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DOE OSTI2024

Potential long-term, global effects of enhancing the domestic terrestrial carbon sink in the United States through no-till and cover cropping

Abstract Background Achieving a net zero greenhouse gas United States (US) economy is likely to require both deep sectoral mitigation and additional carbon dioxide removals to offset hard-to-abate emissions. Enhancing the terrestrial carbon sink, through practices such as the adoption of no-till and cover cropping agricultural management, could provide a portion of these required offsets. Changing domestic agricultural practices to optimize carbon content, however, might reduce or shift US agricultural commodity outputs and exports, with potential implications on respective global markets and land use patterns. Here, we use an integrated energy-economy-land-climate model to comprehensively assess the global land, trade, and emissions impacts of an adoption of domestic no-till farming and cover cropping practices based on carbon pricing. Results We find that the adoption of these practices varies depending on which aspects of terrestrial carbon are valued. Valuation of all terrestrial carbon resulted in afforestation at the expense of domestic agricultural production. In contrast, a policy valuing soil carbon in agricultural systems specifically indicates strong adoption of no-till and cover cropping for key crops. Conclusions We conclude that under targeted terrestrial carbon incentives, adoption of no-till and cover cropping practices in the US could increase the terrestrial carbon sink with limited effects on crop availability for food and fodder markets. Future work should consider integrated assessment modeling of non-CO 2 greenhouse gas impacts, above ground carbon storage changes, and capital and operating cost considerations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.

09 BIOMASS FUELS↗

NASA NTRS2014

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

climate change↗

NASA NTRS2014

Comment on 'Shang S. 2012. Calculating actual crop evapotranspiration under soil water stress conditions with appropriate numerical methods and time step. Hydrological Processes 26: 3338-3343. DOI: 10.1002/hyp.8405'

A previous study analyzed errors in the numerical calculation of actual crop evapotranspiration (ET(sub a)) under soil water stress. Assuming no irrigation or precipitation, it constructed equations for ET(sub a) over limited soil-water ranges in a root zone drying out due to evapotranspiration. It then used a single crop-soil composite to provide recommendations about the appropriate usage of numerical methods under different values of the time step and the maximum crop evapotranspiration (ET(sub c)). This comment reformulates those ET(sub a) equations for applicability over the full range of soil water values, revealing a dependence of the relative error in numerical ET(sub a) on the initial soil water that was not seen in the previous study. It is shown that the recommendations based on a single crop-soil composite can be invalid for other crop-soil composites. Finally, a consideration of the numerical error in the time-cumulative value of ET(sub a) is discussed besides the existing consideration of that error over individual time steps as done in the previous study. This cumulative ET(sub a) is more relevant to the final crop yield.

Time step↗

NASA NTRS2015

AgMIP Training in Multiple Crop Models and Tools

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

farm crops↗

NASA NTRS2019

Global Crop Production: Adaptation to Temperature Increase Is Possible by Maintaining the Current Growing Periods

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology and growth. However, future projections, especially at the global scale, do not consider any agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models (GGCMs) contributing to the AgMIP-Gridded project to quantify the impacts and adaptation potential of field crops under increasing temperature. We study how uniform warming scenarios up to 6 K affect the productivity and growing period duration of five major crops. The design of the experiment aims at understanding adaptation measures targeted to temperature-driven impacts and therefore leaves out changes in any other climate variable. We find that, without adaptation the dominant effect of temperature increase is to shorten the growing period and to reduce yields and production, consistently across crops and regions. We then test the potential of two agronomic measures to contrast warming-induced yield reduction, assuming that (i) cultivars with adjusted phenology would be used to regain the reference growing period duration; (ii) rainfed systems would be converted to irrigated. Despite substantial uncertainties in model parametrization and little agreement in spatial patterns, at the global aggregation, model results are robust. We find that up to 3 K of temperature increase, production losses could be fully compensated by maintaining the original crop growing period. Irrigation would also compensate production losses, but would not reduce the temperature impacts. Across regions, the model ensemble estimates larger adaptation potentials from unchanged growing periods in continental and temperate regions, than in tropical and arid regions, where also irrigation has respectively little effects and availability.

Irrigation↗

NASA NTRS2020

Narrowing Uncertainties in the Effects of Elevated CO2 on Crops

Plant responses to rising atmospheric carbon dioxide (CO2) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO2 concentrations. Recent concerted efforts have narrowed the uncertainties in CO2-induced crop responses so that climate change impact simulations omitting CO2 can now be eliminated. To address remaining knowledge gaps and uncertainties in estimating the effects of elevated CO2 and climate change on crops, future research should expand experiments on more crop species under a wider range of growing conditions, improve the representation of responses to climate extremes in crop models, and simulate additional crop physiological processes related to nutritional quality.

carbon dioxide (CO2)↗

NASA NTRS2023

Emission Factors for Crop Residue and Prescribed Fires in the Eastern US during FIREX-AQ

Agricultural and prescribed burning activities emit large amounts of trace gases and aerosols on regional to global scales. We present a compilation of emission factors (EFs) and emission ratios (ERs) from the eastern portion of the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign in 2019 in the United States, which sampled burning of crop residues and other prescribed fire fuels. FIREX-AQ provided comprehensive chemical characterization of 53 crop residue and 22 prescribed fires. Crop residues burned at different modified combustion efficiencies (MCE), with corn residue burning at higher MCE than other fuel types. Prescribed fires burned at lower MCE (<0.90) which is typical, while grasslands burned at lower MCE (0.90) than normally observed due to moist, green, growing season fuels. Most non-methane volatile organic compounds (NMVOCs) were significantly anticorrelated with MCE except for ethanol and NMVOCs that were measured with less certainty. We identified 23 species where crop residue fires differed by more than 50% from prescribed fires at the same MCE. Crop residue EFs were greater for species related to agricultural chemical use and fuel composition as well as oxygenated NMVOCs possibly due to the presence of metals such as potassium. Prescribed EFs were greater for monoterpenes (5×). FIREX-AQ crop residue average EFs generally agreed with the previous agricultural fire study in the US but had large disagreements with global compilations. FIREX-AQ observations show the importance of regionally-specific and fuel-specific EFs as first steps to reduce uncertainty in modeling the air quality impacts of fire emissions.

air quality↗

NASA NTRSDate not supplied

Open Science Approach to Analyze Climate-Crop Relationships in the US Leveraging GES DISC and Galaxy Workflows

Understanding the intricate relationship between climate variability and agricultural production is crucial for ensuring food security. This study investigates the impact of climate parameters, such as temperature, precipitation, and soil moisture, on major US crop yields. Adopting an open science approach, the study analyzes the impact of climate on agricultural production in the United States. The Galaxy workflow engine serves as the primary tool for integrating climate data from the Goddard Earth Sciences Data and Information Services Center (GES DISC), retrieved via the Giovanni system, with yield statistics from the United States Department of Agriculture’s National Agricultural Statistics Service (USDA NASS). Extensions for reading, preprocessing, and analyzing external data have been developed, enabling the creation of workflows within the Galaxy platform. The development of a reproducible workflow allows for the calculation of seasonal climate averages, which are then assessed for their correlation with crop yields. This methodology ensures the replicability of the research, promoting transparency and collaboration in the scientific community. Correlational and regression analyses have been applied to different sub-zones and crops. The findings from this research offer valuable insights into the relationship between climate parameters and crop yields. These insights contribute to a deeper understanding of climate-crop relationships, providing a solid foundation for informed decision-making in the agricultural sector. The high correlation values indicate a significant relationship between climate parameters and crop yields, underscoring the importance of considering climate factors in agricultural planning and policymaking. This research also exemplifies the power of open science in advancing our understanding of complex environmental and agricultural phenomena. By leveraging open data and services, it provides a robust and replicable framework for future studies in this critical field.

Open science↗

DOE OSTI2026

From chromatin to crop: epigenetic innovations in bioenergy systems

Energy crops encompass a diverse array of plant species cultivated primarily as a source of biomass for energy generation and biofuel production. As such, they play a pivotal role in the transition to sustainable energy systems. However, their productivity is often limited by environmental stresses, nutrient availability, and the need for optimized yield. While traditional breeding and genetic engineering have driven improvements, challenges such as narrow genetic diversity, long development cycles, trait instability, and unexpected gene interactions remain. Epigenetics offers a largely untapped opportunity to overcome these constraints by regulating gene expression through mechanisms that are dynamic, finely tuned, and responsive to environmental and developmental cues. Epigenetic modifications including DNA methylation, histone post-translational changes, and small non-coding RNAs influence nearly all aspects of plant development and physiology, including traits central to bioenergy crops. While these mechanisms are well characterized in model species such as Arabidopsis thaliana, they remain underexplored in many purpose-grown energy crops. This review summarizes the current state of knowledge of epigenetic regulation in bioenergy species, explores how these mechanisms can be leveraged to enhance crop resilience and productivity, and identifies gaps in our understanding. By characterizing epigenetic mechanisms and harnessing epigenetic variation, we can expand the toolkit for developing resilient, high-yielding bioenergy crops to meet future environmental and energy demands.

09 BIOMASS FUELS↗

DOE OSTI2023

Comparative productivity of six bioenergy cropping systems on marginal lands in the Great Lakes Region, United States

Abstract Growing lignocellulosic crops on marginal lands is a promising solution for sustainable biofuel production. We evaluated the productivity of bioenergy cropping systems (switchgrass [ Panicum virgatum L., var. Cave‐In‐Rock], miscanthus [ Miscanthus × giganteus , ‘Illinois clone’], hybrid poplar [ Populus nigra × P. maximowiczii A. Henry ‘NM6’], native grasses [five species], early successional vegetation, and restored prairie vs. historical vegetation [as reference control]) with and without nitrogen fertilization on low‐fertility former cropland at five sites in the Great Lakes Region, United States. We reported biomass yields for the first 7 years after establishment. Switchgrass was most consistently productive across all sites but miscanthus was more productive at three of the five sites. When averaged across sites, years, and nitrogen (N) treatments, biomass yields followed the order miscanthus > switchgrass > hybrid poplar ≈ native grasses > restored prairie > early successional vegetation ≈ historical vegetation, but varied substantially by crop and site, with a significant crop by site interaction. Yields of miscanthus and switchgrass peaked after four–five growing seasons and declined thereafter, while yields of both native grasses and restored prairie increased throughout 6 years with no sign of follow‐on decline, suggesting that polycultures may outperform monocultures over the long term. Yields of early successional vegetation—similar in composition to historical vegetation at each site—did not improve with time. Nitrogen fertilization increased the yields of all cropping systems at all sites. Our results demonstrate the viability of low‐productivity former cropland for long‐term bioenergy production and suggest there is no single crop best suited for all low fertility soils.

Jayawardena, Dileepa M.↗

DOE OSTI2022

A comprehensive analysis of the crop effect on the urban-rural differences in land surface phenology

The response of land surface phenology (LSP) to the urban heat island effect (UHI) is a useful biological indicator for understanding how vegetated ecosystems will be affected by future climate warming. However, vegetation cover in rural areas is often dominated by cultivated land, whose phenological timing is considerably influenced by agricultural managements (e.g., timing of sowing and harvesting), leading to biased conclusions derived from the urban-rural LSP differences. To demonstrate this problem, we investigated the crop influence on the phenological response to a warmer environment resulting from the UHI effect. We partitioned cities in the United States into cultivated and non-cultivated categories according to the proportion of crops in rural areas. We then built continuous buffer zones starting from the urban boundary to explore the urban-rural LSP differences considering the UHI effect on them. In this work, the results suggest crop inclusion is likely to lead to >14 days of urban-rural differences at both the start of the season (SOS) and the end of the season (EOS) between cultivated and non-cultivated cities. The temperature sensitivity (ST) of SOS is overestimated by approximately 2.7 days/°C, whereas the EOS is underestimated by 3.6 days/°C. Removing crop-dominated pixels (i.e., above 50 %) can minimize the influence of crop planting/harvesting on LSP and derive reliable results. We, therefore, suggest explicit consideration of crop impacts in future studies of phenological differences between urban and rural areas and the UHI effect on LSP in urban domains, as presented by this comprehensive study.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

The Role of Climate Covariability on Crop Yields in the Conterminous United States

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R, an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Albedo-induced global warming impact of Conservation Reserve Program grasslands converted to annual and perennial bioenergy crops

Abstract Climate benefit assessments of bioenergy crops often focus on biogeochemical impacts, paying little if any attention to biogeophysical impacts. However, land conversions required for large-scale bioenergy crop production are substantial and may directly affect the climate by altering surface energy balance. In the US, such land conversions are likely to be met in part by converting Conservation Reserve Program (CRP) grassland to bioenergy crops. Here, we converted three 22 year old CRP smooth brome grass fields into no-till corn, switchgrass, or restored prairie bioenergy crops. We assessed the biogeophysical climate impact of the conversions using albedo changes relative to unconverted reference CRP grassland. The corn and perennial fields had higher annual albedo than the grassland they replaced—causing cooling of the local climate. The cooling of the corn field occurred solely during the non-growing season—especially when surfaces were snow-covered, whereas the cooling of the perennial fields was more prominent during the growing season. Compared to biogeochemical impacts with fossil fuel offsets for the same land conversions over eight years, the annual albedo-induced climate benefits add ∼35% and ∼78% to the annual biogeochemical benefits provided from the switchgrass and restored prairie fields, respectively, and offset ∼3.3% of the annual greenhouse gas (GHG) emissions from the corn field. We conclude that albedo-induced climate mitigation from conversion of CRP lands to perennial but not annual bioenergy crops can be substantial, and future climate impact assessments of bioenergy crops should include albedo changes in addition to GHG balances in order to better inform climate policies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Agrivoltaic system design tools for managing trade-offs between energy production, crop productivity and water consumption

Abstract Agrivoltaic systems that locate crop production and photovoltaic energy generation on the same land have the potential to aid the transition to renewable energy by reducing the competition between food, habitat, and energy needs for land while reducing irrigation requirements. Experimental efforts to date have not adequately developed an understanding of the interaction among local climate, array design and crop selection sufficient to manage trade-offs in system design. This study simulates the energy production, crop productivity and water consumption impacts of agrivoltaic array design choices in arid and semi-arid environments in the Southwestern region of the United States. Using the Penman–Monteith evapotranspiration model, we predict agrivoltaics can reduce crop water consumption by 30%–40% of the array coverage level, depending on local climate. A crop model simulating productivity based on both light level and temperature identifies afternoon shading provided by agrivoltaic arrays as potentially beneficial for shade tolerant plants in hot, dry settings. At the locations considered, several designs and crop combinations exceed land equivalence ratio values of 2, indicating a doubling of the output per acre for the land resource. These results highlight key design axes for agrivoltaic systems and point to a decision support tool for their development.

Environmental Sciences & Ecology↗

DOE OSTI2025

Field-scale mapping of California crop water productivity to inform water management in critically overdrafted groundwater basins

Crop water productivity (CWP) metrics can reveal how the dynamics of crop production and water use change across space and time. We use field-scale satellite inputs from 2016–2021 to estimate potential water savings for four crops (almonds, grapes, walnuts, and citrus—which collectively account for approximately one-third of California’s cropland area), within critically overdrafted groundwater sub-basins of California’s San Joaquin Valley. These annual estimates of field-level water savings potential are based on locally achievable CWP values for each crop type. Our findings show considerable spatial variation in CWP and potential water savings within each sub-basin. We find that increasing CWP to peak efficiency (defined as improving fields to the 95th percentile of observed CWP) for four crops could meet up to 36% of the estimated annual overdraft in San Joaquin Valley. For comparison, fallowing 5% of the four crop type fields in the same study area could potentially reduce annual overdraft by 11%. By delivering results at the field scale, our work can inform targeted interventions by irrigation district managers and more efficient allocation of state incentives for improved water management. For example, we estimate that state grant funding for water efficiency upgrades could have amplified potential water savings threefold by targeting investments to the least efficient fields.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Brassica rapa Domestication: Untangling Wild and Feral Forms and Convergence of Crop Morphotypes

The study of domestication contributes to our knowledge of evolution and crop genetic resources. Human selection has shaped wild Brassica rapa into diverse turnip, leafy, and oilseed crops. Despite its worldwide economic importance and potential as a model for understanding diversification under domestication, insights into the number of domestication events and initial crop(s) domesticated in B. rapa have been limited due to a lack of clarity about the wild or feral status of conspecific noncrop relatives. To address this gap and reconstruct the domestication history of B. rapa, we analyzed 68,468 genotyping-by-sequencing-derived single nucleotide polymorphisms for 416 samples in the largest diversity panel of domesticated and weedy B. rapa to date. To further understand the center of origin, we modeled the potential range of wild B. rapa during the mid-Holocene. Our analyses of genetic diversity across B. rapa morphotypes suggest that noncrop samples from the Caucasus, Siberia, and Italy may be truly wild, whereas those occurring in the Americas and much of Europe are feral. Clustering, tree-based analyses, and parameterized demographic inference further indicate that turnips were likely the first crop type domesticated, from which leafy types in East Asia and Europe were selected from distinct lineages. These findings clarify the domestication history and nature of wild crop genetic resources for B. rapa, which provides the first step toward investigating cases of possible parallel selection, the domestication and feralization syndrome, and novel germplasm for Brassica crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Legacy Effects of Cropping System and Precipitation Influence the Core Camelina sativa Microbiome

Camelina ( Camelina sativa L.) is a potential biofuel crop and beneficial rotation crop in dryland cropping systems. Little is known about camelina microbiota or the legacy effect of soil origin/cropping system zones on camelina-associated microbiome assembly. To explore camelina-microbe associations, we grew camelina in the greenhouse using soil transplanted from 33 locations in the dryland wheat production area of eastern Washington. Bacterial, archaeal, and fungal communities from bulk soil, rhizosphere, and endosphere were characterized with 16S rRNA and internal transcribed spacer amplicon sequencing and were analyzed alongside site-specific climatic and edaphic data. We found that soil from the highest precipitation zone had higher alpha diversity than soil from the driest zone, but this effect was not seen in the greenhouse rhizosphere or endosphere. Plant compartment, cropping system zone, and soil origin all significantly influenced microbial composition, with soil pH and organic matter, as well as precipitation at origin, as major predictors. Analysis of abundance–occupancy distributions showed that the Actinobacteriota Aeromicrobium and Marmoricola and the fungus Pseudogymnoascus in the rhizosphere were plant-selected, while the endosphere was characterized by a number of Actinobacteriota, Rhizobium, and Clostridium. Sphingomonas amplicon sequence variants were also consistently enriched in the rhizosphere, suggesting that they are present in soils collected throughout eastern Washington and may represent good candidate biostimulants. Several lignin decomposing fungi had site-specific rhizospheric distributions, suggesting that they may be dispersal-limited or result from the legacy effect of long-term wheat cropping. Overall, this study contributes to our understanding of microbiome assembly in and on camelina roots while also highlighting the potential impact of cropping history on soil- and plant-associated microbiomes. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2025.

Barnes, Elle M↗