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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Lake development and vegetation history in coastal Primor'ye: implications for Holocene climate of the southeastern Russian Far East

Latvia Lake provides one of the few high-resolution palaeoenvironmental records from southeastern Primor'ye. It traces basin, vegetation and climate histories over the past c. 8.6 ka. The Latvia basin experienced four phases, two of which involved frequent shifts amongst lake, lagoon and bay settings (c. 8.6–7.0 cal. ka BP and c. 2.1 cal. ka BP–present). A sandbar was present between c. 7.0 and 6.9 cal. ka BP. The longest interval of Latvia basin stability was from c. 6.9–2.1 cal. ka BP when the basin was a lagoon of varying salinities. Quercus-broadleaf forests characterized the regional vegetation throughout the past c. 8.6 ka. Variations in thermophilous species (e.g. Juglans,Carpinus,Ulmus,Tilia,Syringa) and Pinus koraiensis reflect shifts in temperature and moisture during the Middle Holocene. A period of warmest climate occurred c. 8.6–5.1 cal. ka BP with wettest conditions from c. 7.5–4.3 cal. ka BP, although all changes in temperature and precipitation were gradual. The Latvia Lake results indicate that changes in Middle to Late Holocene climates were linked more closely to shifts in the East Asian Summer Monsoon and less so to sea level oscillations. Here, this investigation demonstrates that lakes of coastal Primor'ye can provide reliable palaeovegetation and palaeoclimate records despite their changing depositional environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Interplay between LHCSR proteins and state transitions governs the NPQ response in Chlamydomonas during light fluctuations

Abstract Photosynthetic organisms use sunlight as the primary energy source to fix CO 2 . However, in nature, light energy is highly variable, reaching levels of saturation for periods ranging from milliseconds to hours. In the green microalga Chlamydomonas reinhardtii , safe dissipation of excess light energy by nonphotochemical quenching (NPQ) is mediated by light‐harvesting complex stress‐related (LHCSR) proteins and redistribution of light‐harvesting antennae between the photosystems (state transition). Although each component underlying NPQ has been documented, their relative contributions to NPQ under fluctuating light conditions remain unknown. Here, by monitoring NPQ in intact cells throughout high light/dark cycles of various illumination periods, we find that the dynamics of NPQ depend on the timescales of light fluctuations. We show that LHCSRs play a major role during the light phases of light fluctuations and describe their role in growth under rapid light fluctuations. We further reveal an activation of NPQ during the dark phases of all high light/dark cycles and show that this phenomenon arises from state transition. Finally, we show that LHCSRs and state transition synergistically cooperate to enable NPQ response during light fluctuations. These results highlight the dynamic functioning of photoprotection under light fluctuations and open a new way to systematically characterize the photosynthetic response to an ever‐changing light environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Taxonomic distribution of metabolic functions in bacteria associated with Trichodesmium consortia

The photosynthetic and diazotrophic cyanobacterium Trichodesmium is a key contributor to marine biogeochemical cycles in the subtropical-oligotrophic oceans. Trichodesmium form colonies that harbor a distinct microbial community in comparison to the surrounding seawater. The presence of their associated bacteria can expand Trichodesmium’s functional potential and is predicted to influence the cycling of carbon, nitrogen, phosphorus, and iron (C, N, P, and Fe). To link the bacteria associated with Trichodesmium to key functional traits and elucidate how community structure can influence nutrient cycling, we characterized Red Sea Trichodesmium colonies using metagenomics and metaproteomics. Colonies harbored bacteria that typically associate with algae and particles, such as the ubiquitous Alteromonas macleodii, but also lineages specific to Trichodesmium, such as members from the order Balneolales. The majority of associated bacteria were auxotrophic for different vitamins, indicating their dependency on vitamin production by Trichodesmium. The associated bacteria carry functional traits including siderophore biosynthesis, reduced phosphorus metabolism, and denitrification pathways. The analysis supports Trichodesmium as an active hotspot for C, N, P, Fe, and vitamin exchange. In turn, Trichodesmium may rely on associated bacteria to meet its high Fe demand as several lineages synthesize photolabile siderophores (e.g., vibrioferrin, rhizoferrin, petrobactin) which can enhance the bioavailability of particulate Fe to the entire consortium. Collectively, the results indicate that Trichodesmium colonies provide a structure where these interactions can take place. While further studies are required to clarify the exact nature of these interactions, Trichodesmium’s reliance on particle and algae-associated bacteria and the observed redundancy of key functional traits likely underpins the resilience of Trichodesmium within an ever-changing global environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metagenomics-resolved genomics provides novel insights into chitin turnover, metabolic specialization, and niche partitioning in the octocoral microbiome

Abstract Background The role of bacterial symbionts that populate octocorals (Cnidaria, Octocorallia) is still poorly understood. To shed light on their metabolic capacities, we examined 66 high-quality metagenome-assembled genomes (MAGs) spanning 30 prokaryotic species, retrieved from microbial metagenomes of three octocoral species and seawater. Results Symbionts of healthy octocorals were affiliated with the taxa Endozoicomonadaceae , Candidatus Thioglobaceae , Metamycoplasmataceae , unclassified Pseudomonadales , Rhodobacteraceae , unclassified Alphaproteobacteria and Ca. Rhabdochlamydiaceae . Phylogenomics inference revealed that the Endozoicomonadaceae symbionts uncovered here represent two species of a novel genus unique to temperate octocorals, here denoted Ca. Gorgonimonas eunicellae and Ca. Gorgonimonas leptogorgiae . Their genomes revealed metabolic capacities to thrive under suboxic conditions and high gene copy numbers of serine-threonine protein kinases, type 3-secretion system, type-4 pili, and ankyrin-repeat proteins, suggesting excellent capabilities to colonize, aggregate, and persist inside their host. Contrarily, MAGs obtained from seawater frequently lacked symbiosis-related genes. All Endozoicomonadaceae symbionts harbored endo-chitinase and chitin-binging protein-encoding genes, indicating that they can hydrolyze the most abundant polysaccharide in the oceans. Other symbionts, including Metamycoplasmataceae and Ca. Thioglobaceae , may assimilate the smaller chitin oligosaccharides resulting from chitin breakdown and engage in chitin deacetylation, respectively, suggesting possibilities for substrate cross-feeding and a role for the coral microbiome in overall chitin turnover. We also observed sharp differences in secondary metabolite production potential between symbiotic lineages. Specific Proteobacteria taxa may specialize in chemical defense and guard other symbionts, including Endozoicomonadaceae , which lack such capacity. Conclusion This is the first study to recover MAGs from dominant symbionts of octocorals, including those of so-far unculturable Endozoicomonadaceae , Ca. Thioglobaceae and Metamycoplasmataceae symbionts. We identify a thus-far unanticipated, global role for Endozoicomonadaceae symbionts of corals in the processing of chitin, the most abundant natural polysaccharide in the oceans and major component of the natural zoo- and phytoplankton feed of octocorals. We conclude that niche partitioning, metabolic specialization, and adaptation to low oxygen conditions among prokaryotic symbionts likely contribute to the plasticity and adaptability of the octocoral holobiont in changing marine environments. These findings bear implications not only for our understanding of symbiotic relationships in the marine realm but also for the functioning of benthic ecosystems at large.

59 BASIC BIOLOGICAL 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 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↗
DOE OSTI2021

2020 Annual Site Environmental Report for Sandia National Laboratories, New Mexico

Sandia National Laboratories, hereinafter referred to as Sandia, is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. This Annual Site Environmental Report was prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting , and is approved for public release. The U.S. Department of Energy (DOE) and its management and operating contractor for Sandia are committed to safeguarding the environment, continually assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented here. This report summarizes the environmental protection, restoration, and monitoring programs in place for Sandia National Laboratories, New Mexico (SNL/NM), during calendar year 2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

2021 Site Environmental Report (SER) for the Ernest Orlando Lawrence Berkeley National Laboratory (LBNL)

Lawrence Berkeley National Laboratory (LBNL, Berkeley Lab) is a multiprogram scientific facility operated by the University of California (UC) for the U.S. Department of Energy (DOE). Berkeley Lab’s research is focused on the physical, biological, environmental, and computational sciences, with the objective of delivering scientific knowledge and discoveries pertinent to DOE’s mission. This annual report describes environmental protection activities and potential impacts resulting from operations conducted in calendar year 2021, unless otherwise indicated. The format and content of this report satisfy the requirements of both DOE Order 231.1B, Administrative Change 1 (Environment, Safety, and Health Reporting) (DOE, 2012) and the operating contract between UC and DOE (DOE Contract No. DE-AC02-05CH11231, also known as Contract 31).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Advancing Transportation Efficiency and Electric Vehicles in Tonga: A Review of Relevant Trends and Best Practices

Tonga is facing a transportation sector characterized by private passenger vehicles, poorly maintained roads and walkways, and an inadequate public transit system. By understanding detailed global and regional trends for transport energy efficiency and electric vehicles (EVs) within this context, the Government of Tonga can proactively plan its future transportation systems. In addition to global and regional trends, this report also covers a variety of international case studies and examines Tonga's own transportation policies and actions through this lens. Jurisdictions leading in EV adoption have implemented policies such as reducing taxes on EVs compared to internal combustion engine (ICE) vehicles, providing subsidies and rebates for EV charger installation, instituting an age limit on imported ICE vehicles, and developing EV maintenance courses to expand the skill set of current automotive technicians. Although there are key challenges and barriers to widespread EV adoption in Tonga, multiple studies have researched potential political, technical, financial, and educational interventions that can be adapted and applied in Tonga. Therefore, the purpose of this report is to synthesize the relevant trends and best practices in order to provide Tonga's Ministry of Meteorology, Energy, Information, Disaster Management, Environment, Climate Change and Communication (MEIDECC) with a wide range of information on electric vehicles (EVs) and transportation efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Los Alamos National Laboratory Director's Strategic Resilience Initiative

The Director’s Strategic Resilience Initiative was created late in 2019 in recognition of the changing geo-political climate. The renewed strategic competition between Russia, China, and the United States, noted in the 2018 National Defense Strategy and the 2018 Nuclear Posture Review, put great power rivalry and competition at the forefront of national security considerations. At the same time, Russian President Vladimir Putin’s March 1, 2018, speech and China’s October 1, 2019, National Day Military Parade, underscored the nuclear dimensions of this new strategic competition. Accompanying this changed strategic environment are rapid advances in an expansive array of relevant technological sectors including affordable and comprehensive global communication and reconnaissance assets, autonomous vehicles, quantum computing, advanced manufacturing, and artificial intelligence.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Sequential Decision Making (SDM) for Mesh Refinement and Model Selection in Multiscale, Multi-Physics Applications

Intelligent automation and decision support are needed to enhance computational efficiency and robustness in multiscale and multi-physics problems, including materials science, manufacturing, and climate and weather modeling. Current scientific computing approaches for enabling decisions by scientists fail to explore the role of learning, reasoning, and probabilistic planning. Often these decisions are not performed in real-time during the computation but are made prior to the start of the computation, which must be interrupted in order to make changes to the prior choices. Such interruptions at different stages of the computation increase the total computing time and the need for a human expert to frequently monitor the results. State of art scientific computing methods consist of rule-based algorithms that cannot automatically adapt to a dynamically changing computing environment. The development of a Sequential Decision Making (SDM) framework will automate scientific computing by optimizing the policies for mesh refinement, time-stepping, model and algorithm selection, resource allocation, and pre and post-processing. Our agent SDM framework for scientific computing will consist of data-driven learning (Classifier), automated reasoning (contextual knowledge), and probabilistic planning (Reinforcement Learning). In this project, we focused on three problems to demonstrate our SDM framework on a set of ordinary and partial differential equations. Classification of Lorenz system regions using Feed-Forward Neural Networks examined learning in the SDM framework. On the other hand, reasoning and planning in the SDM framework were used in two problems: adaptive time-stepping for nonlinear ODEs using on-policy RL algorithms, and adaptive mesh refinement for 2-D PDEs using off-policy RL algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Potential Applications of Quantum Computing at Los Alamos National Laboratory, v0.3.0

Since the scientific revolution in the 16th and 17th centuries, the process of scientific discovery has followed an iterative feedback process of observation, hypothesis development and testing with physical experiments, which is widely referred to as the scientific method. This process remained largely unchanged until the middle of the 20th century, when the emergence of digital computers empowered scientist to build and inspect detailed simulations of physical phenomena. Over the last century, computational tools have transformed modern approaches to scientific discovery by enabling fast and affordable hypothesis testing before physical experiments are conducted, shown in Figure 1-1. Some notable examples include: global climate forecasts to understand how the environment may change over decades [130]; modeling the behavior of plasma to design fusion reactors [59]; and understanding the behavior of molecules in biological processes [161, 223].

36 MATERIALS SCIENCE↗
DOE OSTI2021

SPRUCE Radiocarbon analyses quantify peat carbon losses with increasing temperature in a whole ecosystem warming experiment, 2014-2020

This data set contains three *.csv data files with measurements of organic and inorganic carbon fractions and radiocarbon fractions in peat porewater profiles. Measurements of carbon fractions from enclosure drainage outflows are also included. Porewater profiles were collected up to four times annually from 2014 to 2020 with a piezometer and outflow samples were collected up to eight times annually in 2016 and 2017. Porewater organic and inorganic fractions were measured using a Finnigan Mat Delta V Isotope Ratio Mass Spectrometer and a Shimadzu Total Organic Carbon. Radiocarbon analyses were conducted at Lawrence Livermore National Laboratory (LLNL). The peat soils were subjected to deep peat heating (DPH) beginning in June of 2014 followed by whole ecosystem warming (WEW) in August of 2015 (Hanson et al. 2017). The experimental work was conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).These changes in these inorganic and organic carbon fractions in response to whole ecosystem warming may alter decomposition and microbial communities, as well as overall soil carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

SPRUCE 13C-Phospholipid Fatty Acid (13C-PLFA) Abundances, June 2014-June 2015

This data set provides the results of 13C phospholipid fatty acid analysis (13C-PLFA) of peat samples collected from ambient and experimental plots in the SPRUCE experiment site. The samples used to generate this data set were collected just prior to initiation of deep peat heating (DPH; 03 June 2014), after 3 months (09 September 2014), and after 10 months (16 June 2015). This data set includes the abundances and delta-13C isotopic signatures of individual lipids and of groups of lipids indicating total biomass, fungi, Gram-positive bacteria, Gram-negative bacteria, actinomycetes, and anaerobic bacteria. This dataset contains two files in comma separate (*.csv) format. Cores extending to 250 cm (200 cm in June 2015) were collected and subsampled at 10 cm intervals from 0 and 100 cm and 25 cm intervals below 100 cm depth. During the lipid extraction procedure, samples were pooled into the following depth increments in order to obtain sufficient material to achieve adequate lipid yield: 0-20, 20-50, 50-100, 100-150, 150-200, and 200-250cm.

actinomycetes↗
DOE OSTI2024

SPRUCE Xylem Native Embolism and Leaf Traits of Picea mariana and Larix laricina, 2019

This data set contains measurements of native embolism in branch xylem and associated branch and leaf traits from Picea mariana (Black Spruce) and Larix laricina (Tamarack) from September-October 2019 at the SPRUCE experiment (Hanson et al. 2017). Data are presented in one comma-separated (*.csv) file. Native embolism, a measurement of in-situ embolism in the xylem tissue that blocks water movement, measurements were conducted at the end of the growing season on cut branches using the hydraulic pipette method (see Peters et al. 2023 for full method). In short, branch segments were connected to hydraulic apprentice and flow rates of perfusion liquid were measured using graduated pipettes and stopwatch. After initial conductance measurements, branch segments were flushed using vacuum infiltration and hydraulic conductance was remeasured to calculate the percent loss in conductance due to embolism (PLC). Three branch segments (distal, middle, and proximal) were measured from each branch representing different diameters size classes. This dataset also contains leaf area associated with each measured branch segment, calculate leaf mass per area (LMA), sapwood specific conductivity (Ks), leaf area specific conductivity (Kl) and the sapwood area to leaf area ratio (Huber value). Measurements were made on mature trees from all ten treatment enclosures. One branch from each of five trees per species were used from each enclosure where available. Some plots do not contain five individual Larix laricina, in which case all available trees were sampled. All measurements were conducted in late September/early October 2019, at the end of growing season but before Larix laricina needle senescence. There are 10 experimental plots at SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). These data were collected after the treatments had been running in full for three years, meaning much of the material measured was grown under treatment conditions.

Huber value↗
DOE OSTI2023

SPRUCE Ground Observations of Phenology in Experimental Plots, 2022

This data set consists of one comma separated (*.csv) file containing phenological transition dates, as derived from direct observations of vegetative and reproductive phenology recorded by a human observer, from the SPRUCE experiment during 2022 (2022-03-28 to 2021-11-17), the seventh full year of whole-ecosystem warming (Hanson et al. 2017). Both spring and autumn phenological events are included. Since April 2016, human observers have been directly tracking the phenology of both woody and herbaceous species on a weekly schedule within the SPRUCE experimental chambers, these data are reported in annual ground observations data sets (see Related Data Sets). The observed date reported here is the first survey date in 2022 on which an event/phenophase was definitively observed. This data set also contains a companion file in HTML (*.html) containing figures showing the relationship between the day of year and temperature treatment for different phenological phases by species for 2022.

SPRUCE experiment, plant phenological phases, Spru↗
DOE OSTI2023

SPRUCE Vegetation Phenology in Experimental Plots from Phenocam Imagery, 2015-2022

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2023, with start- and end-of-season phenological transition dates derived through the end of autumn 2022. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step Contains 35 files in *.csv format inside a compressed (*.zip) file. Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e. vegetation type) Contains one file in *.csv format Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure Contains two files in *.csv format, one for snow on trees and one for snow on ground This data set consists of two sets of companion files: Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. Contains three files in HTML format, one for each vegetation type One additional file in HTML format with the transition dates plotted for each vegetation type, by year R files for processing Phenocam files and flags. Contains five files in R file (*.R) format in one compressed (*.zip) file User Note: All imagery is posted in near-real time to the PhenoCam Project web page (http://phenocam.sr.unh.edu/), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/y7z5mau7. The data reported here are based on the complete camera record from SPRUCE and supersedes the previously released phenocam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

SPRUCE Experiment, Marcell Experimental Forest, Sp↗