Modeling agriculture in the Community Land Model

Abstract. The potential impact of climate change on agriculture is uncertain. In addition, agriculture could influence above- and below-ground carbon storage. Development of models that represent agriculture is necessary to address these impacts. We have developed an approach to integrate agriculture representations for three crop types – maize, soybean, and spring wheat – into the coupled carbon–nitrogen version of the Community Land Model (CLM), to help address these questions. Here we present the new model, CLM-Crop, validated against observations from two AmeriFlux sites in the United States, planted with maize and soybean. Seasonal carbon fluxes compared well with field measurements for soybean, but not as well for maize. CLM-Crop yields were comparable with observations in countries such as the United States, Argentina, and China, although the generality of the crop model and its lack of technology and irrigation made direct comparison difficult. CLM-Crop was compared against the standard CLM3.5, which simulates crops as grass. The comparison showed improvement in gross primary productivity in regions where crops are the dominant vegetation cover. Crop yields and productivity were negatively correlated with temperature and positively correlated with precipitation, in agreement with other modeling studies. In case studies with the new crop model looking at impacts of residue management and planting date on crop yield, we found that increased residue returned to the litter pool increased crop yield, while reduced residue returns resulted in yield decreases. Using climate controls to signal planting date caused different responses in different crops. Maize and soybean had opposite reactions: when low temperature threshold resulted in early planting, maize responded with a loss of yield, but soybean yields increased. Our improvements in CLM demonstrate a new capability in the model – simulating agriculture in a realistic way, complete with fertilizer and residue management practices. Results are encouraging, with improved representation of human influences on the land surface and the potentially resulting climate impacts.

[1]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[2]  J. Prioul,et al.  Modelling postsilking nitrogen fluxes in maize (Zea mays) using 15N-labelling field experiments. , 2006, The New phytologist.

[3]  R. Valentini,et al.  A new assessment of European forests carbon exchanges by eddy fluxes and artificial neural network spatialization , 2003 .

[4]  M. Iijima,et al.  Deep Rooting in Winter Wheat: Rooting Nodes of Deep Roots in Two Cultivars with Deep and Shallow Root Systems , 2001, Plant production science.

[5]  Robert B. Jackson,et al.  © 2001 Kluwer Academic Publishers. Printed in the Netherlands. The distribution of soil nutrients with depth: Global patterns and the imprint of plants , 2022 .

[6]  T. Vesala,et al.  On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm , 2005 .

[7]  G. Fischer,et al.  Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080 , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[8]  C. Field,et al.  Global scale climate–crop yield relationships and the impacts of recent warming , 2007, Environmental Research Letters.

[9]  P. Jones,et al.  REPRESENTING TWENTIETH CENTURY SPACE-TIME CLIMATE VARIABILITY. , 1998 .

[10]  N. Ramankutty,et al.  Characterizing the Spatial Patterns of Global Fertilizer Application and Manure Production , 2010 .

[11]  G. Fischer,et al.  Effects of climate change on global food production under SRES emissions and socio-economic scenarios , 2004 .

[12]  Noah S. Diffenbaugh,et al.  Influence of modern land cover on the climate of the United States , 2009 .

[13]  Jacinto F. Fabiosa,et al.  Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change , 2008, Science.

[14]  R. Allmaras,et al.  Corn-Soybean Sequence and Tillage Effects on Soil Carbon Dynamics and Storage , 2007 .

[15]  R. Weiland,et al.  Nitrogen Partitioning in Maize during Ear Development , 1992 .

[16]  K. Nawab,et al.  Response of Specific Leaf Area (SLA), Leaf Area Index (LAI) and Leaf Area Ratio (LAR) of Maize (Zea mays L.) To Plant Density, Rate and Timing of Nitrogen Application , 2007 .

[17]  W. Post,et al.  Soil organic carbon sequestration rates by tillage and crop rotation : A global data analysis , 2002 .

[18]  P. Thornton,et al.  Ecosystem model spin-up: Estimating steady state conditions in a coupled terrestrial carbon and nitrogen cycle model , 2005 .

[19]  Andrew J. Challinor,et al.  Development and assessment of a coupled crop–climate model , 2007 .

[20]  Aude Barbottin,et al.  Nitrogen Remobilization during Grain Filling in Wheat: Genotypic and Environmental Effects , 2005 .

[21]  David M. Lawrence,et al.  Examining the Interaction of Growing Crops with Local Climate Using a Coupled Crop–Climate Model , 2009 .

[22]  T. W. Crawford,et al.  Sources, Fluxes, and Sinks of Nitrogen during Early Reproductive Growth of Maize (Zea mays L.). , 1982, Plant physiology.

[23]  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.

[24]  N. Batjes,et al.  ISRIC-WISE Harmonized Global Soil Profile Dataset (Ver. 3.1) , 2008 .

[25]  B. Dale,et al.  Biofuels, land use change, and greenhouse gas emissions: some unexplored variables. , 2009, Environmental science & technology.

[26]  Navin Ramankutty,et al.  Geographic distribution of major crops across the world , 2004 .

[27]  D. Lobell,et al.  Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields , 2012, Climatic Change.

[28]  C. Boast,et al.  The myth of nitrogen fertilization for soil carbon sequestration. , 2007, Journal of environmental quality.

[29]  Tracey Holloway,et al.  Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology , 2008 .

[30]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[31]  Daniel T. Walters,et al.  Maize Root Biomass and Net Rhizodeposited Carbon , 2006 .

[32]  N. Ramankutty,et al.  Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000 , 2008 .

[33]  Peter E. Thornton,et al.  An Improved Canopy Integration Scheme for a Land Surface Model with Prognostic Canopy Structure , 2007 .

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

[35]  L. Stone,et al.  Top and Root Growth of Irrigated and Nonirrigated Soybeans 1 , 1976 .

[36]  C. Rosenzweig,et al.  Increased crop damage in the US from excess precipitation under climate change , 2002 .

[37]  C. Koven,et al.  Interactive comment on “ CLM 4-BeTR , a generic biogeochemical transport and reaction module for CLM 4 : model development , evaluation , and application ” , 2012 .

[38]  Peter E. Thornton,et al.  Interactive Crop Management in the Community Earth System Model (CESM1): Seasonal Influences on Land–Atmosphere Fluxes , 2012 .

[39]  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.

[40]  W. Collins,et al.  Global climate projections , 2007 .

[41]  K. Oleson,et al.  Use of FLUXNET in the Community Land Model development , 2008 .

[42]  S. Polasky,et al.  Land Clearing and the Biofuel Carbon Debt , 2008, Science.

[43]  S. Malyshev,et al.  The underpinnings of land‐use history: three centuries of global gridded land‐use transitions, wood‐harvest activity, and resulting secondary lands , 2006 .

[44]  Maosheng Zhao,et al.  Improvements of the MODIS terrestrial gross and net primary production global data set , 2005 .

[45]  J. Prioul,et al.  Estimating the Proportion of Nitrogen Remobilization and of Postsilking Nitrogen Uptake Allocated to Maize Kernels by Nitrogen‐15 Labeling , 2007 .

[46]  T. F. Morris,et al.  Long-term effects of tillage and corn stalk return on soil carbon dynamics , 2005 .

[47]  Christopher J. Kucharik,et al.  Contribution of Planting Date Trends to Increased Maize Yields in the Central United States , 2008 .

[48]  C. Müller,et al.  Modelling the role of agriculture for the 20th century global terrestrial carbon balance , 2007 .

[49]  P. Ciais,et al.  European-wide simulations of croplands using an improved terrestrial biosphere model: Phenology and productivity , 2010 .

[50]  B. S. Dhillon,et al.  Genetic Control of Nitrogen Uptake and Translocation in Maize 1 , 1979 .

[51]  François Tardieu,et al.  Modelling leaf expansion in a fluctuating environment: are changes in specific leaf area a consequence of changes in expansion rate? , 1999 .

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

[53]  Jeffrey G. Arnold,et al.  Soil and Water Assessment Tool Theoretical Documentation Version 2009 , 2011 .

[54]  D. Deryng,et al.  Crop planting dates: an analysis of global patterns. , 2010 .

[55]  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 .

[56]  Peter E. Thornton,et al.  Improvements to the Community Land Model and their impact on the hydrological cycle , 2008 .

[57]  Philip B. Duffy,et al.  Biogeophysical impacts of cropland management changes on climate , 2006 .

[58]  W. Wilhelm,et al.  Root system characteristics of two soybean isolines undergoing water stress conditions , 1983 .

[59]  William J. Riley,et al.  CLM4-BeTR, a generic biogeochemical transport and reaction module for CLM4: model development, evaluation, and application , 2012 .

[60]  D. Lobell,et al.  Climate Trends and Global Crop Production Since 1980 , 2011, Science.

[61]  Peter E. Thornton,et al.  Technical Description of the Community Land Model (CLM) , 2004 .

[62]  P. Jones,et al.  Representing Twentieth-Century Space–Time Climate Variability. Part I: Development of a 1961–90 Mean Monthly Terrestrial Climatology , 1999 .

[63]  F. Hons,et al.  Tillage and nitrogen effects on soil organic matter fractions in wheat-based systems , 2006 .

[64]  Keith W. Oleson,et al.  Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models , 2002 .