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At least 217 records · Page 12

Vertical canopy gradients of respiration drive plant carbon budgets and leaf area index

Despite its importance for determining global carbon fluxes, leaf respiration remains poorly constrained in land surface models (LSMs). We tested the sensitivity of the Energy Exascale Earth System Model Land Model – Functionally Assembled Terrestrial Ecosystem Simulator (ELM-FATES) to variation in the canopy gradients of leaf maintenance respiration (R dark ). We ran global and point simulations varying the canopy gradient of R dark to explore the impacts on forest structure, composition, and carbon cycling. In global simulations, steeper canopy gradients of R dark lead to increased understory survival and leaf biomass. Leaf area index (LAI) increased up to 77% in tropical regions compared with the default parameterization, improving alignment with remotely sensed benchmarks. Global vegetation carbon varied from 308 Pg C to 449 Pg C across the ensemble. In tropical forest simulations, steeper gradients of R dark had a large impact on successional dynamics. Results show the importance of canopy gradients in leaf traits and fluxes for determining plant carbon budgets and emergent ecosystem properties such as competitive dynamics, LAI, and vegetation carbon. The high-model sensitivity to canopy gradients in R dark highlights the need for more observations of how leaf traits and fluxes vary along light micro-environments to inform critical dynamics in LSMs.

59 BASIC BIOLOGICAL SCIENCES↗

Hybrid predictive modeling approach simulated evapotranspiration and ecosystem respiration data

This dataset includes measured data used for developing hybrid-predictive-modeling (HPM) approach and simulated evapotranspiration and ecosystem respiration data across several Fluxnet sites, SNOTEL sites and East River locations (Chen et al., 2020 in review). Fluxnet sites considered in this study include: CA-OAS, CA-OBS, US-NR1, US-TON, US-VAR, US-SRM, US-WHS, US-WKG. Snotel sites Butte (ER-BT), Porphyry Creek (ER-PK) and Schofield Pass (ER-SP) are included as well 16 east river locations with different vegetation types denoted by evergreen forests (EF), deciduous forests (DF), riparian shrublands (RS) and meadow grassland (MS). This data package includes: 1) A summary spread sheet of the sites and acronyms for data variables. 2) Processed Fluxnet datasets that are obtained from Fluxnet.fluxdata.org with HPM estimated evapotranspiration (ET) and ecosystem respiration (RECO). Trained models and metrics for parameters for the Fluxnet sites were added in an update on November 2, 2020; 3) Processed SNOTEL datasets obtained from www.nrcs.usda.gov/snow/ and HPM estimated ET and RECO; 4) Weather data at east river locations obtained from DAYMET (daymet.ornl.gov) as well as HPM estimated ET and RECO. NDVI datasets are obtained from Landsat 5, 7 and 8 on Google Earth Engine platform. Detailed QA/QC and sampling methods of measured data are available at the original data source.

54 ENVIRONMENTAL SCIENCES↗

Data and scripts associated with "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams."

This data package is associated with the publication "Coupled primary production and respiration in a large river contrasts with smaller rivers and streams." in review at Limnology and Oceanography (Roley et al. 2023). This study focuses on understanding ecosystem metabolism for the Hanford Reach of the Columbia River in Washington state, a free-flowing stretch with a substantial discharge. Large rivers have been overlooked compared to small and medium rivers due to the challenges associated with measurements. Our study presents novel ways to address these challenges and highlights that metabolism patterns in large rivers differ from those observed in small-medium rivers and requires the application of knowledge and tools beyond those implemented for smaller rivers.This data package includes the data and R scripts for the analyses described in Roley et al. 2023. It includes dissolved oxygen and temperature data from a dissolved oxygen HOBO sensor, light data collected from the National Solar Radiation Database (https://nsrdb.nrel.gov/) and hydrologic variables estimated from the MASS-1 model (Niehus et al.; 2014). It also includes metabolism estimates (gross primary production, ecosystem respiration, and net ecosystem production) estimated via streamMetabolizer (Appling et al.; 2018). All analyses in the paper can be replicated with these data and scripts.The data package is comprised of one main data folder. The folder includes (1) file-level metadata (flmd); (2) a data dictionary (dd) for each data file; (3) data files; and (4) R scripts for metabolism estimates and data analysis. All files are .R, .csv, or .pdf.

54 ENVIRONMENTAL SCIENCES↗

Processed Soil Respiration at the TRACE experimental Warming project, Aug 2015 - Sep 2017, Sabana, Luquillo, Puerto Rico

This data package contains processed measurements of soil carbon dioxide (CO₂) efflux collected using LI-COR LI-8100 soil respiration chambers at the Tropical Responses to Altered Climate Experiment (TRACE) located at the Sabana Field Research Station near Luquillo, Puerto Rico. The TRACE site is a mature, closed-canopy tropical wet forest within the Luquillo Experimental Forest. These data quantify soil surface CO₂ fluxes from both ambient (control) and experimentally warmed plots to evaluate how long-term soil warming affects belowground carbon cycling in tropical ecosystems. The data files include time-series tables of CO₂ flux (µmol CO₂ m⁻² s⁻¹), soil temperature (°C), and ancillary environmental variables, stored in comma-separated values (CSV) format and viewable with any text editor, spreadsheet, or statistical software (e.g., R, Python, Excel). Associated metadata describe plot identifiers, measurement intervals, and processing steps. These data were generated to address the research question: How does sustained soil warming influence soil respiration and carbon flux dynamics in tropical wet forests?

54 ENVIRONMENTAL SCIENCES↗

WHONDRS laboratory time series moisture manipulative experiment from soil core layers across eastern contiguous US: time series aerobic respiration, geochemistry, and aggregates

This dataset supports a broader study examining the effects of wetting and drying on soil layers across the eastern contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata. Samples were collected as part of a collaboration between WHONDRS (Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems; https://whondrs.pnnl.gov) and MONet (Molecular Observation Network; https://www.emsl.pnnl.gov/monet). The field samples (soil cores) were labeled as MEL_##_COR and subsequent subsamples begin with MEL_##. Additional subsamples were taken for the laboratory experiment and were labeled as EL_##. The labels from the MEL field samples and the EL subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EL_01 is a subsample from MEL_01). See the critical details section below for more details on sample naming and experimental design.For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions.This dataset is comprised of (1) a folder containing environmental context photos; (2) file-level metadata; (3) data dictionary; (4) field metadata; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) a subfolder with soil sample data from field samples and the incubation experiment. The sample data subfolder contains (1) effect size; (2) gravimetric moisture from field samples and incubation experiment; (3) respiration rates, raw dissolved oxygen values, and plots; (4) specific conductance, pH, and temperature from the incubation; (5) soil aggregates; (6) a summary containing median values of each data type for each treatment (wet and dry) in the incubation; (7) a summary containing averages for each data type of each soil layer; and (8) methods codes. All files are .csv, .pdf, .jpeg, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

Pyrogenic Organic Matter Laboratory Experiment: Aerobic Respiration and Geochemistry from Variably Inundated Stream Sediments (v3)

This dataset supports a broader study examining the effects of variable inundation and pyrogenic organic matter on ecosystem respiration. The dataset provides data generated from a laboratory batch experiment investigating the interaction between variable inundation conditions (wet and dry sediment) and pyrogenic organic matter (burned and unburned treatments). The contents include time series dissolved oxygen, sediment geochemistry data, and field metadata (including qualitative information on instream and river corridor characteristics). This data package was originally published in November 2025. It was updated in April 2026 (v2; new and modified files) and May 2026 (v3; modified files). See the change history section in the readme for more details For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) international generic sample number (IGSN) mapping file; (5) readme; (6) field protocol; (7) sample name metadata; (8) an environmental context picture for the dry and inundated sampling locations; and (9) a subfolder with sample data from the sediment incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) gravimetric moisture; (4) partial pressure and production rates of carbon dioxide, methane, and nitrous oxide; (5) field wet sediment mass, dry sediment mass, water mass, and field wet sediment volume in incubation and sediment NPOC/TN vials; (6) methods codes; (7) respiration rates, pH, and temperature from after the incubation, raw time series dissolved oxygen and temperature, and a subfolder containing associated plots and scripts; (8) ions; (9) FTICR-MS methods; and (10) a subfolder of 12 Tesla (12T) FTICR-MS data. This folder contains the CoreMS processed data and three subfolders, one containing the .xml files, one containing the CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .html, .Rmd, .py, .cal, .json, or .jpg.

54 ENVIRONMENTAL SCIENCES↗

Model scripts associated with “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale”

NOTE: The manuscript associated with this data package is currently in review. The data/scripts may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final scripts and additional metadata. This data package is associated with the publication “Revisiting controls on hyporheic respiration with knowledge-guided machine learning at continental scale” submitted to Environmental Science & Technology (Zheng et al. 2026). The project combines mechanistic process modeling with knowledge-guided machine learning (KGML) to evaluate how organic matter chemistry, microbial biomass, and physical substrate accessibility regulate realized respiration rates across river corridors. All data used in this paper have been previously published and can be accessed at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719 (Goldman et al., 2020). This data package contains 3 R-markdown (Rmd) preprocessing scripts for the previously published data and subsequent modelling workflows. The full workflow with input and output data can be found in the associated GitHub repository at https://github.com/jianqiuz/KGML-WHONDRS.

Biogeochemistry↗

Measuring Monodisperse Aerosol Transmission in the Los Alamos Respirable Release Fraction Measurement Chamber

The transmission ratio of monodisperse aerosol (between 1 and 20 μm aerodynamic equivalent diameter) was measured in a modified configuration of the Los Alamos RRFMC (Respirable Release Fraction Measurement Chamber). The RRFMC is a newly built, 20- foot tall, airtight chamber for the drop testing of nuclear material storage containers. The RRFMC was integrated into an existing HEPA filtered wind tunnel system, and is capable of direct measurement of Airborne Release Fraction (ARF) and Respirable Release Fraction (RRF) for plutonium and uranium under various accident conditions. Cerium oxide powder is used as a surrogate for plutonium oxide. Real-time aerosol measurements for aerodynamic diameters from 0.5 to 20 μm are performed with a TSI Inc (Shoreview, MN) Model 3321 APS (Aerodynamic Particle Sizer) spectrometer.

47 OTHER INSTRUMENTATION↗

SPRUCE Does dissolved organic matter or solid peat fuel anerobic respiration in peatlands?: Supporting Data

Hopple et al. (2019) investigated whether, as a primary substrate - dissolved organic matter (DOM) or solid peat - was driving anaerobic respiration at surface and at deep depth increments within two bogs and a poor fen in northern Minnesota. To address this question, they used a combination of soil laboratory incubations, as well as in-situ analyses of porewater dissolved organic carbon (DOC) concentrations and specific UV absorbance (SUVA) measurements. Soil samples were collected in June 2013 and July 2014, while porewater samples were taken in July 2013. Data provided include: porewater DOC concentration and SUVA values, soil CH4 and CO2 potential production rates from peat samples exposed to varying DOM concentrations, and soil CH4 and CO2 potential production rates.These data are provided in support of the publication: Does dissolved organic matter or solid peat fuel anerobic respiration in peatlands? (Hopple et al., 2019). This dataset contains four files in comma separate (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗

Sister Dehalobacter Genomes Reveal Specialization in Organohalide Respiration and Recent Strain Differentiation Likely Driven by Chlorinated Substrates

Here we report that the genomes of two closely related Dehalobacter strains (strain CF and strain DCA) were assembled from the metagenome of an anaerobic enrichment culture that reductively dechlorinates chloroform (CF), 1,1,1-trichloroethane (1,1,1-TCA) and 1,1-dichloroethane (1,1-DCA). The 3.1 Mbp genomes of strain CF (that dechlorinates CF and 1,1,1-TCA) and strain DCA (that dechlorinates 1,1-DCA) each contain 17 putative reductive dehalogenase homologous (rdh) genes. These two genomes were systematically compared to three other available organohalide-respiring Dehalobacter genomes (Dehalobacter restrictus strain PER-K23, Dehalobacter sp. strain E1 and Dehalobacter sp. strain UNSWDHB), and to the genomes of Dehalococcoides mccartyi strain 195 and Desulfitobacterium hafniense strain Y51. This analysis compared 42 different metabolic and physiological categories. The genomes of strains CF and DCA share 90% overall average nucleotide identity and >99.8% identity over a 2.9 Mbp alignment that excludes large insertions, indicating that these genomes differentiated from a close common ancestor. This differentiation was likely driven by selection pressures around two orthologous reductive dehalogenase genes, cfrA and dcrA, that code for the enzymes that reduce CF or 1,1,1-TCA and 1,1-DCA. The many reductive dehalogenase genes found in the five Dehalobacter genomes cluster into two small conserved regions and were often associated with Crp/Fnr transcriptional regulators. Specialization is on-going on a strain-specific basis, as some strains but not others have lost essential genes in the Wood-Ljungdahl (strain E1) and corrinoid biosynthesis pathways (strains E1 and PER-K23). The gene encoding phosphoserine phosphatase, which catalyzes the last step of serine biosynthesis, is missing from all five Dehalobacter genomes, yet D. restrictus can grow without serine, suggesting an alternative or unrecognized biosynthesis route exists. In contrast to D. mccartyi, a complete heme biosynthesis pathway is present in the five Dehalobacter genomes. This pathway corresponds to a newly described alternative heme biosynthesis route first identified in Archaea. Ultimately, this analysis of organohalide-respiring Firmicutes and Chloroflexi reveals profound evolutionary differences despite very similar niche-specific metabolism and function.

59 BASIC BIOLOGICAL SCIENCES↗

Emergency Use Respirators in TRA-670

The project was based on the research of the history of the emergency use air purifying respirators (APRs) in TRA-670. Interviews, inspections, and document reviews were conducted. The interviews, inspections, and documents revealed that there were no current documents as to why the emergency use APRs were placed into TRA-670. The APRs were placed into green emergency boxes and stashed around the plant. Though they are checked to ensure they are not messed with, they have not been cleaned or re-verified since 2016 (some since 2014). When interviewees were asked, in an emergency, when they would reach for an APR over an emergency use SCBA, the consensus was that they would not. They would evacuate the facility as quickly as possible. If emergency respiratory protection were needed, a SCBA would be used. This is because, in an emergency scenario, one would not know what is in the air, so the utilization of a SCBA would be the safest option. Overall, the recommendation would be for the removal of the emergency use APRs.

60 APPLIED LIFE SCIENCES↗

Influence of Hydrological Perturbations and Riverbed Sediment Characteristics on Hyporheic Zone Respiration of CO 2 and N 2

Rivers in climatic zones characterized by dry and wet seasons often experience periodic transitions between losing and gaining conditions across the river-aquifer continuum. Infiltration shifts can stimulate hyporheic microbial biomass growth and cycling of riverine carbon and nitrogen leading to major exports of biogenic CO 2 and N 2 to rivers. In this study, we develop and test a numerical model that simulates biological-physical feedback in the hyporheic zone. We used the model to explore different initial conditions in terms of dissolved organic carbon availability, sediment characteristics, and stochastic variability in aerobic and anaerobic conditions from water table fluctuations. Our results show that while highly losing rivers have greater hyporheic CO 2 and N 2 production, gaining rivers allowed the greatest fraction of CO 2 and N 2 production to return to the river. Hyporheic aerobic respiration and denitrification contributed 0.1–2 g/m 2 /d of CO 2 and 0.01–0.2 g/m 2 /d of N 2 ; however, the suite of potential microbial behaviors varied greatly among sediment characteristics. We found that losing rivers that consistently lacked an exit pathway can store up to 100% of the entering C/N as subsurface biomass and dissolved gas. Finally, our results demonstrate the importance of subsurface feedbacks whereby microbes and hydrology jointly control fate of C and N and are strongly linked to wet-season control of initial sediment conditions and hydrologic control of seepage direction. These results provide a new understanding of hydrobiological and sediment-based controls on hyporheic zone respiration, including a new explanation for the occurrence of anoxic microzones and large denitrification rates in gravelly riverbeds.

58 GEOSCIENCES↗

Coupled primary production and respiration in a large river contrasts with smaller rivers and streams

Abstract Although time series in ecosystem metabolism are well characterized in small and medium rivers, patterns in the world's largest rivers are almost unknown. Large rivers present technical difficulties, including depth measurements, gas exchange (, ) estimates, and the presence of large dams, which can supersaturate gases. We estimated reach‐scale metabolism for the Hanford Reach of the Columbia River (Washington state, USA), a free‐flowing stretch with an average discharge of 3173 . We calculated from semi‐empirical models and directly estimated it from tracer measurements. We fixed at the median value from these calculations (0.5 ), and used maximum likelihood to estimate reach‐scale, open‐channel metabolism. Both gross primary production (GPP) and ecosystem respiration (ER) were high (GPP range: 0.3–30.8 g , ER range: 0.8–30.6 g ), with peak GPP and ER occurring in the late summer or early fall. GPP increased exponentially with temperature, consistent with metabolic theory, while light was seasonally saturating. Annual average GPP, estimated at 1500 g carbon , was in the top 2% of estimates for other rivers. GPP and ER were tightly coupled and 90% of GPP was immediately respired, resulting in net ecosystem production near 0. Patterns in the Hanford Reach contrast with those in small‐medium rivers, suggesting that metabolism magnitudes and patterns in large rivers may not be simply scaled from knowledge of smaller rivers.

54 ENVIRONMENTAL SCIENCES↗

The transformation of U(VI) and V(V) in carnotite group minerals during dissimilatory respiration by a metal reducing bacterium

Recent results from laboratory and field studies support that dissimilatory metal reducing (DMR) bacteria influence the fate and transport of uranium in anaerobic subsurface environments. To date, most research efforts have focused on the reduction of soluble U(VI) by DMR bacteria to form insoluble uraninite (UO 2 ). Subsurface environments harbor, however, large reservoirs of U(VI) in solid or mineral form. Uranium that is structure-bound in minerals is expected to be more refractory to microbial reduction than soluble U, based on analogy with Fe respiration. The reducibility of U(VI) could impact the fate of U(IV) by controlling mineral precipitation reactions, which has implications for the long-term immobilization of U in subsurface environments. Here, we studied anoxic cultures of Shewanella putrefaciens CN32 incubated with natural carnotite-group minerals by X-ray diffraction, electron microscopy, scanning transmission X-ray microscopy (STXM). Near-edge X-ray absorption fine structure (NEXAFS) spectroscopy measurements at U-N 4,5 , V-L 2,3 , and O-K edges on cultures incubated up to 10 months show that V(V) was reduced to V(IV), whereas U was not reduced. In contrast, V(V) and U(VI) in solution were both completely reduced to lower oxidation states by CN32, as precipitates within the exopolymer surrounding the bacteria. Assays for the toxicity of U and V to CN32 showed that biofilm formation was stimulated at 0.001 M U(VI), and growth was inhibited at concentrations of U(VI) greater than 0.001 M. Vanadium did not inhibit growth or stimulate biofilm formation at any concentration tested. Investigations of the bacteria-mineral and bacteria-metal interface at the nanometer and molecular scales provide new insights into the co-respiration of V and U that help explain their biogeochemical cycling and have implications for subsurface bioremediation of these elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. A systematic evaluation of the interaction between coastal catchment properties and carbon dioxide (CO2) emission by soil respiration is significant for assessing carbon dynamics and predicting the future trajectory of atmospheric CO2 concentrations in coastal TAIs. The soil CO2 efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation index (kNDVI), climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, there is no one-size-fits-all approach to modeling carbon fluxes in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

54 ENVIRONMENTAL SCIENCES↗

Spatial and temporal dynamics of organohalide-respiring bacteria in a heterogeneous PCE–DNAPL source zone

Effective treatment of sites contaminated with dense non-aqueous phase liquids (DNAPLs) requires detailed understanding of the microbial community responses to changes in source zone strength and architecture. Changes in the spatial and temporal distributions of the organohalide-respiring Dehalococcoides mccartyi ( Dhc ) strains and Geobacter lovleyi strain SZ ( GeoSZ ) were examined in a heterogeneous tetrachloroethene- (PCE-) DNAPL source zone within a two-dimensional laboratory-scale aquifer flow cell. As part of a combined remedy approach, flushing with 2.3 pore volumes (PVs) of 4% (w/w) solution of the nonionic, biodegradable surfactant Tween® 80 removed 55% of the initial contaminant mass, and resulted in a PCE–DNAPL distribution that contained 51% discrete ganglia and 49% pools (ganglia-to-pool ratio of 1.06). Subsequent bioaugmentation with the PCE-to-ethene-dechlorinating consortium BDI-SZ resulted in cis -1,2-dichloroethene (cis-DCE) formation after 1 PV (ca. 7 days), while vinyl chloride (VC) and ethene were detected 10 PVs after bioaugmentation. Maximum ethene yields (ca. 90 μM) within DNAPL pool and ganglia regions coincided with the detection of the vcrA reductive dehalogenase (RDase) gene that exceeded the Dhc 16S rRNA genes by 2.0 ± 1.3 and 4.0 ± 1.7 fold in the pool and ganglia regions, respectively. Dhc and GeoSZ cell abundance increased by up to 4 orders-of-magnitude after 28 PVs of steady-state operation, with 1 to 2 orders-of-magnitude increases observed in close proximity to residual PCE–DNAPL. These observations suggest the involvement of these dechlorinators the in observed PCE dissolution enhancements of up to 2.3 and 6.0-fold within pool and ganglia regions, respectively. Analysis of the solid and aqueous samples at the conclusion of the experiment revealed that the highest VC (≥ 155 μM) and ethene (≥ 65 μM) concentrations were measured in zones where Dhc and GeoSZ were predominately attached to the solids. In conclusion, these findings demonstrate dynamic responses of organohalide-respiring bacteria in a heterogeneous DNAPL source zone, and emphasize the influence of source zone architecture on bioremediation performance.

54 ENVIRONMENTAL SCIENCES↗

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗