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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗
DOE OSTI2025

Hyperspectral leaf reflectance of grasses varies with evolutionary lineage more than with site

Abstract To predict ecological responses at broad environmental scales, grass species are commonly grouped into two broad functional types based on photosynthetic pathway. However, closely related species may have distinctive anatomical and physiological attributes that influence ecological responses, beyond those related to photosynthetic pathway alone. Hyperspectral leaf reflectance can provide an integrated measure of covarying leaf traits that may result from phylogenetic trait conservatism and/or environmental conditions. Understanding whether spectra‐trait relationships are lineage specific or reflect environmental variation across sites is necessary for using hyperspectral reflectance to predict plant responses to environmental changes across spatial scales. We measured hyperspectral leaf reflectance (400–2400 nm) and 12 structural, biochemical, and physiological leaf traits from five grass‐dominated sites spanning the Great Plains of North America. We assessed if variation in leaf reflectance spectra among grass species is explained more by evolutionary lineage (as captured by tribes or subfamilies), photosynthetic pathway (C 3 or C 4 ), or site differences. We then determined whether leaf spectra can be used to predict leaf traits within and across lineages. Our results using redundancy analysis ordination (RDA) show that grass tribe identity explained more variation in leaf spectra (adjusted R 2 = 0.12) than photosynthetic pathway, which explained little variation in leaf spectra (adjusted R 2 = 0.00). Furthermore, leaf reflectance from the same tribe across multiple sites was more similar than leaf reflectance from the same site across tribes (adjusted R 2 = 0.12 and 0.08, respectively). Across all sites and species, trait predictions based on spectra ranged considerably in predictive accuracies ( R 2 = 0.65 to <0.01), but R 2 was >0.80 for certain lineages and sites. The relationship between Vc max , a measure of photosynthetic capacity, and spectra was particularly promising. Chloridoideae, a lineage more common at drier sites, appears to have distinct spectra‐trait relationships compared with other lineages. Overall, our results show that evolutionary relatedness explains more variation in grass leaf spectra than photosynthetic pathway or site, but consideration of lineage‐ and site‐specific trait relationships is needed to interpret spectral variation across large environmental gradients.

Pau, Stephanie [Department of Geography University↗
DOE OSTI2023

Constraining long‐term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Significance of Aggregation Methods in Functional Group Modeling

The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic processes vary among species. An innovation in solving this challenge is the recognition that species can be lumped into “functional groups” based on metabolic similarity, and these functional groups can then be studied in computational models that simulate ecosystem function. Despite the vast resources devoted to functional group studies and the progress made by them, an important logical and biological question has not been formally addressed, “How do the groupings alter the results of modeling studies?” To what extent do modeling results depend on the choices made in aggregating taxa into functional groups. Here, we consider the effects of using different aggregation strategies in simulating the carbon dynamics of a deciduous forest. Understanding the impacts that aggregation strategy has on efforts to simulate regional-to-global-scale forest dynamics offers insights into both ecosystem regulation and model function and addresses this central problem in the study of carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Quantitative, trait-based microbial ecology to accurately model the impacts of nitrogen deposition on soil carbon cycling in the Anthropocene (Final Technical Report)

Atmospheric nitrogen pollution has altered fundamental soil processes, challenging our understanding of the extent to which soils will continue to sequester carbon and slow the pace of future environmental change. While most evidence shows that increases in soil nitrogen have enhanced carbon storage in temperate forests, it remains unclear whether these effects will persist as nitrogen pollution continues to decline. Moreover, there remains uncertainty as to why some forests gain more carbon in response to nitrogen pollution than others. At the heart of this knowledge gap is a failure to link nitrogen–induced shifts in microbial biodiversity with gains or losses in their functional ability to decompose, assimilate, and ultimately stabilize soil carbon. Given that this uncertainty impedes the ability of predictive models to project future soil carbon stocks, there is a critical need to determine how key microbial traits drive soil carbon responses to nitrogen pollution. As such the goals of this project were to: (1) Quantify variation in taxon–specific and community–level microbial traits across gradients in microbial community composition, mycorrhizal symbioses, and nitrogen availability. (2) Integrate empirical data into a novel predictive framework that enhances our ability to project the regional soil carbon consequences of historical nitrogen pollution in temperate forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The relationship between gene traits and transcription in soil microbial communities varies by environmental stimulus

Codon and nucleotide frequencies are known to relate to the rate of gene transcription, yet how these traits shape transcriptional profiles of soil microbial communities remains unclear. Here we test the prediction that functional genes with high codon optimization and energetically lower cost nucleotides (i.e., nucleotides requiring less adenosine triphosphate (ATP) for synthesis) have higher transcriptional expression in a soil microbial community. In laboratory incubations, we subjected an agricultural soil to two separate short-term environmental changes: labile carbon (glucose) addition or a sudden 30-min increase in temperature from 20 °C to 60 °C. Using the total genomic codon frequencies to predict preferred codon usage for each taxon, we then estimated codon optimization for each transcript. On the community level, we found a higher average level of codon optimization after the addition of glucose. Synonymous nucleotide composition in the transcript pool also shifted towards energetically cheaper nucleotides, favoring uracil (U) over adenine (A) and cytosine (C) over guanine (G). Similarly, we found that encoded amino acid usage shifted towards energetically cheaper amino acids in response to labile carbon. In contrast, in communities responding to heat shock, there were no significant differences in the averaged gene traits of expressed transcripts. We used metagenome-assembled-genomes to further examine the ability of gene traits to predict transcriptional responses within and between taxa. We found that traits of individual genes could not reliably predict the level of transcription of a gene within or between taxa—highlighting the limits of this approach. However, we did find that when traits were averaged across several related genes, codon optimization was able to predict levels of transcription in metabolic pathways associated with growth and nutrient uptake in response to glucose. Similar relationships were not observed in response to heat, or for functions associated with stress—such as genes associated with sporulation or heat shock. These results demonstrate that gene traits, such as codon usage, nucleotide selection, and amino acid selection, relate to the transcriptional expression of genes in soil microbial communities and suggests that these relationships may be dependent on both gene function and the specific type of environmental stimuli.

Biological and medical sciences↗
DOE OSTI2023

Antarctic evidence for an abrupt northward shift of the Southern Hemisphere westerlies at 32 ka BP

High-resolution ice core records from coastal Antarctica are particularly useful to inform our understanding of environmental changes and their drivers. Here, we present a decadally resolved record of sea-salt sodium (a proxy for open-ocean area) and non-sea salt calcium (a proxy for continental dust) from the well-dated Roosevelt Island Climate Evolution (RICE) core, focusing on the time period between 40–26 ka BP. The RICE dust record exhibits an abrupt shift towards a higher mean dust concentration at 32 ka BP. Investigating existing ice-core records, we find this shift is a prominent feature across Antarctica. We propose that this shift is linked to an equatorward displacement of Southern Hemisphere westerly winds. Subsequent to the wind shift, data suggest a weakening of Southern Ocean upwelling and a decline of atmospheric CO 2 to lower glacial values, hence making this shift an important glacial climate event with potentially important insights for future projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The recent evolutionary rescue of a staple crop depended on over half a century of global germplasm exchange

Rapid environmental change can lead to population extinction or evolutionary rescue. The global staple crop sorghum (Sorghum bicolor) has recently been threatened by a global outbreak of an aggressive new biotype of sugarcane aphid (SCA; Melanaphis sacchari). We characterized genomic signatures of adaptation in a Haitian breeding population that had rapidly adapted to SCA infestation, conducting evolutionary population genomics analyses on 296 Haitian lines versus 767 global accessions. Genome scans and geographic analyses suggest that SCA adaptation has been conferred by a globally rare East African allele of RMES1, which spread to breeding programs in Africa, Asia, and the Americas. De novo genome sequencing revealed potential causative variants at RMES1. Markers developed from the RMES1 sweep predicted resistance in eight independent commercial and public breeding programs. These findings demonstrate the value of evolutionary genomics to develop adaptive trait technology and highlight the benefits of global germplasm exchange to facilitate evolutionary rescue.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A novel construct for scaling groundwater–river interactions based on machine-guided hydromorphic classification

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. Predictive numerical models are needed to understand responses of river corridors to environmental change and to support sustainable watershed management. We posit that systematic hydromorphic classification provides a scaling construct that facilitates extrapolation of outputs from local-scale mechanistic models to reduced-order models applicable at reach and watershed scales. This in turn offers the potential to improve large-scale predictions of river corridor hydrobiogeochemical processes. Here we present a new machine-guided hydromorphic classification methodology that addresses the key requirements of this objective, and we demonstrate its application to a segment of the Columbia River in the northwestern United States. The resulting hydromorphic classes form spatially coherent and physically interpretable hydromorphic units that exhibit distinct behaviors in terms of distributions of subsurface residence times (a primary control on critical biogeochemical reactions). This approach forms the basis of ongoing research that is evaluating the formulation of reduced-order models and transferability of results to other river reaches and larger scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

New approaches for metabolomics by mass spectrometry

Small molecules constitute a large part of the world around us, including fossil and some renewable energy sources. Solar energy harvested by plants and bacteria is converted into energy rich small molecules on a massive scale. Some of the worst contaminants of the environment and compounds of interest for national security also fall in the category of small molecules. The development of large scale metabolomic analysis methods lags behind the state of the art established for genomics and proteomics. This is commonly attributed to the diversity of molecular classes included in a metabolome. Unlike nucleic acids and proteins, metabolites do not have standard building blocks, and, as a result, their molecular properties exhibit a wide spectrum. This impedes the development of dedicated separation and spectroscopic methods. Mass spectrometry (MS) is a strong contender in the quest for a quantitative analytical tool with extensive metabolite coverage. Although various MS-based techniques are emerging for metabolomics, many of these approaches include extensive sample preparation that make large scale studies resource intensive and slow. New ionization methods are redefining the range of analytical problems that can be solved using MS. This project developed new approaches for the direct analysis of small molecules in unprocessed samples, as well as pushed the limits of ultratrace analysis in volume limited complex samples. The projects resulted in techniques that enabled metabolomics investigations with enhanced molecular coverage, as well as the study of cellular response to stimuli on a single cell level. Effectively individual cells became reaction vessels, where we followed the response of a complex biological system to external perturbation. We established two new analytical platforms for the direct study of metabolic changes in cells and tissues following external perturbation. For this purpose we developed a novel technique, laser ablation electrospray ionization (LAESI), for metabolite profiling of functioning cells and tissues. The technique was based on microscopic sampling of biological specimens by mid-infrared laser ablation followed by electrospray ionization of the plume and MS analysis. The two main shortcomings of this technique had been limited specificity due to the lack of a separation step, and limited molecular coverage, especially for nonpolar chemical species. To improve specificity and the coverage of the metabolome, we implemented the LAESI ion source on a mass spectrometer with ion mobility separation (IMS). In this system, the gas phase ions produced by the LAESI source were first sorted according to their collisional cross sections in a mobility cell. These separated ion packets were then subjected to MS analysis. By combining the atmospheric pressure ionization with IMS, we improved the metabolite coverage. Further enhancement of the non-polar metabolite coverage resulted from the combination of laser ablation with vacuum UV irradiation of the ablation plume. Our results indicated that this new ionization modality provided improved detection for neutral and non-polar compounds. Based on rapid progress in photonics, we had introduced another novel ion source that utilized the interaction of a laser pulse with silicon nanopost arrays (NAPA). In these nanophotonic ion sources, the structural features were commensurate with the wavelength of the laser light. The enhanced interaction resulted in high ion yields. This ultrasensitive analytical platform enabled the MS analysis of single yeast cells. We extended these NAPA studies from yeast to other microorganisms, including green algae (Chlamydomonas reinhardtii) that captured energy from sunlight on a massive scale. Combining cellular perturbations, e.g., through environmental changes, with the newly developed single cell analysis methods enabled us to follow dynamic changes induced in the cells. In effect, we were able to use individual cells as a “laboratory,” and approached the long-standing goal of establishing a “lab-in-a-cell.” Model systems for these studies included cells of cyanobacteria (Anabaena), yeast (Saccharomyces cerevisiae), green algae (C. reinhardtii) and Arabidopsis thaliana.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Greening of the land surface in the world’s cold regions consistent with recent warming

Global ecosystem function is highly dependent on climate and atmospheric composition, yet ecosystem responses to environmental changes remain uncertain. Cold, high-latitude ecosystems in particular have experienced rapid warming, with poorly understood consequences. Here in this study, we use a satellite-observed proxy for vegetation cover—the fraction of absorbed photosynthetically active radiation—to identify a decline in the temperature limitation of vegetation in global ecosystems between 1982 and 2012. We quantify the spatial functional response of maximum annual vegetation cover to temperature and show that the observed temporal decline in temperature limitation is consistent with expectations based on observed recent warming. An ensemble of Earth system models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) mischaracterized the functional response to temperature, leading to a large overestimation of vegetation cover in cold regions. We identify a 16.4% decline in the area of vegetated land that is limited by temperature over the past three decades, and suggest an expected large decline in temperature limitation under future warming scenarios. Finally, this rapid observed and expected decline in temperature limitation highlights the need for an improved understanding of other limitations to vegetation growth in cold regions, such as soil characteristics, species migration, recruitment, establishment, competition and community dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (R T ) in 85 large cities across the conterminous United States for the period 2001–2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and R T was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in R T mainly occurred in cities in relatively cold regions with an annual mean temperature <17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban–rural difference in both SOS and R T was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in R T magnitude in urban areas. Furthermore, these findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Continental scale structuring of forest and soil diversity via functional traits

Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. In conclusion, our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Identification of circadian rhythms in Nannochloropsis species using bioluminescence reporter lines

Circadian clocks allow organisms to predict environmental changes caused by the rotation of the Earth. Although circadian rhythms are widespread among different taxa, the core components of circadian oscillators are not conserved and differ between bacteria, plants, animals and fungi. Stramenopiles are a large group of organisms in which circadian rhythms have been only poorly characterized and no clock components have been identified. In this work, we have investigated cell division and molecular rhythms in Nannochloropsis species. In the four strains tested, cell division occurred principally during the night period under diel conditions; however, these rhythms damped within 2–3 days after transfer to constant light. We developed firefly luciferase reporters for the long-term monitoring of in vivo transcriptional rhythms in two Nannochlropsis species, Nannochloropsis oceanica CCMP1779 and Nannochloropsis salina CCMP537. The reporter lines express anticipatory behavior under light/dark cycles and free-running bioluminescence rhythms with periods of ~21–31 h that damped within ~3–4 days under constant light. Using different entrainment regimes, we demonstrate that these rhythms are modulated by a circadian-type oscillator. In addition, the phase of free-running luminescence rhythms can be modulated pharmacologically using a CK1 ε/δ inhibitor, suggesting a role of this kinase in the Nannochloropsis clock. Finally, together with the molecular and genomic tools available for Nannochloropsis species, these reporter lines represent an excellent system for future studies on the molecular mechanisms of stramenopile circadian oscillators.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Improving the representation of hydrologic processes in Earth System Models

Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in the representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Comparative Genomics and Functional Analysis of Carbohydrate Utilization Networks in Unicyanobacterial Consortia Derived from Hypersaline Lake Microbial Mats

Hot Lake is a meromictic, hypersaline lake located in Washington state, USA. It harbors a phototrophic microbial mat community stable in dramatic seasonal environmental changes. The complexity of natural community hinders to analyze metabolic interactions between its members. To manage this obstacle, unicyanobacterial consortia (UCC) were sampled from the community and sequenced. UCC is a microbial community in which one cyanobacterium serves as the sole primary producer of carbon sources to several heterotrophic bacteria. Recently available metagenomes for two UCC revealed a shared set of 19 microbial operational taxonomic units (OTU), whose individual genomes were reconstructed by co‐assembly and abundance profile binning. We used this genomic data and a comparative genomics approach to infer carbohydrate utilization pathways and their transcription regulation. We scanned all UCC proteomes against the KEGG Orthology, Pfam, GO and SEED databases to reveal genes potentially involved in sugar utilization. Then we analyzed the genomic and functional contexts of gene loci encoding the obtained proteins and reconstructed the respective metabolic pathways and transcriptional regulons. As result, we observed catabolic pathways for 32 various carbohydrates and their derivatives. Distribution of the inferred catabolic pathways has highly mosaic structure across the UCC genomes. The largest number of pathways was observed in two representatives of the Halomonas genus (14–15 pathways) and one Rhodobacteriaceae sp. (15 pathways). In other UCC genomes, we found up to 10 carbohydrate utilization pathways per genome. However in 7 genomes we didn't observe any pathway. The most widely distributed pathways in UCC were the alpha‐glucosides and the DeLey‐Doudoroff galactose utilization pathways. Both were found in 7 genomes. Majority of pathways are distributed among 1–3 genomes. The reconstructed catabolic pathways were partially validated by phenotypic analyses of UCC community members that were isolated in a pure culture. In the Rhodobacteriaceae sp., we found a novel catabolic pathway that was proposed to be involved in mannoheptulose utilization. To our knowledge, the proposed mannoheptulose catabolic pathway is the first case of a pathway for heptose utilization and will require further experimental validation. The identified pathways are potentially regulated by local transcription factors (TFs) that are often co‐localized with the respective sugar catabolic gene loci. For 63 out of the 80 identified TFs we identified their cognate DNA binding motifs and reconstructed regulons using the bioinformatics approach. Support or Funding Information This research was supported by the Genomic Science Program (GSP), Office of Biological and Environmental Research (OBER), and U.S. Department of Energy (DOE) and is a contribution of the Pacific Northwest National Laboratory (PNNL) Foundational Scientific Focus Area.

Leyn, Semen A.↗
DOE OSTI2012

Integrated Genome-Based Studies of Shewanella Echophysiology (Final Scientific/Technical Report)

Shewanella oneidensis MR-1 is a motile, facultative γ-Proteobacterium with remarkable respiratory versatility; it can utilize a range of organic and inorganic compounds as terminal electronacceptors for anaerobic metabolism. The ability to effectively reduce nitrate, S0, polyvalent metals andradionuclides has established MR-1 as an important model dissimilatory metal-reducing microorganism for genome-based investigations of biogeochemical transformation of metals and radionuclides that are of concern to the U.S. Department of Energy (DOE) sites nationwide. Metal-reducing bacteria such as Shewanella also have a highly developed capacity for extracellular transfer of respiratory electrons to solid phase Fe and Mn oxides as well as directly to anode surfaces in microbial fuel cells. More broadly, Shewanellae are recognized free-living microorganisms and members of microbial communities involved in the decomposition of organic matter and the cycling of elements in aquatic and sedimentary systems. To function and compete in environments that are subject to spatial and temporal environmental change, Shewanella must be able to sense and respond to such changes and therefore require relatively robust sensing and regulation systems. The overall goal of this project is to apply the tools of genomics, leveraging the availability of genome sequence for 18 additional strains of Shewanella , to better understand the ecophysiology and speciation of respiratory-versatile members of this important genus. To understand these systems we propose to use genome-based approaches to investigate Shewanella as a system of integrated networks; first describing key cellular subsystems - those involved in signal transduction, regulation, and metabolism - then building towards understanding the function of whole cells and, eventually, cells within populations. As a general approach, this project will employ complimentary "top-down" - bioinformatics-based genome functional predictions, high-throughput expression analyses, and functional genomics approaches to uncover key genes as well as metabolic and regulatory networks. The "bottom-up" component employs more traditional approaches including genetics, physiology and biochemistry to test or verify predictions. This information will ultimately be linked to analyses of signal transduction and transcriptional regulatory systems and used to develop a linked model that will contribute to understanding the ecophysiology of Shewanella in redox stratified environments. A central component of this effort is the development of a data and knowledge integration environment that will allow investigators to query across the individual research domains, link to analysis applications, visualize data in a cell systems context, and produce new knowledge, while minimizing the effort, time and complexity to participating institutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The three major axes of terrestrial ecosystem function

The leaf economics spectrum and the global spectrum of plant forms and functions revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability. Here we derive a set of ecosystem functions from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗