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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy

Remote sensing of solar-induced chlorophyll fluorescence (SIF) offers potential to infer photosynthesis across scales and biomes. Many retrieval methods have been developed to estimate top-of-canopy SIF using ground-based spectroscopy. However, inconsistencies among methods may confound interpretation of SIF dynamics, eco-physiological/environmental drivers, and its relationship with photosynthesis. Using high temporal- and spectral resolution ground-based spectroscopy, we aimed to (1) evaluate performance of SIF retrieval methods under diverse sky conditions using continuous field measurements; (2) assess method sensitivity to fluctuating light, reflectance, and fluorescence emission spectra; and (3) inform users for optimal ground-based SIF retrieval. Analysis included field measurements from bi-hemispherical and hemispherical-conical systems and synthetic upwelling radiance constructed from measured downwelling radiance, simulated reflectance, and simulated fluorescence for benchmarking. Fraunhofer-based differential optical absorption spectroscopy (DOAS) and singular vector decomposition (SVD) retrievals exhibit convergent SIF-PAR relationships and diurnal consistency across different sky conditions, while O2A-based spectral fitting method (SFM), SVD, and modified Fraunhofer line discrimination (3FLD) exhibit divergent SIF-PAR relationships across sky conditions. We find that such behavior holds across system configurations, though hemispherical-conical systems diverge less across sky conditions. O 2 A retrieval accuracy, influenced by atmospheric distortion, improves with a narrower fitting window and when training SVD with temporally local spectra. This may impact SIF-photosynthesis relationships interpreted by previous studies using O 2 A-based retrievals with standard (759–767.76 nm) fitting windows. Fraunhofer-based retrievals resist atmospheric impacts but are noisier and more sensitive to assumed SIF spectral shape than O 2 A-based retrievals. We recommend SVD or SFM using reduced fitting window (759.5–761.5 nm) for robust far-red SIF retrievals across sky conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Impoverishing Roots Will Improve Wheat Yield and Profitability Through Increased Water and Nitrogen Use Efficiencies

We report that more than a 60% increase in crop production is required by the 2050's to feed a growing world population. Understanding how plant functional traits and field management affect crop yields has the potential to improve agricultural productivity, minimize economic and environmental losses, and maximize food security. We explored the influence of winter wheat root characteristics and management on winter wheat growth, yield, and profit using a mechanistic and well-tested ecosystem and crop model, ecosys. We applied and further tested ecosys at an agricultural farm growing winter wheat in Ardmore, Oklahoma, United States. The model accurately predicted observed shoot carbon (R 2 = 0.95), soil moisture (R 2 = 0.67), soil temperature (R 2 = 0.91), and yield (percent error = 17%). Numerical optimization experiments were conducted to explore potential improvements of winter wheat yield and profit by modifying root characteristics, including root radius and root:shoot carbon transfer conductance, and fertilizer inputs. Our results show the potential for simultaneously improving winter wheat yields and profits. The optimum conditions were found to be in the range of root radius between 0.1 and 0.3 mm, carbon transfer conductance between 0.004 and 0.01 h -1 , and the currently applied fertilizer rate of 112 kg ha -1 . Under these conditions, improvements in yields and profits of up to approximately 25% and 110%, respectively, were modeled compared to those under baseline root traits. These improvements were achieved by impoverishing root structures, thereby increasing nutrient allocation to grains. Our results also demonstrate and motivate model structures that integrate the complex network of plant physiology, soil nutrient biogeochemistry, hydrology, and management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Coastal Forest Seawater Exposure Increases Stem Methane Concentration

Methane (CH 4 ) exchange between trees and the atmosphere has recently emerged as an important, but poorly quantified process regulating global climate. The sources (soil and/or tree) and mechanisms driving the increase of CH 4 in trees and degassing to the atmosphere are inadequately understood, particularly for coastal forests facing increased exposure to seawater. Here, we investigated the eco-physiological relationship between tree stem wood density, soil and stem oxygen saturation (an indicator of redox state), soil and stem CH 4 concentrations, soil and stem carbon dioxide (CO 2 ) concentrations, and soil salinity in five forests along the United States coastline. We aim to evaluate the mechanisms underlying greenhouse gas (GHG) increase in trees and the influence of seawater exposure on stem CH 4 accumulation. Seawater exposure corresponded with decreased tree survival and increased tree stem methane. Tree stem wood density was significantly correlated with increased stem CH4 in seawater exposed gymnosperms, indicating that dying gymnosperm trees may accumulate higher levels of CH 4 in association with seawater flooding. Further, we found that significant differences in seawater exposed and unexposed gymnosperm tree populations are associated with increased soil and stem CH 4 and CO 2 , indicating that seawater exposure significantly impacts soil and stem greenhouse gas abundance. Our results provide new insight into the potential mechanisms driving tree CH 4 accumulation within gymnosperm coastal forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Will Anthropogenic Warming Increase Evapotranspiration? Examining Irrigation Water Demand Implications of Climate Change in California

Abstract Climate modeling studies and observations do not fully agree on the implications of anthropogenic warming for evapotranspiration (ET), a major component of the water cycle and driver of irrigation water demand. Here, we use California as a testbed to assess the ET impacts of changing atmospheric conditions induced by climate change on irrigated systems. Our analysis of irrigated agricultural and urban regions shows that warmer atmospheric temperatures have minimal implications for ET rates and irrigation water demands—about one percent change per degree Celsius warming (∼1% °C −1 ). By explicitly modeling irrigation, we control for the confounding effect of climate‐driven soil moisture changes and directly estimate water demand implications. Our attribution analysis of the drivers of ET response to global anthropogenic warming shows that as the atmospheric temperature and vapor pressure deficit depart from the ideal conditions for transpiration, regulation of stomata resistance by stressed vegetation almost completely offsets the expected increase in ET rates that would otherwise result from abiotic processes alone. We further show that anthropogenic warming of the atmosphere has minimal implications for mean relative humidity (<1.7% °C −1 ) and the surface available energy (<0.2% °C −1 ), which are critical drivers of ET. This study corroborates the growing evidence that plant physiological changes moderate the degree to which changes in potential ET are realized as actual ET.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Large Divergence in Tropical Hydrological Projections Caused by Model Spread in Vegetation Responses to Elevated CO 2

Increasing atmospheric CO 2 and associated global warming are expected to alter the global hydrological cycle, thereby posing widespread threats to freshwater availability. However, future hydrological projections differ greatly between models, particularly over the tropical regions. The large difference between model projections directly limits policy planning efforts, and the responsible modeling processes remain unclear. Here, we identify the primary processes accounting for model differences in tropical hydrological changes using multiple CO 2 sensitivity experiments in the Coupled Model Intercomparison Project. We show that differences in projected changes to tropical evapotranspiration, precipitation, and surface water availability mainly arise from model representations of vegetation cover and stomatal conductance responses to elevated CO 2 and associated changes in atmospheric moisture and circulation. Atmospheric responses to sea surface warming contribute additionally to the divergence in hydrological projections. Given the importance of vegetation responses to elevated CO 2 and associated atmosphere feedbacks, our results underscore the need to improve representations of the vegetation physiological response to rising CO 2 and its coupling to the atmosphere, to provide reliable tropical hydrological projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Olivine Dissolution in Simulated Lung and Gastric Fluid as an Analog to the Behavior of Lunar Particulate Matter Inside the Human Respiratory and Gastrointestinal Systems

With the Artemis III mission scheduled to land humans on the Moon in 2025, work must be done to understand the hazards lunar dust inhalation would pose to humans. In this study, San Carlos olivine was used as an analog of lunar olivine, a common component of lunar dust. Olivine was dissolved in a flow-through apparatus in both simulated lung fluid and 0.1 M HCl (simulated gastric fluid) over a period of approximately 2 weeks at physiological temperature, 37°C. Effluent samples were collected periodically and analyzed for pH, iron, silicon, and magnesium ion concentrations. The dissolution rate data derived from our measurements allow us to estimate that an inhaled 1.0 μm diameter olivine particle would take approximately 24 years to dissolve in the human lungs and approximately 3 weeks to dissolve in gastric fluid. Results revealed that inhaled olivine particles may generate the toxic chemical, hydroxyl radical, for up to 5–6 days in lung fluid. Olivine dissolved in 0.1 M HCl for 2 weeks transformed to an amorphous silica-rich solid plus the ferric iron oxy-hydroxide ferrihydrite. Olivine dissolved in simulated lung fluid shows no detectable change in composition or crystallinity. Equilibrium thermodynamic models indicate that olivine in the human lungs can precipitate secondary minerals with fibrous crystal structures that have the potential to induce detrimental health effects similar to asbestos exposure. Our work indicates that inhaled lunar dust containing olivine can settle in the human lungs for years and could induce long-term potential health effects like that of silicosis.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Designing an Observing System to Study the Surface Biology and Geology (SBG) of the Earth in the 2020s

Abstract Observations of planet Earth from space are a critical resource for science and society. Satellite measurements represent very large investments and United States (US) agencies organize their effort to maximize the return on that investment. The US National Research Council conducts a survey of Earth science and applications to prioritize observations for the coming decade. The most recent survey prioritized a visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager to meet a range of needs for studying Surface Biology and Geology (SBG). SBG will be the premier integrated observatory for observing the emerging impacts of climate change by characterizing the diversity of plant life and resolving chemical and physiological signatures. It will address wildfire risk, behavior, and recovery as well as responses to hazards such as oil spills, toxic minerals in minelands, harmful algal blooms, landslides, and other geological hazards. The SBG team analyzed needed instrument characteristics (spatial, temporal, and spectral resolutions, measurement uncertainty) and assessed the cost, mass, power, volume, and risk of different architectures. We present an overview of the Research and Applications trade‐study analysis of algorithms, calibration and validation needs, and societal applications with specifics of substudies detailed in other articles in this special collection. We provide a value framework to converge from hundreds down to three candidate architectures recommended for development. The analysis identified valuable opportunities for international collaboration to increase the revisit frequency, adding value for all partners, leading to a clear measurement strategy for an observing system architecture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300

The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Seeing the Disturbed Forest for the Trees: Remote Sensing Is Underutilized to Quantify Critical Zone Response to Unprecedented Disturbance

Understanding the severity and extent of near surface critical zone (CZ) disturbances and their ecosystem response is a pressing concern in the face of increasing human and natural disturbances. Predicting disturbance severity and recovery in a changing climate requires comprehensive understanding of ecosystem feedbacks among vegetation and the surrounding environment, including climate, hydrology, geomorphology, and biogeochemistry. Field surveys and satellite remote sensing have limited ability to effectively capture the spatial and temporal variability of disturbance and CZ properties. Technological advances in remote sensing using new sensors and new platforms have improved observations of changes in vegetation canopy structure and productivity; however, integrating measures of forest disturbance from various sensing platforms is complex. By connecting the potential for remote sensing technologies to observe different CZ disturbance vectors, we show that lower severity disturbance and slower vegetation recovery are more difficult to quantify. Case studies in montane forests from the western United States highlight new opportunities, including evaluating post-disturbance forest recovery at multiple scales, shedding light on understory vegetation regrowth, detecting specific physiological responses, and refining ecohydrological modeling. Learning from regional CZ disturbance case studies, we propose future directions to synthesize fragmented findings with (a) new data analysis using new or existing sensors, (b) data fusion across multiple sensors and platforms, (c) increasing the value of ground-based observations, (d) disturbance modeling, and (e) synthesis to improve understanding of disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Fusion of Multiple Models for Improving Gross Primary Production Estimation With Eddy Covariance Data Based on Machine Learning

Abstract Terrestrial gross primary production (GPP) represents the magnitude of CO 2 uptake through vegetation photosynthesis, and is a key variable for carbon cycles between the biosphere and atmosphere. Light use efficiency (LUE) models have been widely used to estimate GPP for its physiological mechanisms and availability of data acquisition and implementation, yet each individual GPP model has exhibited large uncertainties due to input errors and model structure, and further studies of systematic validation, comparison, and fusion of those models with eddy covariance (EC) site data across diverse ecosystem types are still needed in order to further improve GPP estimation. We here compared and fused five GPP models (VPM, EC‐LUE, GOL‐PEM, CHJ, and C‐Fix) across eight ecosystems based on FLUXNET2015 data set using the ensemble methods of Bayesian Model Averaging (BMA), Support Vector Machine (SVM), and Random Forest (RF) separately. Our results showed that for individual models, EC‐LUE gave a better performance to capture interannual variability of GPP than other models, followed by VPM and GLO‐PEM, while CHJ and C‐Fix were more limited in their estimation performance. We found RF and SVM were superior to BMA on merging individual models at various plant functional types (PFTs) and at the scale of individual sites. On the basis of individual models, the fusion methods of BMA, SVM, and RF were examined by a five‐fold cross validation for each ecosystem type, and each method successfully improved the average accuracy of estimation by 8%, 18%, and 19%, respectively.

Environmental Sciences & Ecology↗
DOE OSTI2023

Urban Versus Lake Impacts on Heat Stress and Its Disparities in a Shoreline City

Abstract Shoreline cities are influenced by both urban‐scale processes and land‐water interactions, with consequences on heat exposure and its disparities. Heat exposure studies over these cities have focused on air and skin temperature, even though moisture advection from water bodies can also modulate heat stress. Here, using an ensemble of model simulations covering Chicago, we find that Lake Michigan strongly reduces heat exposure (2.75°C reduction in maximum average air temperature in Chicago) and heat stress (maximum average wet bulb globe temperature reduced by 0.86°C) during the day, while urbanization enhances them at night (2.75 and 1.57°C increases in minimum average air and wet bulb globe temperature, respectively). We also demonstrate that urban and lake impacts on temperature (particularly skin temperature), including their extremes, and lake‐to‐land gradients, are stronger than the corresponding impacts on heat stress, partly due to humidity‐related feedback. Likewise, environmental disparities across community areas in Chicago seen for skin temperature are much higher (1.29°C increase for maximum average values per $10,000 higher median income per capita) than disparities in air temperature (0.50°C increase) and wet bulb globe temperature (0.23°C increase). The results call for consistent use of physiologically relevant heat exposure metrics to accurately capture the public health implications of urbanization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reparameterizing Litter Decomposition Using a Simplified Monte Carlo Method Improves Litter Decay Simulated by a Microbial Model and Alters Bioenergy Soil Carbon Estimates

Litter decomposition determines soil organic matter (SOM) formation and plant-available nutrient cycles. Therefore, accurate model representation of litter decomposition is critical to improving soil carbon (C) projections of bioenergy feedstocks. Soil C models that simulate microbial physiology (i.e., microbial models) are new to bioenergy agriculture, and their parameterization is often based on small datasets or manual calibration to reach benchmarks. Here, we reparameterized litter decomposition in a microbial soil C model (CORPSE - Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) using the continental-scale Long-term Inter-site Decomposition Experiment Team (LIDET) dataset which documents decomposition across a range of litter qualities over a decade. Here, we conducted a simplified Monte Carlo simulation that constrained parameter values to reduce computational costs. The LIDET-derived parameters improved modeled C and nitrogen (N) remaining, decomposition rates, and litter mean residence times as compared to Baseline parameters. We applied the LIDET litter decomposition parameters to a microbial bioenergy model (Fixation and Uptake of Nitrogen – Bioenergy Carbon, Rhizosphere, Organisms, and Protection) to examine soil C estimates generated by Baseline and LIDET parameters. LIDET parameters increased estimated soil C in bioenergy feedstocks, with even greater increases under elevated plant inputs (i.e., by increasing residue, N fertilization). This was due to the integrated effects of plant litter quantity, quality, and agricultural practices (tillage, fertilization). Collectively, we developed a simple framework for using large-scale datasets to inform the parameterization of microbial models that impacts projections of soil C for bioenergy feedstocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles With Implicit and Explicit Representations of Soil Microbial Activity

Abstract Nutrient limitation is widespread in terrestrial ecosystems. Accordingly, representations of nitrogen (N) limitation in land models typically dampen rates of terrestrial carbon (C) accrual, compared with C‐only simulations. These previous findings, however, rely on soil biogeochemical models that implicitly represent microbial activity and physiology. Here we present results from a biogeochemical model testbed that allows us to investigate how an explicit versus implicit representation of soil microbial activity, as represented in the MIcrobial‐MIneral Carbon Stabilization (MIMICS) and Carnegie‐Ames‐Stanford Approach (CASA) soil biogeochemical models, respectively, influence plant productivity, and terrestrial C and N fluxes at initialization and over the historical period. When forced with common boundary conditions, larger soil C pools simulated by the MIMICS model reflect longer inferred soil organic matter (SOM) turnover times than those simulated by CASA. At steady state, terrestrial ecosystems experience greater N limitation when using the MIMICS‐CN model, which also increases the inferred SOM turnover time. Over the historical period, however, warming‐induced acceleration of SOM decomposition over high latitude ecosystems increases rates of N mineralization in MIMICS‐CN. This reduces N limitation and results in faster rates of vegetation C accrual. Moreover, as SOM stoichiometry is an emergent property of MIMICS‐CN, we highlight opportunities to deepen understanding of sources of persistent SOM and explore its potential sensitivity to environmental change. Our findings underscore the need to improve understanding and representation of plant and microbial resource allocation and competition in land models that represent coupled biogeochemical cycles under global change scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Environmental stability impacts the differential sensitivity of marine microbiomes to increases in temperature and acidity

Ambient conditions shape microbiome responses to both short- and long-duration environment changes through processes including physiological acclimation, compositional shifts, and evolution. Here, we predict that microbial communities inhabiting locations with larger diel, episodic, and annual variability in temperature and pH should be less sensitive to shifts in these climate-change factors. To test this hypothesis, we compared responses of surface ocean microbes from more variable (nearshore) and more constant (offshore) sites to short-term factorial warming (+3 °C) and/or acidification (pH –0.3). In all cases, warming alone significantly altered microbial community composition, while acidification had a minor influence. Compared with nearshore microbes, warmed offshore microbiomes exhibited larger changes in community composition, phylotype abundances, respiration rates, and metatranscriptomes, suggesting increased sensitivity of microbes from the less-variable environment. Moreover, while warming increased respiration rates, offshore metatranscriptomes yielded evidence of thermal stress responses in protein synthesis, heat shock proteins, and regulation. Future oceans with warmer waters may enhance overall metabolic and biogeochemical rates, but they will host altered microbial communities, especially in relatively thermally stable regions of the oceans.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coral mucus rapidly induces chemokinesis and genome-wide transcriptional shifts toward early pathogenesis in a bacterial coral pathogen

Elevated seawater temperatures have contributed to the rise of coral disease mediated by bacterial pathogens, such as the globally distributed Vibrio coralliilyticus, which utilizes coral mucus as a chemical cue to locate stressed corals. However, the physiological events in the pathogens that follow their entry into the coral host environment remain unknown. Here, we present simultaneous measurements of the behavioral and transcriptional responses of V. coralliilyticus BAA-450 incubated in coral mucus. Video microscopy revealed a strong and rapid chemokinetic behavioral response by the pathogen, characterized by a two-fold increase in average swimming speed within 6 min of coral mucus exposure. RNA sequencing showed that this bacterial behavior was accompanied by an equally rapid differential expression of 53% of the genes in the V. coralliilyticus genome. Specifically, transcript abundance 10 min after mucus exposure showed upregulation of genes involved in quorum sensing, biofilm formation, and nutrient metabolism, and downregulation of flagella synthesis and chemotaxis genes. After 60 min, we observed upregulation of genes associated with virulence, including zinc metalloproteases responsible for causing coral tissue damage and algal symbiont photoinactivation, and secretion systems that may export toxins. Together, our results suggest that V. coralliilyticus employs a suite of behavioral and transcriptional responses to rapidly shift into a distinct infection mode within minutes of exposure to the coral microenvironment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sulfate differentially stimulates but is not respired by diverse anaerobic methanotrophic archaea

Abstract Sulfate-coupled anaerobic oxidation of methane (AOM) is a major methane sink in marine sediments. Multiple lineages of anaerobic methanotrophic archaea (ANME) often coexist in sediments and catalyze this process syntrophically with sulfate-reducing bacteria (SRB), but the potential differences in ANME ecophysiology and mechanisms of syntrophy remain unresolved. A humic acid analog, anthraquinone 2,6-disulfonate (AQDS), could decouple archaeal methanotrophy from bacterial sulfate reduction and serve as the terminal electron acceptor for AOM (AQDS-coupled AOM). Here in sediment microcosm experiments, we examined variations in physiological response between two co-occurring ANME-2 families (ANME-2a and ANME-2c) and tested the hypothesis of sulfate respiration by ANME-2. Sulfate concentrations as low as 100 µM increased AQDS-coupled AOM nearly 2-fold matching the rates of sulfate-coupled AOM. However, the SRB partners remained inactive in microcosms with sulfate and AQDS and neither ANME-2 families respired sulfate, as shown by their cellular sulfur contents and anabolic activities measured using nanoscale secondary ion mass spectrometry. ANME-2a anabolic activity was significantly higher than ANME-2c, suggesting that ANME-2a was primarily responsible for the observed sulfate stimulation of AQDS-coupled AOM. Comparative transcriptomics showed significant upregulation of ANME-2a transcripts linked to multiple ABC transporters and downregulation of central carbon metabolism during AQDS-coupled AOM compared to sulfate-coupled AOM. Surprisingly, genes involved in sulfur anabolism were not differentially expressed during AQDS-coupled AOM with and without sulfate amendment. Collectively, this data indicates that ANME-2 archaea are incapable of respiring sulfate, but sulfate availability differentially stimulates the growth and AOM activity of different ANME lineages.

59 BASIC BIOLOGICAL SCIENCES↗