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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Duration of O 2 Exposure Determines Dominance of Fe II vs CH 4 Production in Tropical Forest Soils

Temporal fluctuations in redox conditions influence the availability of Fe III and greenhouse gas emissions in humid upland soils. However, the impact of fluctuation duration on biogeochemical processes remains unclear. We hypothesized that rates of Fe III reduction and CH 4 production are sensitive to the duration of soil oxygenation. To test this, surface soil from the Luquillo Forest, Puerto Rico, was subjected to fluctuating redox conditions with an anoxic interval of 6 days followed by oxic intervals of either 8, 24, or 72 h. Shorter oxic intervals enhanced Fe reduction, while longer oxic intervals enhanced CH 4 emissions. As O 2 exposure decreased from 72 to 8 h, Fe reduction rates increased from 0.12 ± 0.02 to 0.26 ± 0.05 mmol kg –1 h –1 , whereas cumulative CH 4 decreased from 44.0 ± 4.7 to 12.7 ± 4.6 μmol kg –1 . 13 C-amino acid spikes were preferentially incorporated into the DNA of iron reducers (Anaeromyxobacter sp.) in the shorter oxic treatment (8 h vs 24 h), suggesting that Fe reducers are less inhibited by shorter periods of oxidation. Conversely, longer oxygen pulses appear to suppress Fe reducers more than methanogens, leading to increased CH 4 emissions. These findings highlight the role of the redox oscillation length in modulating biogeochemical processes and greenhouse gas emissions in soils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Diurnal and Seasonal Dynamics of Solar-Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides a powerful proxy for gross primary productivity (GPP). It is particularly promising in boreal ecosystems where seasonal downregulation of photosynthesis occurs without significant changes in canopy structure or chlorophyll content. The use of SIF as a proxy for GPP is complicated by inherent non-linearities due to both physical (illumination effects) and ecophysiological (light use efficiencies) controls at fine spatial (tower/leaf) and temporal (half-hourly) scales. Here, to study the SIF-GPP relationship, we investigated the diurnal and seasonal dynamics of continuous tower-based measurements of SIF, GPP, and common vegetation indices at the Southern Old Black Spruce Site (SOBS) in Saskatchewan, CA over the course of two years. We find that SIF outperforms other vegetation indices as a proxy for GPP at all temporal scales but shows a non-linear relationship with GPP at a half-hourly resolution. At small temporal scales, SIF and GPP are predominantly driven by light and non-linearity between SIF and GPP is due to the light saturation of GPP. Averaged over daily and monthly scales, the relationship between SIF and GPP is linear due to a reduction in the observed PAR range. Seasonal changes in the light responses of SIF and GPP are driven by changes in light use efficiency which co-vary with changes in temperature, while illumination and canopy structure partially linearize the SIF-GPP relationship. Additionally, we find that the SIF-GPP relationship has a seasonal dependency. Our results help clarify the utility of SIF for estimating carbon assimilation in boreal forests.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An emulator for the Lyman-α forest in beyond-ΛCDM cosmologies

Interpreting observations of the Lyman-α forest flux power spectrum requires interpolation between a small number of expensive simulations. We present a Gaussian process emulator modelling the 1D flux power spectrum as a function of the amplitude and slope of the small-scale linear matter power spectrum, and the state of the intergalactic medium at the epoch of interest (2 < z < 4). This parameterisation enables the prediction of the flux power spectrum in extended cosmological models that are not explicitly included in the training set, eliminating the need to construct bespoke emulators for a number of extensions to ΛCDM. Our emulator is appropriate for cosmologies in which the linear matter power spectrum is described to percent level accuracy by just an amplitude and slope across the epoch of interest, and in the regime probed by eBOSS/DESI data. We demonstrate this for massive neutrino cosmologies, where the emulator is able to predict the flux power spectrum in a Σm ν = 0.3 eV neutrino cosmology to sub-percent accuracy, without including massive neutrinos in the training simulations. Further parameters would be required to describe models with sharp features in the linear power, such as warm or light axion dark matter. This work will facilitate the combination of upcoming DESI data with observations of the cosmic microwave background, to obtain constraints on neutrino mass and other extensions to ΛCDM cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

3D correlations in the Lyman-α forest from early DESI data

We present the first measurements of Lyman-α (Lyα) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Lyα absorption using 88 509 quasars at z > 2, and its cross-correlation with quasars using a further 147 899 tracer quasars at z ≳ 1.77. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of 3.8σ, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. As a result, we validate the existing analysis methods of Lyα correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Synthetic spectra for Lyman- α forest analysis in the Dark Energy Spectroscopic Instrument

Synthetic data sets are used in cosmology to test analysis procedures, to verify that systematic errors are well understood and to demonstrate that measurements are unbiased. In this work we describe the methods used to generate synthetic datasets of Lyman-α quasar spectra aimed for studies with the Dark Energy Spectroscopic Instrument (DESI). In particular, we focus on demonstrating that our simulations reproduces important features of real samples, making them suitable to test the analysis methods to be used in DESI and to place limits on systematic effects on measurements of Baryon Acoustic Oscillations (BAO). We present a set of mocks that reproduce the statistical properties of the DESI early data set with good agreement. Additionally, we use a synthetic dataset to forecast the BAO scale constraining power of the completed DESI survey through the Lyman-α forest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Widespread windthrow in Southeast Asian tropical forests verified by satellite observations

Windthrow, defined as abrupt tree mortality caused by intense winds, is well documented in the Neotropics but remains largely unverified in Asian tropical forests. Using Landsat 8 imagery for the period 2020-2022 and established spectral (shortwave-infrared, near-infrared, and red band composites) and morphological criteria (fan-shaped geometry and sharp boundaries), this study verified the presence of windthrow across Sumatra, Borneo, and New Guinea and produced the first georeferenced inventory of 60 events in the region. Event sizes were right-skewed, with many small gaps and few large (>200 ha) disturbances. Orientations were anisotropic, with concentrations of windthrow events pointing west to northwest-to-north and eastward, both aligning with known pathways of organized convection in the Maritime Continent of Southeast Asia. Detection was conservatively biased low by cloud cover, long revisit intervals, and the exclusion of land-use areas. This study provides a verified baseline that enables reproducible mapping with higher resolution sensors and field observations to quantify windthrow frequency, severity, and ecological significance.

Asia’s tropical forests↗
DOE OSTI2022

Effects of short-interval reburns in the boreal forest on soil bacterial communities compared to long-interval reburns

Abstract Increasing fire frequency in some biomes is leading to fires burning in close succession, triggering rapid vegetation change and altering soil properties. We studied the effects of short-interval (SI) reburns on soil bacterial communities of the boreal forest of northwestern Canada using paired sites (n = 44). Both sites in each pair had burned in a recent fire; one site had burned within the previous 20 years before the recent fire (SI reburn) and the other had not. Paired sites were closely matched in prefire ecosite characteristics, prefire tree species composition, and stand structure. We hypothesized that there would be a significant effect of short vs. long fire-free intervals on community composition and that richness would not be consistently different between paired sites. We found that Blastococcus sp. was consistently enriched in SI reburns, indicating its role as a strongly ‘pyrophilous’ bacterium. Caballeronia sordidicola was consistently depleted in SI reburns. The depletion of this endophytic diazotroph raises questions about whether this is contributing to—or merely reflects—poor conifer seedling recolonization post-fire at SI reburns. While SI reburns had no significant effect on richness, dissimilarity between short- and long-interval pairs was significantly correlated with difference in soil pH, and there were small significant changes in overall community composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Stability of tropical forest tree carbon-water relations in a rainfall exclusion treatment through shifts in effective water uptake depth

Increasing severity and frequency of drought is predicted for large portions of the terrestrial biosphere, with major impacts already documented in wet tropical forests. Using a 4-year rainfall exclusion experiment in the Daintree Rainforest in northeast Australia, we examined canopy tree responses to reduced precipitation and soil water availability by quantifying seasonal changes in plant hydraulic and carbon traits for 11 tree species between control and drought treatments. Even with reduced soil volumetric water content in the upper 1 m of soil in the drought treatment, we found no significant difference between treatments for predawn and midday leaf water potential, photosynthesis, stomatal conductance, foliar stable carbon isotope composition, leaf mass per area, turgor loss point, xylem vessel anatomy, or leaf and stem nonstructural carbohydrates. While empirical measurements of aboveground traits revealed homeostatic maintenance of plant water status and traits in response to reduced soil moisture, modeled belowground dynamics revealed that trees in the drought treatment shifted the depth from which water was acquired to deeper soil layers. Finally, these findings reveal that belowground acclimation of tree water uptake depth may buffer tropical rainforests from more severe droughts that may arise in future with climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗
DOE OSTI2023

Comparing Individualized Survival Predictions From Random Survival Forests and Multistate Models in the Presence of Missing Data: A Case Study of Patients With Oropharyngeal Cancer

Background: In recent years, interest in prognostic calculators for predicting patient health outcomes has grown with the popularity of personalized medicine. These calculators, which can inform treatment decisions, employ many different methods, each of which has advantages and disadvantages. Methods: We present a comparison of a multistate model (MSM) and a random survival forest (RSF) through a case study of prognostic predictions for patients with oropharyngeal squamous cell carcinoma. The MSM is highly structured and takes into account some aspects of the clinical context and knowledge about oropharyngeal cancer, while the RSF can be thought of as a black-box non-parametric approach. Key in this comparison are the high rate of missing values within these data and the different approaches used by the MSM and RSF to handle missingness. Results: We compare the accuracy (discrimination and calibration) of survival probabilities predicted by both approaches and use simulation studies to better understand how predictive accuracy is influenced by the approach to (1) handling missing data and (2) modeling structural/disease progression information present in the data. We conclude that both approaches have similar predictive accuracy, with a slight advantage going to the MSM. Conclusions: Although the MSM shows slightly better predictive ability than the RSF, consideration of other differences are key when selecting the best approach for addressing a specific research question. These key differences include the methods’ ability to incorporate domain knowledge, and their ability to handle missing data as well as their interpretability, and ease of implementation. Ultimately, selecting the statistical method that has the most potential to aid in clinical decisions requires thoughtful consideration of the specific goals.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest

Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Data, Photographs, Videos, and Information for the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about the operation of the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) between Nov 1998 to the present (2020). This data archive supplements the primary 30-min data storage for the US-NR1 data (i.e., https://doi.org/10.17190/AMF/1246088) by providing the following: (i) five-minute statistics (means, variances, covariances) of all data measured by the data system between Nov 1998 and September 2020 in netCDF format, (ii) CSV data files saved within the memory of the CR23X data loggers (as well as an archive of the data logger programs), (iii) an archive of previous 30-min ASCII data versions of the US-NR1 AmeriFlux data and information related to each data release (a replica of what can be found at http://urquell.colorado.edu/data_ameriflux/), (iv) a web calendar (in HTML format) documenting activity at the site (a replica of http://urquell.colorado.edu/calendar/), (v) photos (over 15,000) and video taken at the site between years 2001 and present day (2020), and (vi) several auxiliary datasets, primary related to trees near the site, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the PDF: README_ESS_DIVE_USNR1_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comparing the Recovery of Arbuscular and Ectomycorrhizal Stands from Long-Term Nitrogen Fertilization at the Fernow Experimental Forest, WV (2021 and 2022)

This data was generated to answer the research question: After the end of a 30-year nitrogen (N) fertilization experiment in an Eastern temperate forest, to what extent do plant microbial interactions and carbon cycling in arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) dominated stands follow different recovery trajectories?The soil and the roots used in this dataset were sampled from two watersheds (N-fertilized watershed 3 and Reference watershed 7) with 6 AM and 6 ECM dominated stands each, over the course of three months (June, July, August) in 2021 and 2022. The "All_Roots.csv" data includes fine root biomass (in g) scaled to sampled soil (m2) (Scaled_Rt_Bm_gm2), and AM and ECM root colonization (%) in two soil fractions: the organic horizon (O) and the mineral horizon (B). The "All_Enzymes.csv" data includes extracellular soil enzyme activity (N-acetyl-glucosaminidase (NAG), acid phosphatase (AP), β-glucosidase (BG), phenol oxidase and peroxidase), and the ratios of BG to AP (BG:AP) and BG to NAG (BG:NAG) in three soil fractions: the organic horizon (O), the bulk soil (B), and the rhizosphere (R).The "All_Nmin" data includes inorganic N (NO3- and NH4+) pools (unit: μg of N per g of dry soil) measured pre- (I_Nitrate_ugNgsoil and I_Ammonia_ugNgsoil) and post-incubation (F_Nitrate_ugNgsoil and F_Ammonia_ugNgsoil), as well as calculated nitrification (Nitrification_day) and nitrogen mineralization (Mineralization_day) rates per day, in three soil fractions: the organic horizon (O), the bulk soil (B), and the rhizosphere (R).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Evaluating the Persistence of Soil Carbon After a 30-Year Nitrogen Fertilization Experiment at the Fernow Experimental Forest, WV

We sampled soils in a previously nitrogen (N)-fertilized watershed (Watershed 3), which received 35 kg N per hectare annually for 30 years, and a reference watershed (Watershed 7), 4 years after the end of a 30-year N fertilization experiment at the Fernow Experimental Forest in West Virginia. As N deposition has reduced soil pH and plant carbon (C) investments into the rhizosphere, we compared the extent to which removing these potential limitations to microbial decomposition by increasing soil pH, adding artificial root exudates, or elevating soil temperature would increase microbial decomposition (and soil C losses) in soils that have and have not received excess N inputs. As such, we incubated soils with and without the addition of artificial root exudates and dolomitic lime (2 amendment treatments and 1 untreated control), at three different temperatures (15, 20, and 25 C) to simulate warming. We measured soil respiration, enzyme activity (acid phosphatase, N -acetyl-β-glucosaminidase, beta-glucosidase, phenol oxidase, and peroxidase), and microbial biomass carbon in a 15-week microcosm experiment. All of the datasheets include the metadata for all of the treatment combinations from this incubation experiment (ID, incubation temperature, treatment, watershed).The "Soil_Chemistry_Data.csv" data includes (1) the ratio of dry soil weight (g) by wet (or fresh) soil weight (g) after 72 hours at 65 C, (2) the wet (or fresh) weight of the soil samples used to determine soil pH, and (3) soil pH, which was measured in CaCl2. Detailed methods for the measurements of soil pH are described in the datasheet itself.The "Respiration_Data.csv" data includes (1) respiration day for the measurement, and (2) cumulative CO2 respiration (mmol) measured in the microcosms on specific days.The "Microbial_Biomass_Data.csv" data includes (1) mmol microbial biomass carbon per g (dry weight) of soil in each microcosm.The "Enzyme_Data.csv" data includes (1) all extracellular soil enzyme activity (N-acetyl-glucosaminidase (NAG), acid phosphatase (AP), β-glucosidase (BG), phenol oxidase and peroxidase) that we measured in our microcosms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

High resolution characterization of soil dissolved organic matter with FTICR-MS (Fourier-transform ion cyclotron resonance mass spectrometry) from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.This package contains Fourier transform ion cyclotron resonance mass spectrometry (21 Tesla FTICR-MS) data measured in negative and positive ionization mode from water and methanol soil extracts. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) fticr_neg_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (2) fticr_neg_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in negative ion mode, (3) fticr_neg_metadata.csv: metadata for samples/measurements in negative ion mode, (4) fticr_pos_h2oMeoh_data_raw.csv: raw data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (5) fticr_pos_h2oMeoh_data_processed.csv: processed data from combined water (H2O) and methanol (MeOH) extracts in positive ion mode, (6) fticr_pos_metadata.csv: metadata for samples/measurements in positive ion mode.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

SPRUCE Aboveground Vegetation Coverage in Root Ingrowth Core Plots, Marcell Experimental Forest, Minnesota, August 2022

This dataset contains vegetation survey measurements from root ingrowth core plots (Määttä et al. 2025) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. Vegetation surveys were conducted in 0.25 meter2 plots containing root ingrowth cores on August 8th and 9th, 2022 (2022-08-08 to 2022-08-09). The warming and elevated carbon dioxide (CO2) treatments in the dataset include the full treatment gradient: +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +2.25 degrees C (+0 and +500 ppm), +4.5 degrees C (+0 and +500 ppm elevated CO2), +6.75 degrees C (+0 and +500 ppm) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows. This dataset includes measurements of the height and absolute coverage (%) for each vascular plant and moss species, as well as organic litter and dead overstory vascular plants, and the distance from the grid center to the nearest tree and the species of the nearest tree. These data were used as species-specific aboveground plant metadata for assessing the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. 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.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2025

SPRUCE Measurements of Fine Root Production and Chemistry from Root Ingrowth Cores, Marcell Experimental Forest, Minnesota, 2022-2023

This dataset contains fine root production and tissue chemistry measurements from root ingrowth cores. Ingrowth cores were deployed in peat from June 28, 2022 to June 24, 2023 (2022-06-28 to 2023-06-24) inside SPRUCE Experiment plots at the Marcell Experimental Forest in northern Minnesota. The warming and elevated carbon dioxide (CO2) treatments in this dataset include +0 degrees Celsius (C) (+0 and +500 parts per million (ppm) elevated CO2), +4.5 degrees C (+0 and +500 ppm elevated CO2) and +9 degrees C (+0 and +500 ppm elevated CO2) for both hummocks and hollows, as well as +2.25 degrees C (+0 and +500 ppm) and +6.75 degrees C (+0 and +500 ppm) for hollows from minimum 10 cm depth from the peat surface. Measurements include root average diameter, root length, root biomass, and root tissue nitrogen (%N and δ15N) and carbon (%C and δ13C) concentration per plant functional type and microtopographical feature. Root length and biomass are standardized to 10 cm depth. These data were used to assess the warming and elevated CO2 response of fine roots across different peatland microtopographical features (hummocks and hollows) and plant functional types (shrub, spruce and larch). This dataset contains one data file in comma separate (.csv) format. 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.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗
DOE OSTI2026

SPRUCE Bud Cold Hardiness of Trees and Shrubs in Experimental Plots, Marcell Experimental Forest, Minnesota, 2021-2025

This dataset contains bud cold hardiness measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site (Hanson et al, 2017) within the Marcell Experimental Forest in northern Minnesota, USA. Cold hardiness was quantified as the temperature at which low temperature exotherms (LTEs) were identified (i.e., the temperature at which supercooled water within a bud freezes) measured by differential thermal analysis (DTA). Buds were sampled at semi-regular intervals from September 2021 through May 2025 (2021-09-25 to 2025-05-21) across four seasons (2021-2022 through 2024-2025) for four co-occurring boreal peatland tree and shrub species: Picea mariana (PIMA), Larix laricina (LALA), Rhododendron groenlandicum (RHGR), and Chamaedaphne calyculata (CHCA). Samples were collected across the experiment's warming gradient (ambient to +9 degrees Celsius (C)) and pooled by species within each enclosure. These data were used to assess the species- and season-specific effects of experimental warming on cold hardiness and cold damage risk in boreal peatland vegetation (Campos-Arguedas et al, accepted). This dataset contains one data file in comma-separate values (*.csv) format. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Chamaedaphne calyculata↗