SEARCH · Search NASA

Results for “leaf area”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Soil microenvironmental variation drives below‐ground trait variation and interacts with macroclimate to structure above‐ground trait variation of arctic shrubs

Abstract Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic. To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ 15 N and leaf δ 13 C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots ( N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation. We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate. Synthesis . Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change.

Environmental Sciences & Ecology↗

DOE OSTI2021

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (Fv/Fm) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Data from: Biomass yield, yield components and growing season phenotypic measurements of Miscanthus

For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha-1) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index (LAI), and leaf chlorophyll content (LCC)). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018-2021 in Urbana and 2020-2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha-1. Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2-3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management.

Aging↗

DOE OSTI2023

A 30% reduction in switchgrass rhizome reserves did not decrease biomass yield

Abstract A long‐standing question in perennial grass breeding and physiology is whether yield improvement strategies could compromise winter survival. Since perennial grasses rely on stored carbohydrates for winter maintenance and spring regrowth, yield improvement strategies could reduce winter survival if they increase biomass and grain yields at the expense of carbon allocation to storage. Therefore, it is crucial to comprehend the dependence of regrowth on storage reserves. We experimentally depleted switchgrass ( Panicum virgatum L.) rhizome reserves by storing rhizomes for 2 weeks at 5°C (control treatment) and 25°C (reserve‐depleted treatment). During the storage period rhizome respiration was 5.3× higher at 25°C (0.010 μmol CO 2 g −1 min −1 at 5°C vs. 0.054 μmol CO 2 g −1 min −1 at 25°C; p < 0.0001) and the starch content was depleted by 30% by the end of storage. Surprisingly, reserve‐depleted switchgrass had 60% larger leaf area (LA; LA control = 149 cm 2 pot −1 vs. LA depleted = 239 cm 2 pot −1 ; p = 0.013) and produced ~40% more aboveground biomass than control plants (9.46 g pot −1 vs. 6.63 g pot −1 ; p = 0.112). In addition, reserve‐depleted switchgrass restored its rhizome starch reserves to pre‐storage levels. Switchgrass showed a large plasticity among its source‐sink components to buffer the imposed reserve depletion. It increased plant photosynthesis by increasing the photosynthetic leaf area while keeping photosynthesis constant on a leaf area basis and readjusted the timing and activity of sink organs. These results suggest that switchgrass, and potentially other perennial grasses, largely over‐invest in storage reserves. Therefore, current breeding strategies in perennial grasses aimed to extend the aboveground growing season should not compromise crop persistence. Our study also has implications on long‐term yield dynamics as it highlights sink limitations as potential driver of the yield decline commonly observed in perennial grasses 5+ years after cultivation.

Tejera‐Nieves, Mauricio↗

DOE OSTI2025

Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid- to high latitudes

Increasing leaf area and extending vegetation growing seasons are two primary drivers of global greening, which has emerged as one of the most significant responses to climate change. However, it remains unclear how these two leaf acclimation strategies would vary across forests at a large spatial scale. Here, in this study, using multiple satellite-based datasets and field measurements, we analysed the temporal changes (Δ) in maximal leaf area index (LAI max ) and length of the growing season (LOS) from 2002 to 2021 across deciduous broadleaf forests (DBFs) in the middle to high latitudes. Contrary to the widely held assumption of coordination, our results revealed a negative correlation between ΔLAI max and ΔLOS. Notably, the trade-offs between ΔLAImax and ΔLOS were strongly explained by stand age. Younger DBFs, with lower baseline LAI max , predominantly located in eastern Asia, displayed an increase in LAI max with small changes in LOS. This acquisitive strategy facilitated younger DBFs to grow more photosynthetically efficient leaves with low leaf mass per area, enhancing their light use efficiency. Conversely, older DBFs with a higher baseline LAI max , primarily located in North America and Europe, extended their LOS by increasing leaf mass per area. This conservative strategy facilitated older DBFs to produce thicker, but less photosynthetically efficient leaves, resulting in decreased light use efficiency. Our findings offer new insights into the contrasting changes in leaf area and growing season length and highlight their divergent impacts on ecosystem functioning.

Wang, Fangyi [Sun Yat-Sen Univ., Zhuhai (China)]↗

DOE OSTI2020

Plant‐mediated methane transport in emergent and floating‐leaved species of a temperate freshwater mineral‐soil wetland

Abstract Methane flux from freshwater mineral‐soil (FWMS) wetlands and its variability among sites is largely modulated by plant‐mediated transport. However, plant‐mediated transport processes are rarely resolved in land surface models and are poorly parametrized for plants commonly found in FWMS wetlands. Here, relationships between methane flux and CO 2 uptake, as well as plant conductance of methane were evaluated for three plant species and two characteristic functional types: emergent (narrow‐leaved cattail) and floating‐leaved (American lotus and water lily). We found significant but contrasting correlations between methane flux and CO 2 uptake in cattails ( r 2 = 0.51, slope = −0.16, during morning) and water lily ( r 2 = 0.32, slope = 0.064, after midday). This relationship was not significant in American lotus, showing that stomata regulation of methane fluxes is species‐specific and not generalizable across the floating‐leaved plant functional type. Conductance of methane per leaf area showed distinct seasonal dynamics across species. Conductance was similar among the floating‐leaved species (6.2 × 10 −3 m d −1 in lotus and 7.2 × 10 −3 m d −1 in water lily) and higher than conductance in the emergent species (2.7 × 10 −3 m d −1 ). Our results provide direct observations of plant conductance rates and identify the vegetation parameters (leaf area, stomatal conductance) that modify them. Our results further suggest that models of methane emissions from FWMS should parameterize plant‐mediated transport in different plant functional types, scaled by leaf area and with variable seasonal phenological dynamics, and consider possible species‐specific mechanisms that control methane transport through plants.

Villa, Jorge A.↗

DOE OSTI2022

Leaf mass area, Feb2016-May2016, PA-SLZ, PA-PNM, PA-BCI: Panama

This data package contains leaf mass data per unit area measured on a monthly basis from February to April, 2016, at the Bosque Protector San Lorenzo (PA-SLZ) and Parque Natural Metropolitano (PA-PNM) sites in Panama. Data from the Barro Colorado Island (PA-BCI) site are only available for March. This data was collected as part of the 2016 El Niño-Southern Oscillation (ENSO) campaign. Included in this data package are an Excel file with data (2016ENSO_Panama_LMA1) and two Excel files with associated metadata. Also included is a Word document (Metadata_description_2016_ENSO_Panama) with details such as data collection methods, equipment used, and site information. See related datasets for further sample details, leaf water potential, leaf spectra, gas exchange and leaf chemistry. VERSION 2 update. The identification of a species from the PNM site has been corrected as follows: the identification of the tree initially identified as Pseudosamanea guachapele (ALBIED) has been revised to Albizia adinocephala (ALBIAD). The updated data package includes revised data, metadata and protocol documents updated to reflect this change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

An experimental approach for crown to whole-canopy defoliation in forests

Canopy defoliation is an important source of disturbance in forest ecosystems that has rarely been represented in large-scale manipulation experiments. Scalable crown to canopy level experimental defoliation is needed to disentangle the effects of variable intensity, timing, and frequency on forest structure, function, and mortality. We present a novel pressure-washing-based defoliation method that can be implemented at the canopy-scale, throughout the canopy volume, targeted to individual leaves or trees, and completed within a timeframe of hours or days. Pressure washing proved successful at producing consistent leaf-level and whole-canopy defoliation, with 10%–20% reduction in leaf area index and consistent leaf surface area removal across branches and species. This method allows for stand-scale experimentation on defoliation disturbance in forested ecosystems and has the potential for broad application. Studies utilizing this standardized method could promote mechanistic understanding of defoliation effects on ecosystem structure and function and development of synthetic understanding across forest types, ecoregions, and defoliation sources.

Forestry↗

DOE OSTI2025

Data and Scripts associated with a manuscript on ecosystem responses to wildfires in the Columbia River Basin

This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Genetic variation in nitrogen‐use efficiency and its associated traits in dryland winter wheat ( Triticum aestivum L.) cultivars released from the 1940s to the 2010s in Shaanxi Province, China

Abstract BACKGROUND Improving the nitrogen‐use efficiency (NUE) of wheat can help mitigate the problems of poor soil fertility under dryland conditions. We conducted field experiments using three nitrogen (N) fertilization levels (0, 120, and 180 kg ha −1 ) applied to eight dryland wheat cultivars to assess NUE and its associated traits. RESULTS The grain yield significantly increased with the improvement in variety, mainly as a result of a substantial increase in 1000‐grain weight and harvest index. Modern wheat varieties have stabilized at an optimal plant height and exhibited improved performance in terms of NUE, partial N productivity, N harvest index, and grain protein content compared to older varieties. The NUE of wheat gradually increased with variety replacement. The net photosynthesis rate of the flag leaves in the filling stage improved with the year of cultivar release; Increasing soil–plant analysis development (SPAD) values of flag leaves in the flowering and filling stages were observed over time, with the flag leaves of modern varieties showing a high chlorophyll content in the filling stage. Additionally, the principal component analysis showed that the SPAD value, grain number per unit area, transpiration rate, leaf area, and grain protein content positively contributed to the clustering of the N180 and modern cultivars (from the 2000s to 2010s). CONCLUSION Overall, high levels of N application did not significantly improve the NUE of wheat. However, modern wheat varieties can optimize N distribution, increase flag leaf photosynthetic capacity, and improve photosynthesis ability, thus enhancing NUE to achieve high yields under a suitable level of N supply. © 2022 Society of Chemical Industry.

Lian, Huida↗

DOE OSTI2020

Optimization of leaf morphology in relation to leaf water status: A theory

The leaf economic traits such as leaf area, maximum carbon assimilation rate, and venation are all correlated and related to water availability. Furthermore, leaves are often broad and large in humid areas and narrower in arid/semiarid and hot and cold areas. We use optimization theory to explain these patterns. We have created a constrained optimization leaf model linking leaf shape to vein structure that is integrated into coupled transpiration and carbon assimilation processes. The model maximizes net leaf carbon gain (NPPleaf) over the loss of xylem water potential. Modeled relations between leaf traits are consistent with empirically observed patterns. As the results of the leaf shape-venation relation, our model further predicts that a broadleaf has overall higher NPPleaf compared to a narrowleaf. In addition, a broadleaf has a lower stomatal resistance compared to a narrowleaf under the same level of constraint. With the same leaf area, a broadleaf will have, on average, larger conduits and lower total leaf xylem resistance and thus be more efficient in water transportation but less resistant to cavitation. By linking venation structure to leaf shape and using water potential as the constraint, our model provides a physical explanation for the general pattern of the covariance of leaf traits through the safety-efficiency trade-off of leaf hydraulic design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Plant physiology, shrub size, thaw depth and soil water content, Seward Peninsula, Alaska, 2023

Stomatal response to changing irradiance measurements (m curves), CO2 response (ACi) and light response (AQ) curves on common tussock tundra shrub, graminoid and forb species. Data were collected in July 2023 from three sites on the Seward Peninsula, Kougarok Mile 64, Teller Mile 27 and Council. Measurements were made with LI-COR LI-6800 gas exchange systems on 18 species. For samples from Teller and Kougarok, thaw depth, soil moisture content and dGPS locations are also provided for most samples. Canopy height and canopy diameter are provided for shrubs measured at the Teller site. The data package files include data files, metadata files and the complete instrument output for all gas exchange measurements in .csv format, and a pdf describing the experimental protocols. See the related data package NGA508 for foliar trait data (leaf mass per area, leaf nitrogen concentration).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Stomatal response of three Arctic plant species, Seward Peninsula, Alaska, 2022

Stomatal response to changing irradiance measurements on three common tussock tundra shrub species. Data were collected in 2022 from two sites on the Seward Peninsula, Kougarok Mile 64 and Teller Mile 27. Measurements were made with LI-COR LI-6800 gas exchange systems using a slow curve light response method. Light curve observations enable the estimation of stomatal slope and intercept parameters, g1 and g0. The data package files include a data file, metadata files and the complete instrument output for all measurements in .csv format, and a pdf describing the experimental protocol. See the related data package NGA315 for foliar trait data (leaf mass per area, leaf nitrogen concentration) and NGA209 for co-located thaw depth and soil moisture. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2017

Leaf gas exchange measurements on Petasites frigidus (L.) Fr. following a single season warming treatment. Data were collected in 2017 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5-25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017-2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Plant Physiology, Alder and Willow Species, Seward Peninsula, Alaska, 2019

Photosynthetic parameters (Vcmax and Jmax), CO2 response (ACi) curves and dark respiration (Rdark) measurements of tundra shrub species. Data were collected at the NGEE-Arctic Kougarok and Teller study sites on the Seward Peninsula, AK, USA in July 2019. Four species were measured using LI-COR LI-6400 portable gas exchange systems: Alnus viridis ssp. fruticosa, Salix richardsonii and Salix pulchra. The data package files include data files, metadata files, dGPS locations and the complete instrument output for all gas exchange measurements in .csv format. See the related data packages for foliar trait data (leaf mass per area, leaf nitrogen concentration), and leaf spectral reflectance data collected simultaneously on the same shrubs (NGA210, NGA212).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2021

Leaf gas exchange measurements on Carex aquatilis Wahlenb. following a single season warming treatment. Data were collected in 2021 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2018

Leaf gas exchange measurements on Arctagrostis latifolia (R. Br.) Griseb. following a single season warming treatment. Data were collected in 2018 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2019

Leaf gas exchange measurements on Eriophorum angustifolium Honck. following a single season warming treatment. Data were collected in 2019 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format,, and include 4 data files, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗