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NASA NTRS2024

Human Heat Stress Could Offset Potential Economic Benefits of CO 2 Fertilization in Crop Production Under a High-Emissions Scenario

Climate change can significantly impact agriculture, leading to food security challenges. Most previous studies have investigated the direct climate impact on crops while neglecting the impact of heat stress on agricultural labor. Here, we assess the economic consequences of climate impacts on four major crops—maize, soybean, wheat, and rice—for scenarios involving low and high greenhouse gas emissions. Our analysis is based on the output from a new generation of global climate and crop models to drive a multiregional economic model. We find that, even under a high-emission scenario, the effect of CO 2 fertilization could lead to higher yields, resulting in lower prices for major crops, except for maize. However, heat-induced losses in agricultural labor could offset the potential economic benefits of CO 2 fertilization in crop production in Asia and Africa. Our findings emphasize the importance of addressing heat-stress impacts on agricultural labor through proactive adaptation measures.

climate change↗

DOE OSTI2016

Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization

Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA) census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing nitrogen to meet nitrogen demand, the reduced positive bias to 6.9 Bu/acre (or 21% of the country mean) was mainly attributed to consideration of the dynamic interactions between fertilizer demand and supply. Although large bias remains in terms of the spatial pattern (i.e. high county-level RMSE), mainly due to limited performance over the Western US, our results show that optimizing irrigation and fertilization can lead to promising improvement in crop and soybean yield simulations in terms of the mean and variability especially over the Mid-west corn belt, and subsequent evapotranspiration (ET) estimates. Finally, this study demonstrates the CLM4.5 capability for predicting crop yields and their interactions with climate, and highlights the value of continued model improvements and development to understand biogeophysical and biogeochemical impacts of land use and land cover change using an Earth system modeling framework.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Appropriate “marginal” farmlands for second‐generation biofuel crops in North Carolina

Abstract Current research on bioenergy crops shows that perennial grasses can yield substantial amounts of dry biomass with relatively low inputs of water and fertilizer. In order to minimize competition with food production, it has been suggested that bioenergy crops could be directed to land areas less suitable for commodity crops, commonly referred to as “marginal” lands. These are land units with inherent limitations to vegetative growth and production, which may be due to several factors (soil physical and chemical properties, climatic conditions, etc.). However the term “marginal” is an adjective with imprecise meaning, and objective criteria for determining “marginal” lands for siting bioenergy crops are necessary. Here we propose that such criteria may be based on soil survey classifications and realistic yield estimates, and we show an example of its use to justify site selection for bioenergy crops in different regions of North Carolina.

09 BIOMASS FUELS↗

DOE OSTI2021

Supply analysis of preferential market incentive for energy crops

This analysis explores the valuation of feedstock quality attributes of switchgrass and miscanthus – two energy crops poised for future expansion – and compares the relative economic availability of these two crops under two scenarios: (i) uniform price assumptions (i.e., no incentive for quality), and (ii) a scenario of a price premium based on convertibility (i.e., an incentive for quality). Given data on cellulose content, hemicellulose content, and their relative convertibility, miscanthus is expected to be 11% more efficient at conversion to biofuels than switchgrass under the biochemical conversion route. Based on this scenario of improved conversion efficiency and associated profit, we simulate an 11% price premium for miscanthus over other feedstocks in a base-case scenario. By adding this price premium, supplies of miscanthus increase over the base case by about 4 million (44%), 94 million (64%), and 166 million (94%) tons in year 0, 10, and 20 after simulated contracts for production are initiated respectively. These results emphasize that custom simulations are needed to quantify feedstock availability if supplies are intended to reflect grower response to industry demands for feedstock quality specifications. Farmers can grow ‘peas or carrots’, and price signals from biorefineries will influence what energy crops they produce. Recognizing that the energy crop mix is tractable according to quality characteristics is relevant both for near-term and long-term biofuels research and development. Here, we recommend accounting for market preferences for quality attributes when estimating potential future supplies of energy crops.

09 BIOMASS FUELS↗

DOE OSTI2019

Litter quantity, litter chemistry, and soil texture control changes in soil organic carbon fractions under bioenergy cropping systems of the North Central U.S.

Soil organic carbon (SOC) storage is a critical component of the overall sustainability of bioenergy cropping systems. Predicting the influence of cropping systems on SOC under diverse scenarios requires a mechanistic understanding of the underlying processes driving SOC accumulation and loss. We used a density fractionation technique to isolate three SOC fractions that are conceptualized to vary in SOC protection from decomposition. The free light fraction (FLF) is particulate SOC that is present in the inter-aggregate soil matrix, the occluded light fraction (OLF) is contained within aggregates, and the heavy fraction (HF) is associated with minerals. We evaluated surface (0 to 10 cm depth) SOC fraction changes from baseline conditions 5 years after biofuel cropping system establishment at two temperate sites with contrasting soil textures. The biofuel cropping systems included no-till maize, switchgrass, prairie, and hybrid poplar. The FLF concentration (g fraction C g bulk soil-1) did not change significantly from baseline levels under any of the cropping systems at either site after 5 years. Except for poplar, OLF concentrations were reduced in all systems at the site with coarse-textured soils and maintained at the site with fine-textured soils. In poplar systems, OLF concentrations were maintained on coarse-textured soils and increased on fine-textured soils. The HF concentrations also increased under poplar on the coarse-textured soil. A structural equation model indicated that OLF concentrations increased with lower litter C:N, and HF concentrations increased with greater litter quantity and lower litter C:N mass ratios. C:N increased over time within all SOC fractions, suggesting that all pools are sensitive to land-use change on sub-decadal timescales. In agreement with modern SOC theory, our empirical results indicate that increasing litter input quantity and promoting plant species with low C:N litter may improve SOC storage in aggregate and mineral-associated soil fractions.

09 BIOMASS FUELS↗

DOE OSTI2021

Farmer characteristics and decision-making: A model for bioenergy crop adoption

We report the commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

09 BIOMASS FUELS↗

DOE OSTI2026

Mitigating the soil carbon deficit of annual agriculture with perennial bioenergy crops in the U.S. Midwest

Maize ( Zea mays L.) is the dominant bioenergy feedstock in the US Midwest but its cultivation since the early 1800s has incurred substantial losses in soil organic carbon (SOC). We quantified differences in SOC stocks under perennial bioenergy crops of Panicum virgatum L. (switchgrass) and Miscanthus x giganteus Greef et Deuter (miscanthus) planted on former maize and soybean fields relative to maize-based annual cropping and native prairie. Comparisons were made at seven locations across Illinois, USA, spanning a range of climate and soil types. Across sites, SOC stocks to 1-m depth on an equivalent soil mass basis were 146 Mg C ha −1 under prairie, 107 Mg C ha −1 under miscanthus, 97.9 Mg C ha −1 under switchgrass, and 87.7 Mg C ha −1 under maize. Higher SOC demonstrates the potential of perennial bioenergy crops to rebuild the SOC deficit accrued under nearly two centuries of maize-based annual cropping. SOC stock increased in the first 5 years under mature bioenergy crops at four out of seven sites. Carbon isotope (δ 13 C) analyses of surface depths confirmed short-term increases in SOC to be derived from miscanthus and switchgrass. Stocks of SOC could be increased over time under miscanthus or switchgrass cultivation even with annual harvesting, though our measured rates of SOC accumulation were lower than previous estimates for Illinois and varied by site.

bioenergy↗

DOE OSTI2018

Changes in Wood Biomass and Crop Yields in Response to Projected CO 2 , O 3 , Nitrogen Deposition, and Climate

As the world's population increases, so will the demand for food and timber resources. Though carbon dioxide (CO 2 ) fertilization and, to a lesser extent, nitrogen (N) deposition are expected to increase future resource production, changes in ozone (O 3 ) and climate have the potential to decrease production due to increased phytotoxic damage, drought, and heat stress. To determine how crop and timber production may change in the future, we use the Community Land Model version 4.5 with prognostic crops to simulate responses of wood biomass and crop yields to CO 2 , O 3 , N deposition, and climate under Representative Concentration Pathway 8.5 forcings. Generally, rising CO 2 increases wood biomass and crop yields, while projected climate change causes decreases. Small projected changes in O 3 and N deposition do not strongly affect yields, though additional research is needed on future O 3 and N deposition trends and impacts. By the end of the 21st century, global wood biomass increases by ~16% due to the dominating impact of CO 2 . The positive effect of CO 2 on future crop yields is muted by the negative impacts of climate, with a ~5% net global increase. Future projections suggest that rice and wheat yields typically increase under the combination of future forcings, whereas soy and corn yields are regionally variable. While short-term resource management strategies can benefit from planting heat-tolerant species and cultivars, technological advances and intensification, among other management strategies not included here, must be employed to meet the future demand for these resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Climate variation explains a third of global crop yield variability

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for B13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, 460% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (B32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

A sorghum pangenome reference improves global crop trait discovery

Although the green revolution adapted a handful of crops to homogeneous and high-input industrialized agriculture, much of the global population still relies on the local production of variable crop cultivars by low-input smallholder farms. This diversity of unhomogenized crops, like that of the grain and bioenergy crop sorghum, offers raw materials for genetic gain and cultivar improvement. However, breeding efforts can be constrained by highly specialized traits and breeding targets Here, to bridge this diversity, we constructed a 33-member pangenome reference and a diversity panel across 1,984 cultivars and landraces. We leveraged these resources to explore the complex interplay among historical contingency, ongoing adaptation and previously uncharacterized structural diversity. Specifically, our analyses conclusively demonstrated multiple nested and deeply diverged structural variants in the domestication gene SHATTERING1, which distinguish the previously established multicentric origin of sorghum. We then applied landscape genomics to reveal how gene flow and secondary contact created the complex genetic mosaic in contemporary breeding networks. As proof of concept for pangenome-accelerated trait discovery, we connected biosynthetic gene cluster structural variation to phenotypic leaf concentration of the cyanogenic glucoside dhurrin. Combined, these approaches will accelerate breeding and trait discovery and provide a framework for similar applications in other crops.

agricultural genetics↗

DOE OSTI2021

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project’s Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)—explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO2 concentrations and expanded high-latitude gains. The ‘emergence’ of climate impacts consistently occurs earlier in the new projections—before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Jagermeyr, Jonas↗

DOE OSTI2018

Crop productivity changes in 1.5 °C and 2 °C worlds under climate sensitivity uncertainty

Following the adoption of the Paris Agreement, there has been an increasing interest in quantifying impacts at discrete levels of global mean temperature (GMT) increase such as 1.5 °C and 2 °C above pre-industrial levels. Consequences of anthropogenic greenhouse gas emissions on agricultural productivity have direct and immediate relevance for human societies. Future crop yields will be affected by anthropogenic climate change as well as direct effects of emissions such as CO 2 fertilization. At the same time, the climate sensitivity to future emissions is uncertain. Here we investigate the sensitivity of future crop yield projections with a set of global gridded crop models for four major staple crops at 1.5 °C and 2 °C warming above pre-industrial levels, as well as at different CO 2 levels determined by similar probabilities to lead to 1.5 °C and 2 °C, using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts project. For the same CO 2 forcing, we find consistent negative effects of half a degree warming on productivity in most world regions. Increasing CO 2 concentrations consistent with these warming levels have potentially stronger but highly uncertain effects than 0.5 °C warming increments. Half a degree warming will also lead to more extreme low yields, in particular over tropical regions. Our results indicate that GMT change alone is insufficient to determine future impacts on crop productivity.

1.5 °C↗

DOE OSTI2021

Integrated Biorefinery for Valorization of Engineered Bioenergy Crops—A Review

Biorefinery allows production of multiple bioproducts from various biomass and streams using suitable unit operations to improve the economics of process while minimizing waste generation. Biorefinery holds importance in the biofuel industry because multiple coproducts can allow to produce biofuels at a price which is competitive of fossil fuels. Newer generations of cellulosic biomasses are being developed to accumulate lipids and pigments. Such crops, which can be cultivated on land unsuitable for row crops, are aimed to provide drop-in fuels to reduce dependency on fossil fuels and food crops. This review describes the potential of recovery and value addition to different constituents of engineered crops besides producing drop-in fuels. As a result, the work also provides the market value of different products which can be obtained from engineered crops to make an informed decision.

09 BIOMASS FUELS↗

DOE OSTI2021

Vehicle Tracking with Crop-based Detection

End-to-end production of vehicle tracking data from video in real-time and with high accuracy remains a challenging problem due to the computational cost of object detection on each frame. In this work we present Tracking with Crop-based Detection, a method for speeding object tracking in constrained contexts (with stable cameras and relatively-predictable object motion) such as vehicle traffic monitoring. We leverage this context to provide a strong prior for object locations, which we use to 1.) boost detection speed by detecting objects only in regions corresponding to object priors on most frames and 2.) inform the selection of the detector output for each object. We evaluate Crop-based Detection as an extension to the KIOU object tracker (Crop-KIOU) on the UA-DETRAC dataset. The proposed tracker outperforms all other reported algorithms in terms of PR-MOTA, PR-MOTP, and mostly tracked objects on the UA-DETRAC benchmark, establishing a new state-of-the-art. Relative to tracking by detection with KIOU, Crop-KIOU achieves a 26% higher frame-rate and increases accuracy. Furthermore, Tracking with Crop-based Detection can be combined with frame skipping; we show a 149% increase in framerate relative to KIOU with no decrease in accuracy using this combination of methods.

Gloudemans, Derek↗

DOE OSTI2022

Stochastic and deterministic processes shape bioenergy crop microbiomes along a vertical soil niche

Abstract Sustainable biofuel cropping systems aim to address climate change while meeting energy needs. Understanding how soil and plant‐associated microbes respond to these different cropping systems is key to promoting agriculture sustainability and evaluating changes in ecosystem functions. Here, we leverage a long‐term biofuel cropping system field experiment to dissect soil and root microbiome changes across a soil‐depth gradient in poplar, restored prairie and switchgrass to understand their effects on the microbial communities. High throughput amplicon sequencing of the fungal internal transcribed spacer (ITS) and prokaryotic 16S DNA regions showed a common trend of root and soil microbial community richness decreasing and evenness increasing with depth. Ecological niche (root vs. soil) had the strongest effect on community structure, followed by depth, then crop. Stochastic processes dominated the structuring of fungal communities in deeper soil layers while operational taxonomic units (OTUs) in surface soil layers were more likely to co‐occur and to be enriched by plant hosts. Prokaryotic communities were dispersal limited at deeper depths. Microbial networks showed a higher density, connectedness, average degree and module size in deeper soils. We observed a decrease in fungal‐fungal links and an increase of bacteria–bacteria links with increasing depth in all crops, particularly in the root microbiome.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Land-use legacies regulate decomposition dynamics following bioenergy crop conversion

Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter and when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.

09 BIOMASS FUELS↗

DOE OSTI2016

Watershed‐scale impacts of bioenergy crops on hydrology and water quality using improved SWAT model

Abstract Cellulosic bioenergy feedstock such as perennial grasses and crop residues are expected to play a significant role in meeting US biofuel production targets. We used an improved version of the Soil and Water Assessment Tool ( SWAT ) to forecast impacts on watershed hydrology and water quality by implementing an array of plausible land‐use changes associated with commercial bioenergy crop production for two watersheds in the Midwest USA . Watershed‐scale impacts were estimated for 13 bioenergy crop production scenarios, including: production of Miscanthus × giganteus and upland Shawnee switchgrass on highly erodible landscape positions, agricultural marginal land areas and pastures, removal of corn stover and combinations of these options. Water quality, measured as erosion and sediment loading, was forecasted to improve compared to baseline when perennial grasses were used for bioenergy production, but not with stover removal scenarios. Erosion reduction with perennial energy crop production scenarios ranged between 0.2% and 59%. Stream flow at the watershed outlet was reduced between 0 and 8% across these bioenergy crop production scenarios compared to baseline across the study watersheds. Results indicate that bioenergy production scenarios that incorporate perennial grasses reduced the nonpoint source pollutant load at the watershed outlet compared to the baseline conditions (0–20% for nitrate‐nitrogen and 3–56% for mineral phosphorus); however, the reduction rates were specific to site characteristics and management practices.

09 BIOMASS FUELS↗

DOE OSTI2020

In silico assessment of the potential of basalt amendments to reduce N 2 O emissions from bioenergy crops

Abstract The potential of large‐scale deployment of basalt to reduce N 2 O emissions from cultivated soils may contribute to climate stabilization beyond the CO 2 ‐removal effect from enhanced weathering. We used 3 years of field observations from maize ( Zea mays ) and miscanthus ( Miscanthus × giganteus ) to improve the nitrogen (N) module of the DayCent model and evaluate the potential of basalt amendments to reduce N losses and increase yields from two bioenergy crops. We found 20%–60% improvement in our N 2 O flux estimates over previous model descriptions. Model results predict that the application of basalt would reduce N 2 O emissions by 16% in maize and 9% in miscanthus. Lower N 2 O emissions responded to increases in the N 2 :N 2 O ratio of denitrification with basalt‐induced increases in soil pH, with minor contributions from the impact of P additions (a minor component of some basalts) on N immobilization. The larger reduction of N 2 O emissions in maize than in miscanthus was likely explained by a synergistic effect between soil pH and N content, leading to a higher sensitivity of the N 2 :N 2 O ratio to changes in pH in heavily fertilized maize. Basalt amendments led to modest increases in modeled yields and the nitrogen use efficiency (i.e., fertilizer‐N recover in crop production) of maize but did not affect the productivity of miscanthus. However, enhanced soil P availability maintained the long‐term productivity of crops with high nutrient requirements. The alleviation of plant P limitation led to enhanced plant N uptake, thereby contributing to lower microbial N availability and N 2 O emissions from crops with high nutrient requirements. Our results from the improved model suggest that the large‐scale deployment of basalt, by reducing N 2 O fluxes of cropping systems, could contribute to the sustainable intensification of agriculture and enhance the climate mitigation potential of bioenergy with carbon capture and storage strategies.

59 BASIC BIOLOGICAL SCIENCES↗