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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enabling Renewable Energy While Protecting Wildlife: An Ecological Risk-Based Approach to Wind Energy Development Using Ecosystem-Based Management Values

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.

17 WIND ENERGY↗
DOE OSTI2022

Integrating terrestrial scavenging ecology into contemporary wildlife conservation and management

Scavenging plays a vital role in maintaining ecosystem health and contributing to ecological functions; however, research in this sub-discipline of ecology is underutilized in developing and implementing wildlife conservation and management strategies. We provide an examination of the literature and recommend priorities for research where improved understanding of scavenging dynamics can facilitate the development and refinement of applied wildlife conservation and management strategies. Due to the application of scavenging research broadly within ecology, scavenging studies should be implemented for informing management decisions. In particular, a more direct link should be established between scavenging dynamics and applied management programs related to informing pharmaceutical delivery and population control through bait uptake for scavenging species, prevention of unintentional poisoning of nontarget scavenging species, the epidemiological role that scavenging species play in disease dynamics, estimating wildlife mortalities, nutrient transfer facilitated by scavenging activity, and conservation of imperiled facultative scavenging species. This commentary is intended to provide information on the paucity of data in scavenging research and present recommendations for further studies that can inform decisions in wildlife conservation and management. Additionally, we provide a framework for decision making when determining how to apply scavenging ecology research for management practices and policies. Due to the implications that scavenging species have on ecosystem health, and their overall global decline as a result of anthropic activities, it is imperative to advance studies in the field of scavenging ecology that can inform applied conservation and management programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Strontium isoscape of sub-Saharan Africa allows tracing origins of victims of the transatlantic slave trade

Abstract Strontium isotope ( 87 Sr/ 86 Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving 87 Sr/ 86 Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the 87 Sr/ 86 Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression. We demonstrate the efficacy of this Sr isoscape, in combination with other lines of evidence, to trace the African roots of individuals from historic slavery contexts, particularly those with highly radiogenic 87 Sr/ 86 Sr ratios uncommon in the African Diaspora. Our study provides an extensive African 87 Sr/ 86 Sr dataset which includes scientifically marginalized regions of Africa, with significant implications for the archaeology of the transatlantic slave trade, wildlife ecology, conservation, and forensics.

Science & Technology - Other Topics↗
DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗
DOE OSTI2022

Comparing western (Megascops kennicottii) and whiskered (M. trichopsis) screech-owl microbiomes in southern Arizona using a novel 16S rRNA sequencing method

Microbiomes are essential to a host’s physiology and health. Despite the overall importance of microbiomes to animal health, they remain understudied in wildlife. Microbiomes function as physical barriers to invading pathogens, and changes in the diversity or composition of microbes within a host may disrupt this barrier. In order to use microbiomes in wildlife ecology, knowledge of the natural variation within and among species is essential. We compare the diversity and composition of two avian species that share the same habitat and niche in our study area, the western screech-owl (Megascops kennicottii) and the whiskered screech-owl (M. trichopsis). We used a targeted 16S sequencing method to improve the taxonomic resolution of microbiomes. We found similar measures of alpha diversity between species and sample types (cloacal samples vs. fecal samples). However, there were significant differences in bacterial species richness among nestlings from different nest boxes, and the composition differed between the two bird species and among nestlings from different nest boxes. Western screech-owls had more variation in alpha diversity and composition and had fewer bacterial species in their core microbiome than whiskered screech-owls. Siblings are likely to yield similar findings for microbiomes; thus, sampling nestlings from different nests may be most informative for monitoring population-level changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Caught in headlights: Captive white-tailed deer responses to variations in vehicle lighting during imminent collision scenarios

Vehicle collisions with deer (Odocoileus spp.) cause billions of dollars in damages and injure thousands of drivers every year in the United States, and few mitigation methods have proven effective. However, recent research suggests that vehicle lighting might influence white-tailed deer (Odocoileus virginianus; hereafter, deer) responses to oncoming vehicles. Most new vehicles are manufactured with light emitting diode (LED) headlights which differ in total radiance and wavelength of light emitted compared to the previous industry standard of tungstenhalogen (halogen) headlights. Also, frontal vehicle illumination through rear-facing lighting has shown promise in enhancing deer responses to vehicles, but its effectiveness has not been tested under various headlight conditions (headlight type or intensity). As such, it remains unclear how these aspects of vehicle lighting affect deer responses to an approaching vehicle. We used 23 captive, wild-type deer to investigate how variations in vehicle lighting affect deer responses to an approaching vehicle at night, when most collisions occur. We released deer into a 95 m long, 3 m wide chute and approached them from the opposite end with an electric golf cart outfitted with two versions of stock 2017–2020 Ford Fusion headlights (LED and halogen) and a 51 cm rear-facing lightbar to test how vehicle lighting affected deer avoidance behaviors in an imminent, head-on collision scenario. Each deer received eight lighting treatments consisting of unique combinations of headlight type (LED vs. halogen), light intensity (low vs. high beam), and rear-facing lighting (lightbar off vs. on). We measured deer alert and flight behavior using infrared videography. We found that the halogen, high beam, lightbar off treatment had the greatest probability of evoking an alert response. Furthermore, when the lightbar was off, high beams appeared to increase alert probability for halogen headlights. Also, we found evidence that high beam, halogen headlights tend to increase alert probability over high beam, LED headlights, when the lighbar was off. We found no effect of our lighting treatments on deer alert distance, flight probability, or flight initiation distance. Across all behavioral responses, the random effect deer ID explained 0.86–9.19 × more variation than our lighting treatments, reflecting large differences in responses among deer. Overall, we found that vehicle lighting can impact deer behavior during an imminent, head-on collision scenario, although lighting was ineffective at increasing favorable flight behaviors. Future research should investigate how vehicle lighting treatments affect free-ranging, wild deer in a variety of real-world scenarios and at longer approach distances.

White-tailed deer (Odocoileus virginianus) Deer be↗
DOE OSTI2025

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗
DOE OSTI2025

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Small Mammal Trapping Survey for the Lawrence Livermore National Laboratory Site 300 and Corral Hollow Ecological Reserve

ECORP Consulting, Inc. conducted a nocturnal small mammal trapping survey within Lawrence Livermore National Laboratory’s (LLNL) Site 300 and the adjacent California Department of Fish and Wildlife (CDFW) Corral Hollow Ecological Reserve. Both sites are located east of the City of Livermore and southwest of the City of Tracy, Alameda and San Joaquin Counties, California (Figure 1-1). A small mammal trapping survey of the project site was conducted in 2002 in preparation for the 2005 LLNL Site-Wide Environmental Impact Statement (SWEIS; Jones & Stokes 2003). The San Joaquin pocket mouse (Perognathus inornatus) was the only special-status species (federal species of concern) captured on Site 300 during the study (West and Woollett 2003). However, since then P. inornatus was taxonomically split into separate subspecies and the pocket mouse species identified on Site 300 in 2002 is no longer considered a special-status species. The 2002 survey also captured woodrats, but identification of the subspecies was not possible. Further investigation was necessary to determine if the woodrat species on the project site was the federally listed (endangered) riparian (San Joaquin Valley) woodrat (Neotoma macrotis riparia [Formerly described as Neotoma fuscipes riparia]), the common Diablo Range woodrat (N. f. perplexa), or another form.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluating the potential for bird‐habitat models to support biodiversity‐friendly urban planning

Abstract Urban expansion poses a major threat to wildlife populations. Biodiversity‐friendly urban landscapes could deliver benefits for both wildlife and people, by incorporating conservation and ecosystem services objectives. Well‐designed urban developments could also soften the ecological impacts of urbanization. However, delivering urban landscapes that integrate biodiversity requirements effectively remains challenging. Ecological models, designed to predict wildlife population responses to alternative urban designs, could prove effective in supporting the creation of biodiversity‐friendly urban landscapes. Here, we combine national‐scale bird abundance data with high resolution, spatially explicit habitat data to characterize relationships between bird densities and urban landscape form in Britain. From these analyses and cross validation, we evaluate the potential for well‐parameterized, species‐specific models to be used to predict bird densities in novel or modified urban areas. Our analyses indicate that responses of bird abundance to urban habitat are species‐specific and complex, with few variables consistently affecting a large proportion of species. However, contiguous areas of greenspace within urban sites are preferential for accommodating breeding birds, compared to a more fragmented arrangement of multiple, small greenspace patches. In combination, the bird‐habitat relationships identified could successfully predict observed variation in abundance for most bird species considered. Further evaluation of habitat descriptor variables, spatial scales of species' habitat use and analytical modelling approaches may be needed to improve the predictive ability of bird‐habitat models for certain species, particularly waterbirds and those observed less frequently in urban areas. Synthesis and applications . We modelled breeding bird abundance in built‐up areas with respect to the characteristics and contexts of urban environments. While most variables were important for multiple species, responses overall were species‐specific, so simple assemblage metrics, like diversity, will not describe the variation in bird communities well. However, the results illustrate the potential of an evidence‐based, spatially explicit evaluation of urban development impacts on biodiversity, by predicting the consequences for bird numbers. Subject to verification of predictive ability, practitioners can apply the models to compare, for example, land‐sparing and sharing within developments, or to quantify the biodiversity requirements for effective offsetting. This would be facilitated by incorporation into an online tool allowing user‐determined input scenarios.

Plummer, Kate E.↗
DOE OSTI2026

Spatio-temporal dynamics of Hendra virus in Australia reveal stable maintenance of diverse viral clades among Pteropus bats

Hendra virus (HeV) was discovered in 1994 in Australia. Limited genomic data have hindered comprehensive understanding of HeV’s evolutionary dynamics. Here, in this work, we recovered 48 HeV genomes from bats and 9 from horses from Australia between 2016 and 2020, revealing four distinct clades. Each clade was distributed over a large spatial area with multiple clades co-circulating within a single bat roost on the same day and over consecutive years. The diversity and temporal stability of co-circulating clades suggest that viral dynamics are driven by episodic shedding of existing lineages maintained at the population level, rather than immune-driven strain-replacement dynamics. HeV isolates of different clades displayed variation in phenotypic properties but minimal antigenic differences. We provide an overview of evolutionary dynamics, phenotypic properties and assessment of countermeasures for HeV, and provide insights into the processes that maintain virus diversity in bats and influence the potential for viral emergence.

genetic variation↗
DOE OSTI2023

Screening Level Ecological Exposure Assessment Work Plan

This work plan is part of an effort to complete an updated evaluation of the potential for adverse effects from miscellaneous treatment unit emissions to potential ecological receptors within and surrounding Site 200. It will address potential pathways between air emissions from the Lawrence Livermore National Laboratory’s (LLNL) Decontamination and Waste Treatment Facility (DWTF), single emission stack, and ecological receptors (i.e., plants and wildlife) present onsite and within a one-mile radius from the DWTF stack. This work plan outlines the procedures by which data collected as part of the previous investigations will be evaluated to assess risks to ecological receptors. It presents the problem formulation, initial conceptual site models, methods for characterizing exposure, toxicity, and risks that will be used if a more detailed “baseline” ecological risk assessment (BERA) is required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using butterfly survey data to model habitat associations in urban developments

Abstract One approach for measuring the potential biodiversity in new urban construction projects is through ecological models that predict how wildlife will respond. For the United Kingdom, such models have only been developed for birds, but to maximise the extent to which models represent overall biodiversity, species from different indicator groups must be considered. Here, we assess this possibility for butterflies by combining citizen science survey data with high‐resolution digital maps. We derive detailed characteristics of urban landscapes around survey sites using previously established methods and quantify their relationship to counts of adults of 18 butterfly species in urban and peri‐urban settings. Higher butterfly counts were found when traversing urban sites with larger areas of semi‐natural grassland, other managed greenspaces and adjacent arable land. Most of the butterfly community were found to have negative relationships with highly built‐up or fragmented landscapes. We found high species‐specificity for different details of urban form, particularly in habitat elements such as gardens, vegetation around railways and grass verges. Policy implications . Improving biodiversity is now part of legislation governing new construction projects from England and Wales. However, predicting quantitative changes from hypothetical land‐use modifications remains challenging. Our models provide the foundation through which butterfly abundance could be integrated into an urban biodiversity assessment tool, providing species‐ and community‐level statistics to non‐specialists from the urban planning and design sector. This would allow them to hone configurations for built surfaces, private gardens, greenspaces and wildlife areas and assess their capacity to provide residents with the intended access to nature.

Cooper, Joseph E. J.↗
DOE OSTI2021

Carnivore Survey Results for the Lawrence Livermore National Laboratory Site 300

ECORP Consulting, Inc. conducted a suite of carnivore surveys at the Lawrence Livermore National Laboratory’s (LLNL) Experimental Test Site (Site 300; project site). The project site is located east of the City of Livermore and southwest of the City of Tracy, Alameda and San Joaquin Counties, California. Mesocarnivore surveys were conducted on the project site in 2002 in preparation for the 2005 LLNL Site-Wide Environmental Impact Statement (SWEIS; Clark et al. 2003). The 2002 surveys included a combination of spotlighting, camera stations, and scat detection dog surveys. Additional scat detection dog surveys for San Joaquin kit fox (Vulpes macrotis mutica) were performed on Site 300 and the adjacent California Department of Fish and Wildlife’s (CDFW) Corral Hollow Ecological Reserve in 2018 and 2020 (Woollett 2019, 2021). A variety of species, including American badger (Taxidea taxus), coyote (Canis latrans), and bobcat (Lynx rufus), were detected during the previous surveys; however, no San Joaquin kit fox or mountain lion (Puma concolor) were detected. In support of the preparation of the new SWEIS, ECORP performed carnivore surveys to document the carnivores and other animals present on Site 300, with a focus on determining if the federally listed (endangered) and state listed (threatened) San Joaquin kit fox, CDFW Species of Special Concern (SSC) American badger, and/or mountain lion are present on Site 300. American badgers are known to occur on the property and there have been a few sporadic sightings of mountain lions, but San Joaquin kit fox have not been documented on Site 300. Although mountain lion were not detected during the 2002 survey, it has been added as a focal species for this survey because the southern and central coast evolutionary significant units of mountain lions were recently advanced by CDFW as a Candidate species for listing as “threatened” under the California Endangered Species Act.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CORPSE model with litter decomposition parameters derived from the LIDET dataset

This is a version of the CORPSE model (Carbon, Organisms, Rhizosphere and Protection in the Soil Environment, Sulman et al. 2014) that uses litter decomposition parameters derived from a modified Monte Carlo simulation using the LIDET litter decomposition dataset (Long-term Intersite Decomposition Experiment Team, Harmon 2013). The code also includes the Baseline parameters, and the eight other best parameter sets identified in a modified Monte Carlo simulation. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of files:The folder "Input Files" contains one folder for each LIDET site with data necessary to run the model. Note that "(site)" in the filenames below indicates where the LIDET site code appears (see Table 1 for site codes). Data streams include: CORPSE_full_spinup_litter.csv, CORPSE_full_spinup_rhizo.csv, CORPSE_full_spinup_bulk.csv, litterbag_init_100g_6spp.csv: initial C and N (kg C or N/m2) pool values for each soil layer, the litterbag_init_100_6spp.csv file is for the litterbag layer and is the same file for all sites. All initial C and N files have the same columns (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 soilT (site) DOY274start.csv: Average daily soil temperature (oC) interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). soilT (site) DOY274start.csv: Average daily soil volumetric water content (VWC) scalar interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). litter production.csv: Average daily litter production values for each site, data sources listed in Table S3 of related publication. litter (site) CN.csv: C:N ratio for each species from LIDET dataset (Table 2, Harmon 2013). (site).csv: Table indicating number of observations for each species decomposed at each site. Instructions: Save the model code ("CORPSE_LIDET.R") and "Input Files" folder in the same folder. Also make a folder for the model output (e.g., "results_Baseline") in the same folder. Set the working directory (setwd) in the model code to the folder with the files saved in step #1. Select the parameter set to use for the litter and litterbag compartments, comment out all other parameter sets. Run code. Output will be saved in the folder made in step 1. Output destination can be changed as necessary in code section called "Running the model." Table 1 LIDET sites and site codes used in model files. Site Code - Site AND - H.J. Andrews Experimental Forest BNZ - Bonanza Creek Experimental Forest BSF - Blodgett Research Forest CDR - Cedar Creek Natural History Area CPR - Central Plains Experimental Range HBR - Hubbard Brook Experimental Forest HFR - Harvard Forest JUN - Juneau KBS - Kellogg Biological Station KNZ - Konza Prairie Research Natural Area NWT - Niwot Ridge/Green Lakes Valley OLY - Olympic National Park OLY Conifer forest SEV - Sevilleta National Wildlife Refuge SMR - Santa Margarita Ecological Reserve UFL - University of Florida VCR - Virginia Coast Reserve Table 2 LIDET species and species codes used in model files (6 common species). Species - Species Code Sugar maple (Acer saccharum) - ACSA Drypetes (Drypetes glauca) - DRGL Red pine (Pinus resinosa) - PIRE Chestnut oak (Quercus prinus) - QUPR Western redcedar (Thuja plicata) - THPL Wheat (Triticum aestivum) - TRAE References:Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957-974. https://doi.org/https://doi.org/10.1111/gcb.12031 Harmon, M. (2013). LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002. Long-Term Ecological Research. Forest Science Data Bank, Corvallis, OR. [Data set]. Accessed http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023. https://doi.org/10.6073/pasta/f35f56bea52d78b6a1ecf1952b4889c5. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014). Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4, 1099 - 1102. https://doi.org/10.1038/nclimate2436

Juice, Stephanie↗
DOE OSTI2024

Satellite-Based Assessment of Rocket Launch and Coastal Change Impacts on Cape Canaveral Barrier Island, Florida, USA

The Cape Canaveral Barrier Island, home to the National Aeronautics and Space Administration (NASA)’s Kennedy Space Center and the United States (U.S.) Space Force’s Cape Canaveral Space Force Station, is situated in a unique ecological transition zone that supports diverse wildlife. This study evaluates the recent changes in vegetation cover (2016–2023) and dune elevation (2007–2017) within the Cape Canaveral Barrier Island using high-resolution optical satellite and light detection and ranging (LiDAR) data. The study period was chosen to depict the time period of a recent increase in rocket launches. The study objectives include assessing changes in vegetation communities, identifying detectable impacts of liquid propellant launches on nearby vegetation, and evaluating dune elevation and tide level shifts near launchpads. The results indicate vegetation cover changes, including mangrove expansion in wetland areas and the conversion of coastal strands to denser scrubs and hardwood forests, which were likely influenced by mild winters and fire management. While detectable impacts of rocket launches on nearby vegetation were observed, they were less severe than those caused by solid rocket motors. Compounding challenges, such as rising tide levels, beach erosion, and wetland loss, potentially threaten the resilience of launch operations and the surrounding habitats. The volume and scale of launches continue to increase, and a balance between space exploration and ecological conservation is required in this biodiverse region. This study focuses on the assessment of barrier islands’ shorelines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Artificial Intelligence-Assisted Daytime Video Monitoring for Bird, Insect, and Other Wildlife Interactions with Photovoltaic Solar Energy Facilities

Studying bird, insect, and other wildlife interactions with photovoltaic (PV) solar energy facilities is difficult due to limited multi-season, multi-site data. Researchers can address such data gaps by combining passive monitoring and artificial intelligence (AI). As a part of the development of AI-enabled avian–solar monitoring software, we collected over 19,000 h of daytime videos at five PV sites across three U.S. regions between 2019 and 2024. We applied a moving object detection and tracking (MODT Version 1) AI model we developed earlier to 4373 h of the footage to extract moving objects in video frames, and human reviewers interpreted the model output and identified 68,646 bird, 25,968 insect, and 169 other wildlife instances to generate the training/validation dataset. We analyzed the data by site, region, and season, considering ground cover and landscapes. Songbirds were most common, with raptors as the next most frequent group. Most notably, no bird collisions were confirmed in our observations collected from the videos. Birds most often flew over or near panels, with the highest observations in the Midwest and Northeast (approximately 30 observations per hour on average) and fewer in the desert Southwest. Other behaviors included perching, foraging, and nesting. Bird abundance peaked during breeding and migration seasons. AI-assisted video monitoring proved effective for non-invasively studying flying wildlife at solar facilities to inform ecologically mindful energy development.

avian mortality↗
DOE OSTI2023

Racoons ( Procyon Lotor ) Show Higher Trypanosoma Cruzi Detection Rates than Virginia Opossums ( Didelphis Virginiana ) in South Carolina, USA

Chagas disease, a significant public health concern in the Americas, is caused by a protozoan parasite, Trypanosoma cruzi. The life cycle of T. cruzi involves kissing bugs (Triatoma spp.) functioning as vectors and mammalian species serving as hosts. Raccoons (Procyon lotor) and opossums (Didelphis virginiana) have been identified as important reservoir species in the life cycle of T. cruzi, but prevalence in both species in the southeastern US is currently understudied. We quantified T. cruzi prevalence in these two key reservoir species across our study area in South Carolina, US, and identified factors that may influence parasite detection. We collected whole blood from 183 raccoons and 126 opossums and used PCR to detect the presence of T. cruzi. We then used generalized linear models with parasite detection status as a binary response variable and predictor variables of land cover, distance to water, sex, season, and species. Our analysis indicated that raccoons experienced significantly higher parasite detection rates than Virginia opossums, with T. cruzi prevalence found to be 26.5% (95% confidence interval [CI], 20.0–33.8) in raccoons and 10.5% (95% CI, 5.51–17.5) in opossums. Altogether, our results concur with previous studies, in that T. cruzi is established in reservoir host populations in natural areas of the southeastern US.

60 APPLIED LIFE SCIENCES↗