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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydrogen-Bonded Organic Frameworks: A Rising Class of Porous Molecular Materials

Hydrogen-bonded organic frameworks (HOFs) are a class of porous molecular materials that rely on the assembly of organic building blocks by means of hydrogen-bonding interactions to form two-dimensional (2D) and three-dimensional (3D) crystalline networks. The reversible nature of the hydrogen-bond formation endows HOFs with the attributes of solution processability and simple regeneration. High-quality single crystals of HOFs can be grown easily for unambiguous superstructure determination by single-crystal X-ray diffraction, which is crucial for the elucidation of superstructure–property relationships. During the past decade, considerable progress has been achieved in realizing stable HOFs with permanent porosities by focusing on the design of molecular building blocks in order to introduce rigidity, auxiliary [π···π] interactions, and interpenetration of their frameworks to sustain the extended networks. The applications of HOFs are far-reaching, spanning catalysis, energy, and biomedical products as well as the storage and separation of fine chemicals. In this paper, we, first of all, provide an overview of the chronological development of HOFs, starting from the seminal work by Marsh and Duchamp in 1969 on the crystal superstructure of the hydrogen-bonded networks of trimesic acid. We identify the development of novel hydrogen-bonding motifs such as diaminotriazine (DTA), the introduction of the concept of molecular tectonics, and the establishment of permanent porosity in HOFs as being some of the milestones, which incentivized the current burgeoning research endeavors on developing HOFs as multifunctional materials. This Account is focused primarily on surveying the strategies for constructing porous 3D HOFs based on organic building blocks with peripheral carboxyl groups. These strategies are presented in the following categories: (1) the polycatenation of 2D networks by trigonal building blocks to form global 3D frameworks, (2) the utilization of building blocks with 3D geometries—tetrahedral and trigonal prismatic—that are predisposed to form 3D networks, and (3) the docking by shape-fitting of geometrically labile building blocks. We emphasize how the molecular geometry of the building blocks plays an important role in modulating the superstructures of extended frameworks so as to address specific applications. Recognizing that the in silico design of HOFs is the ultimate goal of researchers in this field, we also discuss the recent advances in superstructure prediction that lead to the formation of porous supramolecular crystals and assess the complications in implementing computational methods for HOFs with complex superstructures. We hope this Account will inspire the development of new supramolecular designs and creative approaches to crystal engineering that aid and abet the assembly of multifunctional HOFs with customizable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Linking Hydrology and Dissolved Organic Matter Characteristics in a Subtropical Wetland: A Long-Term Study of the Florida Everglades

Dissolved organic matter (DOM) acts as an important biogeochemical component of aquatic ecosystems that controls nutrient cycling, influences water quality, and links terrestrial and oceanic carbon pools, yet long-term studies of how changing environmental drivers alter its abundance and composition are rare. Using a ten-year, spatially explicit dataset from Everglades National Park (ENP), a globally significant wetland, we investigated the relationships between DOM quality/quantity and hydrologic/climatic drivers along two contrasting marsh-estuarine transects based on generalized linear modeling and a cumulative sums analysis. Analyses revealed distinct spatial, seasonal, and interannual patterns in variability of DOC and optical properties. Landscape-scale seasonal patterns showed an enrichment in microbial-like and protein-like DOM during the dry season relative to the wet season. We found that, while some compositional constituents varied with the solar calendar, responsive to temperature and photoperiod, others varied with the hydrologic calendar. Independent water level and discharge effects indicated strong hydrologic control on DOM quality that differed between the two transects, evidencing differences in their connectivity to areas of high agricultural activity. Across all sites, a significant long-term increasing trend in the fluorescence index was observed, associated with a positive correlation with precipitation and also potential changes in agricultural inputs, with other features associated with drought and hurricanes. Lastly, the cumulative sums analysis revealed differences between the two transects in the sensitivity of DOM composition to decreased water levels associated with 30-year climate scenarios, with the less hydrologically dynamic transect exhibiting greater potential sensitivity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Remote Sensing Technique to Upscale Methane Emission Flux in a Subtropical Peatland

Abstract Quantification of methane (CH 4 ) gas emission from peat is critical to understand CH 4 budget from natural wetlands under a climate warming scenario. Previous studies have focused on prediction and mapping of CH 4 emission flux using process‐based models, while application of statistical‐empirical models for upscaling spatially sparse in situ measurements is scarce. In this study, we developed an empirical remote sensing upscaling approach to estimate CH 4 emission flux in the Everglades using limited in situ point‐based CH 4 emission flux measurements and Landsat data during 2013–2018. We spatially and temporally linked in situ data with Landsat surface reflectance based on temporally composite data sets and developed an object‐based machine learning framework to model and map CH 4 emission flux. An ensemble analysis of two machine learning models, k ‐Nearest Neighbor ( k ‐NN) and Support Vector Machine (SVM), shows that the upscaling approach is promising for predicting CH 4 emission flux with a R 2 of 0.65 and 0.87 based on a fivefold cross‐validation for a dry season and wet season estimation, respectively. We generated emission flux map products that successfully revealed the spatial and temporal heterogeneity of CH 4 emission within the dominant freshwater marsh ecosystem in the Everglades. We conclude that Landsat is promising for upscaling and monitoring CH 4 emission flux and reducing the uncertainty in emission estimates from wetlands.

Zhang, Caiyun↗
DOE OSTI2022

Interplay of River and Tidal Forcings Promotes Loops in Coastal Channel Networks

We report the dense populations that inhabit global coastlines have an uncertain future due to increased flooding, storms, and human modification. The channel networks of deltas and marshes that plumb these coastlines present diverse architectures, including well-studied dendritic topologies. However, the quasi-stable loops that exist in nearly all coastal networks have not yet been explained. We present a model for self-organizing networks inspired by vascular biophysics to show that loops emerge when the relative forcings between rivers and tides are comparable, resulting in interplay between hydrodynamic forcings at short time scales relative to network evolution. Using field data and satellite imaging, we confirm this control on 21 field networks. Our comparison provides compelling evidence that hydrodynamic fluctuations are capable of stabilizing loops in geophysical systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps

Abstract In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH 4 ) flux. In the first part of the study, we used a CH 4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint‐Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH 4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH 4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m −2 s −1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m −2 s −1 . This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy‐covariance towers and creates important insights for the interpretation of hot spots of CH 4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH 4 flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A New Coupled Biogeochemical Modeling Approach Provides Accurate Predictions of Methane and Carbon Dioxide Fluxes Across Diverse Tidal Wetlands

Abstract Tidal wetlands provide valuable ecosystem services, including storing large amounts of carbon. However, the net exchanges of carbon dioxide (CO 2 ) and methane (CH 4 ) in tidal wetlands are highly uncertain. While several biogeochemical models can operate in tidal wetlands, they have yet to be parameterized and validated against high‐frequency, ecosystem‐scale CO 2 and CH 4 flux measurements across diverse sites. We paired the Cohort Marsh Equilibrium Model (CMEM) with a version of the PEPRMT model called PEPRMT‐Tidal, which considers the effects of water table height, sulfate, and nitrate availability on CO 2 and CH 4 emissions. Using a model‐data fusion approach, we parameterized the model with three sites and validated it with two independent sites, with representation from the three marine coasts of North America. Gross primary productivity (GPP) and ecosystem respiration (R eco ) modules explained, on average, 73% of the variation in CO 2 exchange with low model error (normalized root mean square error (nRMSE) <1). The CH 4 module also explained the majority of variance in CH 4 emissions in validation sites ( R 2 = 0.54; nRMSE = 1.15). The PEPRMT‐Tidal‐CMEM model coupling is a key advance toward constraining estimates of greenhouse gas emissions across diverse North American tidal wetlands. Further analyses of model error and case studies during changing salinity conditions guide future modeling efforts regarding four main processes: (a) the influence of salinity and nitrate on GPP, (b) the influence of laterally transported dissolved inorganic C on R eco , (c) heterogeneous sulfate availability and methylotrophic methanogenesis impacts on surface CH 4 emissions, and (d) CH 4 responses to non‐periodic changes in salinity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metabolic interactions underpinning high methane fluxes across terrestrial freshwater wetlands

Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms drive methane cycling, but little is known about their conservation across wetlands. To address this, we integrate 16S rRNA amplicon datasets, metagenomes, metatranscriptomes, and annual methane flux data across 9 wetlands, creating the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This resource is used to link microbiome composition to function and methane emissions, focusing on methane-cycling microbes and the networks driving carbon decomposition. We identify eight methane-cycling genera shared across wetlands and show wetland-specific metabolic interactions in marshes, revealing low connections between methanogens and methanotrophs in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and is a strong predictor of methane flux. In these wetlands it also displays the functional potential for methylotrophic methanogenesis, highlighting the importance of this pathway in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux while providing an extensive publicly available database to advance future wetland research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling methane dynamics in three wetlands in Northeastern China by using the CLM-Microbe model

Wetlands account for up to 70% of the natural source of methane (CH 4 ) in terrestrial ecosystems on a global scale. Soil microbes are the ultimate producers and biological consumers of CH 4 in wetlands. Therefore, simulating microbial mechanisms of CH 4 production and consumptionwould improve the predictability of CH 4 flux in wetland ecosystems. In this study, we applied a microbial-explicit model, the CLM-Microbe, to simulate CH 4 flux in three major natural wetlands in northeastern China. The CLM-Microbe model was able to capture the seasonal variation of gross primary productivity (GPP), dissolved organic carbon (DOC), and CH 4 flux. The CLM-Microbe model explained more than 40% of the variation in GPP and CH 4 flux across sites. Marsh wetlands had higher CH 4 flux than mountain peatlands. Ebullition dominated the CH 4 transport pathway in all three wetlands. The methanogenesis dominates while methanotroph makes a minor contribution to the CH 4 flux, making all wetlands a CH 4 source. Sensitivity analysis indicated that microbial growth and death rates are the key factors governing CH 4 emission and vegetation physiological properties (flnr) and maintenance respiration predominate GPP variation. Explicitly simulating microbial processes allows genomic information to be incorporated, laying a foundation for better predicting CH 4 dynamics under the changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A review of carbon monitoring in wet carbon systems using remote sensing

Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advancements and opportunities to improve bottom–up estimates of global wetland methane emissions

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), contributing approximately 30% of total surface CH 4 emissions, and they have been identified as the largest source of uncertainty in the global CH 4 budget based on the most recent Global Carbon Project CH 4 report. High uncertainties in the bottom–up estimates of wetland CH 4 emissions pose significant challenges for accurately understanding their spatiotemporal variations, and for the scientific community to monitor wetland CH 4 emissions from space. In fact, there are large disagreements between bottom–up estimates versus top–down estimates inferred from inversion of atmospheric CH 4 concentrations. To address these critical gaps, we review recent development, validation, and applications of bottom–up estimates of global wetland CH 4 emissions, as well as how they are used in top–down inversions. These bottom–up estimates, using (1) empirical biogeochemical modeling (e.g. WetCHARTs: 125–208 TgCH 4 yr -1 ); (2) process-based biogeochemical modeling (e.g. WETCHIMP: 190 ± 39 TgCH 4 yr -1 ); and (3) data-driven machine learning approach (e.g. UpCH4: 146 ± 43 TgCH 4 yr -1 ). Bottom–up estimates are subject to significant uncertainties (~80 Tg CH 4 yr -1 ), and the ranges of different estimates do not overlap, further amplifying the overall uncertainty when combining multiple data products. These substantial uncertainties highlight gaps in our understanding of wetland CH 4 biogeochemistry and wetland inundation dynamics. Major tropical and arctic wetland complexes are regional hotspots of CH 4 emissions. However, the scarcity of satellite data over the tropics and northern high latitudes offer limited information for top–down inversions to improve bottom–up estimates. Recent advances in surface measurements of CH 4 fluxes (e.g. FLUXNET-CH 4 ) across a wide range of ecosystems including bogs, fens, marshes, and forest swamps provide an unprecedented opportunity to improve existing bottom–up estimates of wetland CH 4 estimates. We suggest that continuous long-term surface measurements at representative wetlands, high fidelity wetland mapping, combined with an appropriate modeling framework, will be needed to significantly improve global estimates of wetland CH 4 emissions. There is also a pressing unmet need for fine-resolution and high-precision satellite CH 4 observations directed at wetlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Short- and long-term responses of photosynthetic capacity to temperature in four boreal tree species in a free-air warming and rainfall manipulation experiment

Abstract High latitude forests cope with considerable variation in moisture and temperature at multiple temporal scales. To assess how their photosynthetic physiology responds to short- and long-term temperature variation, we measured photosynthetic capacity for four tree species growing in an open-air experiment in the boreal-temperate ecotone `Boreal Forest Warming at an Ecotone in Danger' (B4WarmED). The experiment factorially manipulated temperature above- and below-ground (ambient, +3.2 °C) and summer rainfall (ambient, 40% removal). We measured A/Ci curves at 18, 25 and 32 °C for individuals of two boreal (Pinus banksiana Lamb., Betula papyrifera Marsh.) and two temperate species (Pinus strobus L., Acer rubrum L.) experiencing the long-term warming and/or reduced-rainfall conditions induced by our experimental treatments. We calculated the apparent photosynthetic capacity descriptors VCmax,Ci and Jmax,Ci and their ratio for each measurement temperate. We hypothesized that (i) VCmax,Ci and Jmax,Ci would be down-regulated in plants experiencing longer term (e.g., weeks to months) warming and reduced rainfall (i.e., have lower values at a given measurement temperature), as is sometimes found in the literature, and that (ii) plants growing at warmer temperatures or from warmer ranges would show greater sensitivity (steeper slope) to short-term (minutes to hours) temperature variation. Neither hypothesis was supported as a general trend across the four species, as there was not a significant main effect (across species) of either warming or rainfall reduction on VCmax,Ci and Jmax,Ci. All species markedly increased VCmax,Ci and Jmax,Ci (and decreased their ratio) with short-term increases in temperature (i.e., contrasting values at 18, 25 and 32 °C), and those responses were independent of long-term treatments and did not differ among species. The Jmax,Ci:VCmax,Ci ratio was, however, significantly lower across species in warmed and reduced rainfall treatments. Collectively, these results suggest that boreal trees possess considerable short-term plasticity that may allow homeostasis of VCmax,Ci and Jmax,Ci to a longer term temperature treatment. Our results also caution against extrapolating results obtained under controlled and markedly contrasting temperature treatments to responses of photosynthetic parameters to more modest temperature changes expected in the near-term with climate warming in field conditions.

Forestry↗
DOE OSTI2023

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Abstract Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making.

Holmquist, James R.↗
DOE OSTI2026

Fostering Peat Moss Feedbacks to Accelerate Peatland Restoration

Extensive knowledge exists on plant-species traits and functions, but we understand less about how population- or community-level emergent traits influence ecosystem functioning. This knowledge gap is important for ecosystems like peatlands, arid drylands, salt marshes, seagrass meadows and mangroves, where emergent traits of plant communities can create plant-environment feedbacks that amplify or dampen ecosystem processes. Recent insights from restoration ecology suggest that these feedbacks can critically influence restoration success. Despite growing recognition of emergent trait-driven feedbacks in other ecosystems, they remain underexplored in peatland restoration, world’s most carbon-dense ecosystem. Here, we review emergent self-amplifying and self-dampening feedbacks with net positive effects for peat moss-dominated systems. We show how these feedbacks can promote key physical, chemical, and biological processes that enhance peat moss growth, increase water retention, and reduce microbial decomposition of organic matter. Understanding and fostering these feedbacks offers a promising framework to accelerate peatland restoration across diverse degradation states.

Sphagnum↗
DOE OSTI2021

The xylem of anisohydric Quercus alba L. is more vulnerable to embolism than isohydric codominants

Abstract The coordination of plant leaf water potential (Ψ L ) regulation and xylem vulnerability to embolism is fundamental for understanding the tradeoffs between carbon uptake and risk of hydraulic damage. There is a general consensus that trees with vulnerable xylem more conservatively regulate Ψ L than plants with resistant xylem. We evaluated if this paradigm applied to three important eastern US temperate tree species, Quercus alba L., Acer saccharum Marsh. and Liriodendron tulipifera L., by synthesizing 1600 Ψ L observations, 122 xylem embolism curves and xylem anatomical measurements across 10 forests spanning pronounced hydroclimatological gradients and ages. We found that, unexpectedly, the species with the most vulnerable xylem ( Q. alba ) regulated Ψ L less strictly than the other species. This relationship was found across all sites, such that coordination among traits was largely unaffected by climate and stand age. Quercus species are perceived to be among the most drought tolerant temperate US forest species; however, our results suggest their relatively loose Ψ L regulation in response to hydrologic stress occurs with a substantial hydraulic cost that may expose them to novel risks in a more drought‐prone future.

Benson, Michael C.↗
DOE OSTI2021

Draft Genome Sequence of Scheffersomyces spartinae ARV011, a Marine Yeast Isolate

We report the draft genome sequence of Scheffersomyces spartinae ARV011, which was isolated from the Great Sippewissett Marsh in Falmouth, Massachusetts. Sequencing was performed using the Illumina NovaSeq 6000 platform, yielding 7,598,030 read pairs 250 bp in length. This resulted in a total draft genome size of 12,132,557 bp.

Villarreal, Alex R.↗
DOE OSTI2022

Nutrient and carbon concentrations in dated soil cores at US-OWC Ameriflux wetland site (OWC NERR)

Soil cores were sampled at the Old Woman Creek (OWC) National Estuarine Research Reserve at the south shore of Lake Erie, near Huron, Ohio, USA. OWC is a temperate mineral soil marsh. We dated the soil cores using lead isotope analysis and measured the concentrations of carbon and nutrients (nitrogen, phosphorus) throughout the core depths. We analyzed 36 cores, sampled along three transects at areas of the wetland with different hydrological regimes. Each transect included three coring sites at different water depth categories (shallow, intermediate deep) with four core samples per coring site. The data can be used to determine the carbon sequestration rates and nutrient accumulation rates, at multiple locations throughout OWC wetland.Dataset, in csv format, with data variables in columns, and different cores and core depths slices in rows, includes results from 36 sediment cores (0-30 cm depth) taken at 9 locations (4 replicates at each location) along 3 gradients of water depth (shallow, intermediate, deep), each at a different hydrologic location (outflow, backflow, middle). At each depth slice within a core, we provide depth, date (using 210Pb), bulk density, and the concentrations of carbon, nitrogen, phosphorus, d13C, and d15N.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ELM-Wet: Inclusion of a wetland landunit with sub-grid representation of eco-hydrological patches and hydrological forcing in E3SM Land Model (ELM)

Wetlands emit the most biogenic methane (CH4) and present the greatest uncertainty in the global CH4 budget. Modeling these emissions is challenging due to the temporal and spatial variability in wetland structure and CH4 flux rates, along with complex interactions among hydrological, ecological, meteorological, and microbial processes that govern CH4 dynamics. To address these issues, we aim to enhance the accuracy of wetland representation in the U.S. Department of Energy’s Exascale Earth System Model (E3SM) Land Model, ELM. This effort led to the development of ELM-Wet, which incorporates a dedicated wetland landunit with subgrid representation of eco-hydrological patch types. We implement wetland-specific hydrology by imposing site-specific constraints on surface water levels, thereby allowing different patches to sustain varying depths of inundation. Additionally, we refined the calculation of aerenchyma transport diffusivity based on observed conductance across different vegetation types. We validated these enhancements through site-specific simulations of a coastal freshwater wetland, the Salvador WMA Freshwater Marsh (Ameriflux, site ID US-LA2), located in the coast of Louisiana (29.85N,90.29W) at an elevation of 0 m. The site was simulated with ELM-Wet and the default version ELMv1. We use Bayesian Optimization to parameterize CO2 and CH4 fluxes. Eddy covariance observations of CO2 and CH4 fluxes from 2012-2013 were used to train the model and data from 2021 were used for validation. In this repository, we include all the output of all the simulations performed using different versions of ELMv1 and ELM-Wet, all input required to the model, and the Matlab scripts we used to processed the output data. ELM-Wet_flmd.csv includes a detailed description of the datasets files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

COMPASS-FME Synoptic Site Characterization

This dataset contains soil biogeochemical and physicochemical characterization data for the COMPASS-FME synoptic sites.This dataset also contains data for the paper Patel et al. 2025 "Transition zones at the changing coastal terrestrial-aquatic interface", https://doi.org/10.1029/2025JG008978.Coastal soils are a significant but highly uncertain component of global biogeochemical cycles. These systems experience unique spatial and temporal variability in biogeochemical processes, driven by wetland-to-upland gradients and hydrological fluctuations. We studied drivers of coastal soil variability (a) at regional scales and (b) across transects from upland forest to wetland, in two contrasting regions — Lake Erie, a freshwater lacustrine system, and Chesapeake Bay, a saltwater estuarine system. Salinity-related analytes were a key driver of soil variability, not just in the saltwater system, but surprisingly, also in the freshwater system. We had hypothesized linear trends in biogeochemical parameters along the TAI – however, contrary to expectations, transition soils were not consistently intermediate between upland and wetland endmembers; the non-monotonic trends of carbon, phosphorus, iron along our transects suggest that these are key analytes to study in our regions. Rapidly changing soil factors across coastal gradients provide insights into which soil processes may act as precursors to ecosystem shifts. Our comprehensive soil characterization across the coastal transects provides essential data for mechanistic modeling of ecosystem dynamics.The data are provided as processed, csv files. Raw data and processing scripts can be accessed on GitHub (https://github.com/COMPASS-DOE/cmps-soil_characterization).A note on the nomenclature: the experimental design represents three points along the coastal gradient -- upland, transition, and wetland. "wetland" is referred to as "marsh" in the corresponding paper. The two terms can be used interchangeably for the sites in this study.

54 ENVIRONMENTAL SCIENCES↗