Biophysical impacts of climate-smart agriculture in the Midwest United States.

The potential impacts of climate change in the Midwest United States present unprecedented challenges to regional agriculture. In response to these challenges, a variety of climate-smart agricultural methodologies have been proposed to retain or improve crop yields, reduce agricultural greenhouse gas emissions, retain soil quality and increase climate resilience of agricultural systems. One component that is commonly neglected when assessing the environmental impacts of climate-smart agriculture is the biophysical impacts, where changes in ecosystem fluxes and storage of moisture and energy lead to perturbations in local climate and water availability. Using a combination of observational data and an agroecosystem model, a series of climate-smart agricultural scenarios were assessed to determine the biophysical impacts these techniques have in the Midwest United States. The first scenario extended the growing season for existing crops using future temperature and CO2 concentrations. The second scenario examined the biophysical impacts of no-till agriculture and the impacts of annually retaining crop debris. Finally, the third scenario evaluated the potential impacts that the adoption of perennial cultivars had on biophysical quantities. Each of these scenarios was found to have significant biophysical impacts. However, the timing and magnitude of the biophysical impacts differed between scenarios.

[1]  Tracy E. Twine,et al.  Evaluating a terrestrial ecosystem model with satellite information of greenness , 2008 .

[2]  J. Lenters,et al.  Quantifying the impact of groundwater depth on evapotranspiration in a semi-arid grassland region , 2009 .

[3]  R. Arritt,et al.  Regional climate impacts of a biofuels policy projection , 2013 .

[4]  C. Kucharik,et al.  Residue, respiration, and residuals: Evaluation of a dynamic agroecosystem model using eddy flux measurements and biometric data , 2007 .

[5]  Devon E. Worth,et al.  Impact of land use change on the diurnal cycle climate of the Canadian Prairies , 2013 .

[6]  Christopher B. Field,et al.  Direct impacts on local climate of sugar-cane expansion in Brazil , 2011 .

[7]  Water use efficiency of perennial and annual bioenergy crops in central Illinois. , 2013 .

[8]  J. Lenters,et al.  Surface water balance of the continental United States, 1963–1995: Regional evaluation of a terrestrial biosphere model and the NCEP/NCAR reanalysis , 2000 .

[9]  B. Kimball,et al.  Global Warming Can Negate the Expected CO2 Stimulation in Photosynthesis and Productivity for Soybean Grown in the Midwestern United States1[W][OA] , 2013, Plant Physiology.

[10]  R. Betts.  Offset of the potential carbon sink from boreal forestation by decreases in surface albedo , 2000, Nature.

[11]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[12]  J. Steiner.  Tillage and Surface Residue Effects on Evaporation from Soils , 1989 .

[13]  Andrew E. Suyker,et al.  Land management and land-cover change have impacts of similar magnitude on surface temperature , 2014 .

[14]  J. Norman,et al.  Surface energy balance of a corn residue-covered field , 1998 .

[15]  Hideki Kobayashi,et al.  Integration of MODIS land and atmosphere products with a coupled‐process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales , 2011 .

[16]  A. VanLoocke,et al.  Rising ozone concentrations decrease soybean evapotranspiration and water use efficiency whilst increasing canopy temperature. , 2012, The New phytologist.

[17]  D. Lawrence,et al.  Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model , 2011 .

[18]  C. Kucharik,et al.  A biophysical model of Sugarcane growth , 2012 .

[19]  Stephen J. Del Grosso,et al.  Impact of second‐generation biofuel agriculture on greenhouse‐gas emissions in the corn‐growing regions of the US , 2012 .

[20]  E. Kalnay,et al.  North American Regional Reanalysis: Evaluation Highlights and Early Usage , 2005 .

[21]  Christopher B Field,et al.  Direct climate effects of perennial bioenergy crops in the United States , 2011, Proceedings of the National Academy of Sciences.

[22]  Nathalie de Noblet-Ducoudré,et al.  Climatic Impact of Global-Scale Deforestation: Radiative versus Nonradiative Processes , 2010 .

[23]  Christopher M. Danforth,et al.  The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place , 2013, PloS one.

[24]  N. Ramankutty,et al.  Green surprise? How terrestrial ecosystems could affect earth’s climate , 2003 .

[25]  I. E. Woodrow,et al.  A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions , 1987 .

[26]  William J. Sacks,et al.  Crop management and phenology trends in the U.S. Corn Belt: Impacts on yields, evapotranspiration and energy balance , 2011 .

[27]  Tamlin M. Pavelsky,et al.  Evaluation of present and future North American Regional Climate Change Assessment Program (NARCCAP) regional climate simulations over the southeast United States , 2012 .

[28]  Carl J. Bernacchi,et al.  Carbon budget of mature no-till ecosystem in North Central Region of the United States , 2005 .

[29]  C. Delire,et al.  Evaluating the performance of a land Surface / ecosystem model with biophysical measurements from contrasting environments , 1999 .

[30]  James W. Jones,et al.  Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison , 2013, Proceedings of the National Academy of Sciences.

[31]  C. Kucharik,et al.  Evaluating the impacts of land management and climate variability on crop production and nitrate export across the Upper Mississippi Basin , 2003 .

[32]  Richard G. Jones,et al.  A Regional Climate Change Assessment Program for North America , 2009 .

[33]  Douglas A. Miller,et al.  A Conterminous United States Multilayer Soil Characteristics Dataset for Regional Climate and Hydrology Modeling , 1998 .

[34]  M. Tedesco,et al.  An updated Antarctic melt record through 2009 and its linkages to high‐latitude and tropical climate variability , 2009 .

[35]  Rattan Lal,et al.  No-tillage and soil-profile carbon sequestration : An on-farm assessment , 2008 .

[36]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[37]  P. K. Snyder,et al.  Modeling the Atmospheric Response to Irrigation in the Great Plains. Part I: General Impacts on Precipitation and the Energy Budget , 2012 .

[38]  J. Seibert,et al.  Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods , 2012 .

[39]  M. S. Moran,et al.  Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence , 2014, Proceedings of the National Academy of Sciences.

[40]  Richard D. Starr,et al.  Major-Element Abundances on the Surface of Mercury: Results from the MESSENGER Gamma-Ray Spectrometer , 2012 .

[41]  D. G. Rao,et al.  Consequences of future climate change and changing climate variability on maize yields in the midwestern United States , 2000 .

[42]  Carl J. Bernacchi,et al.  The impacts of Miscanthus×giganteus production on the Midwest US hydrologic cycle , 2010 .

[43]  C. Kucharik.  Evaluation of a Process-Based Agro-Ecosystem Model (Agro-IBIS) across the U.S. Corn Belt: Simulations of the Interannual Variability in Maize Yield , 2003 .

[44]  J. Amthor,et al.  The role of maintenance respiration in plant growth , 1984 .

[45]  P. K. Snyder,et al.  Drought and Deforestation: Has Land Cover Change Influenced Recent Precipitation Extremes in the Amazon? , 2014 .

[46]  M. Zeri,et al.  Carbon exchange by establishing biofuel crops in Central Illinois , 2011 .

[47]  Gregory P. Asner,et al.  Variability in Leaf and Litter Optical Properties: Implications for BRDF Model Inversions Using AVHRR, MODIS, and MISR , 1998 .

[48]  Carl J. Bernacchi,et al.  A Regional Comparison of Water Use Efficiency for Miscanthus, Switchgrass and Maize , 2012 .

[49]  D. Deryng,et al.  Simulating the effects of climate and agricultural management practices on global crop yield , 2011 .

[50]  D. Pollard,et al.  A Global Climate Model (GENESIS) with a Land-Surface Transfer Scheme (LSX). Part II: CO2 Sensitivity , 1995 .

[51]  D. Pollard,et al.  A Global Climate Model (GENESIS) with a Land-Surface Transfer Scheme (LSX). Part I: Present Climate Simulation. , 1995 .

[52]  W. Schlenker,et al.  Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change , 2009, Proceedings of the National Academy of Sciences.

[53]  William J. Sacks,et al.  Effects of global irrigation on the near-surface climate , 2009 .

[54]  Christopher J. Kucharik,et al.  Miscanthus Establishment and Overwintering in the Midwest USA: A Regional Modeling Study of Crop Residue Management on Critical Minimum Soil Temperatures , 2013, PloS one.

[55]  T. Sauer,et al.  Crop residue effects on surface radiation and energy balance — review , 1996 .

[56]  Richard M. Cruse,et al.  Sustainable Biofuels Redux , 2008, Science.

[57]  Summary for Policy-makers Arctic Pollution Issues 2015 , .

[58]  R. Nelson,et al.  Ozone Exposure Response for U.S. Soybean Cultivars: Linear Reductions in Photosynthetic Potential, Biomass, and Yield1[W][OA] , 2012, Plant Physiology.

[59]  Mikhail Ovchinnikov,et al.  Droplet nucleation: Physically‐based parameterizations and comparative evaluation , 2011 .

[60]  Pete Smith,et al.  'Agriculture', in Climate change 2007: mitigation , 2007 .

[61]  Marcos Heil Costa,et al.  Climate-regulation services of natural and agricultural ecoregions of the Americas , 2012 .

[62]  F. D’Ortenzio,et al.  Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors (MERIS, SeaWiFS and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project) , 2008 .

[63]  Christopher J Kucharik,et al.  Integrated BIosphere Simulator (IBIS) yield and nitrate loss predictions for Wisconsin maize receiving varied amounts of nitrogen fertilizer. , 2003, Journal of environmental quality.

[64]  Y. Qian,et al.  A Modeling Study of Irrigation Effects on Surface Fluxes and Land–Air–Cloud Interactions in the Southern Great Plains , 2013 .

[65]  Carl J. Bernacchi,et al.  The conversion of the corn/soybean ecosystem to no‐till agriculture may result in a carbon sink , 2005 .

[66]  D. Lobell,et al.  Food security and food production systems , 2017 .

[67]  C. Kucharik,et al.  Impacts of recent climate change on Wisconsin corn and soybean yield trends , 2008 .

[68]  A. Thomson,et al.  Climate Impacts on Agriculture: Implications for Crop Production , 2011 .

[69]  Xuesong Zhang,et al.  Sustainable bioenergy production from marginal lands in the US Midwest , 2013, Nature.

[70]  D. Lobell,et al.  The Influence of Climate Change on Global Crop Productivity1 , 2012, Plant Physiology.

[71]  G. Collatz,et al.  Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer , 1991 .

[72]  C. Field,et al.  Potential impact of U.S. biofuels on regional climate , 2009 .

[73]  Wim Klaassen,et al.  The contribution of ocean‐leaving DMS to the global atmospheric burdens of DMS, MSA, SO2, and NSS SO4= , 2003 .