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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment endpoints with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. In this work we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints. We used a publicly available aquatic ecosystem model AQUATOX that integrates environmental fate of chemicals and their impacts on food webs in aquatic environments. By simulating a range of exposure patterns, we illustrated how exposure to a hypothetical insecticide could affect aquatic species populations (e.g., recreational fish abundance) and environmental properties (e.g., water clarity) that would in turn affect delivery of ecosystem services. Different results were observed for different species of fish, thus the decision to manage the use of the insecticide for ecosystem services derived by anglers depends upon the favored species of fish. In our hypothetical shallow reservoir, water clarity was mostly driven by changes in food web dynamics, specifically the presence of zooplankton. In contrast to the complex response by fishing value, water clarity increased with reduced insecticide use, which produced a monotonic increase in value by waders and swimmers. Our research clearly showed the importance of considering nonlinear ecosystem feedbacks where the presence of insecticide changed the modeled food-web dynamics in unexpected ways. Our study introduces one of the main advantages of using ecological models for risk assessment, namely the ability to generalize to meaningful levels of organization and to facilitate quantitative comparisons among alternative scenarios and associated trade-offs among them while explicitly accounting for different groups of beneficiaries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Ecogenomics of virophages and their giant virus hosts assessed through time series metagenomics

Virophages are small viruses that co-infect eukaryotic cells alongside giant viruses (Mimiviridae) and hijack their machinery to replicate. While two types of virophages have been isolated, their genomic diversity and ecology remain largely unknown. Here we use time series metagenomics to identify and study the dynamics of 25 uncultivated virophage populations, 17 of which represented by complete or near-complete genomes, in two North American freshwater lakes. Taxonomic analysis suggests that these freshwater virophages represent at least three new candidate genera. Ecologically, virophage populations are repeatedly detected over years and evolutionary stable, yet their distinct abundance profiles and gene content suggest that virophage genera occupy different ecological niches. Co-occurrence analyses reveal 11 virophages strongly associated with uncultivated Mimiviridae, and three associated with eukaryotes among the Dinophyceae, Rhizaria, Alveolata, and Cryptophyceae groups. Together, these findings significantly augment virophage databases, help refine virophage taxonomy, and establish baseline ecological hypotheses and tools to study virophages in nature.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Annotation of the Corymbia terpene synthase gene family shows broad conservation but dynamic evolution of physical clusters relative to Eucalyptus

Terpenes are economically and ecologically important phytochemicals. Their synthesis is controlled by the terpene synthase (TPS) gene family, which is highly diversified throughout the plant kingdom. The plant family Myrtaceae are characterised by especially high terpene concentrations, and considerable variation in terpene profiles. Many Myrtaceae are grown commercially for terpene products including the eucalypts Corymbia and Eucalyptus. Eucalyptus grandis has the largest TPS gene family of plants currently sequenced, which is largely conserved in the closely related E. globulus. However, the TPS gene family has been well studied only in these two eucalypt species. The recent assembly of two Corymbia citriodora subsp. variegata genomes presents an opportunity to examine the conservation of this important gene family across more divergent eucalypt lineages. Manual annotation of the TPS gene family in C. citriodora subsp. variegata revealed a similar overall number, and relative subfamily representation, to that previously reported in E. grandis and E. globulus. Many of the TPS genes were in physical clusters that varied considerably between Eucalyptus and Corymbia, with several instances of translocation, expansion/contraction and loss. Notably, there was greater conservation in the subfamilies involved in primary metabolism than those involved in secondary metabolism, likely reflecting different selective constraints. The variation in cluster size within subfamilies and the broad conservation between the eucalypts in the face of this variation are discussed, highlighting the potential contribution of selection, concerted evolution and stochastic processes. Finally, these findings provide the foundation to better understand terpene evolution within the ecologically and economically important Myrtaceae.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2014

Maximum entropy models of ecosystem functioning

Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on the information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2015

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2017

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

Background: Viral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we used in silico mock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. Results: Tools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, and IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization methods specifically developed for metagenomes provided the best estimates. Conclusions: These simulations provide benchmarks for selecting analysis cut-offs and establish that an optimized sample-to-ecological-inference viromics pipeline is robust for making ecological inferences from natural viral communities. Continued development to better accessing RNA, rare, and/or diverse viral populations and improved reference viral genome availability will alleviate many of viromics remaining limitations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Measuring Cellular-scale Nutrient Distribution in Algal Biofilms with Synchrotron Confocal Infrared Microspectroscopy

The microscope and infrared spectrometer are two of the most useful tools for the study of biological materials, and their combined analytical power far exceeds the sum of the two. Performing molecular spectroscopy through a microscope superimposes chemical information onto the physical microstructure obtained from the optical microscope when visible and infrared information are collected under the same conditions. The instrument developments that enable current infrared microspectroscopic studies began with the introduction of the first research-grade infrared microscope, patented in 1989 (1). By 1993, published reports using this method to determine macroalgae (seaweed) cell-wall composition appeared (2-4). Since these initial reports, the use of infrared microspectroscopy (IMS) in microalgal (single cells or groups of cells) research has grown. Primarily, cultured algae have been used to hone IMS methodology and evaluate its capabilities in algal research (5-8). Studies involving natural, mixed species assemblages, which can utilize the spatial resolution potential of this technique fully are rare (9-11). For instance, in a recent review of IMS microalgal ecological research (12), only 3 of the 29 peer-reviewed publications investigated natural algal assemblages. Both thermal and synchrotron infrared sources provide a resolution capable of measuring individual algae in mixed species assemblages, and each has its advantages. For example, thermal source IMS is more accessible, allowing more samples to be analyzed than synchrotron IMS. However, synchrotron IMS with confocal masking provides superior resolution, which can be critical in isolating small or contiguous cells. Algal ecology is the study of the interaction between algae and their environment. Infrared microspectroscopy addresses a major logistical problem in this field, obtaining species-specific cellular biochemical information from natural, mixed-species assemblages (11,12). Benthic (bottom-dwelling) algae, for example, grow in a three-dimensional matrix (biofilm) composed of different cell sizes, shapes, and configurations. The optical and ecological challenge of studying algae is apparent from Figure 1, which shows a photomicrograph of algal chlorophyll fluorescence on a rock. Several issues make it difficult to obtain single species measurements with standard techniques: cell sizes can vary over an order of magnitude; species can occur as single cells, long filaments, or globular colonies; a number of different species can be found within a few square millimeters; and fluorescence can vary across cells (that is, the physiological state varies across cells). Synchrotron IMS is a tool that can be used to begin to overcome these spatially related challenges by giving a species- and location-specific measurement of an individual alga's relative chemical composition and distribution. This technique enables algal ecologists to focus on new, ecologically relevant questions such as what level (that is, cell, colony, and population) best defines a species' response to environmental change. For instance, many species occur as single cells and thus can be measured as individual organisms. However, the variety of growth forms and sizes can make it difficult to define the best unit to measure multicellular groups in terms of its functional role such as primary productivity (that is, carbon incorporation) and nutrient cycling. Understanding how individual algal species within a diverse community respond to environmental changes can help predict how changes in assemblage structure will impact overall assemblage function.

59 BASIC BIOLOGICAL SCIENCES↗