The NGEE Arctic Team Defends the Phase 4 Proposal
The NGEE Arctic team presented and defended a proposal for Phase 4 science in front of a review panel comprising nearly a dozen international arctic empiricists and modelers.
The NGEE Arctic team presented and defended a proposal for Phase 4 science in front of a review panel comprising nearly a dozen international arctic empiricists and modelers.
We are conducting a greenhouse experiment with live Arctic thermokarst wetland vegetation to pinpoint important biogeochemical processes in these changing ecosystems.
Energy conducted by water can result in faster and deeper permafrost thaw.
High-resolution maps of near-surface permafrost for three watersheds on the Seward Peninsula, Alaska derived from machine learning.
A Raspberry Pi-based open-source, low-power camera system improves monitoring of plant seasonality in arctic environments.
Causal loop diagram analysis can be a valuable tool in assessing structural- and parameter-based model uncertainty.
We are grateful to conduct our scientific research on lands stewarded by Alaska Native Communities.
As scientists become part of larger teams and take part in broader and more diverse scientific endeavors, they must all become leaders in creating cultures of safety, inclusion, and trust.
The first climate scientist to head the US Department of Energy’s Office of Science, Dr. Asmeret Asefaw Berhe, visited a long-time NGEE Arctic study site at the Barrow Environmental Observatory.
Integrating aboveground PFTs with belowground biogeochemistry and gas fluxes.
How will species persist if the pressures of wildfire amplify under a warmer climate?
Arctic vegetation classes miss variation in rooting depth distribution and rhizosphere priming-induced carbon emmissions.
Leading the way to improved understanding and communication of fundamental and cutting-edge findings on Arctic permafrost.
Characterizing the primary environmental controls on watershed soil water geochemical variation in the Arctic is critical to better understand geochemical cycling and predict future changes.
The anticipated approach for NGEE Arctic Phase 4 leverages computational, diagnostic, remote sensing, and data synthesis tools to quantify improvements in prediction of climate–ecosystem feedbacks at the global scale in an Arctic-informed version of the land surface component of the Department of Energy’s (DOE’s) Energy Exascale Earth System Model (E3SM). NGEE Arctic Phase 4 will deliver an unprecedented ability to predict the consequences of interacting Arctic processes for the global climate.
The presence and thawing of permafrost strongly control both gradual and catastrophic movements of soil on watershed hillslopes in complex and often difficult to predict patterns and rates.
Nitrous oxide strongly inhibits CH4 and MeHg formation, resulting from the complicated interplay of microbial processes in anoxic soils that ultimately determine how climate change will influence greenhouse gas formation and mercury transformation in the Arctic ecosystem.
NGEE Arctic Tabletop scenarios are facilitating field preparedness across sister groups and societies.
Aboveground, this sedge species transfers recently fixed carbon from blades to newly developing tillers, whereas belowground, fixed carbon is preferentially allocated to terminal fine root tips.
Independent evaluation using process model simulations reveals shortcomings in machine learning techniques commonly used to upscale and forecast ecosystem processes.
From under the clouds to in the clouds: unoccupied aerial systems and piloted sub-orbital airborne remote sensing enables scientists to better characterize the spatial variation in Arctic vegetation composition across scales.
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The NGEE Arctic Rainfall Simulator (NARS) was deployed to study interflow discharge rates following a simulated 100-year storm event.
Strong feedback among soil, terrain, and vegetation properties and snow accumulation that create heterogeneity in thermal, hydrological, and biogeochemical regimes across the studied watershed.
Researchers used remote sensing and random forest models to quantify the importance of landscape parameters including topography, vegetation, and meteorological factors.
Model simulations show that it may take several centuries of warming and wildfire increases for Alaska to become a net source of CO2 to the atmosphere.
A new study provides insight into our current knowledge of nitrogen fixation by non-symbiotic organisms living in soil, litter, decomposition wood, lichens, mosses, and insects.
NGEE Arctic scientists developed and led a successful workshop in which experimentalists from NGEE Arctic and other Environmental System Science (ESS) projects ran the E3SM Land Model (ELM).
A new algorithm was developed to generate high–spatiotemporal resolution estimates of snow-covered area using commercial satellite imagery.
Integrating geophysics with topographic and multispectral data into a machine learning classifier is a promising approach for mapping the distribution of near-surface permafrost in regions of discontinuous permafrost.
The ESS community generates a variety of multidisciplinary data, and the purpose of the reporting formats is to create a level of consistency that will allow for better integration and analysis of data.
NGEE Arctic prepared a science activities report highlighting the results and conclusions of its recent snow campaign for the Kougarok Hillslope field site owned by Mary’s Igloo Native Corporation (MINC).
View metrics about the NGEE Arctic metadata records and data downloads.
View metrics about the NGEE Arctic metadata records and data downloads.
A large-scale sequencing effort explored microbial life in soils and permafrost of Barrow Environmental Observatory.
Synchrotron radiation-based Fourier transform infrared spectral imaging shines light to microbial metabolism and soil chemistry of Arctic permafrost.
Simulations of coupled carbon and Fe cycling show that the effect of Fe on CH4 production varies with substrate availability.
Ecosys, a process-rich terrestrial ecosystem model, reveals that watershed variability in soil temperatures, vegetation cover, and carbon fluxes is driven by near-surface hydrology and soil properties
Fernanda Santos and Amy Breen visited burned and unburned areas at the Kougarok fire site to evaluate the impact of wildfires on soil carbon storage.
Results from manipulative field experiment indicate that both nutrient availability and root traits shift rapidly in response to a single growing season of elevated temperature, but these changes did not result in faster plant nitrogen uptake.
Successful application of the 13C label to a tundra wetland ecosystem.
Not considering dispersal and fire leads to overestimating shrub expansion in Arctic tundra and its role as a carbon sink.
Analysis of CH4 emissions derived alongside geophysical electrical resistivity measurements revealed that localized hot spots of CH4 (>500 mg m2 d-1) were observed in two study site locations.
Fluorescence automated measurement equipment (FAME) was installed at the NGEE Arctic Council, Alaska site, and a surprisingly strong signal of sun-induced chlorophyll fluorescence (SIF) was obtained.
The NGEE Arctic Rainfall Simulator (NARS) was designed, built, and tested and is now being deployed to the Seward Peninsula of Alaska.
An approach combining thermal modeling, Bayesian inference, and soil temperature time series with vertical spatial resolution reveals under what conditions soil thermal diffusivity can be reliably inferred.
The NGEE Arctic team recently presented our Phase 3 progress and plans to the US Department of Energy’s Biological and Environmental Research program managers.
The accurate representation of microbial functional guilds within ecosystem models is critical for predicting ecosystem recovery on multi-decadal time scales.
Environmental controls on soil pore water concentrations of several solutes are inferred from spatial variability, co-located measurements, and thermodynamic geochemical models.
Localized Fe plaque formation was identified on roots obtained from Arctic tundra, indicating the potential for these roots to release oxygen gas and alter subsurface redox biogeochemistry.
Combining a data availability and needs analysis for parameters with qualitative causal loop analysis helps to identify parameters that are in most need of additional field data.
Deepening of the thaw layer resulted in increased concentrations and age of DOC in surface and pore waters that may contribute to greenhouse gas emissions as warming increases permafrost thaw.
Analysis highlights the challenges and opportunities for reducing model uncertainty associated with estimation of gross primary productivity in the Arctic boreal region.
Isotopic labels elucidate the impact of a single warm growing season on belowground interactions among plants, soils, and microbes.
Regional modeling study shows that twenty-first century climate warming will shift the seasonality of the carbon cycle across Alaska.
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View metrics about the NGEE Arctic metadata records and data downloads.
A friendly reminder about the NGEE Arctic Project Data Archiving & Sharing Policy that aligns with the DOE Policy for Digital Research Data Management and the expectations of the ESS-DIVE data center.
Multi-scale, multi-type Arctic tundra datasets enabled the submeter estimation of daytime average net ecosystem exchanges.
Metrics about the NGEE Arctic metadata records and data downloads.
Best practices, a computer package, and hands-on tutorials to guide the application of a powerful technique for prediction of plant traits from hyperspectral data.
Fall and wintertime root and soil biogeochemistry, which are not well represented in large-scale land models, strongly affect 21st century shrub expansion.
Scientists on the NGEE Arctic project find that topography and landscape hydrology are key environmental controls on observed Arctic shrub expansion of the past three decades.
A woodier Arctic will alter the carbon balances by affecting a complex set of soil-plant-atmosphere interactions.
Participants across the NGEE Arctic team participated in Table Top exercises for increasing awareness and encouraging improved safety responsiveness to potentially dangerous field work scenarios.
Model sensitivity and uncertainty varied spatially across the highly heterogeneous Arctic tundra plant communities, illustrating the complexity inherent in model uncertainty in the Arctic.
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