Engineering topics

Euskirchen, Eugenie

Publications and source records attributed to Euskirchen, Eugenie.

At least 19 records

DOE OSTI2025

Network of networks: Time series clustering of AmeriFlux sites

Environmental observation networks, such as AmeriFlux, are foundational for monitoring ecosystem response to climate change, management practices, and natural disturbances; however, their effectiveness depends on their representativeness for the regions or continents. We proposed an empirical, time series approach to quantify the similarity of ecosystem fluxes across AmeriFlux sites. We extracted the diel and seasonal characteristics (i.e., amplitudes, phases) from carbon dioxide, water vapor, energy, and momentum fluxes, which reflect the effects of climate, plant phenology, and ecophysiology on the observations, and explored the potential aggregations of AmeriFlux sites through hierarchical clustering. While net radiation and temperature showed latitudinal clustering as expected, flux variables revealed a more uneven clustering with many small (number of sites < 5), unique groups and a few large (> 100) to intermediate (15–70) groups, highlighting the significant ecological regulations of ecosystem fluxes. Many identified unique groups were from under-sampled ecoregions and biome types of the International Geosphere-Biosphere Programme (IGBP), with distinct flux dynamics compared to the rest of the network. At the finer spatial scale, local topography, disturbance, management, edaphic, and hydrological regimes further enlarge the difference in flux dynamics within the groups. Nonetheless, our clustering approach is a data-driven method to interpret the AmeriFlux network, informing future cross-site syntheses, upscaling, and model-data benchmarking research. Finally, we highlighted the unique and underrepresented sites in the AmeriFlux network, which were found mainly in Hawaii and Latin America, mountains, and at under-sampled IGBP types (e.g., urban, open water), motivating the incorporation of new/unregistered sites from these groups.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

AmeriFlux FLUXNET-1F US-ICh Imnavait Creek Watershed Heath Tundra

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ICh Imnavait Creek Watershed Heath Tundra. This is the FLUXNET version of the carbon flux data for the site US-ICh Imnavait Creek Watershed Heath Tundra produced by applying the standard ONEFlux (1F) software. Site Description - The Imnavait Creek Watershed Heath Tundra (Ridge Station) is located near Imnavait Creek in Alaska, north of the Brooks Range in the Kuparuk basin near Lake Toolik and the Toolik Field Station. The Kuparuk River has its headwaters in the Brooks Range and drains through northern Alaska into the Arctic Ocean. Within these headwaters lies the Imnavait basin at an average elevation of 930 m. Water tracks run down the hill in parallel zones with a spacing of approximately 10 m. The Ridge Station was deployed at the end of Summer 2007.

Euskirchen, Eugenie↗

DOE OSTI2023

Upscaling Wetland Methane Emissions From the FLUXNET–CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

Wetlands are responsible for 20%–31% of global methane (CH 4 ) emissions and account for a large source of uncertainty in the global CH 4 budget. Data-driven upscaling of CH 4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH 4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH 4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH 4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ~0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH 4 emissions of 146 ± 43 TgCH 4 y –1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH 4 y –1 ) and overlaps with top-down atmospheric inversion models (155–200 TgCH 4 y –1 ). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH 4 fluxes has the potential to produce realistic extra-tropical wetland CH 4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Permafrost and Climate Change: Carbon Cycle Feedbacks From the Warming Arctic

Rapid Arctic environmental change affects the entire Earth system as thawing permafrost ecosystems release greenhouse gases to the atmosphere. Understanding how much permafrost carbon will be released, over what time frame, and what the relative emissions of carbon dioxide and methane will be is key for understanding the impact on global climate. In addition, the response of vegetation in a warming climate has the potential to offset at least some of the accelerating feedback to the climate from permafrost carbon. Temperature, organic carbon, and ground ice are key regulators for determining the impact of permafrost ecosystems on the global carbon cycle. Together, these encompass services of permafrost relevant to global society as well as to the people living in the region and help to determine the landscape-level response of this region to a changing climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-BZB Bonanza Creek Thermokarst Bog

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-BZB Bonanza Creek Thermokarst Bog. This is the FLUXNET version of the carbon flux data for the site US-BZB Bonanza Creek Thermokarst Bog produced by applying the standard ONEFlux (1F) software. Site Description - Intermediate to old age thermokarst collapse scar boreal bog in the Tanana Lowlands of Interior Alaska. Peat soils ~1-m thick. Recharged by precipitation and runoff from the surrounding forested peat plateaus. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-BZF Bonanza Creek Rich Fen

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-BZF Bonanza Creek Rich Fen. This is the FLUXNET version of the carbon flux data for the site US-BZF Bonanza Creek Rich Fen produced by applying the standard ONEFlux (1F) software. Site Description - The rich fen is in the boreal peatland lowlands of the Tanana Flats in interior Alaska. Lacks near-surface permafrost even though the surrounding landscape is marked by the presence of permafrost. Peat depth is 1-2m. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-BZo Bonanza Creek Old Thermokarst Bog

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-BZo Bonanza Creek Old Thermokarst Bog. This is the FLUXNET version of the carbon flux data for the site US-BZo Bonanza Creek Old Thermokarst Bog produced by applying the standard ONEFlux (1F) software. Site Description - Old thermokarst collapse scar boreal bog (several hundred years old) in the Tanana Lowlands of Interior Alaska. Peat soils ~1-m thick. Recharged by precipitation and runoff from the surrounding forested peat plateaus. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-BZS Bonanza Creek Black Spruce

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-BZS Bonanza Creek Black Spruce. This is the FLUXNET version of the carbon flux data for the site US-BZS Bonanza Creek Black Spruce produced by applying the standard ONEFlux (1F) software. Site Description - Mature black spruce boreal forest with cold, permafrost soils on a peat plateau. In the Tanana lowlands in interior Alaska. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-ICt Imnavait Creek Watershed Tussock Tundra

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ICt Imnavait Creek Watershed Tussock Tundra. This is the FLUXNET version of the carbon flux data for the site US-ICt Imnavait Creek Watershed Tussock Tundra produced by applying the standard ONEFlux (1F) software. Site Description - The Imnavait Creek Watershed Tussock Tundra (Biocomplexity Station) is located near Imnavait Creek in Alaska, north of the Brooks Range in the Kuparuk basin near Lake Toolik and the Toolik Field Station. The Kuparuk River has its headwaters in the Brooks Range and drains through northern Alaska into the Arctic Ocean. Within these headwaters lies the Imnavait basin at an average elevation of 930 m. Water tracks run down the hill in parallel zones with a spacing of approximately 10 m. The Biocomplexity Station was deployed in 2004, and it has been in operation during the melt seasons ever since.

Euskirchen, Eugenie↗

DOE OSTI2022

Causality guided machine learning model on wetland CH 4 emissions across global wetlands

Wetland CH 4 emissions are among the most uncertain components of the global CH 4 budget. The complex nature of wetland CH 4 processes makes it challenging to identify causal relationships for improving our understanding and predictability of CH 4 emissions. In this study, we used the flux measurements of CH 4 from eddy covariance towers (30 sites from 4 wetlands types: bog, fen, marsh, and wet tundra) to construct a causality-constrained machine learning (ML) framework to explain the regulative factors and to capture CH 4 emissions at sub-seasonal scale. We found that soil temperature is the dominant factor for CH 4 emissions in all studied wetland types. Ecosystem respiration (CO 2 ) and gross primary productivity exert controls at bog, fen, and marsh sites with lagged responses of days to weeks. Integrating these asynchronous environmental and biological causal relationships in predictive models significantly improved model performance. More importantly, modeled CH 4 emissions differed by up to a factor of 4 under a +1°C warming scenario when causality constraints were considered. These results highlight the significant role of causality in modeling wetland CH 4 emissions especially under future warming conditions, while traditional data-driven ML models may reproduce observations for the wrong reasons. Our proposed causality-guided model could benefit predictive modeling, large-scale upscaling, data gap-filling, and surrogate modeling of wetland CH 4 emissions within earth system land models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

AmeriFlux FLUXNET-1F US-ICs Imnavait Creek Watershed Wet Sedge Tundra

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ICs Imnavait Creek Watershed Wet Sedge Tundra. This is the FLUXNET version of the carbon flux data for the site US-ICs Imnavait Creek Watershed Wet Sedge Tundra produced by applying the standard ONEFlux (1F) software. Site Description - The Imnavait Creek Watershed Wet Sedge Tundra (Fen Station) is located near Imnavait Creek in Alaska, north of the Brooks Range in the Kuparuk basin near Lake Toolik and the Toolik Field Station. The Kuparuk River has its headwaters in the Brooks Range and drains through northern Alaska into the Arctic Ocean. Within these headwaters lies the Imnavait basin at an average elevation of 930 m. Water tracks run down the hill in parallel zones with a spacing of approximately 10 m. The Fen Station was deployed at the end of Summer 2007.

Euskirchen, Eugenie↗

DOE OSTI2022

AmeriFlux US-BZo Bonanza Creek Old Thermokarst Bog

This is the AmeriFlux version of the carbon flux data for the site US-BZo Bonanza Creek Old Thermokarst Bog. Site Description - Old thermokarst collapse scar boreal bog (several hundred years old) in the Tanana Lowlands of Interior Alaska. Peat soils ~1-m thick. Recharged by precipitation and runoff from the surrounding forested peat plateaus. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2022

The ABCflux database: Arctic–boreal CO 2 flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO 2 ) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO 2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO 2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO 2 fluxes and to better estimate the terrestrial ABZ CO 2 budget.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗

DOE OSTI2021

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi-site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. In this work we used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet-based multi-resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the dominant predictor for wetlands with smaller variations in temperature (e.g., seasonal tropical/subtropical wetlands). Changes in seasonal FCH4 lagged fluctuations in WTD by ~17 ± 11 days, and lagged air and soil temperature by median values of 8 ± 16 and 5 ± 15 days, respectively. Temperature and WTD were also dominant predictors at the multiday scale. Atmospheric pressure (PA) was another important multiday scale predictor for peat-dominated sites, with drops in PA coinciding with synchronous releases of CH 4 . At the diel scale, synchronous relationships with latent heat flux and vapor pressure deficit suggest that physical processes controlling evaporation and boundary layer mixing exert similar controls on CH 4 volatilization, and suggest the influence of pressurized ventilation in aerenchymatous vegetation. In addition, 1- to 4-h lagged relationships with ecosystem photosynthesis indicate recent carbon substrates, such as root exudates, may also control FCH4. By addressing issues of scale, asynchrony, and nonlinearity, this work improves understanding of the predictors and timing of wetland FCH4 that can inform future studies and models, and help constrain wetland CH 4 emissions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

AmeriFlux US-BZB Bonanza Creek Thermokarst Bog

This is the AmeriFlux version of the carbon flux data for the site US-BZB Bonanza Creek Thermokarst Bog. Site Description - Intermediate to old age thermokarst collapse scar boreal bog in the Tanana Lowlands of Interior Alaska. Peat soils ~1-m thick. Recharged by precipitation and runoff from the surrounding forested peat plateaus. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗

DOE OSTI2021

AmeriFlux US-BZF Bonanza Creek Rich Fen

This is the AmeriFlux version of the carbon flux data for the site US-BZF Bonanza Creek Rich Fen. Site Description - The rich fen is in the boreal peatland lowlands of the Tanana Flats in interior Alaska. Lacks near-surface permafrost even though the surrounding landscape is marked by the presence of permafrost. Peat depth is 1-2m. Primary wind direction in the summer is WSW.

Euskirchen, Eugenie↗