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At least 91 records · Page 5

Conceptualizing Coproduced Climate Research as Care: Practical Lessons Learned With Women Farmland‐Owners in the Central Midwest United States

ABSTRACT This article's team of interdisciplinary researchers and conservation educator‐practitioners learned with, and from, a group of women farmland‐owners regarding how to conceptualize coproduced climate research by putting “care” at the center—care for the soil, for relationships, for data. We outline the creation and evolution of a storytelling‐based conservation program that allowed our diverse group to discover how the language of care could integrate climate analysis, conservation, and relationship‐building to foster tangible solutions. As a result of the project, the women landowners took actions that supported social‐environmental resilience—from planting cover crops to fostering watershed/neighborhood relationships. Our diverse group of women landowners and researchers had very different experiences with conservation and often very different views on climate change itself, but, through storytelling and the language of care, we not only coproduced knowledge but also created relationships and action. This article outlines specific practices for how to inflect a coproduced process for climate resilience with practices that promote care and yield action projects.

Shenk, Linda [Department of English Iowa State Uni↗

Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation

Remote sensing estimation of evapotranspiration (ET) directly quantifies plant water consumption and provides essential information for irrigation scheduling, which is a pressing need for California vineyards as extreme droughts become more frequent. Many ET models take satellite-derived Leaf Area Index (LAI) as a major input, but how uncertainties of LAI estimations propagate to ET and the partitioning between evaporation and transpiration is poorly understood. Here we assessed six satellite-based LAI estimation approaches using Landsat and Sentinel-2 images against ground measurements from four vineyards in California and evaluated ET sensitivity to LAI in the thermal-based two-source energy balance (TSEB) model. We found that radiative transfer modeling-based approaches predicted low to medium LAI well, but they significantly underestimated high LAI in highly clumped vine canopies (RMSE ~ 0.97 to 1.27). Cubist regression models trained with ground LAI measurements from all vineyards achieved high accuracy (RMSE ~ 0.3 to 0.48), but these empirical models did not generalize well between sites. Red edge bands and the related vegetation index (VI) from the Sentinel-2 satellite contain complementary information of LAI to VIs based on near-infrared and red bands. TSEB ET was more sensitive to positive LAI biases than negative ones. Positive LAI errors of 50% resulted in up to 50% changes in ET, while negative biases of 50% in LAI caused less than 10% deviations in ET. However, even when ET changes were minimal, negative LAI errors of 50% led to up to a 40% reduction in modeled transpiration, as soil evaporation and plant transpiration responded to LAI change divergently. These findings call for careful consideration of satellite LAI uncertainties for ET modeling, especially for the partitioning of water loss between vine and soil or cover crop for effective vineyard irrigation management.

54 ENVIRONMENTAL SCIENCES↗

Chemical identity of carbon substrates drives differences in denitrification and N 2 O reduction within agricultural soils

Rates of nitrous oxide (N 2 O) production from agricultural soils are highly variable across space and time. Improving predictions of N 2 O emissions will require improving our understanding of the drivers of denitrification and the sources of variability in the rates of N 2 O production between soils and over time. While the amount of available carbon (C) is a known control on denitrification and N 2 O reduction, relatively little attention has been paid to the effect of the chemical identity of C substrates on rates of denitrification and N 2 O reduction. We investigated the effects of twelve different C-substrate additions on the production and reduction of N 2 O in five soils taken from two distinct agricultural locations in Michigan under multiple land uses. We provided additions of glucose, cellulose, N-acetyl-glucosamine, chitin, amino acids, protein, vanillyl alcohol, lignin, citrate, succinate, methanol, and water in laboratory denitrification potential assays to determine the effects of denitrifier C preference on denitrification rates. We found that amino acids, protein, and organic acids stimulated the greatest rates of denitrification potential across all land uses. Similarly, we found these same substrates caused the most N 2 O reduction, resulting in the lowest net concentrations of N 2 O. Soils from agricultural rotations without cover crops had overall lower rates of denitrifier activity, leading to less net N 2 O production compared to soils from other land uses. In general, C-utilization patterns were similar among all soils, and C-substrate identity had a much stronger effect than land use. Here, we demonstrate that the chemical identity of available C gives rise to wide variability in rates of denitrification and N 2 O reduction.

60 APPLIED LIFE SCIENCES↗

Agricultural practices influence soil microbiome assembly and interactions at different depths identified by machine learning

Agricultural practices affect soil microbes which are critical to soil health and sustainable agriculture. To understand prokaryotic and fungal assembly under agricultural practices, we use machine learning-based methods. We show that fertility source is the most pronounced factor for microbial assembly especially for fungi, and its effect decreases with soil depths. Fertility source also shapes microbial co-occurrence patterns revealed by machine learning, leading to fungi-dominated modules sensitive to fertility down to 30 cm depth. Tillage affects soil microbiomes at 0-20 cm depth, enhancing dispersal and stochastic processes but potentially jeopardizing microbial interactions. Cover crop effects are less pronounced and lack depth-dependent patterns. Machine learning reveals that the impact of agricultural practices on microbial communities is multifaceted and highlights the role of fertility source over the soil depth. Machine learning overcomes the linear limitations of traditional methods and offers enhanced insights into the mechanisms underlying microbial assembly and distributions in agriculture soils.

60 APPLIED LIFE SCIENCES↗

Shifting agricultural practices to produce sustainable, low carbon intensity feedstocks for biofuel production

The carbon intensity (CI) of biofuel's well-to-pump life cycle is calculated by life cycle analysis (LCA) to account for the energy/material inputs of the feedstock production and fuel conversion stages and the associated greenhouse gas (GHG) emissions during these stages. The LCA is used by the California Air Resources Board's Low Carbon Fuel Standard (LCFS) program to calculate CI and monetary credits are issued based on the difference between a given fuel's CI and a reference fuel's CI. Through the Tier 2 certification program under which individual fuel production facilities can submit their own CIs with their facility input data, the LCFS has driven innovative technologies to biofuel conversion facilities, resulting in substantial reductions in GHG emissions as compared to the baseline gasoline or diesel. A similar approach can be taken to allow feedstock petition in the LCFS so that lower-CI feedstock can be rewarded. Here we examined the potential for various agronomic practices to improve the GHG profiles of corn ethanol by performing feedstock-level CI analysis for the Midwestern United States. Our system boundary covers GHG emissions from the cradle-to-farm-gate activities (i.e. farm input manufacturing and feedstock production), along with the potential impacts of soil organic carbon change during feedstock production. We conducted scenario-based CI analysis of ethanol, coupled with regionalized inventory data, for various farming practices to manage corn fields, and identified key parameters affecting cradle-to-farm-gate GHG emissions. The results demonstrate large spatial variations in CI of ethanol due to farm input use and land management practices. In particular, adopting conservation tillage, reducing nitrogen fertilizer use, and implementing cover crops has the potential to reduce GHG emissions per unit corn produced when compared to a baseline scenario of corn–soybean rotation. This work shows a large potential emission offset opportunity by allowing feedstock producers a path to Tier 2 petitions that reward low-CI feedstocks and further reduce biofuels' CI. The prevalence of significant acreage that has not been optimized for CI suggests that policy changes that incentivize optimization of this parameter could provide significant additionality over current trends in farm efficiency and adoption of conservation practice.

09 BIOMASS FUELS↗

Soil management practices can contribute to net carbon neutrality in California

Stabilizing climate requires reducing greenhouse gas (GHG) emissions and storing atmospheric carbon dioxide (CO 2 ) in land or ocean systems. Soil management practices can reduce GHG emissions or sequester atmospheric CO 2 into inorganic and organic forms. However, whether soil carbon strategies represent a viable and impactful climate mitigation pathway is uncertain. A specific question concerns the role that land-management practices and soil amendments can play in realizing California's ambition for carbon neutrality by 2045. Here we examine the carbon flux impacts of soil conservation (i.e., compost, reduced tillage, cover crop) and enhanced silicate rock weathering (EW) practices at different areal extents of implementation in cropland, grassland, and savanna in California under two climate change cases. We show that with implementation areas of 15% or 50% of private cultivated land, grassland, and savanna in California, soil conservation practices alone can contribute $1.4^{2.1}_{0.7}$% ($-1.8^{-2.7}_{ -0.9}$ Mt CO 2 eq y -1 ) and $4.6^{6.9}_{2.3}$% ($-6.0^{-8.9}_{-3.0}$ Mt CO 2 eq y -1 ) of the additional emissions reduction needed (beyond previous targets) to meet the 2045 net neutrality goal (-129.3 Mt CO 2 eq y -1 ), respectively, on an average annual basis, including climate uncertainty. Including EW in these scenarios increases the total contributions of management practices to $4.1^{5.6}_{2.5}$% ($-5.2^{-7.3}_{-3.2}$ Mt CO 2 eq y -1 ) and $13.5^{18.6}_{8.2}$% ($-17.5^{-24.2}_{-10.7}$ Mt CO 2 eq y -1 ), respectively, of this reduction. This highlights that the extent of implementation area is a major factor in determining benefits and that EW has the potential to make a real contribution to net reduction targets. Results are similar across climate cases, indicating that contemporary field data can be used to make future projections. With EW there remains mechanistic uncertainties, however, such as rock dissolution rate and environmental controls on weathering products, which require additional field research to improve understanding of the technological efficacy of this approach for California's 2045 carbon neutrality goal.

54 ENVIRONMENTAL SCIENCES↗

Using a Multi‐Institutional Ensemble of Watershed Models to Assess Agricultural Conservation Effectiveness in a Future Climate

This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.

54 ENVIRONMENTAL SCIENCES↗

Exploring Camelina sativa lipid metabolism regulation by combining gene co-expression and DNA affinity purification analyses

Camelina (Camelina sativa) is an annual oilseed plant that is gaining momentum as a biofuel cover crop. Understanding gene regulatory networks is essential to deciphering plant metabolic pathways, including lipid metabolism. Furthermore, we take advantage of a growing collection of gene expression datasets to predict transcription factors (TFs) associated with the control of Camelina lipid metabolism. We identified approximately 350 TFs highly co-expressed with lipid-related genes (LRGs). These TFs are highly represented in the MYB, AP2/ERF, bZIP, and bHLH families, including a significant number of homologs of well-known Arabidopsis lipid and seed developmental regulators. After prioritizing the top 22 TFs for further validation, we identified DNA-binding sites and predicted target genes for 16 out of the 22 TFs tested using DNA affinity purification followed by sequencing (DAP-seq). Enrichment analyses of targets supported the co-expression prediction for most TF candidates, and the comparison to Arabidopsis revealed some common themes, but also aspects unique to Camelina. Within the top potential lipid regulators, we identified CsaMYB1, CsaABI3AVP1-2, CsaHB1, CsaNAC2, CsaMYB3, and CsaNAC1 as likely involved in the control of seed fatty acid elongation and CsaABI3AVP1-2 and CsabZIP1 as potential regulators of the synthesis and degradation of triacylglycerols (TAGs), respectively. Altogether, the integration of co-expression data and DNA-binding assays permitted us to generate a high-confidence and short list of Camelina TFs involved in the control of lipid metabolism during seed development.

59 BASIC BIOLOGICAL SCIENCES↗

AmeriFlux US-RGo Glenn County Organic Rice Farm

This is the AmeriFlux version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm. Site Description - Organically farmed medium-grain brown rice field in Glenn County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field check is approx. 7 ha in size (1,250 ft by 250 ft), part of a 75+ acre site in several checks with commercial rice over rice rotation on Tehama silt loam, management practices include winter cover crops and AWD.

Schuppenhauer, Michael R.↗

AmeriFlux FLUXNET-1F US-RGo Glenn County Organic Rice Farm

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm. This is the FLUXNET version of the carbon flux data for the site US-RGo Glenn County Organic Rice Farm produced by applying the standard ONEFlux (1F) software. Site Description - Organically farmed medium-grain brown rice field in Glenn County, California. Part of a five-year, ground-truthing field study under the DOE ARPA-E SMARTFARM project. Field check is approx. 7 ha in size (1,250 ft by 250 ft), part of a 75+ acre site in several checks with commercial rice over rice rotation on Tehama silt loam, management practices include winter cover crops and AWD.

Schuppenhauer, Michael R.↗

AmeriFlux US-CLN Coles Farm North

This is the AmeriFlux version of the carbon flux data for the site US-CLN Coles Farm North. Site Description - The land was given to Iowa State University in 1974, and was a corn-soybean rotation with conventional tillage operation until 2015. In 2016, the management was moved to strip tillage corn-soybean rotation with cover crops. The field is located east of Williams, IA.

Neale, Christopher [Daugherty Water for Food Insti↗

AmeriFlux US-CLS Coles Farm South

This is the AmeriFlux version of the carbon flux data for the site US-CLS Coles Farm South. Site Description - The land was given to Iowa State University in 1974, and was a corn-soybean rotation with conventional tillage operation until 2015. In 2016, the management was moved to strip tillage corn-soybean rotation with cover crops. The field is located east of Williams, IA.

Prueger, John H. [National Laboratory for Agricult↗

AmeriFlux FLUXNET-1F US-RC5 Moses Lake on-farm site

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-RC5 Moses Lake on-farm site. This is the FLUXNET version of the carbon flux data for the site US-RC5 Moses Lake on-farm site produced by applying the standard ONEFlux (1F) software. Site Description - The Moses Lake On-farm site operated 2013-2015 as part of a cluster of 5 towers (RC1 to RC5) operated for the Regional Approaches to Climate Change (REACCH) USDA-supported research project. The field was a half-circle irrigated plot with the irrigation pivot located on the edge of the field and the flux tower located next to the center of the pivot. The field was in wheat from tower establishment in June 2013 to harvest in August 2013. A cover crop of arugula and mustard was grown from August to October 2013. Potatoes were grown April to August 2014 and wheat (a spring cultivar planted in fall) was grown October 2014 to June 2015. Soils are coarse sandy loam mollisols in the Timmerman series. The site topography is flat.

Chi, Jinshu [The Hong Kong University of Science a↗

AmeriFlux US-LMS LMRB LTAR Schmidt Farm

This is the AmeriFlux version of the carbon flux data for the site US-LMS LMRB LTAR Schmidt Farm. Site Description - Agricultural field in MS Delta with cover crops and minimal tillage

Witthaus, Lindsey [USDA ARS]↗

Deeply Rooted: Evaluating Plant Rooting Depth as a Means for Enhanced Soil Carbon Sequestration (Full Technical Report)

Soils store three times as much carbon (C) as the atmosphere, but are not at capacity, and enhanced soil C storage is considered an essential strategy to mitigate rising atmospheric CO 2 levels. Agricultural soils have experienced substantial C loss in the past century due to poor agricultural practices and erosion. A shift towards deep-rooting crops and low-impact soil management could potentially increase long-term sequestration of C fixed by plants and stored in their root tissues, particularly for crops that have naturally deep root systems (>1 meter). A substantial amount of the CO 2 taken up by plants is allocated to their root systems, and because C deposited in deep soil layers has a longer residence time (up to millennia, in contrast to C deposited in topsoils), C increases at depth may have better long-term C sequestration potential than topsoils. However, the accrual, turnover, and stabilization of C in subsoils is a critical knowledge gap. We investigated a deeply rooted plant, switchgrass (Panicum virgatum), as a means of increasing carbon stocks in marginal and agricultural soils. We hypothesized that deep (>30 cm) SOC stocks would be greater under bioenergy crops relative to stocks under shallow-rooted conventional crop cover. To test this hypothesis, we compared soil depth profiles beneath deeply rooted switchgrass (cultivated for 4-30 years) and paired shallowrooted annual controls. We studied 12 field sites, 3 that were collected in 2018 before the start of the project as part a Department of Energy (DOE) Sustainable Biofuels study, and 9 that we collected in 2019 on a national field sampling campaign across the eastern US. In our publication from the 2018 study, which was written in collaboration with the LLNL Soil Microbiome Scientific Focus Area (SFA), we found that C stocks increased under switchgrass, but that the increases were dependent on soil texture. In the 2019 study, we found that carbon accrual tended to occur most consistently in low C soil in the southern US, which could indicate that perennial grasses may be a viable strategy to increase SOC in marginals soils in this region. We have published two studies from the 2019 sampling campaign thus far, we measured microbial growth parameters that will aid in modeling subsoil carbon cycling, and we found that switchgrass appears to move water upward in the soil profile and could promote drought tolerance, which a phenomenon commonly performed by trees known as ‘hydraulic redistribution;’ our study is the first to show this can occur in deep-rooted grasses. Finally, we published a modeling paper in collaboration with the LLNL Soil Microbiome SFA, where we found that poorly crystalline minerals are abundant and strongly correlated with organic C in geographically limited zones with enhanced weathering rates. Our results will inform technological development in the agricultural carbon sequestration sector as well as future negative emissions policies.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

CRISPR/Cas9-Induced fad2 and rod1 Mutations Stacked With f ae1 Confer High Oleic Acid Seed Oil in Pennycress (Thlaspi arvense L.)

Pennycress (Thlaspi arvense L.) is being domesticated as an oilseed cash cover crop to be grown in the off-season throughout temperate regions of the world. With its diploid genome and ease of directed mutagenesis using molecular approaches, pennycress seed oil composition can be rapidly tailored for a plethora of food, feed, oleochemical and fuel uses. Here, we utilized Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 technology to produce knockout mutations in the FATTY ACID DESATURASE2 (FAD2) and REDUCED OLEATE DESATURATION1 (ROD1) genes to increase oleic acid content. High oleic acid (18:1) oil is valued for its oxidative stability that is superior to the polyunsaturated fatty acids (PUFAs) linoleic (18:2) and linolenic (18:3), and better cold flow properties than the very long chain fatty acid (VLCFA) erucic (22:1). When combined with a FATTY ACID ELONGATION1 (fae1) knockout mutation, fad2 fae1 and rod1 fae1 double mutants produced ~90% and ~60% oleic acid in seed oil, respectively, with PUFAs in fad2 fae1 as well as fad2 single mutants reduced to less than 5%. MALDI-MS spatial imaging analyses of phosphatidylcholine (PC) and triacylglycerol (TAG) molecular species in wild-type pennycress embryo sections from mature seeds revealed that erucic acid is highly enriched in cotyledons which serve as storage organs, suggestive of a role in providing energy for the germinating seedling. In contrast, PUFA-containing TAGs are enriched in the embryonic axis, which may be utilized for cellular membrane expansion during seed germination and seedling emergence. Under standard growth chamber conditions, rod1 fae1 plants grew like wild type whereas fad2 single and fad2 fae1 double mutant plants exhibited delayed growth and overall reduced heights and seed yields, suggesting that reducing PUFAs below a threshold in pennycress had negative physiological effects. Taken together, our results suggest that combinatorial knockout of ROD1 and FAE1 may be a viable route to commercially increase oleic acid content in pennycress seed oil whereas mutations in FAD2 will likely require at least partial function to avoid fitness trade-offs.

09 BIOMASS FUELS↗

Accuracy, Bias, and Improvements in Mapping Crops and Cropland across the United States Using the USDA Cropland Data Layer

The U.S. Department of Agriculture’s (USDA) Cropland Data Layer (CDL) is a 30 m resolution crop-specific land cover map produced annually to assess crops and cropland area across the conterminous United States. Despite its prominent use and value for monitoring agricultural land use/land cover (LULC), there remains substantial uncertainty surrounding the CDLs’ performance, particularly in applications measuring LULC at national scales, within aggregated classes, or changes across years. To fill this gap, we used state- and land cover class-specific accuracy statistics from the USDA from 2008 to 2016 to comprehensively characterize the performance of the CDL across space and time. We estimated nationwide area-weighted accuracies for the CDL for specific crops as well as for the aggregated classes of cropland and non-cropland. We also derived and reported new metrics of superclass accuracy and within-domain error rates, which help to quantify and differentiate the efficacy of mapping aggregated land use classes (e.g., cropland) among constituent subclasses (i.e., specific crops). We show that aggregate classes embody drastically higher accuracies, such that the CDL correctly identifies cropland from the user’s perspective 97% of the time or greater for all years since nationwide coverage began in 2008. We also quantified the mapping biases of specific crops throughout time and used these data to generate independent bias-adjusted crop area estimates, which may complement other USDA survey- and census-based crop statistics. Our overall findings demonstrate that the CDLs provide highly accurate annual measures of crops and cropland areas, and when used appropriately, are an indispensable tool for monitoring changes to agricultural landscapes.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of eastern gamagrass as dual-purpose complementary bioenergy and forage feedstock to switchgrass

Switchgrass (SG) is considered a model bioenergy crop and a warm-season perennial grass (WSPG) that traditionally served as forage feedstock in the United States. To avoid the sole dependence on SG for bioenergy production, evaluation of other crops to diversify the pool of feedstock is needed. We conducted a 3-year field experiment evaluating eastern gamagrass (GG), another WSPG, as complementary feedstock to SG in one- and two-cut systems, with or without intercropping with crimson clover or hairy vetch, and under different nitrogen (N) application rates. Our results showed that GG generally produced lower biomass (by 29.5%), theoretical ethanol potential (TEP, by 2.8%), and theoretical ethanol yield (TEY, by 32.9%) than corresponding SG under the same conditions. However, forage quality measures, namely acid detergent fiber (ADF), crude protein (CP), and elements P, K, Ca, and Mg were significantly higher in GG than those in SG. Nitrogen fertilizer significantly enhanced biomass (by 1.54 Mg ha -1 ), lignin content (by 2.10 g kg -1 ), and TEY (787.12 L ha -1 ) in the WSPGs compared to unfertilized treatments. Intercropping with crimson clover or hairy vetch did not significantly increase biomass of the WSPGs, or TEP and TEY in unfertilized plots. This study demonstrated that GG can serve as a complementary crop to SG and could be used as a dual-purpose crop for bioenergy and forage feedstock in farmers' rotations.

09 BIOMASS FUELS↗