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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2024

Generating Dominating Sets Using Locally Defined Centrality Measures

The dominating set problem has many practical applications but is well-known to be NP-hard. Therefore, there is a need for efficient heuristic algorithms, especially in applications such as ad hoc wireless networks. Most distributed algorithms proposed in the literature assume that each node has knowledge of the network structure. We propose a distributed heuristic algorithm that uses two rounds of communication, and where each node has only local information, both in terms of network structure and dominating set assignment. First, each node calculates a local centrality measure to determine whether it is part of the dominating set D. The second round guarantees D is a dominating set by adding any non-dominated nodes. We compare several centrality measures and show that the Shapley centrality, derived from the Shapley value in game theory, is theoretically motivated and performs well in practice on several synthetic and real-world networks.

Network↗
DOE OSTI2025

Dielectron production in central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02TeV

The first measurement of the 𝑒 + ⁢𝑒 − pair production at midrapidity and low invariant mass in central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV at the Large Hadron Collider is presented. The yield of 𝑒 + ⁢𝑒 − pairs is compared with a cocktail of expected hadronic decay contributions in the invariant mass (𝑚𝑒⁢𝑒) and pair transverse momentum (𝑝 T,𝑒⁢𝑒 ) ranges 𝑚 𝑒⁢𝑒 < 3.5 GeV/𝑐 2 and 𝑝 T,𝑒⁢𝑒 < 8 GeV/𝑐. For 0.18 < 𝑚 𝑒⁢𝑒 < 0.5 GeV/𝑐 2 the ratio of data to the cocktail of hadronic contributions amounts to 1.40 ± 0.11⁢(stat.) ± 0.23 ⁢(syst.) ± 0.16⁢ (cocktail) and 1.42 ± 0.11⁢ (stat.) ± 0.23 (syst.)$^{+0.24}_{−0.29}$ ⁢(cocktail), including or not including medium effects in the estimation of the heavy-flavor background, respectively. It is consistent with predictions from two different models for an additional contribution of thermal 𝑒+⁢𝑒− pairs from the hadronic and partonic phases. In the intermediate-mass range (1.2 < 𝑚 𝑒⁢𝑒 < 2.6 GeV/𝑐 2 ), the pair transverse impact parameter of the 𝑒 + ⁢𝑒 − pairs (DCA𝑒⁢𝑒, where “DCA” denotes “distance of closest approach”) is used for the first time in Pb-Pb collisions to separate displaced dielectrons from heavy-flavor hadron decays from a possible (thermal) contribution produced at the interaction point. The data are consistent with a suppression of 𝑒 + ⁢𝑒 − pairs from $𝑐\bar{𝑐}$ and an additional prompt component. Finally, the first direct-photon measurement in the 10% most central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV is reported via the study of virtual direct photons in the transverse momentum range 1 < 𝑝 T < 5 GeV/𝑐. A model including prompt photons, as well as photons from the preequilibrium and fluid-dynamic phases, can reproduce the result, while being at the upper edge of the data uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗
DOE OSTI2025

Topology-Aware Reinforcement Learning for Voltage Control: Centralized and Decentralized Strategies

Volt-VAR control (VVC) methods based on deep reinforcement learning (DRL) can effectively control distribution grid voltage and minimize power loss by implementing corrective and preventive control measures on the reactive power output of inverter-based distributed energy resources (DERs). However, model-free DRL-based VVC approaches usually cannot capture the important topological feature of the power system since they use a fully-connected network (FCN) to deliver the action. Therefore, this paper proposes a graph convolutional network (GCN)-based DRL approach that can employ the topological information of the network to take better control action for regulating the voltage. Our implementation allows for both centralized and decentralized configurations, utilizing a single agent and multiple agents respectively. Although the centralized GCN-based DRL approach has its advantages of minimizing voltage fluctuation and power loss, it is not suitable for large scale power systems due to its challenges in terms of scalability, computation speed and potential single points of failure. Therefore, these problems can be resolved using the decentralized GCN-based DRL approach. Moreover, to ensure the safe operation of the model, our proposed approach incorporates an exponential barrier function while formulating the reward function for each agent. To validate performance of the proposed approaches, the proposed model is tested on modified IEEE test systems and the performances are measured in terms on voltage fluctuation reduction, minimization of power loss and computational speed. Finally, the results show that the proposed topology-aware approach outperforms the FCN-based DRL approach in terms of reducing voltage fluctuation and minimizing power loss of the network. Moreover, it is shown that the decentralized GCN-based DRL has faster computational speed than other approaches.

42 ENGINEERING↗
NASA NTRS2019

Identification of Absorbing Aerosol Types at a Site in the Northern Edge of Indo-Gangetic Plain and a Polluted Valley in the Foothills of the Central Himalayas

Identification of atmospheric aerosol types and characterization of absorbing aerosols, based on AErosol RObotic NETwork (AERONET) data collected during 2013–2014 over two sites in Nepal: Lumbini in the northernmost part of central Indo-Gangetic Plain (IGP) and Kathmandu Valley in foothills of the central Himalayas, have been conducted in the present study. The relationship between four aerosol parameters; Extinction Angstrom Exponent (EAE), Absorption Angstrom Exponent (AAE), Single Scattering Albedo (SSA) and Real Refractive Index (RRI) was analyzed to study the aerosol types. This resulted in the identification of two types of aerosols concerning their origin: biomass burning and urban/industrial mix. Furthermore, to understand the absorbing aerosol types, the relationship between aerosol size parameters; Fine Mode Fraction (FMF) and Angstrom Exponent (AE), and aerosol absorption characteristics; SSA and AAE were investigated. In regards to the absorbing aerosol types, ‘Mostly BC’ was the dominant absorbing aerosol, over both sites, with comparatively negligible contribution from other absorbing aerosol types such as dust. The aerosol subtypes obtained from satellite-borne CALIPSO instrument supported the results derived from the AERONET data. The CALIPSO images also indicated that the aerosols over the foothills of the Himalayas could extend to the height of >5 km above the ground, which could be transported towards the Himalayan and Tibetan Plateau (HTP) region with sensitive ecosystems. The multi-sites based study of long-term records is required to elucidate the nature and trends of aerosols in the HTP region and any perturbation to the atmospheric environment and other environments in this region.

Aerosol types↗
NASA NTRS2021

The Current State and Future of the Former Central Nervous System Risk Managed by Space Radiation Element Part of NASA’s Human Research Program

Historically, the Space Radiation Element, as part of the NASA Human Research Program, was responsible for the scientific strategy and funding of research focused on characterizing and mitigating the effects of space radiation exposure on the central nervous system (CNS). During the past few of years, there have been two major changes that have affected the management of the science associated with the CNS risk. The first major change was the integration of several related risks: CNS (C), Behavioral medicine (B), and sensorimotor (S) to be managed as an integrated effort called CBS. CBS was formed to accelerate research on combined spaceflight stressors, specifically space radiation, microgravity, isolation, and confinement. CBS was managed by Human Factors and Behavioral Performance (HFBP) with support and inputs from Space Radiation as well as Human Health Countermeasures. Secondly, and more recently, the CNS risk was absorbed by the behavioral medicine risk currently also held by HFPB. As a result, the gaps associated with CNS were removed and aspects of them are represented in the BMED gaps (link). However, due to recent changes in element leadership, budget, and timeline, extensive restructuring of CBS is in progress. In addition, in an effort to harmonize datasets to be used in modelling efforts, an Animal Standardization TIM was held in June 2021 to standardize the type of behavioral and cognitive tasks as well as experimental set-ups. This presentation is an effort to communicate with the radiation research community concerning the strategy, management, and future of the former central nervous system risk and the role of the Space Radiation Element.

central nervous system↗
NASA NTRSDate not supplied

Lessons learned from replicating services for flood prediction and monitoring in Asia to the assessment of hurricane impacts in Central America

In October and November 2020, two dangerous back-to-back hurricanes, Eta and Iota, made landfall in Central America. The SERVIR program - a joint effort of NASA and the U.S. Agency for International Development, and whose motto is “connecting space to village” was able to leverage two tools originally developed for use in other regions for predicting and assessing the flood impacts of the hurricanes. The GEOGLoWS Streamflow Prediction tool - originally implemented in the Hindu Kush Himalayan region - was used for predicting potential flooding ahead of landfall by Eta and Iota. In conjunction, the Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) framework - originally developed along with SERVIR-Mekong - was used for post-event flood mapping, leveraging its ability to map floods in cloud-covered areas using synthetic aperture radar (SAR) imagery from the Copernicus program. Both tools were used in support of disaster coordination efforts being led by the Central American Regional Disaster Prevention Center (CEPREDENAC), in conjunction with its sister agency, the Regional Water Resources Committee (CRRH). The support provided to regional entities - and to their stakeholder national governments - served as an example of rapid generation of Earth observation products for disaster response. Feedback on those products was also provided, especially in terms of the implications of (i) calibration of predicted river volumes, and (ii) the latency of the input Earth observation imagery and attempts to map the floods’ maximum extents. An upcoming NASA DEVELOP project will also seek to strengthen the capability of CEPREDENAC and CRRH to apply HYDRAFloods for future extreme events. The application of the tools also provides a useful case study on capacity building, in terms of how Earth observation data and models can be replicated across regions.

Capacity building↗
NASA NTRS2023

Warming Overwhelms the Efficacy of Wet Conditions to Moderate Extreme Heat and Atmospheric Aridity Across the Central Plains

While the relationships between dry land surface conditions, heat, and aridity have been well-established, few studies have addressed whether global warming will affect the ability of wet conditions to moderate high temperatures and atmospheric aridity. Using Coupled Model Intercomparison Project Phase 6 models, we demonstrate that absolute changes in the monthly maximum temperature distribution during Central North American summers strongly outweigh the historical cooling effect of high precipitation and soil moisture conditions. Although wet conditions nearly always prevent concurrent extreme temperatures in the baseline period, these conditions are 40%–48% and 96%–98% less effective at 1 and 2° of global warming, respectively. However, high precipitation and soil moisture partially retain the ability to constrain concurrent high vapor pressure deficit conditions below historical thresholds at 1–2° of warming. Our results highlight the growing vulnerability of Central North America to warmer temperatures and drier atmospheric conditions, even during periods of high precipitation and soil moisture.

global warming↗
NASA NTRSDate not supplied

Warming Reduces the Efficacy of Wet Conditions to Moderate Extreme Heat and Atmospheric Aridity Across the Central Plains

In the literature, dry land surface conditions possess a well-established association with extreme heat and high atmospheric aridity, especially in regions that experience strong land-atmosphere feedbacks. However, few studies have examined whether global warming will impact the ability of wet conditions to constrain high temperatures and atmospheric aridity occurrences. Here we investigate how wet conditions, which we define using precipitation and soil moisture, constrain high temperature and high vapor pressure deficit during the warm season over the Central Plains in North America at different global warming levels (0-3 degrees K). Using a CMIP6 multi-model ensemble, we show that absolute changes in the maximum temperature distribution outweigh the historical cooling effect of high precipitation or soil moisture conditions, reducing the probability of non-extreme maximum temperatures under global warming. Strikingly, the conditional likelihood of non-extreme maximum temperatures falls from 97-98% at baseline conditions to 50-58% at 1 degree of global warming. Once 2 degrees of warming is reached, there is very little probability of constraining extreme maximum temperatures. On the other hand, high precipitation and high soil moisture are able to better retain the ability to constrain concurrent high vapor pressure deficit conditions – moving from 99% at baseline conditions to 81-91% at 1 degree of warming and 26-42% at 2 degrees of warming. With our results, we find that the extent of this retention is dependent on how individual models represent relative changes in the VPD distribution as temperatures warm. Overall, our results highlight the growing vulnerability of the Central North American region to warmer temperatures and drier atmospheric conditions, even during periods of high precipitation and soil moisture.

Extreme heat↗
DOE OSTI2026

Measurement of medium-induced acoplanarity in central Au-Au and 𝑝⁢𝑝 collisions at $\sqrt{s_{NN}}$ = 200 GeV using direct-photon + jet and 𝜋 0 + jet correlations

The STAR Collaboration reports measurements of acoplanarity using semi-inclusive distributions of charged-particle jets recoiling from direct photon and 𝜋 0 triggers, in central Au–Au and 𝑝⁢𝑝 collisions at $\sqrt{s_{NN}}$ = 200 GeV. Significant medium-induced acoplanarity broadening is observed for large but not small recoil jet resolution parameter, corresponding to recoil jet yield enhancement up to a factor of ≈ 20 for trigger-recoil azimuthal separation far from 𝜋. This phenomenology is indicative of the response of the quark-gluon plasma to excitation, but not the scattering of jets off of its quasiparticles. As a result, the measurements are not well described by current theoretical models which incorporate jet quenching.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Influence of plateau, slope, and valley on soil hydrology during the dry season in a Central Amazon old‐growth forest

Soil moisture regulates plant water supply and drought sensitivity in tropical forests, yet its vertical and topographic variation remains poorly characterized. We combined high-frequency time-domain reflectometry measurements from 5 to 100 cm across plateau, slope, and valley landforms at the Zona Florestal 2 research site north of Manaus, Central Amazonia, to quantify how soil moisture memory, timing of responses to rainfall, dry-down rates (τ), and soil–water depletion vary across these contrasting landforms. Landform-specific soil moisture calibration curves ensured accurate volumetric water content estimates in these highly weathered soils. During the 2023 dry-to-wet transition (August–November), soil moisture memory showed strong topographic contrasts, with valley profiles increasing from ∼47 h at 5 cm to ∼154 h at 100 cm, while plateaus exhibited higher near-surface persistence (∼124 h at 5 cm) but weaker memory at depth. Dry-down behavior reinforced these differences as valley soils exhibited τ values exceeding ∼200 h, more than double the characteristic τ of plateau soils (∼90 h). Rainfall–soil moisture correlations indicated immediate responses at shallow depths in valleys and progressively longer lags with depth on plateaus and slopes. These hydrologic patterns were mirrored in depletion profiles, which declined sharply below 30 cm on plateaus but remained high and sustained throughout the upper meter in slopes and valleys. Together, these findings provide the first depth-resolved field measurements of soil moisture memory, rainfall coupling, dry-down constants, and depletion dynamics across major upland landforms in Central Amazonia and offer clear observational benchmarks for improving land-surface and ecosystem model representations of soil–water processes.

Hillslope↗
DOE OSTI2024

Search for central exclusive production of top quark pairs in proton-proton collisions at $\sqrt{s}$ = 13 TeV with tagged protons

A search for the central exclusive production of top quark-antiquark pairs ($t\overline{t}$) is performed for the first time using proton-tagged events in proton-proton collisions at the LHC at a centre-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 29.4 fb -1 . The $t\overline{t}$ decay products are reconstructed using the central CMS detector, while forward protons are measured in the CMS-TOTEM precision proton spectrometer. An observed (expected) upper bound on the production cross section of 0.59 (1.14) pb is set at 95% confdence level, for collisions of protons with fractional momentum losses between 2 and 20%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantifying soil organic matter stock distribution and origin following over a century of maize-based cropping in the former tallgrass prairie region of central USA

Tallgrass prairie conversion to maize-based agriculture in central North America has resulted in substantial loss of soil organic carbon (SOC) in less than two centuries. However, evaluations of how management practices may mitigate SOC losses are generally limited in soil depth and/or duration, missing long-term SOC stock outcomes that manifest over timescales of decades or longer. To address this, we sampled soils in year 145 of the Morrow Plots experiment to (i) evaluate effects of crop rotation and fertility management on SOC stocks and (ii) distinguish prairie- versus maize-derived SOC after continuous maize cropping since 1876 using stable carbon isotope ( 13 C) natural abundance. Soil organic carbon stock by equivalent soil mass (ESM) was + 30.7 Mg C ha −1 (+31.7 %) higher under maize-oat-alfalfa than continuous maize, but similar between maize-soybean and continuous maize. NPK fertilization and manuring did not influence SOC stocks by ESM. Response of SOC stocks at 15 cm depth intervals to NPK fertilization varied by depth and crop rotation, with lower SOC stocks at 30–45 cm under continuous maize and maize-soybean. Maize-derived C ranged 19.5–59.6 % of SOC stock across depths, indicating the majority of SOC was still derived from tallgrass prairie even after 145 years of continuous maize cropping. Our results confirm the potential of diversified crop rotation for minimizing SOC losses relative to tallgrass prairie at the supracentennial scale, and highlight the importance of relic prairie soil organic matter for future crop production in central North America.

crop rotation↗
DOE OSTI2024

Characteristics of Precipitation and Mesoscale Convective Systems Over the Peruvian Central Andes in Multi 5‐Year Convection‐Permitting Simulations

Abstract Using the Weather Research and Forecasting model with two planetary boundary layer schemes, ACM2 and MYNN, convection‐permitting model (CPM) regional climate simulations were conducted for a 6‐year period, including a one‐year spin‐up period, at a 15‐km grid spacing covering entire South America and a nested convection‐permitting 3‐km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4‐km simulation covering South America produced by National Center for Atmospheric Research (NCAR), three gridded precipitation products, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and mesoscale convective systems (MCSs) in the Peruvian central Andes region. Results show that all km‐scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3‐km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4‐km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low‐level jet and terrain‐induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests model improvements and better model configurations for future regional climate projections.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗
DOE OSTI2025

Restoring Historic Forest Disturbance Frequency Would Partially Mitigate Droughts in the Central Sierra Nevada Mountains

Forest thinning and prescribed fire are expected to improve the climate resilience and water security of forests in the western U.S., but few studies have directly modeled the hydrological effects of multi-decadal landscape-scale forest disturbance. By updating a distributed process-based hydrological model (DHSVM) with vegetation maps from a distributed forest ecosystem model (LANDIS-II), we simulate the water resource impacts of forest management scenarios targeting partial or full restoration of the pre-colonial disturbance return interval in the central Sierra Nevada mountains. In a fully restored disturbance regime that includes fire, thinning, and insect mortality, reservoir inflow increases by 4%–9% total and 8%–14% in dry years. At sub-watershed scales (10–100 km2), thinning dense forests can increase streamflow by >20% in dry years. In a thinner forest, increased understory transpiration compensates for decreased overstory transpiration. Consequentially, 73% of streamflow gains are attributable to decreased overstory rain and snow interception loss. Thinner forests can increase headwater peak flows, but reservoir-scale peak flows are almost exclusively influenced by climate. Uncertainty in future precipitation causes high uncertainty in future water yield, but the additional water yield attributable to forest disturbance is about five times less sensitive to annual precipitation uncertainty. This partial decoupling of the streamflow disturbance response from annual precipitation makes disturbance especially valuable for water supply during dry years. Our study can increase confidence in the water resource benefits of restoring historic forest disturbance frequencies in the central Sierra Nevada mountains, and our modeling framework is widely applicable to other forested mountain landscapes.

Boardman, Eli N. [University of Nevada, Reno, NV (↗
DOE OSTI2026

Mapping Critical Vulnerabilities in Natural Gas Pipeline Systems through Network Centrality and GIS Analytics

Natural gas plays a central role in the US energy landscape, providing 43% of electricity generation in 2023. Its exclusive recovery ability on pipelines for transmission underscores the importance of understanding the disruption recovery ability of this infrastructure. This study employs a network-based analytical framework integrating geographic information systems (GIS) with multiple centrality measures—betweenness, closeness, degree, and eigenvector—to pinpoint key segments and evaluate the structural robustness of the national pipeline network. Pipelines are grouped by System ID and Operator ID to capture variations across organizational and physical structures. The analysis reveals uneven patterns of network influence, where certain pipelines function as critical connectors or dominant hubs. Spatial mapping highlights geographic dependencies and potential chokepoints, offering a clear view of where targeted risk prevention measures would be most effective. The findings provide practical guidance for prioritizing maintenance, enhancing system robustness, and mitigating risks to ensure a stable and secure energy supply. Future research will expand the framework to incorporate dynamic operational data and real-time network behavior.

Peterson, Steven [ORNL] (ORCID:0000000287672998)↗
DOE OSTI2025

Community composition and abundance of wild bees at row crop-grassland interfaces in west central Nebraska

Abstract Perennial mixed forb and grassland habitats are crucial to conservation of pollinators and connectivity of habitats in intensely farmed landscapes. This study aims to understand the effects of land use on the pollinator community by describing bee abundance, species richness and community composition in perennial conservation grasslands and adjacent annual row crops located in west central Nebraska. In 2022 and 2023, we collected and identified bees via sticky traps at 4 locations (center and edge of adjacent grasslands and crop fields) at 6 replicated sites. We collected 1,768 specimens from sticky traps, resulting in 70 species within 28 genera. Halictidae accounted for 84% of the specimens collected. Bee abundance was influenced by the simple effects of land use (grassland vs. crops), edge adjacency, and the month and year of collection. Differences in bee abundance within a collection date were found mostly in early 2022 (May and June) and late 2023 (September), when the crop center location was generally the lowest, with some evidence for spillover of bees from the grassland into the crop edge during the early summer months. Bee species richness was affected only by month and was not significantly different by land use and edge adjacency. Bee community composition overlapped across the 4 locations, although there were significant dissimilarities between crop fields and grasslands. Surveys of the plant community revealed very low abundance of blooming stems and plant taxonomic richness at crop locations for all sampling periods, while grassland locations were comparatively high and varied over time. Plant communities showed no overlap between crop field and grassland locations. Overall, we found that conservation grasslands, while not seeded specifically with pollinator-attractive forbs, provide diverse resources to support wild bee communities in west central Nebraska; crop edges may also provide non-plant resources such as nesting sites and irrigation water. Going forward, better understanding pollinator species composition and resource utilization relative to land use characteristics and drought conditions will allow for better tailoring of conservation efforts and management strategies in Nebraska and across the larger region.

Entomology↗