This research project will establish and integrate benchmarks of soybean sustainability in Illinois using soil health, water quality and climate-smart metrics. By evaluating metrices across a range of soil health management practices – which double as climate-smart practices – and across regions of Illinois, we will identify and deliver sustainability benchmarks customized for our state’s diverse soybean production systems. Quantifying nutrient and carbon footprints in a comprehensive manner will provide a tangible basis for informing soil health management in soybean production, position the sustainability of Illinois soybean in national and global markets, and lay the foundation for Illinois soybeans to capitalize on rapidly emerging carbon markets.
To achieve this, we will evaluate multiple sustainability outcomes at field experiment sites that represent Illinois soil-climate regions. At each site, replicated soil health management treatments will be evaluated for the soybean phase in two soybean rotation systems. Soil health indicators (biological, chemical, physical), nutrient losses by leaching, soil carbon sequestration and greenhouse gas (GHG) emissions – including high CO2-equivalency gases of CH4 and N2O – will be measured to quantify soil, water quality, and climate footprints across systems.
By establishing benchmarks of sustainability and quantifying how soil health practices impact soil, water quality and climate-smart metrics, this work will deliver an evidence-based foundation for valorizing Illinois soybeans in the global market and for carbon markets as a climate-smart commodity, which according to USDA is an agricultural commodity produced by practices that reduce GHG emissions and/or sequester carbon. Soybean-specific soil health practices that double as water quality-protective practices, in particular cover cropping and conservation tillage, can offer a third benefit: carbon credits. Illinois and the greater Midwest have strong but relatively unquantified potential for carbon credits by increasing soil carbon and decreasing GHG emissions by these two practices. This potential is likely to be greater for soybean relative to corn, given greater adaptability of soybean to reduced or no-tillage and cover cropping, and the absence of nitrogen fertilization that otherwise typically entails appreciable N2O emissions. However, variability in soil and cropping systems can markedly influence soybean’s net carbon footprint, which should be balanced with yield outcomes to comprehensively gauge environmental footprints. This work will do so for Illinois.
Proposed Methods
Experimental design. Soil health practices and sustainability metrices will be evaluated at three sites in southern (Ewing), central (Urbana), and northwestern (Monmouth) Illinois, for four cropping seasons. The soybean phase of (1) a soybean-corn rotation (Ewing, Urbana, Monmouth) and in (2) a double-crop wheat-soybean with corn rotation (Ewing, Urbana only) will be evaluated. By having the soybean phase present in each year, a total of 12 site years will be achieved for each crop rotation and management treatment combination. Two well-established soil health management practices of cover cropping and tillage will be tested: cover cropping, as none vs cereal rye, and tillage, as conventional tillage vs no-till. The four treatments resulting from this 2×2 will have five replicates in a fully randomized complete block design to provide sufficient statistical power to detect often subtle signals in soil carbon and soil health responses, and to detect treatment signals in often variable GHG emissions. Because both crop phases will be present every year, total experimental unit plots per crop-year are 2 phases × 4 trt × 5 reps = 40 plots annually at Monmouth and 2 × 4 × 5 × 2 soybean rotation systems = 80 plots annually at Urbana and Ewing each, totaling 600 plots over four cropping seasons. Each experimental unit plot will be 40’ wide × 60’ long to accommodate 16 rows of soybean (30” spacing). Field sites will be managed according to the Illinois Agronomy Handbook and regional practices, including fertilizer with P, K and micronutrients based on soil tests, and control of weeds with preemergence and, as needed, post-emergence herbicide applications.
Soil health. A suite of indicators that monitor chemical, physical, and biological soil health will be measured. Standard soil health metrics endorsed by the Soil Health Institute – and which PI Margenot advised USDA NRCS KSSL on – will be assessed6 : chemical indicators of pH, available nitrate-N and ammonium-N, Mehlih-3 P, labile carbon (POXC); physical indicators of soil aggregate stability (large macroaggregates, small macroaggregates, microaggregates) and bulk density; biological indicators of mineralizable carbon, soil microbial biomass carbon and nitrogen, and activities of soil enzymes of ß-glucosidase, glucosaminidase, aminopeptidase, and phosphatase. Soil health indicators will be measured every spring before planting and fall after harvest in each treatment plot, for soils sampled at 0-6” depth by hand auger. Which indicators are most and least sensitive to soil health practices by the three sites, which differ in soil type, will be used to identify soybean cropping-specific soil health indicators using factor analysis7 . Soil health indicators will be integrated using factor analysis, recently developed by Margenot and collaborators7 , as well as standard scoring functions (e.g., Cornell Soil Health Assessment).
Water quality: nutrient leaching. Lysimeters will be used to measure N and P leaching losses, enabling calculation of nutrient footprints with direct implications for water quality. This builds on a 2020 ISA award to Margenot in which his team has customized the resin bead lysimeter approach8 for the Illinois context. Duplicate resin lysimeters per treatment replicate plot will be installed at 24” depth (1200 total) to capture leaching nitrate-N and phosphate-P4, 43, 44 . Lysimeters will be installed in November after harvest, and collected in April prior to installation of a fresh set of lysimeters for in-season assessment of nutrient leaching. Nitrate-N and phosphate-P extracted from resins will be used to estimate N and P leaching loads of treatments (lb/ac). Since lysimeter collection and soil health sampling will occur at the same spring and fall timepoints, this will allow integration of soil health and water quality outcomes across soybean systems.
Soil carbon stocks. Annual carbon stocks and early indicators of carbon change will be quantified by sampling soils to 36” cm using a Giddings hydraulic probe. The Margenot Lab already possesses a hydraulic probe mounted on a tractor for routine soil sampling for organic carbon stock determination. Intact cores will be sectioned into five depth intervals (0-3, 3-6, 6-12, 12-24, 24-36”), each of which will be analyzed for bulk density9 and total organic carbon by dry combustion following acid fumigation for carbonate removal10 if soil pH > 7.2, which we anticipate for some sites at >24” depth. Each treatment plot will be sampled in duplicate to account for shortrange spatial variability11 . Soil carbon stocks will be first calculated on a fixed depth basis for each15 cm layer, and then on a full-pedon basis using both fixed depth and equivalent soil mass basis12 for inter- vs intra-field comparisons, respectively13.
To monitor changes in soil carbon that forecast changes in total stocks and thus carbon sequestration, we will also measure early indicators of carbon accrual that enable mechanistic explanation of field-specific response to soil health practices: particulate organic matter (POM) and mineral-associated organic matter (MAOM)14 . These carbon sequestration indicators are anticipated to capture soil carbon response to tillage15 and cover crops16 even if total soil carbon stocks do not statistically change within the four cropping seasons.
GHG emissions. We will measure emissions of the three major greenhouse gases (GHG) – CO2, CH4, and N2O – in order to quantify the full GHG footprint, because the non-CO2 gases have a CO2 equivalence of 84x for CH4 and 298x for N2O. The effect of management practices on GHG emissions, and N2O emissions in particular, is widely recognized to be extremely challenging to quantify because soil N2O emissions are characterized by “hot spots and hot moments”, in which much of the emissions occur in a short period of time or space. To address temporal heterogeneity in GHG emissions, we will perform frequent sampling on both a fixed date (weekly) and eventbased, following rainfall and tillage events. To address spatial heterogeneity, we will sample at three separate locations within each field treatment replicate (i.e., 3 x 5 replicate plots x 4 treatments = 60 gas samples per site in soybean phase per event). To quantify all three major GHG simultaneously, we will employ a Gasmet GT5000 portable infrared analyzer for manual chamber on-site measurements. The Margenot Lab already has a Gasmet analyzer ($61,000 value) for in-field measurement of GHG emissions. The data generated from this ambitious effort will be critical to improve understanding of the GHG-based component of the carbon credit for soybean production systems across Illinois contexts and soil health practices.
Yields and yield-scaled water quality and climate outcomes. Soybean yield will be determine by measuring yields for each treatment replicate plot with harvest of the middle 8 of 16 soybean rows. Production costs of the four treatments for each site and cropping season will be calculated using FarmDoc templates. Nutrient losses and GHG emissions will be scaled or normalized to yield (e.g., lb P lost per bu), known as yield-scaling17 . The yield-scaled metric contextualizes nutrient losses for productivity, and for climate-smart commodities, uses CO2 equivalents that account for carbon sequestered in soil and the CO2 ‘effect’ (equivalency) of the greenhouse gases of CO2 (1x), CH4 (84x), and N2O (298x). This will serve as the basis for the nutrient loss (water quality) and climate (CO2 equivalents) footprints of soybeans across the evaluated systems. In addition to identifying soybean-specific soil health indicators that respond to context-specific management practices (please see above), we will integrate soil health indicators with water quality and climate footprints through factor analysis. This is anticipated to identify likely synergies among these three sustainability metrices specific to region and management practices.