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DOE OSTI2021

A micrometeorological flux perspective on brush management in a shrub-encroached Sonoran Desert grassland

Woody plant encroachment typically limits the forage productivity of managed rangelands and alters a panoply of semiarid ecosystem processes and services. Intervention strategies to reduce woody plant abundance, collectively termed “brush management”, often lack observations to quantify and interpret changes in ecosystem processes. Furthermore, comparative studies between treated and untreated areas should account for heterogeneity since plant composition, microclimate, topoedaphic factors, and historical land use can substantially vary over short distances in drylands. Here, in this work, we quantify ecosystem responses to brush management after a single aerial herbicide application on an 18 hectare shrub-encroached grassland (savanna) in southern Arizona, USA. We conducted a pre- and post-treatment comparison of a flux tower site in the treated area with that of a tower in a nearby control site. The comparison, spanning a seven year period, included: (1) ground, airborne, and satellite-based measurements of vegetation structure, and (2) eddy covariance measurements. The herbicide treatment defoliated the dominant shrub (velvet mesquite, Prosopis velutina) and led to a temporary reduction in summer greening, but full foliar recovery occurred within two years. Contrary to expectations, perennial grass cover decreased and bare soil cover increased on the treated site. Relative amounts of evapotranspiration were reduced, while carbon uptake increased during the 2 year post-treatment period at the treated site due to a higher water use efficiency in the following spring. During mesquite recovery, carbon uptake was enhanced by higher gross primary productivity and accompanied by a decrease in ecosystem respiration relative to the untreated site. Mesquite recovery was facilitated by access to deep soil water, carbohydrate reserves in rooting systems, and a lower competition from reduced perennial grass cover.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

4D electrical resistivity tomography for assessing the influence of vegetation and subsurface moisture on railway cutting condition

Instability of slopes, embankments, and cuttings on the railway network is increasingly prevalent globally. Monitoring vulnerable infrastructure aids in geotechnical asset management, and improvements to transport safety and efficiency. Here, we examine the use of a novel, near-real-time Electrical Resistivity Tomography (ERT) monitoring system for assessing the stability of a railway cutting in Leicestershire, United Kingdom. In 2015, an ERT monitoring system was installed across a relict landslide (grassed) and an area of more stable ground on either side (wooded), to monitor changes in electrical resistivity through time and space, and to assess the influence of different types of vegetation on the stability of transportation infrastructure. Two years of 4-Dimensional ERT monitoring results are presented here, and petrophysical relationships developed in the laboratory are applied to calibrate the resistivity models in order to provide an insight into hydrogeological pathways within a railway cutting. The influence of vegetation type on subsurface moisture pathways and on slope stability is also assessed – here we find that seasonal subsurface changes in moisture content and soil suction are exacerbated by the presence of trees (wooded area). This results in shrink-swell behaviour of the clays comprising the railway cutting, resulting in fissuring and a reduction in shear strength, leading to instability. As such, it is proposed that on slopes comprised of expansive soils, grassed slopes are beneficial for stability. Insights into the use of 4-D ERT for monitoring railway infrastructure gained from this study may be applied to the monitoring of critical geotechnical assets elsewhere.

58 GEOSCIENCES↗

DOE OSTI2023

Radionuclide surrogate aerosolization, resuspension and suppression in hazardous situations

Radioactive fire following nuclear accidents causes resuspension of radioactive contamination that can spread over large areas. Although many papers focus on particle deposition and resuspension, a limited number of studies model its suppression. Even less data is available for the comparison of emissions across particle size, surface, and mode of resuspension. In this study, cerium dioxide surrogate for internal hazards such as radionuclide particle matter was aerosolized into a large chamber and subsequently resuspended after sedimentation. Resuspension was induced by common modes of human movement including walking, wind, and driving on common surfaces including polyvinyl chloride (PVC), artificial grass (turf), and concrete in a 5.8 m long, 3.7 m wide and 3 m high tent. The resuspension was experimentally measured for two particle sizes (1 and 10 μm) at three different heights (0.3 m, 1.2 m, and 2.4 m) and compared across size, surface, and mode of resuspension. Particle size distribution was measured using an aerodynamic particle sizer and the resuspended particles were collected with the wetted wall cyclone aerosol collector and quantitated using inductively coupled plasma mass spectrometry. The testing was repeated with the F-500 fire retardant application to study its effect on resuspension. In this study, artificial grass flooring was found to generate the most resuspension, with walking on turf for the 1 μm particle testing yielding the highest factor overall. Concrete had the lowest resuspension, showing variations in the size distribution of aerosol as a function of height from the source resuspension factors. The application of fire retardant was found to significantly reduce surrogate resuspension, regardless of resuspension method or testing surface. Here, the results provide impactful information regarding the different modes of resuspension including human transport (walking and driving) and wind for the resuspension of radionuclide surrogate particles deposited onto common surfaces and the effect of fire retardant application on their resuspension, leading to higher levels of safety for nuclear energy plants and facilities.

42 ENGINEERING↗

DOE OSTI2023

Using SWMM for emergency response planning: A case study evaluating biological agent transport under various rainfall scenarios and urban surfaces

To assist in emergency preparedness for a biological agent terrorist attack or accidental pathogen release, potential contaminant levels and migration pathways of spores spread by urban stormwater were evaluated using a Storm Water Management Model (SWMM) of U.S. Coast Guard Base Elizabeth City, North Carolina. The high temporal-spatial resolution SWMM model was built using spore concentrations in stormwater runoff from asphalt, grass, and concrete collected from a point-scale field study. The subsequent modeled contamination scenarios included a notional plume release and point releases mimicking the field study under three rainfall conditions. The rainfall scenarios included a 6-hour natural rainfall event on Dec. 8, 2021 and two design storms (2-year and 100-year events). The observed spore concentrations from asphalt and concrete from the actual field experiment were applied to calibrate the washoff parameters in the SWMM model, using an exponential washoff function. The calibrated washoff coefficient (c 1 ) and exponent (c 2 ) were 0.01 and 1.00 for asphalt, 0.05 and 1.45 for grass, and 2.45 and 1.00 for concrete, respectively. The calibrated SWMM model simulated spore concentrations in runoff at times and magnitudes similar to the field study data. In the point release modeled scenario, the concrete surface generated 55.6% higher average spore concentrations than asphalt. Similarly, in the field experiment, a 175% (p < 0.05) higher average spore concentration in surface runoff was observed from concrete than from asphalt. Here, this study demonstrates how SWMM may be used to evaluate spore washoff from urban surfaces under different precipitation amounts, intensities, and durations, and how visualized spatial migration pathways in stormwater runoff may be used for emergency planning and remediation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗

DOE OSTI2026

Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China

Shrub fractional abundance (SFA), the proportion of shrub cover per unit area, serves as a critical indicator of environmental aridity and ecosystem health in arid and semi-arid regions, particularly across the Mongolian steppe. However, large-scale SFA mapping in Mongolian steppe ecosystems remains challenging due to the small crown size of shrubs, their sparse distribution, and spectral overlap with coexisting low vegetation (e.g., grasses and herbs), which hinders accurate detection using coarser-resolution satellite data or traditional field surveys. To address these challenges, we developed a two-step approach that integrates very-high-resolution (VHR) imagery, time-series Sentinel-2 data, and deep learning techniques. First, we generated high-accuracy benchmark maps of individual shrub crowns from 0.5 m VHR imagery by combining manual segmentation with a hybrid deep learning framework (Dino V2 and convolutional neural networks). Second, we used these shrub crown maps as training data to build an XGBoost model for predicting SFA from 20 m Sentinel-2 time-series data, leveraging phenological information to improve estimation. We validated our approach across 70 sites (1km 2 each) in the Inner Mongolia Autonomous Region, which is representative of Mongolian steppe ecosystems. From VHR imagery, we mapped 1.31 million shrub crowns with an accuracy of R 2 = 0.92. Scaling up with Sentinel-2 data yielded regional SFA maps with an R 2 = 0.60. Further SHAP (SHapley Additive exPlanations) analysis on the developed XGBoost model revealed that phenological metrics (particularly observations in early-May, mid-July, and late-September), which distinguish shrub phenology from that of other land cover types (e.g., grasses and bare soil), were the most influential predictors of SFA. Finally, our regional SFA maps uncovered unimodal relationships between shrub distribution and climate variables, peaking at mean annual minimum temperatures near 0 °C and annual precipitation around 200 mm. Collectively, these findings demonstrate how the integration of multi-source remote sensing and machine learning can overcome historical limitations in SFA mapping, enabling accurate, spatially continuous assessments across vast Inner-Mongolian steppe ecosystems. Our framework has the potential to be applied to other steppe ecosystems and dryland ecosystems across the Mongolian steppe and beyond, offering a foundation for improved monitoring and ecological impact assessments in the face of global climate changes.

Arid and semi-arid landscapes↗

DOE OSTI2021

Environmental harshness mediates the relationship between aboveground and belowground communities in Antarctica

Linkages between aboveground and belowground communities are a key but globally under-researched component of responses to environmental change. Given the logistical complications to studying these relationships, much of our knowledge derives from laboratory experiments and localized field studies which have so far yielded inconsistent results. Because environmental factors may alter relationships between above- and belowground communities, there is a need for broad-scale field studies testing these interactions. The Antarctic Peninsula provides an ideal test setting, given the relatively simple communities both above- and belowground. The Peninsula is also experiencing rapid environmental changes, including alterations in species diversity and distribution both above- and belowground. Thus, an improved understanding of the broad-scale consequences of altered environments and vegetation communities for the soil microbiome is of high priority. To determine the nature and strength of the relationship between in situ plant and soil communities across a broad spatial scale and range of environmental conditions, we sampled soil communities at 9 locations (spanning 60–72°S along the Scotia Arc and Antarctic Peninsula) beneath the major aboveground habitats (moss, grass, lichen, algae and bare soil). We measured a comprehensive suite of soil physicochemical properties, microbial (bacterial and fungal) diversity and composition, and invertebrate abundance and community composition to determine the relationships between plant and soil communities. Furthermore, our results suggest that, with increased environmental severity, plant cover types become more important for influencing the physicochemical soil environment, and therefore the soil microbial communities. Although we found site-specific relationships, broad-scale patterns reveal significant differences among bare soils and vegetated soils, particularly soils beneath grass and moss. This suggests that expansion of vegetation communities under current climate warming projections will be accompanied by shifts in the soil microbiome, with important implications for the ecosystem functioning with which they are associated.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Selecting Suitable Near-Native Lignins for Research

There are several methods to isolate near-native lignins, including milled-wood lignin, enzymatic lignin, cellulolytic enzyme lignin, and enzymatic mild-acidolysis lignin. Which one is the most representative of the native lignin? Herein, near-native lignins were isolated from different plant groups and structurally analyzed to determine how well these lignins represented their native lignin counterparts. Analytical methods were applied to understand the molecular weight, monomer composition, and distribution of interunit linkages in the structure of the lignins. The results indicated that either enzymatic lignin or cellulolytic enzyme lignin may be used to represent native lignin in softwoods and hardwoods. None of the lignins, however, appeared to represent native lignins in grasses (monocot plants) because of substantial syringyl/guaiacyl differences. Furthermore, complicating the understanding of grass lignin structure, large amounts of hydroxycinnamates acylate their polysaccharides and, when released, are often conflated with actual lignin monomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in situ and remote sensing data sets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

Cheng, Yanyan↗

DOE OSTI2020

A genome resource for green millet Setaria viridis enables discovery of agronomically valuable loci

Abstract Wild and weedy relatives of domesticated crops harbor genetic variants that can advance agricultural biotechnology. Here we provide a genome resource for the wild plant green millet ( Setaria viridis ), a model species for studies of C 4 grasses, and use the resource to probe domestication genes in the close crop relative foxtail millet ( Setaria italica ). We produced a platinum-quality genome assembly of S. viridis and de novo assemblies for 598 wild accessions and exploited these assemblies to identify loci underlying three traits: response to climate, a ‘loss of shattering’ trait that permits mechanical harvest and leaf angle, a predictor of yield in many grass crops. With CRISPR–Cas9 genome editing, we validated Less Shattering1 ( SvLes1 ) as a gene whose product controls seed shattering. In S. italica , this gene was rendered nonfunctional by a retrotransposon insertion in the domesticated loss-of-shattering allele SiLes1-TE (transposable element). This resource will enhance the utility of S. viridis for dissection of complex traits and biotechnological improvement of panicoid crops.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Proteomic and metabolic disturbances in lignin-modified Brachypodium distachyon

Abstract Lignin biosynthesis begins with the deamination of phenylalanine and tyrosine (Tyr) as a key branch point between primary and secondary metabolism in land plants. Here, we used a systems biology approach to investigate the global metabolic responses to lignin pathway perturbations in the model grass Brachypodium distachyon. We identified the lignin biosynthetic protein families and found that ammonia-lyases (ALs) are among the most abundant proteins in lignifying tissues in grasses. Integrated metabolomic and proteomic data support a link between lignin biosynthesis and primary metabolism mediated by the ammonia released from ALs that is recycled for the synthesis of amino acids via glutamine. RNA interference knockdown of lignin genes confirmed that the route of the canonical pathway using shikimate ester intermediates is not essential for lignin formation in Brachypodium, and there is an alternative pathway from Tyr via sinapic acid for the synthesis of syringyl lignin involving yet uncharacterized enzymatic steps. Our findings support a model in which plant ALs play a central role in coordinating the allocation of carbon for lignin synthesis and the nitrogen available for plant growth. Collectively, these data also emphasize the value of integrative multiomic analyses to advance our understanding of plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Pyruvate, phosphate dikinase regulatory protein impacts light response of C4 photosynthesis in Setaria viridis

In C4 plants, the pyruvate (Pyr), phosphate dikinase regulatory protein (PDRP) regulates the activity of the C4 pathway enzyme Pyr, phosphate dikinase (PPDK) in a light-/dark-dependent manner. The importance of this regulatory action to C4 pathway function and overall C4 photosynthesis is unknown. To resolve this question, we assessed in vivo PPDK phospho-regulation and whole leaf photophysiology in a CRISPR–Cas9 PDRP knockout (KO) mutant of the NADP-ME C4 grass green millet (Setaria viridis). PDRP enzyme activity was undetectable in leaf extracts from PDRP KO lines. Likewise, PPDK phosphorylated at the PDRP-regulatory Thr residue was immunologically undetectable in leaf extracts. PPDK enzyme activity in rapid leaf extracts was constitutively high in the PDRP KO lines, irrespective of light or dark pretreatment of leaves. Gas exchange analysis of net CO2 assimilation revealed PDRP KO leaves had markedly slower light induction kinetics when leaves transition from dark to high-light or low-light to high-light. In the initial 30 min of the light induction phase, KO leaves had an ~15% lower net CO2 assimilation rate versus the wild-type (WT). Despite the impaired slower induction kinetics, we found growth and vigor of the KO lines to be visibly indistinguishable from the WT when grown in normal air and under standard growth chamber conditions. However, the PDRP KO plants grown under a fluctuating light regime exhibited a gradual multi-day decline in Fv/Fm, indicative of progressive photosystem II damage due to the absence of PDRP. Collectively, our results demonstrate that one of PDRP’s functions in C4 photosynthesis is to ensure optimal photosynthetic light induction kinetics during dynamic changes in incident light.

Plant Sciences↗

DOE OSTI2022

Root responses to elevated CO 2 , warming and irrigation in a semi-arid grassland: Integrating biomass, length and life span in a 5-year field experiment

Plant roots mediate the impacts of environmental change on ecosystems, yet knowledge of root responses to environmental change is limited because few experiments evaluate multiple environmental factors and their interactions. Inferences about root functions are also limited because root length dynamics are rarely measured. Using a 5-year experiment in a mixed-grass prairie, we report the responses of root biomass, length and life span to elevated carbon dioxide (CO 2 ), warming, elevated CO 2 and warming combined, and irrigation. Root biomass was quantified using soil cores and root length dynamics were assessed using minirhizotrons. By comparing root dynamics with published results for soil resources and above-ground productivity, we provide mechanistic insights into how climate change might impact grassland ecosystems. In the upper soil layer, 0–15 cm depth, both irrigation and elevated CO 2 alone increased total root length by twofold, but irrigation decreased root biomass and elevated CO 2 had only small positive effects on root biomass. The large positive effects of irrigation and elevated CO 2 alone on total root length were due to increases in both root length production and root life span. The increased total root length and life span under irrigation and elevated CO 2 coincided with apparent shifts from water limitation of plant growth to nitrogen limitation. Warming alone had minimal effects on root biomass, length and life span in this shallow soil layer. Warming and elevated CO 2 combined increased root biomass and total root length by c. 25%, but total root length in this treatment was lower than expected if the effects of CO 2 and warming alone were additive. Treatment effects on total root length and root life span varied with soil depth and root diameter. Synthesis. Sub-additive effects of CO 2 and warming suggest studies of elevated CO 2 alone might overestimate the future capacity of grassland root systems to acquire resources. In this mixed-grass prairie, elevated CO 2 with warming stimulated total root length and root life span in deeper soils, likely enhancing plant access to more stable pools of growth-limiting resources, including water and phosphorus. Therefore, these root responses help explain previous observations of higher, and more stable, above-ground productivity in these projected climate conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Plant diversity and functional identity drive grassland rhizobacterial community responses after 15 years of CO 2 and nitrogen enrichment

Abstract Improved understanding of bacterial community responses to multiple environmental filters over long time periods is a fundamental step to develop mechanistic explanations of plant–bacterial interactions as environmental change progresses. This is the first study to examine responses of grassland root‐associated bacterial communities to 15 years of experimental manipulations of plant species richness, functional group and factorial enrichment of atmospheric CO 2 (eCO 2 ) and soil nitrogen (+N). Across the experiment, plant species richness was the strongest predictor of rhizobacterial community composition, followed by +N, with no observed effect of eCO 2 . Monocultures of C 3 and C 4 grasses and legumes all exhibited dissimilar rhizobacterial communities within and among those groups. Functional responses were also dependent on plant functional group, where N 2 ‐fixation genes, NO 3− ‐reducing genes and P‐solubilizing predicted gene abundances increased under resource‐enriched conditions for grasses, but generally declined for legumes. In diverse plots with 16 plant species, the interaction of eCO 2 +N altered rhizobacterial composition, while +N increased the predicted abundance of nitrogenase‐encoding genes, and eCO 2 +N increased the predicted abundance of bacterial P‐solubilizing genes. Synthesis : Our findings suggest that rhizobacterial community structure and function will be affected by important global environmental change factors such as eCO 2 , but these responses are primarily contingent on plant species richness and the selective influence of different plant functional groups.

Revillini, Daniel↗

DOE OSTI2022

Testing unified theories for ozone response in C 4 species

Abstract There is tremendous interspecific variability in O 3 sensitivity among C 3 species, but variation among C 4 species has been less clearly documented. It is also unclear whether stomatal conductance and leaf structure such as leaf mass per area (LMA) determine the variation in sensitivity to O 3 across species. In this study, we investigated leaf morphological, chemical, and photosynthetic responses of 22 genotypes of four C 4 bioenergy species (switchgrass, sorghum, maize, and miscanthus) to elevated O 3 in side‐by‐side field experiments using free‐air O 3 concentration enrichment (FACE). The C 4 species varied largely in leaf morphology, physiology, and nutrient composition. Elevated O 3 did not alter leaf morphology, nutrient content, stomatal conductance, chlorophyll fluorescence, and respiration in most genotypes but reduced net CO 2 assimilation in maize and photosynthetic capacity in sorghum and maize. Species with lower LMA and higher stomatal conductance tended to show greater losses in photosynthetic rate and capacity in elevated O 3 compared with species with higher LMA and lower stomatal conductance. Stomatal conductance was the strongest determinant of leaf photosynthetic rate and capacity. The response of both area‐ and mass‐based leaf photosynthetic rate and capacity to elevated O 3 were not affected by LMA directly but negatively influenced by LMA indirectly through stomatal conductance. These results demonstrate that there is significant variation in O 3 sensitivity among C 4 species with maize and sorghum showing greater sensitivity of photosynthesis to O 3 than switchgrass and miscanthus. Interspecific variation in O 3 sensitivity was determined by direct effects of stomatal conductance and indirect effects of LMA. This is the first study to provide a test of unifying theories explaining variation in O 3 sensitivity in C 4 bioenergy grasses. These findings advance understanding of O 3 tolerance in C 4 grasses and could aid in optimal placement of diverse C 4 bioenergy feedstock across a polluted landscape.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Species interactions amplify functional group responses to elevated CO 2 and N enrichment in a 24‐year grassland experiment

Abstract Plant functional groups (FGs) differ in their response to global changes, although species within those groups also vary in such responses. Both species and FG responses to global change are likely influenced by species interactions such as inter‐specific competition and facilitation, which are prevalent in species mixtures but not monocultures. As most studies focus on responses of plants growing in either monocultures or mixtures, but rarely both, it remains unclear how interspecific interactions in diverse ecological communities, especially among species in different FGs, modify FG responses to global changes. To address these issues, we leveraged data from a 16‐species, 24‐year perennial grassland experiment to examine plant FG biomass responses to atmospheric CO 2 , and N inputs at different planted diversity. FGs differed in their responses to N and CO 2 treatments in monocultures. Such differences were amplified in mixtures, where N enrichment strongly increased C3 grass success at ambient CO 2 and C4 grass success at elevated CO 2 . Legumes declined with N enrichment in mixtures at both CO 2 levels and increased with elevated CO 2 in the initial years of the experiment. Our results suggest that previous studies that considered responses to global changes in monocultures may underestimate biomass changes in diverse communities where interspecific interactions can amplify responses. Such effects of interspecific interactions on responses of FGs to global change may impact community composition over time and consequently influence ecosystem functions.

Mohanbabu, Neha↗

DOE OSTI2022

Agroecosystem model simulations reveal spatial variability in relative productivity in biomass sorghum and maize in Iowa, USA

Biomass sorghum (Sorghum bicolor L. Moench) is an annual C 4 grass that has emerged as a candidate bioenergy crop but has not been widely grown in the United States. Corn (Zea mays L.), another annual C 4 grass, has been produced on a large scale in the United States for biofuels. Iowa leads the nation in both corn and ethanol production. The high productivity of corn in Iowa creates the research question: could biomass sorghum be as or more productive than corn in the state in terms of bioenergy? Efforts to use crop models to fill the gaps left by field experimentation on biomass sorghum have also been limited thus far. To address our research question, we collected biophysical data on biomass sorghum grown in Iowa for two growing seasons, used them to develop a biomass sorghum module in an agroecosystem model (Agro-IBIS), and predict the potential performance of biomass sorghum across Iowa compared to maize. Despite dry conditions in 2019 and 2020, average biomass sorghum yields were 17.20 Mg ha –1 . By comparison, average corn aboveground biomass was higher in 2020 (22.02 Mg ha –1 ). Soil cores indicated average belowground biomass of 1.46 Mg ha –1 , with roots concentrated near the surface (73% of biomass above 50 cm in a 1 m core). When biomass sorghum model parameters were calibrated with measured values, model output was in close agreement with measured biomass (slope = 0.932, R 2 = 0.91) and evapotranspiration (slope = 0.757, R 2 = 0.64). Subsequent regional simulations revealed a notable latitudinal gradient in biomass sorghum yield, with a strong linear relationship between yield and seasonal growing degree-days (R 2 = 0.89). When these yields were compared to simulated corn aboveground biomass yields, only 3.4% of the state had biomass sorghum yields that were significantly higher than corn. This number was reduced to 0.3% when comparing the crops in terms of energy ethanol yield. Thus, we conclude biomass sorghum must be improved to be competitive with corn as an annual biofuel crop in Iowa. This study provides a baseline against which to compare advancements in sorghum breeding for biomass and stress tolerance in Iowa.

Agro-IBIS↗

DOE OSTI2023

Climate cooling benefits of cellulosic bioenergy crops from elevated albedo

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum ( Sorghum bicolor ), switchgrass ( Panicum virgatum L.), and giant miscanthus ( Miscanthus × giganteus) , and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo ( α s ) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆ α ) and albedo‐induced radiative forcing (RF ∆ α ). We used a nearby forest as a historical native cover type to estimate reference albedo and RF ∆ α change upon original land use conversion, and a continuous no‐till maize ( Zea mays L .) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually, α s differed significantly ( p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annual α s (0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing season α s in perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS) α s (0.370 ± 0.020) was much higher than growing season α s (0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF αMAIZE : −3.83 ± 1.00 W m −2 ; RF αFOREST : −16.75 ± 3.01 W m −2 ). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest.

Lei, Cheyenne↗