Predicting long term cover crop impacts on soil quality using a cropping systems model

Cover crops have been proposed as a good option to improve water quality, decrease soil erosion and increase soil productivity in Iowa fields. This project uses a cropping system model to test those proposals while allowing for potential effects of climate change on cropping systems at the same time

Covering the ground: A transformative approach to scientific learning for greater cover crop adaptation in Iowa

This project studied how farmers are making cover crops work in their cropping systems, which are dominated by corn and soybean rotations in much of Iowa. Researchers shared considerable data on cover crops with farmers in four focus groups and then encouraged them to engage with other farmers about their knowledge and experience with cover crops

Where should we apply biochar?

The heating of biomass under low-oxygen conditions generates three co-products, bio-oil, biogas, and biochar. Bio-oil can be stabilized and used as fuel oil or be further refined for various applications and biogas can be used as an energy source during the low-oxygen heating process. Biochar can be used to sequester carbon in soil and has the potential to increase crop yields when it is used to improve yield-limiting soil properties. Complex bio-physical interactions have made it challenging to answer the question of where biochar should be applied for the maximum agronomic and economic benefits. We address this challenge by developing an extensive informatics workflow for processing and analyzing crop yield response data as well as a large spatial-scale modeling platform. We use a probabilistic graphical model to study the relationships between soil and biochar variables and predict the probability and magnitude of crop yield response to biochar application. Our results show an average increase in crop yields ranging from 4.7% to 6.4% depending on the biochar feedstock and application rate. Expected yield increases of at least 6.1% and 8.8% are necessary to cover 25% and 10% of US cropland with biochar. We find that biochar application to crop area with an expected yield increase of at least 5.3%–5.9% would result in carbon sequestration offsetting 0.57%–0.67% of US greenhouse gas emissions. Applying biochar to corn area is the most profitable from a revenue perspective when compared to soybeans and wheat because additional revenues accrued by farmers are not enough to cover the costs of biochar applications in many regions of the United States

Predicting long-term cover crop impacts on soil quality using a cropping systems model

Increased attention is being paid to cover crops as an option to reduce water pollution and decrease soil degradation in Iowa. More producers are experimenting with cover crops to increase soil productivity. However, when this project began there was little research to demonstrate the long-term impacts that cover crops have on crop yields. There were no estimates to quantify how much environmental benefit a cover crop could provide in terms of erosion and soil carbon changes. Such estimates are beneficial to demonstrate the long-term improvements that a cover crop affords in Iowa, particularly for corn-soybean rotations where the winter planting window is narrow, presenting a significant short-term challenge for producers. Using a cropping systems model such as APSIM (Agricultural Production Systems sIMulator) can offer estimates of potential benefits for farmers and policy makers which might take many years to observe in a traditional field trial. The objectives of this research were to: • Measure crop growth and soil properties at a representative corn-soybean field site with a winter rye cover crop to provide specific parameters necessary to establish and test APSIM and to analyze field data for treatment effects of the cover crop. • Use APSIM simulations to estimate the impact of long-term cover crops on soil carbon, soil erosion, soil water dynamics, and average main crop yields as well as cover crop impacts following more variable rainfall seasons, a projected climate change impact for the Midwest United States

Development of a data-assimilation system to forecast agricultural systems: A case study of constraining soil water and soil nitrogen dynamics in the APSIM model

As we face today\u27s large-scale agricultural issues, the need for robust methods of agricultural forecasting has never been clearer. Yet, the accuracy and precision of our forecasts remains limited by current tools and methods. To overcome the limitations of process-based models and observed data, we iteratively designed and tested a generalizable and robust data-assimilation system that systematically constrains state variables in the APSIM model to improve forecast accuracy and precision. Our final novel system utilizes the Ensemble Kalman Filter to constrain model states and update model parameters at observed time steps and incorporates an algorithm that improves system performance through the joint estimation of system error matrices. We tested this system at the Energy Farm, a well-monitored research site in central Illinois, where we assimilated observed in situ soil moisture at daily time steps for two years and evaluated how assimilation impacted model forecasts of soil moisture, yield, leaf area index, tile flow, and nitrate leaching by comparing estimates with in situ observations. The system improved the accuracy and precision of soil moisture estimates for the assimilation layers by an average of 42% and 48%, respectively, when compared to the free model. Such improvements led to changes in the model\u27s soil water and nitrogen processes and, on average, increased accuracy in forecasts of annual tile flow by 43% and annual nitrate loads by 10%. Forecasts of aboveground measures did not dramatically change with assimilation, a fact which highlights the limited potential of soil moisture as a constraint for a site with no water stress. Extending the scope of previous work, our results demonstrate the power of data assimilation to constrain important model estimates beyond the assimilated state variable, such as nitrate leaching. Replication of this study is necessary to further define the limitations and opportunities of the developed system

Nitrogen Fertilizer Rate Effects on Soil Organic Carbon in Iowa Continuous Corn and Corn-Soybean Systems

Nitrogen fertilizer rate is a key factor affecting soil organic C (SOC) in corn-based cropping systems. The objective of this study was to determine the change in SOC in response to long-term N rates for continuous corn and corn-soybean cropping systems at two sites in Iowa. Soil samples were collected to a depth of 15 cm in 1999 and again in 2014 after 15 years of corn N rate treatments ranging from 0 to 269 kg ha-1. The soil samples were analyzed for total C and N concentrations. For continuous corn at both sites, the average annual change in SOC increased significantly from below 0 Mg ha-1 yr-1 where no N was applied, to an optimum of approximately 0.13 Mg ha-1 yr-1 at N rates between 150 and 200 kg ha-1. For corn-soybean rotations, the average annual change in SOC was generally below 0 Mg ha-1 yr-1 and increased slightly, but not significantly, with increasing N rate. The results indicate that adequately fertilized continuous corn systems have the potential to accrue more SOC than corn-soybean rotations

The trouble with cover crops: Farmers’ experiences with overcoming barriers to adoption

Cover crops are known to promote many aspects of soil and water quality, yet estimates find that in 2012 only 2.3% of the total agricultural lands in the Midwestern USA were using cover crops. Focus groups were conducted across the Corn Belt state of Iowa to better understand how farmers confront barriers to cover crop adoption in highly intensive agricultural production systems. Although much prior research has focused on analyzing factors that help predict cover crop use on farms, there is limited research on how farmers navigate and overcome field-level (e.g. proper planting of a cover crop) and structural barriers (e.g. market forces) associated with the use of cover crops. The results from the analysis of these conversations suggest that there is a complex dialectical relationship between farmers\u27 individual management decisions and the broader agricultural context in the region that constrains their decisions. Farmers in these focus groups shared how they navigate complex management decisions within a generally homogenized agricultural and economic landscape that makes cover crop integration challenging. Many who joined the focus groups have found ways to overcome barriers and successfully integrate cover crops into their cropping systems. This is illustrated through farmers\u27 descriptions of their ‘whole system’ approach to cover crops management, where they described how they prioritize the success of their cover crops by focusing on multiple aspects of management, including changes they have made to nutrient application and modifications to equipment. These producers also engage with farmer networks to gain strategies for overcoming management challenges associated with cover crops. Although many participants had successfully planted cover crops, they tended to believe that greater economic incentives and/or more diverse crop and livestock markets would be needed to spur more widespread adoption of the practice. Our results further illustrate how structural and field-level barriers constrain individual actions, as it is not simply the basic agronomic considerations (such as seeding and terminating cover crops) that pose a challenge to their use, but also the broader economic and market drivers that exist in agriculturally intensive systems. Our study provides evidence that reducing structural barriers to adoption may be necessary to increase the use of this conservation practice to reduce environmental impacts associated with intensive agricultural production

Simulating long-term impacts of cover crops and climate change on crop production and environmental outcomes in the Midwestern United States

It is critical to evaluate conservation practices that protect soil and water resources from climate change in the Midwestern United States, a region that produces one-quarter of the world’s soybeans and one-third of the world’s maize. An over-winter cover crop in a maize–soybean rotation offers multiple potential benefits that can reduce the impacts of higher temperatures and more variable rainfall; some of the anticipated changes for the Midwest. In this experiment we used the Agricultural Production Systems sIMulator (APSIM) to understand how winter rye cover crops impact crop production and environmental outcomes, given future climate change. We first tested APSIM with data from a long-term maize–soybean rotation with and without winter rye cover crop field site. Our modeling work predicted that the winter rye cover crop has a neutral effect on maize and soybean yields over the 45 year simulation period but increases in minimum and maximum temperatures were associated with reduced yields of 1.6–2.7% by decade. Soil carbon decreased in both the cover crop and no cover crop simulations, although the cover crop is able to significantly offset (3% less loss over 45 years) this decline compared to the no cover crop simulation. Our predictions showed that the cover crop led to an 11–29% reduction in erosion and up to a 34% decrease in nitrous oxide emissions (N2O). However, the cover crop is unable to offset future predicted yield declines and does not increase the overall carbon balance relative to current soil conditions