L.) Merr.] rotations, grain-and stover-harvested continuous corn systems with and without a cover crop, and reconstructed prairies with and without N fertilization on soils with subsurface drainage. Soil-surface CO 2 e uxes, T s , and q v were measured from 2008 to 2011. Models calibrated with weekly measured SCE ins , T s , and q v throughout the growing season produced lower root mean squared error (RMSE) than models calibrated with several weeks of hourly measured data. Model selection signi cantly a ected SCE ins estimations, with models that use only T s parameters having lower RMSE than models that use both T s and q v . However, the model that produced the lowest RMSE during validation estimated growing-season SCE that did not signi cantly di er from numerical integration of weekly measured SCE ins . All models had similar residual errors with autocorrelated trends at monthly, weekly, and hourly scales. Autoregressive moving average functions were able to precisely describe the temporal err ors. To accurately model SCE ins and scale across time, improvement of temporal errors in T s -and q v -based SCE ins models is needed to obtain accurate and precise closure of C balances for managed and natural ecosystems.
Global Change Biology, 2004
Elevated atmospheric CO 2 may alter decomposition rates through changes in plant material quality and through its impact on soil microbial activity. This study examines whether plant material produced under elevated CO 2 decomposes differently from plant material produced under ambient CO 2 . Moreover, a long-term experiment offered a unique opportunity to evaluate assumptions about C cycling under elevated CO 2 made in coupled climate-soil organic matter (SOM) models. Trifolium repens and Lolium perenne plant materials, produced under elevated (60 Pa) and ambient CO 2 at two levels of N fertilizer (140 vs. 560 kg ha À1 yr À1 ), were incubated in soil for 90 days. Soils and plant materials used for the incubation had been exposed to ambient and elevated CO 2 under free air carbon dioxide enrichment conditions and had received the N fertilizer for 9 years. The rate of decomposition of L. perenne and T. repens plant materials was unaffected by elevated atmospheric CO 2 and rate of N fertilization. Increases in L. perenne plant material C : N ratio under elevated CO 2 did not affect decomposition rates of the plant material. If under prolonged elevated CO 2 changes in soil microbial dynamics had occurred, they were not reflected in the rate of decomposition of the plant material. Only soil respiration under L. perenne, with or without incorporation of plant material, from the low-N fertilization treatment was enhanced after exposure to elevated CO 2 . This increase in soil respiration was not reflected in an increase in the microbial biomass of the L. perenne soil. The contribution of old and newly sequestered C to soil respiration, as revealed by the 13 C-CO 2 signature, reflected the turnover times of SOM-C pools as described by multipool SOM models. The results do not confirm the assumption of a negative feedback induced in the C cycle following an increase in CO 2 , as used in coupled climate-SOM models. Moreover, this study showed no evidence for a positive feedback in the C cycle following additional N fertilization.
FARMSIM: an integrated tool to model greenhouse gas emissions at the farm level
Impacts of changes in external drivers (global change, N deposition, management, land use change etc.) on fluxes and exchange of N, C and GHG in terrestrial ecosystems 2.1. Impact of land use on stream C and N export in the Danish landscape of Bjerringbro 2.2. Soil chamber and eddy covariance measurements of CO 2 , CH 4 and N 2 O exchange in a deciduous oak woodland in south east England 2.3. Does a land use change influence N dynamics and N2O fluxes on degraded fen peatland? 2.4. C sequestration in intensively managed grasslands is expensive 2.5. Effects of legume density and stocking rate on N 2 O emissions of an upland pasture 64 2.6. The greenhouse gas budget of an intensively managed cropping system in the Mediterranean climate 2.7. Seasonal dynamics of dissolved CH 4 in stream water-contribution to the annual C budget on a northern fen 65 2.8. Production and emission of N 2 O from a drained and afforested peat soil 3. Plot scale modelling of processes controlling the biosphere-atmosphere exchange of trace gases to predict effects of changes in climate, land use and land management on gas exchange of C and N compounds 3.1. Methane production and consumption in upland forest soil layers determined from concentration profiles and chamber fluxes 3.2. Temporal dynamics of N 2 O emissions on compacted or not compacted sugar beet fields: measurement and modelling 3.3. Simulating soil N 2 O and CO 2 emissions from arable organic and conventional systems using two biogeochemical models 3.4. Improving N 2 O simulation with the Pasture Simulation Model (PaSim) 3.5. Simulation of nitrous oxide peak emissions from grassland on drained peat soils 69 4. Up-scaling from plot to regional scales-analysing interactions on different spatial scales 4.1. Ammonia, N 2 O and CO 2 concentration and flux measurements on an agricultural landscape near Bjerringbro, Denmark 4.2. Matter fluxes between atmosphere and an agricultural surface-Modified Bowen Ratio (MBR) versus Eddy Covariance (EC) Measurements 4.3. Temporal and small scale spatial variability of chamber measured N and C trace gas fluxes following slurry application 1.6. Nitrifier denitrification can be a source of N 2 O from soil: a revised approach to the dual isotope labelling method
Modeling soil CO2 emissions from ecosystems
Biogeochemistry, 2005
We present a new soil respiration model, describe a formal model testing procedure, and compare our model with five alternative models using an extensive data set of observed soil respiration. Gas flux data from rangeland soils that included a large number of measurements at low temperatures were used to model soil CO 2 emissions as a function of soil temperature and water content. Our arctangent temperature function predicts that Q 10 values vary inversely with temperature and that CO 2 fluxes are significant below 0°C. Independent data representing a broad range of ecosystems and temperature values were used for model testing. The effects of plant phenology, differences in substrate availability among sites, and water limitation were accounted for so that the temperature equations could be fairly evaluated. Four of the six tested models did equally well at simulating the observed soil CO 2 respiration rates. However, the arctangent variable Q 10 model agreed closely with observed Q 10 values over a wide range of temperatures (r 2 = 0.94) and was superior to published variable Q 10 equations using the Akaike information criterion (AIC). The arctangent temperature equation explained 16-85% of the observed intra-site variability in CO 2 flux rates. Including a water stress factor yielded a stronger correlation than temperature alone only in the dryland soils. The observed change in Q 10 with increasing temperature was the same for data sets that included only heterotrophic respiration and data sets that included both heterotrophic and autotrophic respiration.
The Influence of Agroclimatic Factors on Soil CO2 Emissions
Collegium Antropologicum, 2014
There has been a significant increase of atmospheric greenhouse gas (GHG) concentrations since industrial revolution till nowadays. Approximately 10% of total GHG emissions in Croatia belong to the agricultural sector. In this sector, one part of CO 2 is released from soil by soil respiration (soil CO 2 efflux). Due to these facts, it is of scientists' interest to determine the influence of tillage treatments on soil CO 2 efflux and to determine a relationship between tillage induced CO 2 emissions and climatic factors. Field experiment with six different tillage treatments was set up on Stagnic Luvisols near Daruvar (central lowland Croatia). Tillage treatments were: black fallow (BF), ploughing up and down the slope to 30 cm (PUDS), no -tillage (NT), ploughing up and down slope to 30 cm (PAS), very deep ploughing across the slope to 50 cm (VDPAS) and subsoiling across the slope to 50 cm (SSPAS). Soil CO 2 efflux was measured using closed static chamber method to quantify soil CO 2 efflux during 2012 (n=13) when cover crop was corn. Tillage had a significant effect on CO 2 efflux. The lowest average CO 2 efflux was determined at the BF treatment with the average CO 2 efflux of 29.4 kg ha -1 day -1 . Comparing the treatments with the cover crop, the highest average CO 2 efflux was determined at the NT treatment followed by SSPAS, VDPAS, PAS and PUDS treatment with the average CO 2 efflux of 90.9 kg ha -1 day -1 , 83.5 kg ha -1 day -1 , 68.9 kg ha -1 day -1 , 66.7 kg ha -1 day -1 , 56.0 kg ha -1 day -1 respectively. Average CO 2 effluxes were moderate positively correlated with soil temperatures at 10 cm depth (r=0.42), moderate positively correlated with air temperature (r=0.45), and non correlated with soil moisture content at 10 cm depth (r=0.08), while strong negatively correlated with relative air humidity (r=0.55). The CO 2 efflux was higher during the second half of spring and in the first half of summer while lower CO 2 efflux was determined during the period autumn -winter CO 2 effluxes were higher in first half of corn growing season than in the second half of corn growing season and the period without the cover crop. Our study suggests that tillage practices have significant influence on soil CO 2 emissions.