Recipient Organization
UNIV OF MINNESOTA
(N/A)
ST PAUL,MN 55108
Performing Department
(N/A)
Non Technical Summary
The agricultural landscape in the Midwest U.S. is dominated by 2-crop rotations, primarily corn and soybeans. The combination of changing climate patterns and dependence on a simpletwo-crop rotational scheme is concerning because these 2-crop rotations may lack resilience to changing weather patterns (Gaudin et al. 2013; 2015). The solution requires a tactical approach that strives to build greater crop resilience to climate-related stress (over a short timeframe, i.e. days to weeks) and better understand how greater crop resilience can subsequently increase crop stability (over a long timeframe, i.e. years). Furthermore, we need to be able to predict how these relationships will evolve over time (i.e. decades) given climate change. However,potential benefits of more-diverse cropping systems will depend on whether they are profitable enough to be widely adopted.This proposal will employ the above strategy by:comparing resilience (recovery and resistance) of corn to soil water deficits or excesses among five cropping systems (differing in rotational diversity) across three years and three locations (9 new site-years).projecting yield variation in these five systems over years under various climate-change scenarios, using crop modeling and our experimental data for 18 total site-years.predicting the extent to which adoption of potentially more-resilient systems may be constrained by economics, including limited demand for minor crops.We will use short-range optical sensing of the plant canopy to measure resistance and recovery from experimental plots with different soil water deficit or excess regimes. We will focus our attention on the corn phase of five different cropping systems, which are representative of a wider class of options. Model-based simulations will be leveraged to explore mechanistic links between crop and yield responses in the context of experimental results and plausible future climate scenarios across the region. Economic analysis will be conducted to assess the current profitability of the five diversified cropping systems and how profitability may change if a system is widely adopted. This proposed study will be conducted at three locations in Minnesota with contrasting soil and weather conditions. Our proposed research is positioned to determine the performance of crops from diversified rotation practices under variable conditions of soil, weather (i.e., precipitation), and management practices. This will allow us to advance our understanding of the effect of diversification on corn resilience and yield stability.
Animal Health Component
100%
Research Effort Categories
Basic
(N/A)
Applied
100%
Developmental
(N/A)
Goals / Objectives
We will test the hypothesis that increased crop rotational diversity can enhance within-season crop resilience (greater resistance or faster recovery) and crop stability (reduced variability in yield over years) from stress caused by changes in soil water availability during critical periods of crops growth and development. We will also test a related hypothesis that diversified cropping systems will lead to greater crop production under a changing climate. We will extend these results to test the hypothesis that diversified cropping patterns will lead to greater risk-adjusted profitability.We will consider both rotational crop diversity over growing seasons (i.e., corn-soybean, corn-soybean-wheat, and corn-corn-alfalfa-alfalfa-alfalfa) and within-season crop intensification (i.e.,corn-soybean/rye and corn-camelina/soybean).We will address threecentral questions in our proposed research project: 1. To what extent is crop resilience to soil-waterconditionsinfluenced by cropping system x environment interaction and how consistentis this relationship?We expect significant effects of contrasting rotations on resilience.However, the extent to which this occurs might be site specific as a resultofcropping system x environment interaction (as seen in FIg. 2).To assess consistency, we will compare the same cropping systems under conditions of varied soil moisture over three years at three locations that differ in soil andweather conditions. We will examine this consistency in the context of local environmental patterns (precipitation, evaporative demand, temperature, and solar radiation)2. Will observed resilience and stability persist under conditions of a future climate scenario?What are the risks and benefits associated with each of the diversification strategies on overall crop productivity?For example, cover crops can benefit soil health by enhancing both water infiltration as well as soil water-holding capacity through gradual increases in organic matter. Conversely, cover crops can add risk by reducing available soil water through greater overallwater use, thus introducing risk to current or future crops.Whicheffect will dominateover time and/or conditions of a future climate change?Similarly, a winter oilseed crop in corn-soybean rotations requires crop management practices often sensitive to in-season weather conditions, including timing for relay or sequential planting. The overlapping growth period of two crops could severely impact the establishment of the main crop (e.g., soybean).3. Will current profitability or economic scalability limit adoption of more-diverse cropping systems?Potential regional and global benefits of more-diverse cropping systems will depend on whether they are profitable enough to be widely adopted. Two aspects of profitability may encourage or limit adoption. First, how profitable and risky is a system with current prices? Longer rotations provide whole-farm "portfolio insurance" - farms using three-year rotations risk crop-specific failures on only one-third of their land, rather than half. However, in longer rotations, the crops that are usually most profitable must be grown less often. Intensification strategies such as cover crops can be integrated into shorter, potentially more-profitable rotations, but they have direct economic costs and may consume resources that could have been used for cash crops. Second, how are prices and profitability likely to change if enough farmers adopt these systems? If new crops designed to diversify farming systems become popular, will prices fall enough to undermine economic sustainability? With current prices, for example, adding alfalfa to a maize-soybean rotation can decrease water pollution without sacrificing profitability (Davis et al., 2012). But the potential to expand such systems depends on how alfalfa prices would change with increasing supply. As a counter-example, widespread addition of cover crops to corn-soybean rotations would not affect prices for corn or soybeans. In addition to cover crops, our more-diverse systems include examples of a globally-marketed crop (wheat), a hay crop for which transport crops may limit markets (alfalfa), and a niche crop whose small current market may expand (camelina).Specific Objectives1)Determine within-year crop plant resilience as influenced by soil water stress across five cropping system diversification strategies and three environments.2) Model the effect of diversified rotations on within-year crop resilience, yield stability, and sustainability, under conditions of current and future climate scenarios3)Assess the profitability of different cropping systems under current prices and as supply of crops change.
Project Methods
This project will be conducted at three locations utilizing the MN Long-Term Agricultural Research Network (MLTARN) located at the North Central, Southwest, and Southern Research and Outreach Centers of the University of Minnesota, representing a range of soil types, precipitation, and temperature gradients. The experimental design is a randomized complete block in a split-split plot arrangement with four replications. The main plot will be the crop-rotation sequence with subplots comprising soil-moisture regimes. The soil-moisture and corn treatments will only be applied in the corn year of a rotation, which is also the year when most of our measurements will be made. Main plots are 6 m x 12 m with subplots comprising a 6 x 6 m area. These are contained within a larger 24 m x 24 m cropping system area. All crops will be managed according to Best Management Practices at each location per University of Minnesota guidelines.Objective 1.Soil water regime treatments include natural precipitation (control), soil water deficit (50% of natural precipitation), and an extreme precipitation event. For the water deficit treatment, partial rainout shelters will be used to prevent 50% of precipitation from entering the plot area.Shelters will be installed approximately 2-3 weeks prior to the tasseling stage in corn at each of the three sites. In order to evaluate the recovery component of crop resilience in water deficit plots, we will terminate that soil water deficit conditionapproximately 6-8 days prior to the silking stage in corn. To prevent subsurface water flow to these plots, plastic barriers will be installed along the border of each shelter to a depth of 1 m.The extreme precipitation treatment will involve irrigation of each plot with 15 cm of water over a 30-minute period approximately 10 days prior to the tasseling stage in corn.Soil volumetric water content in each plot will be tracked at six depths (10. 20, 30, 40, 60, and 100 cm) using a PR2/6 moisture probe (Delta-T, UK). Air temperature, incident solar radiation and vapor pressure deficit will be closely monitored inside and outside the rainout shelters. The resistance component of resilience to drought will be reflected in the initial canopy-temperature (via IR thermometry) increase in drought plots, while the recovery component will be reflected in the timing of temperature convergence with control plots. We will also calculate the Crop Water Stress Index (CWSI) and measure Normalized Difference Vegetation Index (NDVI) and the Photochemical Reflectance Index (PRI).Volumetric soil water content will be obtained with a PR2/6 probe (Delta-T, UK) weekly.Additional corn plant data will include plant growth and development with plant biomass partitioned as grain and stover. Grain yield will be measured in the center rows at the end of the growing season using a research-plot combine. Data will be analyzed using the MIXED procedure in SAS (SAS institute, Cary, NC) at ∝ = 0.05. Weather conditions will be monitored with existing automated weather stations located at each MLTARN location.We will evaluate several stability indices using data obtained in this study.Objective 2.Effects of diversified rotations modulating weather-related physical shocks, mainly precipitation, on resilience and yield of crops will be modeled within the Decision Support System for Agrotechnology Transfer (DSSAT). The Crop Environment Resource Synthesis Maize (CERES-Maize) and other models in DSSAT will be used. The Cropping Systems Model (CSM)-CERES-Maize will be used to simulate the response of corn to limited soil-water. The five cropping systems treatments in this study will be simulated using the Sequence Analysis of DSSAT. Crop models to be used include the CSM-CERES-Maize and -Wheat and the CSM-CROPGRO-Alfalfa, -Soybean, and -Canola. The models will be calibrated and validated using experimental data. Model performance will be assessed using the root mean square error (RMSE), the index of agreement, and the model efficiency. Input data to run the models in DSSAT include daily weather data, soil properties for each horizon, cultivar and management. Cultivars from our experimental site will be introduced into the DSSAT models using built-in crop templates based on cultivar-specific genetic and stages-of-development information. Field data from the different crop rotations at different locations will be used to provide much of the crop-based data. Model outputs will be used to assess possible trade-offs of more-diverse systems. Calibrated models will be used to simulate the effect of diversified rotations on crop resilience and yield stability under current and future climate scenarios. Observed weather data for model calibration will be obtained from each of the experimental sites. Long-term weather data for simulations will be obtained from NOAA's Climate Data Center (https://www.ncdc.noaa.gov/). DSSAT-Perturb (https://www.climsystems.com/dssat-perturb/) will be used to generate future weather data on a local scale (Yin et al., 2013).Objective 3.We will employ the partial enterprise budgeting method to explore the profitability of the current system and more diverse cropping systems. For each of the cropping systems in this project, we will collect the direct costs, labor costs and overhead costs.Unit costs for materials will be collected from the experiment sites, published sources and vendor retail prices. Labor costs will be calculated for three categories: unskilled labor, disease/pest control labor, and skilled managerial labor. The hours of labor input will be collected from the experiment sites. The hourly wage rates will be collected from the Bureau of Labor Statistics. The overhead costs will be divided into two categories: fuel and other overhead costs including depreciation, interest, insurance, repair and maintenance, equipment, etc. The market prices for the crops will be from USDA National Statistics Service data. Yield data will be collected from the experiment sites. For each cropping system, profit and profit margin will be calculated. Partial equilibrium models will be developed to analyze how the equilibrium prices, equilibrium quantity, and profit will change for the studied crops when more farmers adopt the cropping systems. Inthe partial equilibrium method, supply equals demand in one or more markets so that prices stabilize at their equilibrium level. The partial equilibrium model has been widely used in studying agricultural markets. In the partial equilibrium model, the supply side of the market consists of identical producers. They produce a crop using constant returns to scale Cobb-Douglas production functions and sell their product in a competitive market. Thus, the aggregated Cobb-Douglas production function for the whole market is defined. The demand side of the crop market consists of domestic users and foreign users. Domestic and foreign demands are represented using constant price elasticity functions.Elasticities will be obtained from the existing literature or calculated using existing consumption data such as Nielsen scanner data,Bureau of Labor Statistics' consumer expenditure survey data, USDA crop utilization data, and Food and Agricultural Association consumption data. Using the partial equilibrium model, different scenarios will be simulated to examine how the number of farms adopting the cropping systems impact the equilibrium prices and quantities of the crops and the profitability of the studied cropping systems. Sensitivity analysis will be conducted to analyze how external shocks such as yield change or labor cost change impact the profitability of these cropping systems.