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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Environmental controls on the light use efficiency of terrestrial gross primary production

Abstract Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf‐level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy‐level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C 3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed‐effects model. The same model design was fitted to site‐based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine learning analysis reveals relationship between pomacentrid calls and environmental cues

Sound production rates of fishes can be used as an indicator for coral reef health, providing an opportunity to utilize long-term acoustic recordings to assess environmental change. As acoustic datasets become more common, computational techniques need to be developed to facilitate analysis of the massive data files produced by long-term monitoring. Machine learning techniques demonstrate an advantage in the identification of fish sounds over manual sampling approaches. Here we evaluated the ability of convolutional neural networks to identify and monitor call patterns for pomacentrids (damselfishes) in a tropical reef region of the western Pacific. A stationary hydrophone was deployed for 39 mo (2014-2018) in the National Park of American Samoa to continuously record the local marine acoustic environment. A neural network was trained—achieving 94% identification accuracy of pomacentrids—to demonstrate the applicability of machine learning in fish acoustics and ecology. The distribution of sound production was found to vary on diel and interannual timescales. Additionally, the distribution of sound production was correlated with wind speed, water temperature, tidal amplitude, and sound pressure level. This research has broad implications for state-of-the-art acoustic analysis and promises to be an efficient, scalable asset for ecological research, environmental monitoring, and conservation planning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm-2 yr-1 for boreal, temperate and tropical sites, respectively), influenced by each model's initial forest state. Models captured mature forest carbon content but showed compensating effects between overestimated growth and underestimated mortality rates. This first multi-model benchmarking identifies growth and mortality rates as critical calibration targets and highlights the need to refine postdisturbance establishment conditions for model development. We outline specific benchmarking variables needed to improve predictions of forest responses to environmental change.

demographic vegetation model benchmarking↗
DOE OSTI2024

COMPASS-FME Synoptic Sites Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v1-2 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

COMPASS-FME Synoptic Sites Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-0 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Sentinel protist taxa of the McMurdo Dry Valley lakes, Antarctica: a review

High-latitude meromictic lakes such as those in the Antarctic McMurdo Dry Valleys (MDV) harbor aquatic ecosystems dominated by the microbial loop. Within this habitat, which is limited year-round by light and nutrients, protists, or single celled eukaryotes, play outsized roles in the food web as the dominant primary producers and the apex predators. Thus, the MDV lake ecosystem represents an ideal system to study the role of sentinel protist taxa in carbon and nutrient cycling. The perennially ice-covered lakes are part of the McMurdo Long Term Ecological Research (McM LTER; mcmlter.org) established in 1993. In this review we will highlight the diversity and trophic roles of the MDV lake protist community and compare environmental factors driving spatiotemporal patterns in key protist taxa in two lakes within the McM LTER, Lakes Bonney and Fryxell. We will then discuss lessons learned from manipulated experiments on the impact of current and future climate-driven environmental change on sensitive protist taxa. Last, we will integrate knowledge gained from 25 years of lab-controlled experiments on key photosynthetic protists to extend our understanding of the function of these extremophiles within the MDV aquatic food webs. Our research group has studied the distribution and function of the MDV microbial community for nearly two decades, training the next generation of scientists to tackle future problems of these globally significant microbes. This review article will also highlight early career scientists who have contributed to this body of work and represent the future of scientific understanding in the Anthropocene.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations

Gross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS- and GPP-related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP-only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Representing Global Soil Erosion and Sediment Flux in Earth System Models

Abstract Soil erosion produces enormous amounts of sediment, carbon, and nutrient fluxes from land to rivers, thus playing crucial roles in global biogeochemical cycles and food security. To predict soil erosion in the context of climate and land use changes, we explicitly parameterize cropland management actions (i.e., irrigation, conserved agriculture, and crop residue management) and geological factors (i.e., lithology and glacier) in the Energy Exascale Earth System Model (E3SM) soil erosion module. The erosion model is calibrated using a global‐scale regionalized parameter calibration method. The spatial variabilities of the modeled and the Revised Universal Soil Loss Equation (RUSLE) based benchmark soil erosion are consistent across vegetation, climate and soil properties. Compared with independent data, our model shows a bias reduction in 59% of the observations relative to the RUSLE‐based soil erosion, with 53% of the bias reduction exceeding 50%. This improvement is mainly due to a better representation of the topographic effect on soil erosion. Our results indicate that conserved agriculture practices have effectively reduced soil erosion in cropland by over 25% in the United States and Argentina. In contrast, irrigation has increased soil erosion in many Asian countries. For upland sediment flux, our model is consistent with the WBMsed benchmark data in inter‐basin variability but could be more skillful in simulating intra‐basin variability because it couples soil erosion and sediment flux explicitly. The developed model provides useful skills for more realistic predictions of soil erosion and river sediment dynamics under environmental changes.

58 GEOSCIENCES↗
NASA NTRS2003

Aging Wire Insulation Assessment by Phase Spectrum Examination of Ultrasonic Guided Waves

Wire integrity has become an area of concern to the aerospace community including DoD, NASA, FAA, and Industry. Over time and changing environmental conditions, wire insulation can become brittle and crack. The cracks expose the wire conductor and can be a source of equipment failure, short circuits, smoke, and fire. The technique of using the ultrasonic phase spectrum to extract material properties of the insulation is being examined. Ultrasonic guided waves will propagate in both the wire conductor and insulation. Assuming the condition of the conductor remains constant then the stiffness of the insulator can be determined by measuring the ultrasonic guided wave velocity. In the phase spectrum method the guided wave velocity is obtained by transforming the time base waveform to the frequency domain and taking the phase difference between two waveforms. The result can then be correlated with a database, derived by numerical model calculations, to extract material properties of the wire insulator. Initial laboratory tests were performed on a simple model consisting of a solid cylinder and then a solid cylinder with a polymer coating. For each sample the flexural mode waveform was identified. That waveform was then transformed to the frequency domain and a phase spectrum was calculated from a pair of waveforms. Experimental results on the simple model compared well to numerical calculations. Further tests were conducted on aircraft or mil-spec wire samples, to see if changes in wire insulation stiffness can be extracted using the phase spectrum technique.

Anastasi, Robert F.↗
DOE OSTI2026

Synthesizing land use and demographic change in Southeast Asia’s smaller urbanized areas from 2000–2015

The majority of the human population now reside in urban areas today. The United Nations estimates that nearly half of all urban dwellers currently live in cities smaller than 500 000 persons and the majority of future urban growth will take place in Asia and Africa, likely in these smaller urban areas, not mega cities. Thus, understanding the factors that influence urban demographic trajectories in small urban areas is critical to address sustainable and equitable policy initiatives related to food security, changing climate hazard exposure, and economic opportunities. Here we focus on Southeast Asia—a region historically characterized by lower urban population proportions, yet with a rapidly shifting dynamic demographic—to examine correlates of demographic change among smaller cities. We combine two open-source satellite-informed datasets: GHS urban center database (2015) and age-sex gridded data from WorldPop to calculate socio-demographic characteristics to model drivers of change in annualized urban population growth from 2000–2015 for 505 urbanized places. We find a general pattern of decreasing dependency ratios as city-size increases for most urban areas in Southeast Asia. Higher rates of growth and more variation is observed for smaller cities—those with fewer than 300 000 persons, the lowest population limit for UN data on urbanization. When examining covariates of urban population growth, we find significant statistical associations of population change in smaller urbanized areas with climatic, economic, and land cover/land use variables, but with country-specific variations. Characterizing a continuum of urban population development in the context of changing environmental, economic and climate conditions has been an important sustainable development and equity issue for decades, but newer analysis of city-level drivers allows for systematic inquiry thus moving beyond total population counts for policy-relevant insight.

Southeast Asia synthesis↗
DOE OSTI2023

TomocuPy – efficient GPU-based tomographic reconstruction with asynchronous data processing

Fast 3D data analysis and steering of a tomographic experiment by changing environmental conditions or acquisition parameters require fast, close to real-time, 3D reconstruction of large data volumes. Here a performance-optimized TomocuPy package is presented as a GPU alternative to the commonly used central processing unit (CPU) based TomoPy package for tomographic reconstruction. TomocuPy utilizes modern hardware capabilities to organize a 3D asynchronous reconstruction involving parallel read/write operations with storage drives, CPU–GPU data transfers, and GPU computations. In the asynchronous reconstruction, all the operations are timely overlapped to almost fully hide all data management time. Since most cameras work with less than 16-bit digital output, the memory usage and processing speed are furthermore optimized by using 16-bit floating-point arithmetic. As a result, 3D reconstruction with TomocuPy became 20–30 times faster than its multi-threaded CPU equivalent. Full reconstruction (including read/write operations and methods initialization) of a 2048 3 tomographic volume takes less than 7 s on a single Nvidia Tesla A100 and PCIe 4.0 NVMe SSD, and scales almost linearly increasing the data size. To simplify operation at synchrotron beamlines, TomocuPy provides an easy-to-use command-line interface. Efficacy of the package was demonstrated during a tomographic experiment on gas-hydrate formation in porous samples, where a steering option was implemented as a lens-changing mechanism for zooming to regions of interest.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Accounting for herbaceous communities in process‐based models will advance our understanding of “grassy” ecosystems

Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Novel Freshwater to Marine Evolutionary Transition Revealed within Methylophilaceae Bacteria from the Arctic Ocean

Bacteria inhabiting polar oceans, particularly the Arctic Ocean, are less studied than those at lower latitudes. Discovering bacterial adaptations to Arctic Ocean conditions is essential for understanding responses to the accelerated environmental changes occurring in the North. The Methylophilaceae are emerging as a model for investigating the genomic basis of habitat adaptation, because related lineages are widely distributed across both freshwater and marine ecosystems. Here, we investigated Methylophilaceae diversity in the salinity-stratified surface waters of the Canada Basin, Arctic Ocean. In addition to a diversity of marine OM43 lineages, we report on the genomic characteristics and evolution of a previously undescribed Methylophilaceae clade (BS01) common to polar surface waters yet related to freshwater sediment Methylotenera species. BS01 is restricted to the lower-salinity surface waters, while OM43 is found throughout the halocline. An acidic proteome supports a marine lifestyle for BS01, but gene content shows increased metabolic versatility compared to OM43 and evidence for ongoing genome-streamlining. Phylogenetic reconstruction shows that BS01 colonized the pelagic ocean independently of OM43 via convergent evolution. Salinity adaptation and differences in one-carbon and nitrogen metabolism may play a role in niche differentiation between BS01 and OM43. In particular, urea utilization by BS01 is predicted to provide an ecological advantage over OM43 given the limited amount of inorganic nitrogen in the Canada Basin. These observations provide further evidence that the Arctic Ocean is inhabited by distinct bacterial groups and that at least one group (BS01) evolved via a freshwater to marine environmental transition.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2023

Accounting for Herbaceous Communities in Process-Based Models Will Advance Our Understanding of “Grassy” Ecosystems

Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process-based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet.

biogeochemistry↗
DOE OSTI2024

Understanding and modeling current and future coastal wetland methane dynamics (Final Report)

The coastal terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system that plays a critical role in biogeochemical cycling. Due to its dynamic nature, the processes that regulate decomposition and methane (CH 4 ) emissions are of greater significance at the TAI than in upland systems. Despite this, we have limited mechanistic understanding of how climate stressors interact to regulate the electron acceptors and donors that determine decomposition pathways within TAIs, including the generation of hot spots and hot moments. Accurately modeling these processes is critical for incorporating the coastal TAI into Earth systems models, such as DOE’s E3SM. With previous DOE support, we adapted an aerobic terrestrial representation of decomposition using PFLOTRAN, a reactive flow and transport model, and added anerobic decomposition pathways, salinity, and oxygen (O 2 ) that fluctuates independently of water table level. However, because this model (PFLOTRAN TAI ) is based on decomposition rates and organic matter carbon to nitrogen ratios from terrestrial systems, its performance in TAI systems is currently limited by the lack of empirical data to properly parameterize variables. In addition, while PFLOTRAN TAI can simulate movement of O 2 into sediments, it is not currently capable of tracking the movement of CH 4 gas through plant tissues due to both current model structure and lack of available data. Our overall objective of the project was the increase our mechanistic understanding of CH 4 dynamics in response to environmental change, such that we can improve the representation of these dynamics in PFLOTRAN. We installed automated flux chambers in a new field-scale active soil warming experiment and set up marsh organs (mesocosms) to test effects of warming, flooding, and salinity. This resulted in a new dataset consisting of chamber-level CH 4 flux measurements across multiple sites, ecological conditions, and timeframes, as well as corresponding measurements on porewater chemistry, soil carbon quality, plant biomass, and redox reaction rates. Using these data, we improved PFLOTRAN TAI to more accurately model CH 4 dynamics and successfully tested our hypotheses. This grant contributed to the professional development of 3 postdocs, 4 undergraduate interns, 4 teacher interns, 17 technicians, and 15 participatory scientists. The automated chamber technology designed for this grant has also been shared with multiple new projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A tale of two extremes: Temperature sensitivity of carbon loss from cool and hot soils

Soils represent the largest terrestrial carbon (C) pool, and the flux of carbon dioxide (CO 2 ) from soils to the atmosphere is ~ 6-10 times more than anthropogenic emissions. Understanding responses of soil CO 2 emissions to warming is crucial for evaluating feedback to ongoing environmental changes. The relationship between microbial respiration and temperature is typically modeled using a Q 10 function. Generally, observations of the apparent Q 10 of soil respiration are higher for cold vs. warm ecosystems, reflecting expected biophysical controls of Arrhenius kinetics. However, results from two field warming experiments in the tropics contradict this expectation, both observing extraordinarily high soil respiration responses to in situ warming. Our overall objective for the proposed work is to reduce uncertainty in temperature sensitivity of soil C loss by systematically synthesizing underlying mechanisms related to soil C turnover and stabilization. We are evaluating the temperature sensitivity of soil respiration in ecosystems across temperature extremes (e.g., arctic/boreal and tropical systems) by integrating data collected from field warming experiments with machine learning and biogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

COMPASS-FME Synoptic Sites Level 2 Sensor Data v2-1

This is the version 2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. Please see v2-1 L2 Sensor Package QStart.pdf for detailed information on data package structure, temporal coverage, and versioning.

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
NASA NTRS1994

Paleolimnology of the McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys presently contain more than 20 permanent lakes and ponds, which vary markedly in character. All, with the exception of a hypersaline pond, have a perennial ice-cover. The dry valley lakes, and lakes in other ice-free regions of continental Antarctica, are unique on this planet in that they consistently maintain a thick year-round ice cover (2.8-6.0 m) over liquid water. The persistent ice covers minimize wind-generated currents and reduce light penetration, as well as restricting sediment deposition into a lake and the exchange of atmospheric gases between the water column and the atmosphere. From a paleolimnological perspective, the dry valley lakes offer an important record of catchment and environmental changes. These lakes are also modern-day equivalents of periglacial lakes that were common during glacial periods at temperate latitudes. The present lakes are mostly remnants of larger glacial lakes that occupied the valleys in the past, perhaps up to 4.6 Ma ago. Two of the valleys contain evidence of being filled with large glacial lakes within the last 10000 years. Repeated drying and filling events since then have left a characteristic impression on the salt profiles of some lakes creating a unique paleo-indicator within the water column. These events are also marked in the sediments by the concentration and dilution of certain chemical constituents, particularly salts, and are also corroborated by carbonate speciation and oxygen isotope analysis. Stratigraphic analysis of dry valley lake sediments is made difficult by the occurrence of an 'old carbon' reservoir creating spurious radiocarbon dates, and by the high degree of spatial variability in lake sedimentation. From a biological perspective, the lakes are relatively simple, containing various taxa of planktonic and benthic microorganisms, but no higher forms of life, which is an advantage to paleolimnologists because there is no bioturbation in the sediments. Useful biological paleo-indicators found in the sediments include cyanobacterial filament sheaths, diatom frustules and other eukaryotic algal cells, protozoan cysts, photosynthetic pigments, and minerals (e.g. carbonates) associated with microbial activity. Future work will benefit from fully characterizing the connection between the ice covers, environmental conditions, and paleo-indicators, thereby allowing refinement of inferences made concerning the paleoenvironment. New dating techniques need to be tested in this environment to overcome the problems associated with radiocarbon dating. The establishment of a detailed and focused paleolimnological campaign is proposed.

Non-NASA Center↗