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Rapid organic carbon spiraling in a headwater stream linked with streamflow, biogeochemistry, and canopy phenology

Headwater streams are abundant worldwide and important to global biogeochemical cycles, serving as critical processors and transporters of C. C spiraling is a useful way to understand the retention and mineralization of organic C (OC) in streams. However, analyses of seasonal and interannual variability in OC spiraling are currently limited. In this study, we aimed to understand the temporal patterns and driving mechanisms of OC spiraling, which will inform our understanding of future OC changes under climate change. We used 7 y of daily data in a small headwater stream (Walker Branch, Tennessee, USA) to assess seasonal and interannual variability in OC spiraling length (S OC ) and mineralization velocity (v fOC ), as well as their potential related variables. On average, S OC in Walker Branch was ~10× shorter than in previously studied small streams, indicating strong connections between the water column and the benthic environment where OC mineralization mostly takes place. OC spiraling was faster during the more biologically active periods of spring and autumn compared with more elongated OC spiraling in summer and winter, when OC retention was lower and downstream transport was higher. Gross primary production (GPP) was most strongly related to S OC and v fOC . Photosynthetically active radiation (PAR) and NO 3 − were also positively and negatively related to v fOC , respectively. Trends toward earlier and longer canopy cover and reduced GPP and PAR may result in longer S OC and slower v fOC , reducing localized instream processing of OC and potentially shunting more OC downstream. However, long-term observations indicate reduced NO 3 − at Walker Branch, suggesting opposing effects to those of GPP and PAR, leading to faster v fOC and greater OC retention. Time-series analyses of OC spiraling in streams can enhance our understanding of current and future responses of OC processing and downstream transport to climate change, as well as implications for downstream OC dynamics.

biological activity↗

Normalized Solar-Induced Fluorescence Responds Earlier Than Vegetation Indices to the 2019 North China Plain Drought

Recently, solar-induced chlorophyll fluorescence (SIF) from satellites has shown potential for evaluating vegetation status and stress responses. Fluorescence quantum yield ($Φ_F$) is essentially linked to vegetation stress. However, the complex physiological and structural responses of SIF and $Φ_F$ to drought need further study. This study normalized SIF as SIFn to account for angular variations and fluctuations in photosynthetically active radiation (PAR), aiming for more accurate drought monitoring. SIFn anomalies were compared to historical baselines (2019–2021 averages) of vegetation indices (VIs), raw SIF, and $Φ_F$ during a 2019 drought in the North China Plain (NCP). Here, the results show SIFn provides an effective method for drought monitoring, showing the earliest decline compared to raw SIF, VIs, and $Φ_F$. In the first two weeks of drought, SIFn decreased by 8.2%, 7.0%, 12.5%, and 8.2% across the four NCP subdivisions. SIFn outperformed other indicators, proving sensitive to early drought detection. SIFn was also examined for tracking drought alleviation by rainfall. The uncertainty under different viewing geometries was quantified. SIFn anomalies showed a strong correlation with rainfall anomalies (R: 0.45 ~ 0.52) and meteorological factors like PAR (R: 0.80 ~ 0.84) and relative humidity (R:0.52 ~ 0.54). The correlation of near-infrared reflectance (NIRv) and $Φ_F$ anomalies with SIF was weak during drought onset (R: 0.16 ~ 0.32) but strong at the end (R: 0.83 ~ 0.87). These suggest both canopy structure (mainly characterized by NIRv) and vegetation chlorophyll ($Φ_F$) are impacted by drought and influence SIF at different stages.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Whole Ecosystem Warming (WEW) Environmental Data and Water Table Summaries, Marcell Experimental Forest, Minnesota, 2015-2024

This data set contains observations of photosynthetically active radiation (PAR), precipitation, soil temperature, soil volumetric water content, air temperature, relative humidity, and normalized water table depth that are summarized on a daily, weekly, monthly, and annual basis for each of the SPRUCE plots. Observations span 2015-2024. This dataset draws on several datasets (Hanson et al. 2016; Hanson et al. 2020; and Warren, unpublished data) and compiles these environmental observations into useful formats for data analysis. These environmental metrics can be used to understand the environmental conditions inside SPRUCE environmental chambers throughout the durations of the experiment and can be paired with other data for modeling and analysis. R code used to generate these files is provided as part of the data package. This dataset contains four data files in comma separate (.csv) format and a compressed folder (*.zip) containing three R (*.r) scripts. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. User note: Users must cite the original dataset/s along with this dataset when publishing any analyses using this dataset. Details on the dataset used to compile each variable are available in the header row of the files and in the user guide.

air temperature↗

Patch-level CO2 and CH4 fluxes and porewater concentrations in experimental wetlands, 5 and 10 PPT saltwater intrusion simulations, Louisiana 2023-2024

This dataset containes carbon dioxide (CO2) and methane (CH4) flux measurements collected from wetland vegetation patches dominated by Typha domingensis and Panicum hemitomon to assess greenhouse gas flux responses to experimental saltwater intrusion (SWI) pulses. Measurements were conducted before, during, and after simulated SWI events at target salinities of approximately 5 parts per thousand (ppt) with durations of 6, 10, and 17 days and 10 ppt with a duration of 48 days, alongside a control wetland (with no salinity added, flood manipulation only). These data were generated to evaluate how the magnitude and duration of SWI alter wetland carbon exchange and related biogeochemical and plant responses. This data package includes flux measurements from the wetland surface (i.e, soil/water surface and enclosed vegetation) and from the soil/water surface only; porewater and surface water concentrations of CO2 and CH4; salinity, pH, electrical conductivity collected in porewater (at 5, 10, and 20 cm soil depths) and in surface water; soil redox potential; leaf spectral indices, leaf vapor pressure deficit, stomatal conductance; water level, salinity, and photosynthetically active radiation; and aboveground biomass.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL RESPIRA↗

BTRIC Technical Support for Appalachia: FY 2024 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This report investigates the effects of various concentrations of CO 2 on the photosynthesis and biomass accumulation of crops growing in an AgPod, using kale as the test crop. In the first year of the study, increasing the CO 2 concentration in the AgPod was found to promote higher photosynthetic rates in kale plants up to 1,300 ppm (the highest CO 2 concentration measured). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until reaching unusually high levels of photosynthetically active radiation (PAR, > 1,200 µmol m -1 s -1 ) and CO 2 concentration (> 1,100 ppm). Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched controlled environment agriculture (ECEA). During the second year of the study, a second crop was planted to confirm the actual effects on growth with increased CO 2 concentrations. Our results suggest that growing kale plants in the AgPod system at higher CO 2 levels resulted in a successful and highly productive crop, up to three times the amount grown at 415 CO 2 . Further, the kale plants grown under higher CO 2 conditions (1000 ppm) are not CO 2 saturated and can potentially further improve yield at even higher CO 2 environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Iron dissolution from Patagonian dust in the Southern Ocean: under present and future conditions

Although the input of desert dust as a key source of trace metals in the Southern Ocean (SO) has been previously studied, the dissolution process of metals in surface waters, particularly iron (Fe), remain poorly understood. Given the crucial role of Fe in primary production and the biological carbon pump in the SO, we focused on experimental estimations of Fe dissolution from Patagonian dust, the primary natural dust source in the SO. Our study considered both current and projected future conditions, encompassing sea-surface warming, acidification, increased photosynthetically active radiation, and doubled dust inputs. Through controlled laboratory experiments using filtered SO seawater, conducted over 7 days, we assessed changes in particulate Fe (pFe) concentrations, Fe redox speciation (Fe(II)/Fe(III)), and in the mineralogy of Fe-bearing dust in abiotic condition. The predominant minerals in the dust included quartz and aluminosilicates, with silicon (Si), aluminum (Al), and Fe as the major elements. No significant alterations in the mineralogy and the elemental composition of the dust were recorded during the dissolution experiments, neither under present nor under projected future conditions. The particulate Fe(II)/Fe(III) ratio remained consistently at 0.25 during the experiments, unaffected by changed conditions. Consequently, changes in environmental conditions in the SO would therefore not significantly alter the mineralogy and redox speciation of pFe in the Patagonian dust. On the contrary, pFe exhibited a dissolution rate of 3.8% and 1.6% per day under present and future conditions, respectively. The environmental changes anticipated for 2100 in the SO will likely to result in a decrease in the dissolution rate of pFe. Thus, even though a doubling of dust input by 2100 is anticipated, it will unlikely provide significantly more dissolved Fe (dFe) in seawater in the SO. Consequently, the future intensification of Patagonian dust inputs may not alleviate the Fe limitation in the SO.

54 ENVIRONMENTAL SCIENCES↗

High-shade dryland agrivoltaic conditions enhanced carbon uptake and water-use efficiency in zucchini ( Cucurbita pepo )

Introduction: The increasing global demand for food and energy is intensifying land-use competition. Agrivoltaic systems are a multifunctional land-use approach that vertically integrates the production of agricultural crops and solar power on the same land area. Most food crops are adapted to full-sun conditions, and the physiological responses of these crops to the novel microclimate under solar panels remain poorly understood. We hypothesized that the microclimate beneath the high-density photovoltaic system would influence carbon uptake, water use, and yield outcomes of zucchini summer squash.Methods: We conducted a field experiment in a hot, semi-arid climate on zucchini (Cucurbita pepo). Plants were grown under an agrivoltaic system with a 75% ground cover ratio (GCR) and in a full-sun control plot, each with two irrigation regimes (100 and 50%). We measured leaf-level photosynthesis, microclimate variables, and fruit yield at plant maturity and throughout the growing season.Results: The agrivoltaic array reduced photosynthetically active radiation (PAR) by ~79%, resulting in a cooler (−1.1 °C), more humid environment with higher soil moisture. These microclimatic conditions enhanced midday photosynthesis and daily cumulative carbon uptake. However, fruit yield was consistently lower under the panels, indicating a shift in carbon allocation toward vegetative growth. Photosynthesis was primarily driven by PAR across treatments, while soil moisture significantly influenced photosynthesis only in the control plots, suggesting water limitation was alleviated under the panels.Discussion: These findings highlight a trade-off between improved physiological performance and reduced yield under high-density agrivoltaics. While the system buffered heat and drought stress and improved overall plant function, excessive shade reduced reproductive output. Optimizing panel density or selecting crops cultivated for non-fruit yields will be essential for balancing food production and energy generation in dryland agrivoltaic settings.

14 SOLAR ENERGY↗

An Adaptive Dynamic Agrivoltaic Production Tool

In the pursuit of sustainable and land-use-efficient solutions to mitigate climate change, the concept of agrivoltaic systems, which integrate renewable solar energy into conventional agriculture, has emerged. By deploying solar arrays above the crop field, these systems are designed to maximize the land use efficiency or, in other words, the value of generated electricity and crop yield per unit area. While power generation has been extensively studied and modeled, research gaps persist in simulating crop performance [1], [2]. Early studies utilized generalized relationships between photosynthetically active radiation (PAR) and crop production. However, significant variations in crop performance due to other factors, such as weather and soil, can compromise the reliability of the results [2]. Current studies focus on comprehensive process-based crop models, such as DSSAT [3] and STICS [4]. Nevertheless, the validation status varies greatly across different species, and the validation process requires well-designed experiments to adjust specific processes. For less common shade-tolerant crops with limited validation, such as cabbage, physiological behaviors can be difficult to predict [5]. This study investigates an adaptive dynamic agrivoltaic production tool (ADAPT) with few data requirements and minimal on-site calibration that can be easily applied in real applications.

Long, Qirui↗

NGEE Arctic Tram: Radiation and Environmental Measurements over Low- and High-Centered Polygon Vegetation Communities, Barrow, Alaska, 2014-2017

These data were generated from an observational platform (Tram), an automated cart carrying a suite of radiation and remote sensing instruments running on 68 meters of elevated track 1 to 1.5 meters above the surface of the vegetation communities of low- and high-centered polygon ground. The Tram is in the footprint of the NGEE Arctic/AmeriFlux eddy covariance flux tower (US-NGB) at the Barrow Environmental Observatory, Barrow, Alaska, and operated before, during, and after the growing seasons of 2014-2017. Dataset includes one user guide (*.pdf) with final and raw *.csv data files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

CO2 Profiling System for CO2 Storage (a1-level)

The Southern Great Plains (SGP) carbon dioxide flux (CO2FLUX) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), sensible heat, and momentum. The systems use the eddy covariance technique, which computes the fluxes from the vertical wind speed in combination with the concentrations of CO2 and H2O, temperature, and horizontal wind speed, respectively. A 3D sonic anemometer obtains the wind components and the temperature, while an infrared gas analyzer measures CO2 and H2O. A sub-system also measures half-hour averages of radiation, meteorological, and soil measurements.

54 ENVIRONMENTAL SCIENCES↗

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↗

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment 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 Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. 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 variable-specific 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, 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 normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 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↗

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 2 Sensor Data v2-1

This is the version v2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. 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. Please see v2-1 TEMPEST L2 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. 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. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗

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↗

Leafweb: Leaf Gas Exchange and Pulse-Amplitude Modulated Fluorometry for C4 Species, June 2026 Release

This dataset contains leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry for 98 C4 species. The C4 photosynthetic pathway employs specialized CO2 concentration mechanisms and Kranz anatomy to enrich CO2 concentration around Rubisco, the enzyme that catalyzes carbon fixation in the Calvin-Benson cycle to suppress photorespiration and increase the use efficiencies of light, nitrogen, and water as compared to the C3 photosynthetic pathways. Large-scale C4 photosynthetic datasets are relatively scarce, which has affected C4 photosynthesis research. To improve C4 photosynthetic data availability, Leafweb organized an effort to systematically collect, compile, standardize, and organize measurements of leaf gas exchange and/or Pulse-Amplitude Modulated (PAM) fluorometry of C4 species. This derived a C4 photosynthetic dataset containing measurements made by independent researchers in multiple countries in various environments (field, garden, or greenhouse). It covers three biochemical subtypes – the nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME), nicotinamide adenine dinucleotide-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK) subtypes. This dataset is useful for using Artificial Intelligence / Machine Learning and mechanistic models to study C4 photosynthesis and compare across different biochemical subtypes. This dataset contains 3 compressed (*.zip) folders containing 1,892 data files in comma-separate values (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Zhou, Haoran [Tianjin University, China]↗

Impacts of Dual-Use Solar (Agrivoltaics) on Crop Productivity and the Agricultural Economy in Massachusetts and Beyond

This project contributes applied research to better understand the impacts of agrivoltaics on farm microclimates, crop productivity, and economics at the farm and sector level. The site trial research is divided into two sets of site trials integrated into commercial farm and agrivoltaic operations – one set on annual vegetable and hay crops and one on perennial cranberry bog operations. The economic research developed methods for recording and evaluating changes in farm operations and costs, and on the public perception of and willingness-to-accept agrivoltaics.

14 SOLAR ENERGY↗

Effect of glutathione-coated Mn-doped ZnS quantum dots on nutrient delivery in basil ( Ocimum basilicum ) plants

Ensuring efficient nutrient delivery while minimizing environmental impacts remains a significant challenge for modern agriculture. Nanotechnology-based fertilizers offer promising strategies to improve nutrient uptake and bioavailability in plants. This research aims to evaluate the use of Glutathione-coated Manganese-doped Zinc Sulfide quantum dots (GSH-ZnS-Mn QDs) as a potential nano fertilizer for basil (Ocimum basilicum). QDs' physicochemical properties were characterized using UV–Vis spectroscopy, photoluminescence, FTIR, and energy-dispersive X-ray spectroscopy, confirming successful Mn doping and glutathione surface functionalization. Basil plants were exposed to different concentrations of GSH-ZnS-Mn QDs under soil and hydroponic conditions. Plant growth parameters, oxidative stress responses, photosynthetic pigments, and macro- and micronutrient uptake were assessed using biochemical assays and inductively coupled plasma optical emission spectrometry (ICP-OES). Elemental uptake, spatial distribution, and zinc speciation were further investigated using synchrotron-based micro-X-ray fluorescence (μ-XRF) imaging and X-ray absorption near-edge structure (XANES) spectroscopy. Results show that exposure to GSH-ZnS-Mn QDs resulted in a concentration-dependent increase in leaf and stem biomass, accompanied by enhanced Zn accumulation in plant tissues. Catalase activity decreased across all tested concentrations, suggesting a shift toward glutathione-dependent antioxidant pathways rather than oxidative damage. Chlorophyll levels exhibited moderate reductions at higher concentrations. The higher increase in macronutrient (K, Ca, and Mg) uptake was reported in plants exposed to 200 ppm of QDs. μ-XRF imaging indicated a selective accumulation of Zn in roots and stems, with partial translocation to leaves. XANES analyses revealed that Zn from QDs was mainly converted into organic Zn species, such as Zn-phytate, Zn-acetate, and Zn-cysteine, indicating transformation and complexation within the plant. The findings demonstrate that a glutathione coating on GSH-ZnS-Mn QDs improves biocompatibility and nutrient delivery efficiency. These results highlight the relevance of surface functionalization in regulating nanoparticle fate, transformation, and nutrient bioavailability, supporting the potential application of GSH–ZnS–Mn QDs as modern nano fertilizers.

Basil↗