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In Depth...
Measurements and Modeling of Carbon and Nitrogen Cycling and Crop Yield in Agro-ecosystems of Southern Wisconsin
a project by Chris Kucharik
in collaboration with Prof. Kristofor Brye, University of Arkansas-Fayetteville, and Prof. John Norman, UW-Madison
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Agriculture in the Midwest US faces the formidable challenge of improving crop productivity while simultaneously mitigating the environmental consequences of intense management. Land management practices such as no-tillage agriculture and tallgrass prairie restoration have been proposed as a possible means to sequester atmospheric carbon, helping to refurbish soil fertility and replenish organic matter that was lost due to previous agricultural management practices. Likewise, prairie restoration has been proposed as a means to help reduce excess nitrogen runoff into waterways.
We studied soil and vegetation properties over a six-year period (1995-2000), and assembled measurements of soil organic carbon (SOC) and nitrogen (N), N-mineralization, soil surface CO2 flux, leached C and N in managed (maize; Zea mays L.) and natural (prairie) ecosystems near the University of Wisconsin Agricultural Research Station at Arlington. This project concurrently examined the simultaneous response of nitrate-nitrogen (NO3-N) leaching losses and maize (Zea mays L.) yield to varied fertilizer-N management using field observations and a dynamic terrestrial ecosystem model.
Experiment Site
Field data were collected during a 6-year period from 1995 through 2000 in four maize agroecosystems at the University of Wisconsin’s Agricultural Research Station near Arlington, WI (43o 17' N, 89o 22' W). The field experiment was conducted on a Plano silt loam soil (fine-silty, mixed, superactive, mesic Typic Argiudoll) with < 2% slope. A randomized complete block was established for maize tillage treatments of conventional chisel-plowed (CP) and no-tillage (NT) in Fall 1994. A 105-day relative maturity hybrid maize variety was planted for each tillage treatment at two fertilizer-N application levels to represent optimal and deficient N requirements for maize. Nitrogen-fertilized tillage treatment combinations received 180 kg N ha-1 yr-1 of surface broadcast-applied ammonium nitrate (NH4NO3) immediately following planting, while the N-unfertilized tillage treatments received no supplemental N. Grain was harvested annually and residue was returned to the soil surface. For the CP treatments, tillage occurred in the fall following harvest and seed-bed was prepared by disking in the spring before planting.
Model Development
Our purpose was to develop the capability to study the simultaneous interactions between climate variability, land management, soils, crop growth, C and N cycles, and agrochemical leaching across a continuum of spatial scales. Field measurements were used for model verification. We developed process-based crop models, based primarily on differences in C3 and C4 plant physiology and crop phenology, which are responsive to management options and environmental stressors. Our approach takes advantage of the mechanistic nature of a well-tested Dynamic Global Ecosystem Model (DGEM), the Integrated BIosphere Simulator (or IBIS) and minimized the number of variables that control crop growth and behavior. Many crop models are reliant on numerous empirical parameters that require adjustment depending on species, hybrid, and geographic location. The structure of the IBIS crop-modeling framework allows for other crop types (e.g., soybean, spring and winter wheat) to be simulated in addition to maize.
Our approach, which does not require hybrid-specific input constants, is necessary because the IBIS model is frequently used to simulate interactions of the soil-plant-atmosphere system across continental scales at coarse resolution (0.5 degree or 5 minute terrestrial grid). Detailed crop growth parameters such as heat units to maturity and the response of specific hybrids to water and nitrogen limitations are not currently available as gridded datasets at these scales. We designed this type of ecosystem modeling approach so that we could study land-use change impacts on regional hydrology, the impact of N-fertilizer usage on nitrate flux to waterways, and the effects of irrigation and climate variability on crop growth across large scales. This modeling approach also gives us significant capability to diagnose the impact of land management on C cycling and C sequestration potential.
Model implementation was also desired for much finer scales, both at an individual-field scale (~ 100 m2) and a precision agriculture scale (~ 25 m2), where some flexibility in altering model parameters was desired. Generally, crop hybrid information such as heat units required to silking and physiological maturity is readily available at the field scale. Thus, the modeling approach does allow for these types of variables to be readily adjusted if desired. A precision agriculture version of this model has been developed also (referred to at the Precision Agricultural Landscape Modeling System or PALMS).
Version 2 of the IBIS model provided the starting framework for crop model development. The original IBIS model included, in a single integrated framework for natural vegetation, representations of land-surface processes (energy, water, and momentum exchange between soil, vegetation, and the atmosphere), canopy physiology (canopy photosynthesis and conductance), natural vegetation phenology, vegetation dynamics (allocation, turnover, and competition between plant types), and terrestrial C balance (net primary production, tissue turnover, soil C, and organic matter decomposition). These processes are organized in a hierarchical framework and operate at time steps ranging from 60 min to 1 year. This approach allows for explicit coupling among ecological, biophysical, and physiological processes occurring on different timescales. This modeling framework was adapted and modified to provide the capability to simulate typical C3 and C4 crop types across the central US.
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The IBIS model structure, adapted for cropping systems. Model output includes crop yield, dry matter production (leaves, stem, root, and grain), harvest index, daily leaf area index (LAI), root growth and turnover, total plant N-uptake, net N-mineralization, plant tissue C and N, evapotranspiration, soil C and N, and soil CO2 flux.
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IBIS simulations of potential future SOC storage (1999-2050) at Arlington, Wisconsin based on 3 simulations of prairie NPP (low – 0.25, mid – 0.40, and high – 0.63 kg C m-2 y-1, dark lines), and 3 levels of maize production (low yield 4 Mg ha-1, mid yield 7.5 Mg ha-1, and high yield 10 Mg ha-1, gray lines) assumed to remain constant during this time period. Future simulations do not account for potential changes in climate or atmosphericCO2 levels. Adapted from Kucharik et al., 2001.
IBIS simulated responses of maize yield and NO3-N leaching to N-fertilizer applications at planting (adapted from Kucharik and Brye, 2003).
IBIS simulations of maize yield (top) and nitrate-N leaching (botton) compared with field measurements at Arlington for Chisel-plowed (CP), no-tillage (NT), fertilized (f) and unfertilized (nf) treatments. Fertilized maize had 180 kg N ha-1 applied at planting.
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Relevant publications
Kucharik, C.J. and K.R. Brye (2003). Integrated BIosphere Simulator (IBIS) yield and nitrate loss predictions for Wisconsin maize receiving varied amounts of Nitrogen fertilizer. Journal of Environmental Quality 32, 247-268.
Kucharik, C.J., K. R. Brye, J. M. Norman, J. A. Foley, S. T. Gower, and L. G. Bundy (2001). Measurements and modeling of carbon and nitrogen cycling in agroecosystems of southern Wisconsin: Potential for SOC sequestration during the next 50 years, Ecosystems 4, 237-258.
This research was supported by a NASA-IDS research grant to J.A. Foley, J.M. Norman, M.T. Coe, and C.J. Kucharik.
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