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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Signaling from below: rodents select for deeper fruiting truffles with stronger volatile emissions

Many plant and fungal species use volatile organic compounds (VOCs) as chemical signals to convey information about the location or quality of their fruits or fruiting bodies to animal dispersers. Identifying the environmental factors and biotic interactions that shape fruit selection by animals is key to understanding the evolutionary processes that underpin chemical signaling. Using four Elaphomyces truffle species, we explored the role of fruiting depth, VOC emissions, and protein content in selection by five rodent species. We used stable isotope analysis of nitrogen (δ15N) in truffles to estimate fruiting depth, proton-transfer-reaction mass spectrometry to determine volatile emission composition, and nitrogen concentrations to calculate digestible protein of truffles. We coupled field surveys of truffle availability with truffle spore loads in rodent scat to determine selection by rodents. Despite presumably easier access to the shallow fruiting species, E. americanus (0.5-cm depth) and E. verruculosus (2.5-cm depth), most rodents selected for truffles fruiting deeper in the soil, E. macrosporus (4.1-cm depth) and E. bartlettii (5.0-cm depth). The deeper fruiting species had distinct VOC profiles and produced significantly higher quantities of odiferous compounds. Myodes gapperi (southern red-backed vole), a fungal specialist, also selected for truffles with high levels of digestible protein, E. verruculosus and E. macrosporus. Our results highlight the importance of chemical signals in truffle selection by rodents and suggest that VOCs are under strong selective pressures relative to protein rewards. Strong chemical signals likely allow detection of truffles deep within the soil and reduce foraging effort by rodents. Finally, for rodents that depend on fungi as a major food source, protein content may also be important in selecting truffles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here, in this study, we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap-nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID-19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site-level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Differential DNA methylation and metabolite profiling of Atlantic killifish (Fundulus heteroclitus) from the New Bedford Harbor Superfund site

Atlantic killifish (Fundulus heteroclitus) is a valuable model in evolutionary toxicology to study how the interactions between genetic and environmental factors serve the adaptive ability of organisms to resist chemical pollution. Killifish populations inhabiting environmental toxicant-contaminated New Bedford Harbor (NBH) show phenotypes tolerant to polychlorinated biphenyls (PCBs) and differences at the transcriptional and genomic levels. However, limited research has explored epigenetic alterations and metabolic effects in NBH killifish. To identify the involvement of epigenetic and metabolic regulation in the adaptive response of killifish, we investigated tissue- and sex-specific differences in global DNA methylation and metabolomic profiles of NBH killifish populations, compared to sensitive populations from a non-polluted site, Scorton Creek (SC). The results revealed that liver-specific global DNA hypomethylation and differential metabolites were evident in fish from NBH compared with those from SC. The sex-specific differences were not greater than the tissue-specific differences. We demonstrated liver-specific enriched metabolic pathways (e.g., amino acid metabolic pathways converged into the urea cycle and glutathione metabolism), suggesting possible crosstalk between differential metabolites and DNA hypomethylation in the livers of NBH killifish. Additional investigation of methylated gene regions is necessary to understand the functional role of DNA hypomethylation in the regulation of enzyme-encoding genes associated with metabolic processes and physiological changes in NBH populations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Rapidly Changing Range Limits in a Warming World: Critical Data Limitations and Knowledge Gaps for Advancing Understanding of Mangrove Range Dynamics in the Southeastern USA

Climate change is altering species’ range limits and transforming ecosystems. For example, warming temperatures are leading to the range expansion of tropical, cold-sensitive species at the expense of their cold-tolerant counterparts. In some temperate and subtropical coastal wetlands, warming winters are enabling mangrove forest encroachment into salt marsh, which is a major regime shift that has significant ecological and societal ramifications. Here, we synthesized existing data and expert knowledge to assess the distribution of mangroves near rapidly changing range limits in the southeastern USA. We used expert elicitation to identify data limitations and highlight knowledge gaps for advancing understanding of past, current, and future range dynamics. Mangroves near poleward range limits are often shorter, wider, and more shrublike compared to their tropical counterparts that grow as tall forests in freeze-free, resource-rich environments. The northern range limits of mangroves in the southeastern USA are particularly dynamic and climate sensitive due to abundance of suitable coastal wetland habitat and the exposure of mangroves to winter temperature extremes that are much colder than comparable range limits on other continents. Thus, there is need for methodological refinements and improved spatiotemporal data regarding changes in mangrove structure and abundance near northern range limits in the southeastern USA. Advancing understanding of rapidly changing range limits is critical for foundation plant species such as mangroves, as it provides a basis for anticipating and preparing for the cascading effects of climate-induced species redistribution on ecosystems and the human communities that depend on their ecosystem services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Excessive radon-based radiation in indoor air caused by soil building materials in traditional homes on Đồng Văn karst plateau, northern Vietnam

Radon-based radiation from natural soil building materials is an important factor likely influencing residents’ health as a contributing source of natural radiation. This work aims to quantify the nuclide-specific α-radiation of isotopes 222 Rn and 220 Rn in common types of houses in a region of northern Vietnam, Ɖông Văn karst plateau, to preliminarily (i) evaluate the total annual effective dose rates and (ii) assess the relative risk of cancer induction from indoor α-radiation for inhabitants. The average 222 Rn concentrations in all house types were lower than 100 Bq m -3 , but 220 Rn abundances were far higher than 222 Rn, even up to >1000 Bq m -3 in air close to a wall of unfired-soil bricks. The estimated total annual effective dose rates from indoor 222 Rn and 220 Rn and their progenies to residents with daily exposure of 13 h in the various types of houses range from 3.1 to 4.3 mSv a -1 for houses constructed with modified materials, but up to higher than 6 mSv a -1 in houses with raw building materials. The average risk of developing lung cancer as a consequence of a lifetime exposure to indoor α-radiation in affected homes ranges from 3.9% to 14.6%. 220 Rn and its metallic progenies contribute more than 80% of the total average lung cancer risk from total radon, being responsible for a range of 2.7–14.6% of the risk of developing lung cancer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using deep transfer learning and satellite imagery to estimate urban air quality in data-poor regions

Urban air pollution is a critical public health challenge in low-and-middle-income countries (LMICs). At the same time, LMICs tend to be data-poor, lacking adequate infrastructure to monitor air quality (AQ). As LMICs undergo rapid urbanization, the socio-economic burden of poor AQ will be immense. Here we present a globally scalable two-step deep learning (DL) based approach for AQ estimation in LMIC cities that mitigates the need for extensive AQ infrastructure on the ground. We train a DL model that can map satellite imagery to AQ in high-income countries (HICs) with sufficient ground data, and then adapt the model to learn meaningful AQ estimates in LMIC cities using transfer learning. The trained model can explain up to 54% of the variation in the AQ distribution of the target LMIC city without the need for target labels. The approach is demonstrated for Accra in Ghana, Africa, with AQ patterns learned and adapted from two HIC cities, specifically Los Angeles and New York.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Sunsetting coal power in China

Reducing CO 2 emissions from coal-fired electricity generation in China is critical to limit global warming. Long-term projections of China's electricity supply tend to assume that coal generation will be a mainstay of China's electricity system through 2050, due to limitations in the scalability of hydropower, nuclear, and natural gas generation and the commercial availability of carbon capture and storage. This paper examines the resource, economic, and institutional implications of reducing and replacing coal generation in China with mostly renewable energy and energy storage by 2040. We find that the scale of solar, wind, and storage resources needed to do so is on the order of 100–150 GW/year of solar and wind capacity and 15 GW/year of energy storage from 2020 to 2025, growing to 250 GW/year and 90 GW/year, respectively, from 2025 to 2040. We then also evaluate the sensitivities if coal plants are retired by 2050.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Environmental fate of radiocesium in biota inhabiting a contaminated ecosystem on the U.S. Department of Energy's Savannah River Site

Although biomagnification of radiocesium ( 137 Cs) has been reported in food webs, most previous research has been limited to select trophic linkages. Few studies have included a comprehensive survey of fauna associated with aquatic, semi-aquatic, and terrestrial habitats within a single study framework. The objectives of this study were to advance our understanding of the dynamics of 137 Cs accumulation within food webs by quantifying 137 Cs activity across a wide range of biota found within a contaminated canal, as well as test the hypothesis that life-stage and body size influence 137 Cs bioaccumulation in select herpetofauna. With extensive sampling across multiple taxa collected from a contaminated canal system and associated floodplain on the Savannah River Site, we assessed 137 Cs activity and stable nitrogen isotopes for both aquatic organisms that were restricted to the contaminated effluent canal, and semi-aquatic organisms able to move freely between the contaminated canal and the adjacent uncontaminated terrestrial habitat. We found 137 Cs activity to be highly variable among species, with evidence for and against biomagnification in semi-aquatic and aquatic organisms, respectively. Furthermore, 137 Cs activity decreased with life stage and body size in bullfrogs (Lithobates catesbeianus), despite post-metamorphic bullfrogs having a more carnivorous diet compared to tadpoles, while cottonmouths (Agkistrodon piscivorus) retained similar 137 Cs activity regardless of their age and size. While evidence of biomagnification has been observed in some contaminated systems, results of our study suggest the extent to which 137 Cs biomagnifies within food webs is context-dependent and likely influenced by a suite of biotic and abiotic factors. Further, our data indicate sampling of a broad suite of species and environmental attributes are needed to elucidate the fate and dynamics of anthropogenic pollutants within contaminated ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Degradation and fate of 2,4-dinitroanisole (DNAN) and its intermediates treated with Mg/Cu bimetal: Surface examination with XAS, DFT, and LDI-MS

In this article, a novel Mg-based bimetal reagent (Mg/Cu) was used as an enhanced reductive system to degrade insensitive munition 2,4-dinitroanisole (DNAN), a contaminant found in energetic-laden waste. Degradation of DNAN was significantly impacted by dissolved oxygen and studied in anoxic and oxic bimetal systems (i.e., purging with N 2 , air, or O 2 gas). Degradation occurred through sequential nitroreduction: first one nitro group was reduced (ortho or para) to form short-lived intermediates 2-amino-4-nitroanisole or 4-amino-2-nitroanisole (2-ANAN or 4-ANAN), and then subsequent reduction of the other nitro group formed 2,4-diaminoanisole (DAAN). The nitro-amino intermediates demonstrated regioselective reduction in the ortho position to 2-ANAN; Regioselectivity was also impacted by the anoxic/oxic environment. Under O 2 -purging DNAN degradation rate was slightly enhanced, but most notably O 2 significantly accelerated DAAN generation. DAAN also further degraded only in the oxygenated Mg/Cu system. Adsorption of DNAN byproducts to the reagent occurred regardless of anoxic/oxic condition, resulting in a partition of carbon mass between the adsorbed phase (27%-35%) and dissolved phase (59%-72%). Additional surface techniques were applied to investigate contaminant interaction with Cu. Density functional theory (DFT) calculations identified preferential adsorption structures for DNAN on Cu with binding through two O atoms of one or both nitro groups. X-ray absorption spectroscopy (XAS) measurements determined the oxidation state of catalytic metal Cu and formation of a Cu-O-N bond during treatment. Laser desorption ionization mass spectrometry (LDI-MS) measurements also identified intermediate 2-ANAN adsorbed to the bimetal surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A generic scenario analysis of end-of-life plastic management: Chemical additives

Plastic growing demand and the increment in global plastics production have raised the number of spent plastics, out of which over 90% are either landfilled or incinerated. Both methods for handling spent plastics are susceptible to releasing toxic substances, damaging air, water, soil, organisms, and public health. Improvements to the existing infrastructure for plastics management are needed to limit chemical additive release and exposure resulting from the end-of-life (EoL) stage. This article analyzes the current plastic waste management infrastructure and identifies chemical additive releases through a material flow analysis. Additionally, we performed a facility-level generic scenario analysis of the current U.S. EoL stage of plastic additives to track and estimate their potential migration, releases, and occupational exposure. Potential scenarios were analyzed through sensitivity analysis to examine the merit of increasing recycling rates, using chemical recycling, and implementing additive extraction post-recycling. Our analyses identified that the current state of plastic EoL management possesses high mass flow intensity toward incineration and landfilling. Although maximizing the plastic recycling rate is a reasonably straightforward goal for enhancing material circularity, the conventional mechanical recycling method requires improvement because major chemical additive release and contamination routes act as obstacles to achieving high-quality plastics for future reuse and should be mitigated through chemical recycling and additive extraction. In conclusion, the potential hazards and risks identified in this research create an opportunity to design a safer closed-loop plastic recycling infrastructure to handle additives strategically and support sustainable materials management efforts to transform the US plastic economy from linear to circular.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

What lies beneath: Vertical temperature heterogeneity in a Mediterranean woodland savanna

As the availability of satellite and airborne thermal infrared remote sensing (TIR-RS) data increases and their spatial, temporal, and spectral resolutions improve, researchers are finding diverse applications for TIR-RS measurements. TIR-RS is now commonly applied in regional- and continental-scale analyses, such as those focused on fire and surface energy balance. However, its application lags in plant physiology and ecology, for which a finer-scale understanding of plant canopy temperatures would be useful to elucidate plant water dynamics, for example. In particular, while methods to disaggregate TIR-RS pixels in horizontal space have advanced, possible vertical stratification of plant canopy temperature and its implications for understanding the correspondence between TIR-RS and finer-scale, field-based thermal measurements (e.g. made with a thermal camera) remain unexplored. Here, we use data from a thermal camera deployed concurrently with the recent ECOSTRESS mission to quantify vertical temperature gradients within tree canopies and temperatures of over- vs. under-story plants in a Mediterranean woodland savanna. We then leverage diverse ancillary data to maximize the geometric comparability of ECOSTRESS and thermal camera measurements, in order to assess the extent to which the two forms of thermal measurements correspond. Specifically, we ask: (1) What are the patterns of intra-canopy and over- vs. under-story vertical temperature in a Mediterranean woodland savanna?, and (2) How can vertically-resolved, but spatially-limited field-based temperature measurements be reconciled with spatially-extensive, but surface-only, temperature measurements of a space-borne remote sensor? Further, we found consistent patterns of vertical thermal heterogeneity both within tree canopies and between ecosystem over- and under-stories. The daytime difference between the top and bottom thirds of blue oak canopies was, on average, 0.48 ° C – and sometimes several times larger. Notably, canopy tops are cooler, likely associated with the under-story grass reaching daytime temperatures often exceeding over-story temperatures by 10° C. Given the consistency of the intra-canopy temperature gradients, we expected the ECOSTRESS sensor would be in better agreement with camera measurements of canopy tops than bulk canopies or canopy bottoms. However, within-canopy gradients were overwhelmed by other sources of disagreement between the measurements, in part associated with upscaling camera measurements across space. Overall, thermal camera and ECOSTRESS measurements were largely in agreement at night (pixel RMSE = 1.1°C), but they were more divergent during times of low (but >0 W/m2) and high incoming solar radiation (daytime pixel RMSE = 3.5°C).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An evaluation of meteorological data prediction over Washington, D.C.: Comparison of DCNet observations and NAM model outputs

This study presents an example of how outputs of operational and readily-available mesoscale numerical models can be adapted to initialize dispersion calculations within the urban surface roughness layer. Three years of urban meteorological observations from central Washington, DC, are compared against forecast outputs of the North American Mesoscale (NAM) model. NAM wind speed predictions underestimate the observations in light winds and overestimate the measurements in high winds. Average wind directions are consistent. However, an adjustment of the predicted direction of the plume by –20° is needed. The uncertainty associated with this adjustment is large in light NAM wind speed with no evident variation by season. The values of the standard deviation of the wind direction, σθ derived from NAM model outputs underestimate the observations by a small amount (about –1.5 to –2.5°). The results presented here indicate that mesoscale numerical model outputs can provide information adequate for dispersion calculations. However, levels of uncertainty associated with implementation of the suggested procedures increase with decreasing wind speed, causing considerable uncertainty in the implementation of adjustments as low wind speed conditions are approached. Results and recommendations reported here should not be extended to other numerical models or other cities without further testing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Groundwater-native Fe(II) oxidation prior to aeration with H 2 O 2 to enhance As(III) removal

Groundwater contaminated with arsenic (As) must be treated prior to drinking, as human exposure to As at toxic levels can cause various diseases including cancer. Conventional aeration-filtration applied to anaerobic arsenite (As(III)) contaminated groundwater can remove As(III) by co-oxidizing native iron (Fe(II)) and As(III) with oxygen (O 2 ). However, the As(III) removal efficiency of conventional aeration can be low, in part, because of incomplete As(III) oxidation to readily-sorbed arsenate (As(V)). In this work, we investigated a new approach to enhance As(III) co-removal with native Fe(II) by the anaerobic addition of hydrogen peroxide (H 2 O 2 ) prior to aeration. Experiments were performed to co-oxidize Fe(II) and As(III) with H 2 O 2 (anaerobically), O 2 (aerobically), and by sequentially adding of H 2 O 2 and O 2 . Aqueous As(III) and As(V) measurements after the reaction were coupled with solid-phase speciation by Fe and As K-edge X-ray absorption spectroscopy (XAS). We found that complete anaerobic oxidation of 100 µM Fe(II) with 100 µM H 2 O 2 resulted in co-removal of 95% of 7 µM As(III) compared to 44% with 8.0-9.0 mg/L dissolved O 2 . Furthermore, we found that with 100 µM Fe(II), the initial Fe(II):H 2 O 2 ratio was a critical parameter to remove 7 µM As(III) to below the 10 µg/L (0.13 µM) WHO guideline, where ratios of 1:4 (mol:mol) Fe(II):H 2 O 2 led to As(III) removal matching that of 7 µM As(V). The improved As(III) removal with H 2 O 2 was found to occur partly because of the well-established enhanced efficiency of As(III) oxidation in Fe(II)+H 2 O 2 systems relatively to Fe(II)+O 2 systems. However, the XAS results unambiguously demonstrated that a large factor in the improved As(III) removal was also due to a systematic decrease in crystallinity, and thus increase in specific surface area, of the generated Fe(III) (oxyhydr)oxides from lepidocrocite in the Fe(II)+O 2 system to poorly-ordered Fe(III) precipitates in the Fe(II)+H 2 O 2 system. The combined roles of H 2 O 2 (enhanced As(III) oxidation and structural modification) can be easily overlooked when only aqueous species are measured, but this dual impact must be considered for accurate predictions of As removal in groundwater treatment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Threat by marine heatwaves to adaptive large marine ecosystems in an eddy-resolving model

Marine heatwaves (MHWs), episodic periods of abnormally high sea surface temperature, severely affect marine ecosystems. Large marine ecosystems (LMEs) cover ~22% of the global ocean but account for 95% of global fisheries catches. Yet how climate change affects MHWs over LMEs remains unknown because such LMEs are confined to the coast where low-resolution climate models are known to have biases. Here, using a high-resolution Earth system model and applying a ‘future threshold’ that considers MHWs as anomalous warming above the long-term mean warming of sea surface temperatures, we find that future intensity and annual days of MHWs over the majority of the LMEs remain higher than in the present-day climate. Better resolution of ocean mesoscale eddies enables simulation of more realistic MHWs than low-resolution models. These increases in MHWs under global warming pose a serious threat to LMEs, even if resident organisms could adapt fully to the long-term mean warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Unraveling the functional dark matter through global metagenomics

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Increased salinity decreases annual gross primary productivity at a Northern California brackish tidal marsh

Tidal marshes sequester 11.4–87.0 Tg C yr –1 globally, but climate change impacts can threaten the carbon capture potential of these ecosystems. Tidal marshes occur across a wide range of salinity, with brackish marshes (0.5–18 ppt (parts per thousand)) dominating global tidal marsh extents. A diverse mix of freshwater- and saltwater-tolerant plant and microbial communities has led researchers to predict that carbon cycling in brackish wetlands may be less sensitive to changes in salinity than fresh- or saltwater wetlands. Rush Ranch, a well-monitored brackish tidal wetland of the San Francisco Bay National Estuarine Research Reserve, experiences highly variable annual salinity regimes. Within a five-year period (2014–2018), Rush Ranch experienced particularly extreme drought-induced salinization during the 2014 and 2015 growing seasons. During drought years, tidal channel salinity rose from a 15 year baseline of 4.7 ppt to growing season peaks of 10.3 ppt and 12.5 ppt. Continuous eddy covariance data from 2014 to 2018 demonstrate that during drought summers, gross primary productivity (GPP) decreased by 24%, whereas ecosystem respiration remained similar among all five years. Stepwise linear regression revealed that salinity, not air temperature or tidal height, was the dominant driver of annual GPP. A random forest model trained to predict GPP based on environmental data from low salinity years (i.e. naive to salinization) significantly over predicted GPP in drought years. When growing season salinities were doubled, annual estimates of net ecosystem exchange of CO 2 decreased by up to 30%. These results provide ecosystem-scale evidence that increased salinity influences CO 2 fluxes dominantly through reductions in GPP. This relationship provides a starting point for incorporating the effect of changes in salinity in wetland carbon models, which could improve wetland carbon forecasting and management for climate resilience.

54 ENVIRONMENTAL SCIENCES↗