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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Remote Sensing the Patterns of Vector-borne Disease in El Nino and non-El Nino Years

The relationship between El Nino and non-El Nino and the patterns of vector-borne disease can be viewed at a variety of spatial and temporal scales. At one extreme are long term predictions of changing precipitation and temperature patterns at continental and global scales. At the opposite extreme are the local or site specific ecological changes associated with the long term events. In order to understand and address the human health consequences of El Nino events, especially the patterns of vector-borne diseases, it is necessary to combine both scales of observation. At a local or regional scale the patterns of vector-borne diseases are determined by temperature, precipitation, and habitat availability. These factors, as well as disease incidence can be altered by El Nino events. Remote sensing data such as that acquired by the NOAA AVHRR and Landsat TM sensors can be used to characterize and monitor changing ecological conditions and therefore predict vector-borne disease patterns. The authors present the results of preliminary work on the analysis of historical AVHRR and TM data acquired during El Nino and nonfatal Nino years to characterize ecological conditions in Peru on a monthly basis. This information will then be combined with disease data to determine the relationship between changes in ecological conditions and disease incidence. Our goal is to produce a sequence of remotely sensed images which can be used to show the ecological and disease patterns associated with long term El Nino events and predictions.

Wood, B. L.↗
DOE OSTI2023

Quantifying the local adaptive landscape of a nascent bacterial community

Abstract The fitness effects of all possible mutations available to an organism largely shape the dynamics of evolutionary adaptation. Yet, whether and how this adaptive landscape changes over evolutionary times, especially upon ecological diversification and changes in community composition, remains poorly understood. We sought to fill this gap by analyzing a stable community of two closely related ecotypes (“L” and “S”) shortly after they emerged within the E. coli Long-Term Evolution Experiment (LTEE). We engineered genome-wide barcoded transposon libraries to measure the invasion fitness effects of all possible gene knockouts in the coexisting strains as well as their ancestor, for many different, ecologically relevant conditions. We find consistent statistical patterns of fitness effect variation across both genetic background and community composition, despite the idiosyncratic behavior of individual knockouts. Additionally, fitness effects are correlated with evolutionary outcomes for a number of conditions, possibly revealing shifting patterns of adaptation. Together, our results reveal how ecological and epistatic effects combine to shape the adaptive landscape in a nascent ecological community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predator mass mortality events restructure food webs through trophic decoupling

Predators have a key role in structuring ecosystems. However, predator loss is accelerating globally, and predator mass-mortality events (MMEs)—rapid large-scale die-offs—are now emblematic of the Anthropocene epoch. Owing to their rare and unpredictable nature, we lack an understanding of how MMEs immediately impact ecosystems. Past predator-removal studies may be insufficient to understand the ecological consequences of MMEs because, in nature, dead predators decompose in situ and generate a resource pulse, which could alter ensuing ecosystem dynamics by temporarily enhancing productivity. Here we experimentally induce MMEs in tritrophic, freshwater lake food webs and report ecological dynamics that are distinct from predator losses or resource pulses alone, but that can be predicted from theory. MMEs led to the proliferation of diverse consumer and producer communities resulting from weakened top-down predator control and stronger bottom-up effects through predator decomposition. In contrast to predator removals alone, enhanced primary production after MMEs dampened the consumer community response. As a consequence, MMEs generated biomass dynamics that were most similar to those of undisturbed systems, indicating that they may be cryptic disturbances in nature. These biomass dynamics led to trophic decoupling, whereby the indirect beneficial effects of predators on primary producers are lost and later materialize as direct bottom-up effects that stimulate primary production amid intensified herbivory. Furthermore, these results reveal ecological signatures of MMEs and demonstrate the feasibility of forecasting novel ecological dynamics arising with intensifying global change.

Food webs↗
DOE OSTI2024

Landscape fragmentation overturns classical metapopulation thinking

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally (“residents”) were often more resilient to fragmentation than long-ranging “migrants.” This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Convergence and divergence in science and practice of urban and rural forest restoration

Forest restoration has never been higher on policymakers' agendas. Complex and multi-dimensional arrangements across the urban–rural continuum challenge restorationists and require integrative approaches to strengthen environmental protection and increase restoration outcomes. It remains unclear if urban and rural forest restoration are moving towards or away from each other in practice and research, and whether comparing research outcomes can help stakeholders to gain a clearer understanding of the interconnectedness between the two fields. This study aims to identify the challenges and opportunities for enhancing forest restoration in both urban and rural systems by reviewing the scientific evidence, engaging with key stakeholders and using an urban–rural forest restoration framework. Using the Society for Ecological Restoration's International Principles as discussion topics, we highlight aspects of convergence and divergence between the two fields to broaden our understanding of forest restoration and promote integrative management approaches to address future forest conditions. Our findings reveal that urban and rural forest restoration have convergent and divergent aspects. We emphasise the importance of tailoring goals and objectives to specific contexts and the need to design different institutions and incentives based on the social and ecological needs and goals of stakeholders in different regions. Here we discuss the challenges of achieving high levels of ecological restoration and the need to go beyond traditional ecology to plan, implement, monitor, and adaptively manage restored forests. We suggest that rivers and watersheds could serve as a common ground linking rural and urban landscapes and that forest restoration could interact with other environmental protection measures. We note the potential for expanding the creative vision associated with increasing tree-containing environments in cities to generate more diverse and resilient forest restoration outcomes in rural settings. This study underscores the value of integrative management approaches in addressing future forest conditions across the urban–rural continuum. Our framework provides valuable insights for policymakers, researchers, and decision-makers to advance the field of forest restoration and address the challenges of restoration across the urban–rural continuum. The rural–urban interface serves as a convergence point for forest restoration, and both urban and rural fields can benefit from each other's expertise.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparative Genomic Analyses of Cellulolytic Machinery Reveal Two Nutritional Strategies of Marine Labyrinthulomycetes Protists

Labyrinthulomycetes are a group of ubiquitous and diverse unicellular Stramenopiles and have long been known for their vital role in ocean carbon cycling. However, their ecological function from the perspective of organic matter degradation remains poorly understood. This study reports high-quality genomes of two newly isolated Labyrinthulomycetes strains, namely, Botryochytrium sp. strain S-28 and Oblongichytrium sp. strain S-429, and provides molecular analysis of their ecological functions using comparative genomics and a biochemical assay. Our results suggest that Labyrinthulomycetes may occupy multiple ecological niches in marine ecosystems because of the significant differences in gene function among different genera. Certain strains could degrade wheat bran independently by secreting cellulase. The key glycoside hydrolase families (GH1, GH5, and GH9) related to cellulase and the functional domains of carbohydrate-active enzymes (CAZymes) were more enriched in their genomes. This group can actively participate in marine biochemical cycles as decomposers. In contrast, other strains that could not produce cellulase may thrive as “leftover scavengers” and act as a source of nutrients to the higher-trophic-level plankton. In addition, our findings emphasize the dual roles of endoglucanase, acting as both exo- and endoglucanases, in the process of cellulose degradation. Using genomic, biochemical, and phylogenetic analyses, our study provides a broader insight into the nutritional patterns and ecological functions of Labyrinthulomycetes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

CHESS 2025: Field-collected vegetation attributes and site photos

This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Samples were collected in the field using tablet computers and digital forms, with target data differing by sample type (individual trees, individual shrubs, or 1-meter square plots of meadow and subshrub vegetation). Field samples were collected within 72 hours of airborne data collection using the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. Remote sensing data for the project is available on ESS-DIVE (DOI and citation to be added upon publication). Field data collected included canopy height and per-species horizontal proportional cover for meadow plots, species identity and height information for shrubs, as well as species identity, height, diameter at breast height, and health assessment information for trees. Photos of the focal site and surrounding landscape were taken for all sampling sites and are included in this archive. Green leaves or needles were collected for plant trait and foliar chemistry analysis. This data is archived separately (DOI and citation to be added upon publication). High-precision geospatial data for each sample (crown perimeter polygons for trees and shrubs, plot boundaries for meadow plots) is available here (Henderson et al., 2026). Field and remote sensing protocols largely followed those of a previous field and airborne imaging campaign performed in 2018 (described in Chadwick et al. 2020). Field data from the 2018 campaign can be found here (Chadwick et al., 2020 doi:10.15485/1618130). Because different field measurements were taken for meadow, shrub, and tree sites, data from these three sample types are archived as separate tables (chess_meadow_site_cleaned.csv, chess_shrub_site_cleaned.csv, chess_tree_site_cleaned.csv). Meadow proportional cover data is stored in a separate table (chess_meadow_cover_cleaned.csv). Taxonomy was treated identically between sample types, and the dataset shares a common set of voucher specimens (chess_voucher_IDs_cleaned.csv), as well as a single species list (chess_species_list_cleaned.csv). All taxonomic determinations were performed to the species level, and adhere to the Global Biodiversity Information Facility (GBIF) backbone taxonomy as of January 10th, 2026 (GBIF Secretariat 2023). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

CHESS 2025: Crown polygons and extracted reflectance for field sampling sites

This dataset contains (1) crown polygons for each tree, meadow, and shrub site sampled in the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS) campaign (in geojson format, .geojson) and (2) extracted reflectance, uncertainty, and shade estimates for each crown polygon from the 2018 National Ecological Observatory Network (NEON) and 2025 CHESS campaigns. (in CSV format, .csv). Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). Crown polygons were manually delineated for each site in the 2025 campaign using a combination of field-collected GPS data (doi:10.15485/3022418), RGB (red, green, blue) and false color reflectance mosaics (doi:10.15485/3013535), and LiDAR-derived (Light Detection and Ranging) canopy height (CHM) and digital surface (DSM) models (DOI and citation to be added upon publication). Where there was misalignment between the spectrometer- and LiDAR-derived data products, polygons prioritized alignment with the spectrometer-derived data products. Polygons were delineated conservatively to only select pixels representative of vegetation samples collected in the field. Crown polygons for 2018 are published at (doi:10.15485/1618130) and were developed using the same protocol. For each polygon, all pixels from all flightlines were extracted where the pixel centroid was contained within the polygon. For each pixel, we extracted the surface reflectance, uncertainty, and shade estimates. Details on the extracted datasets are available at (doi:10.15485/3013527, doi:10.15485/3013535). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

CHESS 2025: Post-survey report for 2025 NEON AOP Assignable Asset collection of East River and Washington Gulch, Almont and Upper Taylor watersheds at Crested Butte, CO

This report contains details of the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) Research Support Services (RSS) Assignable Asset (AA) flights of the East River, Almont and Upper Taylor watersheds near Crested Butte, CO, June–July 2025. The Rocky Mountain Biological Laboratory (RMBL) contracted the NEON AOP AA flights to observe watersheds of interest near Crested Butte with remotely sensed data including high resolution LiDAR, imaging spectroscopy, and high-resolution camera imagery. The report includes a summary of the acquired flight lines over the planned survey areas, results of calibration flights, and results of the acquired data. The report details how the AOP has met the contracted delivery requirements in terms of the data delivered, quality of the data, and describes issues that resulted in data degradation or data loss. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Experimentally determined traits shape bacterial community composition one and five years following wildfire

Abstract Wildfires represent major ecological disturbances, burning 2–3% of Earth’s terrestrial area each year with sometimes drastic effects above- and belowground. Soil bacteria offer an ideal, yet understudied system within which to explore fundamental principles of fire ecology. To understand how wildfires restructure soil bacterial communities and alter their functioning, we sought to translate aboveground fire ecology to belowground systems by determining which microbial traits are important post-fire and whether changes in bacterial communities affect carbon cycling. We employed an uncommon approach to assigning bacterial traits, by first running three laboratory experiments to directly determine which microbes survive fires, grow quickly post-fire and/or thrive in the post-fire environment, while tracking CO 2 emissions. We then quantified the abundance of taxa assigned to each trait in a large field dataset of soils one and five years after wildfires in the boreal forest of northern Canada. We found that fast-growing bacteria rapidly dominate post-fire soils but return to pre-burn relative abundances by five years post-fire. Although both fire survival and affinity for the post-fire environment were statistically significant predictors of post-fire community composition, neither are particularly influential. Our results from the incubation trials indicate that soil carbon fluxes post-wildfire are not likely limited by microbial communities, suggesting strong functional resilience. From these findings, we offer a traits-based framework of bacterial responses to wildfire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A primer on forest structure measurement with lidar for ecologists

Light detection and ranging (lidar) technology has fundamentally advanced the way we measure forest structure, facilitating new insights into ecological processes. Lidar for forest ecology applications is deployed on multiple types of platforms that operate from the ground, air, or space, and each has associated strengths and limitations. Ideally, the choice of what kind of lidar to use in a particular study should be guided by the ecological question of interest; however, practical considerations of cost, data availability, and processing tools can be equally important. This synthesis is a practical introduction to how different lidar platforms characterize forest structure (e.g., tree size/location, wood volume, branching structure, aboveground biomass, leaf properties), designed for a general audience of ecologists (not remote sensing scientists) seeking an accessible introduction to the use of lidar. We also provide examples of novel ecological insights from recent lidar research and describe current limitations and areas of expected improvement. Last, we include an appendix of data collected from terrestrial, mobile, unoccupied aerial system, airplane, and satellite lidar platforms within a common temperate forest area, with associated code to allow new lidar users to visualize and manipulate data in R.

Cushman, KC [ORNL] (ORCID:0000000234641151)↗
DOE OSTI2023

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Exploring viral particle, soil, and extraction buffer physicochemical characteristics and their impacts on extractable viral communities

Viruses are expected to be pivotal members of soil ecosystems, and recent advances in viral size fraction metagenomic (viromic) approaches have improved our ability to interrogate soil viral ecology. However, viromics relies on extraction buffers to effectively desorb viral particles from the soil matrix for downstream analysis, and viral extraction efficiency could be affected by the interplay between viral particles, soils, and extraction buffer chemistry. Here, we investigated whether extraction buffer chemistry affected extractable viral community composition measured by viromics from different soil types, for both biological (samples collected 1 m apart) and technical (subsamples from the same soil homogenate) replicates. We investigated pH manipulation of protein-supplemented phosphate-buffered saline buffer (PPBS, pHs 4.5, 5.5, 6.5, and 7.5) on forest, grassland and wetland soils that exhibited different soil edaphic properties, and we tested different buffer chemistries (PPBS, Carbonated Buffer, Glycine, and Saline Magnesium) on just the wetland soil. Spatial distance (i.e., biological replicate) was the primary driver of extractable viral community composition across all buffers and soils tested. Differences in viral community composition according to extraction buffer properties were only observed in the grassland technical replicates at PPBS buffer pH 4.5, and in both the wetland technical and biological replicates treated with different buffer chemistries, but the effects of buffer chemistry were secondary to spatial distance in the biological replicates. The lack of buffering capacity in the grassland soil technical replicates likely increased sorption of viral particles at pH 4.5, but neither protein composition nor isoelectric point explained this phenomenon. In conclusion, given that most soil viral ecological studies to date include sample collection over distances much farther apart than the 1-m distances considered here, results suggest that extraction buffer chemistry is likely of much lower importance than ecological considerations, such as spatial distance, in the design of future soil viral ecological investigations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Stoichiometric Ecotoxicology for a Multisubstance World

Nutritional and contaminant stressors influence organismal physiology, trophic interactions, community structure, and ecosystem-level processes; however, the interactions between toxicity and elemental imbalance in food resources have been examined in only a few ecotoxicity studies. Integrating well-developed ecological theories that cross all levels of biological organization can enhance our understanding of ecotoxicology. In the present article, we underline the opportunity to couple concepts and approaches used in the theory of ecological stoichiometry (ES) to ask ecotoxicological questions and introduce stoichiometric ecotoxicology, a subfield in ecology that examines how contaminant stress, nutrient supply, and elemental constraints interact throughout all levels of biological organization. This conceptual framework unifying ecotoxicology with ES offers potential for both empirical and theoretical studies to deepen our mechanistic understanding of the adverse outcomes of chemicals across ecological scales and improve the predictive powers of ecotoxicology.

60 APPLIED LIFE SCIENCES↗