Estimating the impacts of climate change on crop yields and N2O emissions for conventional and no-tillage in Southwestern Ontario, Canada (original) (raw)
Related papers
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.
Climatic Change, 2015
The effect of climate change on crop production and nitrate-nitrogen (NO 3 -N) pollution from subsurface drained fields is of a great concern. Using the calibrated and validated RZWQM2 (coupled with CERES-Maize and CROPGRO in DSSAT), the potential effects of climate change and elevated atmospheric CO 2 concentrations (CO 2 ) on tile drainage volume, NO 3 -N losses, and crop production were assessed integrally for the first time for a corn-soybean rotation cropping system near Gilmore City, Iowa. RZWQM2 simulated results under 20-year observed historical weather data (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) and ambient CO 2 were compared to those under 20-year projected future meteorological data (2045-2064) and elevated CO 2 , with all management practices unchanged. The results showed that, under the future climate, tile drainage, NO 3 -N loss and flow-weighted average NO 3 -N concentration (FWANC) increased by 4.2 cm year −1 (+14.5 %), 11.6 kg N ha −1 year −1 (+33.7 %) and 2.0 mg L −1 (+ 16.4 %), respectively. Yields increased by 875 kg ha −1 (+28.0 %) for soybean [Glycine max (L.) Merr.] but decreased by 1380 kg ha −1 (−14.7 %) for corn (Zea mays L.). The yield of the C 3 soybean increased mostly due to CO 2 enrichment but increased temperature had negligible effect. However, the yield of C 4 corn decreased largely because of fewer days to physiological maturity due to increased temperature and limited benefit of elevated CO 2 to corn yield under subhumid climate. Relative humidity, short wave radiation and wind speed had small or negligible impacts on FWANC or grain yields. With the predicted trend, this study suggests that to mitigate NO 3 -N pollution from subsurface drained corn-soybean field in Iowa is a more challenging task in the future without changing current management practices. This study also demonstrates the advantage of an agricultural system model in assessing climate change Climatic Change
Assessing the effects of climate change on crop production and GHG emissions in Canada
Agriculture, Ecosystems & Environment, 2013
Regions in northern latitudes are likely to be strongly affected by climate change with shifts in weather that may be conducive to increased agricultural productivity. In this study the DNDC model was used to assess the effect of climate change on crop production and GHG emissions at long-term experimental sites in Canada. Crop production in the model was parameterized using measured data, and then simulations were performed using historical weather and future IPCC SRES climate scenarios (2040-2069). The DNDC model predicted that for western Canada under the SRES scenarios and no change in cultivar, yields of spring wheat would increase by 37% and winter wheat by 70%. Corn responded favorably to an increase in heat units at the eastern site with a 60% increase in yields. At all locations, yields were projected to increase further when new cultivars with higher GDD requirements were assumed. These increases were notable considering that the estimated soil water deficit indices indicated that there could be less water available for crop growth in the future. However, when accounting for increased water use efficiency under elevated CO 2 , DNDC predicted less crop water stress. Nitrous oxide emissions per ton of wheat were projected to increase across most of western Canada by about 60% on average for the A1b and A2 SRES scenarios and by about 30% for the B1 scenario. Nitrous oxide emissions per unit area were predicted to increase under corn production at the eastern location but to remain stable per ton of grain. Model results indicated that climate change in Canada will favor increased crop production but this may be accompanied by an increase in net GHG emissions for small grain production.
Modelling C, N, water and heat dynamics in winter wheat under climate change in southern Sweden
Agriculture, Ecosystems & Environment, 2001
The possible consequences of climate change on carbon and nitrogen budgets of winter wheat were examined by means of model predictions. Biomass, nitrogen, water and heat dynamics were simulated for long-term climatic conditions in central and southern Sweden for a clay soil and a sandy soil. The effects of elevated atmospheric CO 2 and changed climate as predicted for 2050 were simulated daily with two linked process orientated models for soil and plant (SOIL/SOILN). The models had previously been calibrated against several variables at the sites under present conditions, and the long-term predictions at present climate were shown to correspond reasonably well with measured soil C and N trends in long-term experiments. The climate and CO 2 conditions for the year 2050 were represented by climatic scenarios from a global climate model, and the elevated atmospheric CO 2 concentration was assumed to change plant parameter values in accordance with literature data.
Horticulturae, 2016
As with any other crop, maize yield is a response to environmental factors such as soil, weather, and management. In a context of climate change, understanding responses is crucial to determine mitigation and adaptation strategies. Crop models are an effective tool to address this. The objective was to present a procedure to assess the impacts of climate scenarios on maize N use efficiency and yield, with the effect of cultivar (n = 2) and planting date (n = 5) as adaptation strategies. The study region was Santa Catarina, Brazil, where maize is cultivated on more than 800,000 ha (average yield: 4.63 t•ha −1). Surveying and mapping of crop land was done using satellite data, allowing the coupling of weather and 253 complete soil profiles in single polygons (n = 4135). A Decision Support System for Agrotechnology Transfer (DSSAT) crop model was calibrated and validated using field data (2004-2010 observations). Weather scenarios generated by Regional Climatic Models (RCMs) were selected according their capability of reproducing observed weather. Simulations for the 2012-2040 period (437 ppm CO 2) showed that without adaptation strategies maize production could be reduced by 12.5%. By only using the best cultivar for each polygon (combination of soil + weather), the total production was increased by 6%; when using both adaptation strategies-cultivar and best planting date-the total production was increase by 15%. The modelling process indicated that the N use efficiency increment ranged from 1%-3% (mostly due to CO 2 increment, but also due to intrinsic soil properties and leaching occurrence). This analysis showed that N use efficiency rises in high CO 2 scenarios, so that crop cultivar and planting date are effective tools to mitigate deleterious effects of climate change, supporting energy crops in the study region.
Soil greenhouse gas fluxes and global warming potential in four high-yielding maize systems
Global Change Biology, 2007
Crop intensification is often thought to increase greenhouse gas (GHG) emissions, but studies in which crop management is optimized to exploit crop yield potential are rare. We conducted a field study in eastern Nebraska, USA to quantify GHG emissions, changes in soil organic carbon (SOC) and the net global warming potential (GWP) in four irrigated systems: continuous maize with recommended best management practices (CCrec) or intensive management (CC-int) and maize-soybean rotation with recommended (CS-rec) or intensive management (CS-int). Grain yields of maize and soybean were generally within 80-100% of the estimated site yield potential. Large soil surface carbon dioxide (CO 2 ) fluxes were mostly associated with rapid crop growth, high temperature and high soil water content. Within each crop rotation, soil CO 2 efflux under intensive management was not consistently higher than with recommended management. Owing to differences in residue inputs, SOC increased in the two continuous maize systems, but decreased in CS-rec or remained unchanged in CS-int. N 2 O emission peaks were mainly associated with high temperature and high soil water content resulting from rainfall or irrigation events, but less clearly related to soil NO 3 -N levels. N 2 O fluxes in intensively managed systems were only occasionally greater than those measured in the CC-rec and CS-rec systems. Fertilizer-induced N 2 O emissions ranged from 1.9% to 3.5% in 2003, from 0.8% to 1.5% in 2004 and from 0.4% to 0.5% in 2005, with no consistent differences among the four systems. All four cropping systems where net sources of GHG. However, due to increased soil C sequestration continuous maize systems had lower GWP than maizesoybean systems and intensive management did not cause a significant increase in GWP. Converting maize grain to ethanol in the two continuous maize systems resulted in a net reduction in life cycle GHG emissions of maize ethanol relative to petrol-based gasoline by 33-38%. Our study provided evidence that net GHG emissions from agricultural systems can be kept low when management is optimized toward better exploitation of the yield potential. Major components for this included (i) choosing the right combination of adopted varieties, planting date and plant population to maximize crop biomass productivity, (ii) tactical water and nitrogen (N) management decisions that contributed to high N use efficiency and avoided extreme N 2 O emissions, and (iii) a deep tillage and residue management approach that favored the build-up of soil organic matter from large amounts of crop residues returned. *Within each column, season, and year emissions followed by the same letter are not significantly different at Po0.05. w Growing season refers to the period from emergence to harvest of the crop. z Nongrowing season refers to the period from harvest of the crops in fall to crop emergence in spring. CO 2 , carbon dioxide; N 2 O, nitrous oxide.
Global Change Biology, 2012
Major sources of greenhouse gas (GHG) emissions from agricultural crop production are nitrous oxide (N 2 O) emissions resulting from the application of mineral and organic fertilizer, and carbon dioxide (CO 2) emissions from soil carbon losses. Consequently, choice of fertilizer type, optimizing fertilizer application rates and timing, reducing microbial denitrification and improving soil carbon management are focus areas for mitigation. We have integrated separate models derived from global data on fertilizer-induced soil N 2 O emissions, soil nitrification inhibitors, and the effects of tillage and soil inputs of soil C stocks into a single model to determine optimal mitigation options as a function of soil type, climate, and fertilization rates. After Monte Carlo sampling of input variables, we aggregated the outputs according to climate, soil and fertilizer factors to consider the benefits of several possible emissions mitigation strategies, and identified the most beneficial option for each factor class on a per-hectare basis. The optimal mitigation for each soil-climate-region was then mapped to propose geographically specific optimal GHG mitigation strategies for crops with varying N requirements. The use of empirical models reduces the requirements for validation (as they are calibrated on globally or continentally observed phenomena). However, as they are relatively simple in structure, they may not be applicable for accurate site-specific prediction of GHG emissions. The value of this modelling approach is for initial screening and ranking of potential agricultural mitigation options and to explore the potential impact of regional agricultural GHG abatement policies. Given the clear association between management practice and crop productivity, it is essential to incorporate characterization of the yield effect on a given crop before recommending any mitigation practice.
Global and Planetary Change, 2011
Simulation models can be valuable to investigate potential effects of climate change on greenhouse gas emissions from terrestrial ecosystems. DNDC (the DeNitrification-DeComposition model) was tested against observed soil respiration data from adjacent pasture and arable fields in the Irish midlands. The arable field was converted from grassland approximately 50 years ago and managed since 2003 under two different tillage systems; conventional and reduced tillage. Both fields were located on the same soil type, classified as a free draining sandy loam soil derived from fluvial glacial gravels with low soil moisture holding capacity. Soil respiration measurements were made from January 2003 to August 2005. Three climate scenarios were investigated, a baseline of measured climatic data from a weather station at the field site, and high and low temperature sensitivity scenarios predicted by the Community Climate Change Consortium for Ireland (C4I) based on the Hadley Centre Global Climate Model (HadCM 3 ) and the Intergovernment Panel on Climate 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.
Soil Carbon Response to Projected Climate Change in the US Western Corn Belt
Journal of Environmental Quality, 2018
The western US Corn Belt is projected to experience major changes in growing conditions due to climate change over the next 50 to 100 yr. Projected changes include increases in growing season length, number of high temperature stress days and warm nights, and precipitation, with more heavy rainfall events. The impact these changes will have on soil organic carbon (SOC) needs to be estimated and adaptive changes in management developed to sustain soil health and system services. The process-based model CQESTR was used to model changes in SOC stocks (0-30 cm) of continuous corn (Zea mays L.) and a corn-soybean [Glycine max (L.) Merr.] rotation under disk, chisel, ridge, and no-tillage using projected growing season conditions for the next 50 yr. Input for the model was based on management and harvest records from a long-term tillage study (1986-2015) in eastern Nebraska, and model output was validated using measured changes in SOC from 1999 to 2011 in the study. The validated model was used to estimate changes in SOC over 17 yr under climatic conditions projected for 2065 under two scenarios: (i) crop yields increasing at the observed rate from 1971 to 2016 or (ii) crop yields reduced due to negative effects of increasing temperature. CQESTR estimates of SOC agreed well with measured SOC (R 2 = 0.70, P < 0.0001). Validated model simulated changes in SOC under projected climate change differed among the three soil depths (0-7.5, 7.5-15, and 15-30 cm). Summed over the 0-to 30-cm depth, there were significant three-way interactions of year × rotation × yield (p = 0.014) and year × tillage × yield (p < 0.001). As yield increased, SOC increased under no-tillage continuous corn but was unchanged under no-tillage corn-soybean and ridge tillage regardless of cropping system. Under chisel and disk tillage, SOC declined regardless of cropping system. With declining yields SOC decreased regardless of tillage or cropping system. These results highlight the interaction between genetics and management in maintaining yield trends and soil C.