Engineering topics

Iversen, Colleen M.

Publications and source records attributed to Iversen, Colleen M..

At least 19 records

DOE OSTI2025

Brief communication: Monitoring snow depth using small, cheap, and easy-to-deploy snow–ground interface temperature sensors

Abstract. Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. We trained a random forest machine learning model to predict snow depth from variability in snow–ground interface temperature. The model performed well on Alaska's Seward Peninsula where it was trained and at Arctic evaluation sites (RMSE ≤ 0.15 m). It performed poorly at temperate sites with deeper snowpacks, partially due to training data limitations. Small temperature sensors are cheap and easy to deploy, so this technique enables spatially distributed and temporally continuous snowpack monitoring at high latitudes to an extent previously infeasible.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

SPRUCE Root Tip and Ectomycorrhizal Fungi Colonization Measurements from Ingrowth Cores, 2017

This data set contains root tip and ectomycorrhizal fungi colonization measurements taken from ingrowth cores from the SPRUCE experiment (Hanson et al. 2017) that were deployed during the 2017 growing season (2017-06 to 2017-10-01). This study explored the relationship between warming treatments and fine-root growth. Increased fine-root growth may increase root exudates and accelerate turnover, representing an underlying mechanism for peat decomposition through priming, as exudates provide a labile carbon source to the microbial community. Roots of two tree species were studied: an evergreen conifer Picea mariana (black spruce) and a deciduous conifer Larix laricina (tamarack). Measurements include root tips counts and densities by tree species and the abundance of ectomycorrhizal colonization on root tips. 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.

black spruce [Picea mariana]↗

DOE OSTI2024

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Getting allometry right at the Oak Ridge free‐air CO 2 enrichment experiment: Old problems and new opportunities for global change experiments

Societal Impact Statement Free‐air CO 2 enrichment (FACE) experiments provide essential data on forest responses to increasing atmospheric CO 2 for evaluations of climate change impacts on humanity. Understanding and reducing the uncertainty in the experimental results is critical to ensure scientific and public confidence in the models and policy initiatives that derive therefrom. One source of uncertainty is the estimation of tree biomass using mathematical relationships between biomass and easily obtained and non‐destructive measurements (allometry). We evaluated the robustness of the allometric relationships established at the beginning of a FACE experiment and discuss the challenges and opportunities for the new generation of FACE experiments. Summary Long‐term field experiments to elucidate forest responses to rising atmospheric CO 2 concentration require allometric equations to estimate tree biomass from non‐destructive measurements of tree size. We analyzed whether the allometric equations established at the beginning of a free‐air CO 2 enrichment (FACE) experiment in a Liquidambar styraciflua plantation were still valid at the end of the 12 year experiment. Aboveground woody biomass was initially predicted by an equation that included bole diameter, taper, and height, assuming that including taper and height as predictors would accommodate changes in tree structure that might occur over time and in response to elevated CO 2 . At the conclusion of the FACE experiment, we harvested 23 trees, measured dimensions and dry mass of boles and branches, and extracted and measured the woody root mass of 10 trees. Although 10 of the harvested trees were larger than the trees used to establish the allometric relationship, measured aboveground woody biomass was well predicted by the original allometry. The initial linear equation between bole basal area and woody root biomass underestimated final root biomass by 28%, but root biomass was just 21% of total wood mass, and errors in aboveground and belowground estimates were offsetting. The allometry established at the beginning of the experiment provided valid predictions of tree biomass throughout the experiment. New allometric approaches using terrestrial laser scanning should reduce an important source of uncertainty in decade‐long forest experiments and in assessments of centuries‐long forest biomass accretion used in evaluating carbon offsets and climate mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Responses of vascular plant fine roots and associated microbial communities to whole-ecosystem warming and elevated CO 2 in northern peatlands

Warming and elevated CO 2 (eCO 2 ) are expected to facilitate vascular plant encroachment in peatlands. The rhizosphere, where microbial activity is fueled by root turnover and exudates, plays a crucial role in biogeochemical cycling, and will likely at least partially dictate the response of the belowground carbon cycle to climate changes. We leveraged the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment, to explore the effects of a whole-ecosystem warming gradient (+0°C to 9°C) and eCO 2 on vascular plant fine roots and their associated microbes. We combined trait-based approaches with the profiling of fungal and prokaryote communities in plant roots and rhizospheres, through amplicon sequencing. Warming promoted self-reliance for resource uptake in trees and shrubs, while saprophytic fungi and putative chemoorganoheterotrophic bacteria utilizing plant-derived carbon substrates were favored in the root zone. Conversely, eCO 2 promoted associations between trees and ectomycorrhizal fungi. Trees mostly associated with short-distance exploration-type fungi that preferentially use labile soil N. Additionally, eCO 2 decreased the relative abundance of saprotrophs in tree roots. Our results indicate that plant fine-root trait variation is a crucial mechanism through which vascular plants in peatlands respond to climate change via their influence on microbial communities that regulate biogeochemical cycles.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The Arctic Plant Aboveground Biomass Synthesis Dataset

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m -2 ) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Climate warming and elevated CO 2 alter peatland soil carbon sources and stability

Peatlands are an important carbon (C) reservoir storing one-third of global soil organic carbon (SOC), but little is known about the fate of these C stocks under climate change. Here, we examine the impact of warming and elevated atmospheric CO 2 concentration (eCO 2 ) on the molecular composition of SOC to infer SOC sources (microbe-, plant- and fire-derived) and stability in a boreal peatland. We show that while warming alone decreased plant- and microbe-derived SOC due to enhanced decomposition, warming combined with eCO 2 increased plant-derived SOC compounds. We further observed increasing root-derived inputs (suberin) and declining leaf/needle-derived inputs (cutin) into SOC under warming and eCO 2 . The decline in SOC compounds with warming and gains from new root-derived C under eCO 2 , suggest that warming and eCO 2 may shift peatland C budget towards pools with faster turnover. Together, our results indicate that climate change may increase inputs and enhance decomposition of SOC potentially destabilising C storage in peatlands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

How deep should we go to understand roots at the top of the world?

Harsh environmental conditions and the short summers of northern, high-latitude biomes impose unique constraints on the plants that live in the arctic tundra and the boreal forest. To escape the harsh aboveground environment, plants in these habitats often allocate a large portion of their biomass belowground to facilitate nutrient acquisition. In turn, the proximity of living plant roots to vast stores of sequestered soil carbon in these biomes means that shifts in rooting depth distribution and the size of the root–soil interface could significantly contribute to ongoing climate change. Indeed, plant ‘priming’ of rhizosphere decomposition via root exudation, particularly from shallowly distributed roots, can lead to losses of carbon from tundra soils. While we have a hard-won understanding of the distribution of plant communities across the arctic tundra and the boreal forest from direct field observations scaled to the landscape level using climate-informed mapping techniques (i.e. the Circumpolar Arctic Vegetation Map (CAVM); Walker et al. , 2005), these vegetation maps are only the tip of the iceberg (Iversen et al. , 2015). Root form and function remain hidden beneath the land surface. In an article recently published in New Phytologist , Blume-Werry et al. (2023, 10.1111/nph.18998) asked whether rooting depth distribution, and ensuing carbon emissions, could be inferred from commonly used vegetation mapping classifications across the pan-Arctic. An important question to guide our understanding, mapping, and prediction of belowground characteristics and ecosystem feedbacks at the top of the world. Unfortunately, they found that the answer was ‘not quite’. While rooting depth distribution varied demonstrably, in turn causing substantial changes in modeled carbon emissions via rhizosphere ‘priming’, variation across rooting depth profiles did not correspond with vegetation mapping classes. If we are unable to predict belowground rooting depth distributions across large spatial scales by leveraging aboveground vegetation community distributions, how then should belowground researchers proceed?

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

The importance of trait selection in ecology

Two recent publications have explored the importance of roots for understanding plant form and function but reached opposite conclusions on the basis of largely overlapping data. Carmona et al. concluded that their results “do not confirm the strong covariation between leaf and fine-root traits predicted by the plant economics spectrum hypothesis”. By contrast, Weigelt et al. concluded that “key leaf and fine-root traits were aligned along the expected [fast–slow] ‘conservation’ gradient of plant economic investment”. Furthermore, here we reflect on the causes for the apparent discrepancies of these studies and show that the rationale behind trait selection is vital for the conclusions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Thermal acclimation of plant photosynthesis and autotrophic respiration in a northern peatland

Peatlands contain one-third of global soil carbon (C), but the responses of peatland ecosystems to long-term warming are not well understood. Here, we pursue an emergent understanding of warming effects on ecosystem C fluxes at peatlands by constraining a process-oriented model, the terrestrial ECOsystem model, with observational data from a long-term warming experiment at the Spruce and Peatland Responses Under Changing Environments site. Model-based assessments show that ecosystem-level photosynthesis and autotrophic respiration exhibited significant thermal acclimation, with temperature sensitivities being linearly decreased with warming. Using the thermal-acclimated parameter values, simulated gross primary production, net primary production, and plant autotrophic respiration (R a ), were all lower than those simulated with non-thermal acclimated parameter values. In contrast, ecosystem respiration simulated with thermal acclimated parameter values was higher than that simulated with non-thermal acclimated parameter values. Net ecosystem CO 2 exchange was much higher after constraining model parameters with observational data from the warming treatments, releasing C at a rate of 28.3 g C m -2 yr -1 °C -1 . Our data-model integration study suggests that peatlands are likely to release more C than previously estimated. Earth system models may overestimate C uptake by peatlands under warming if physiological thermal acclimation of plants is not incorporated. Thus, it is critical to consider the long-term physiological thermal acclimation of plants in the models to better predict global C dynamics under future climate and their feedback to climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Climate drivers alter nitrogen availability in surface peat and decouple N 2 fixation from CH 4 oxidation in the Sphagnum moss microbiome

Peat mosses (Sphagnum spp.) are keystone species in boreal peatlands, where they dominate net primary productivity and facilitate the accumulation of carbon in thick peat deposits. Sphagnum mosses harbor a diverse assemblage of microbial partners, including N 2 -fixing (diazotrophic) and CH 4 -oxidizing (methanotrophic) taxa that support ecosystem function by regulating transformations of carbon and nitrogen. In this work, we investigate the response of the Sphagnum phytobiome (plant + constituent microbiome + environment) to a gradient of experimental warming (+0°C to +9°C) and elevated CO 2 (+500 ppm) in an ombrotrophic peatland in northern Minnesota (USA). By tracking changes in carbon (CH 4 , CO 2 ) and nitrogen (NH 4 -N) cycling from the belowground environment up to Sphagnum and its associated microbiome, we identified a series of cascading impacts to the Sphagnum phytobiome triggered by warming and elevated CO 2 . Under ambient CO 2 , warming increased plant-available NH 4 -N in surface peat, excess N accumulated in Sphagnum tissue, and N 2 fixation activity decreased. Elevated CO 2 offset the effects of warming, disrupting the accumulation of N in peat and Sphagnum tissue. Methane concentrations in porewater increased with warming irrespective of CO 2 treatment, resulting in a ~10× rise in methanotrophic activity within Sphagnum from the +9°C enclosures. Warming's divergent impacts on diazotrophy and methanotrophy caused these processes to become decoupled at warmer temperatures, as evidenced by declining rates of methane-induced N 2 fixation and significant losses of keystone microbial taxa. In addition to changes in the Sphagnum microbiome, we observed ~94% mortality of Sphagnum between the +0°C and +9°C treatments, possibly due to the interactive effects of warming on N-availability and competition from vascular plant species. Collectively, these results highlight the vulnerability of the Sphagnum phytobiome to rising temperatures and atmospheric CO 2 concentrations, with significant implications for carbon and nitrogen cycling in boreal peatlands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

SPRUCE Sphagnum Phytobiome Responses to Whole Ecosystem Warming and Elevated Atmospheric CO2 in July, 2017-2021

This dataset reports the carbon (C) and nitrogen (N) isotopic composition of Sphagnum moss tissue collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Tissues were collected inside the SPRUCE experimental study plot, where air and peat warming are combined in whole-ecosystem warming treatments, from 2019-2021. Additionally, rates of nitrogen fixation and methane oxidation measured for Sphagnum from 2017, 2019, and 2021. Sphagnum tissue % water content was measured at all timepoints. This dataset was used to conduct analyses within Petro et al (2023). Sphagnum C and N concentrations and 13C and 15N isotopic natural abundance were determined for three replicate Sphagnum tissue samples collected from inside the SPRUCE enclosures in July 2019-2021. Elemental and isotope analyses were conducted at the University of Georgia – Center for Applied Isotope Studies (CAIS; https://cais.uga.edu/). Plant elemental analysis was performed by the micro-Dumas method, while isotopic natural abundance was measured by isotope ratio mass spectrometry. 13C natural abundance is expressed as the per mille (‰) deviation from the Pee Dee Belemnite standard (PDB) 13C:12C ratio (δ13C), while 15N natural abundance is expressed as the ‰ deviation from the N2 atmospheric 15N:14N ratio (δ15N). Rates of nitrogen fixation and methane oxidation were measured using serum bottle incubations performed with Sphagnum collected inside the SPRUCE enclosures in July 2017, 2019, and 2021. Rates were calculated according to the amount of 15N-N2 or 13C-CH4 (methane) incorporated into the Sphagnum tissue or incubation headspace over the 48-hour intion period. In 2017, incubations were performed in growth chambers set to the temperature of the experimental plots during Sphagnum sampling. In 2019 and 2021, the incubations were performed directly inside the experimental plots. The 13C and 15N isotopic natural abundance data and rate measurements presented in this dataset provide insight into the impacts of whole-ecosystem warming and elevated atmospheric carbon dioxide (CO2) on N and C cycling within the Sphagnum phytobiome. This dataset contains two data files in comma-separate values (*.csv) format. Additional metadata are provided: two data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format. Additional datasets on NH4-N availability, porewater concentrations of CH4 and CO2, and Sphagnum groundcover within the SPRUCE experimental plots are available. These are outlined in the Related Datasets section in the user guide.

delta 13 carbon↗

DOE OSTI2023

Embracing fine-root system complexity in terrestrial ecosystem modeling

Projecting the dynamics and functioning of the biosphere requires a holistic consideration of whole-ecosystem processes. However, biases toward leaf, canopy, and soil modeling since the 1970s have constantly left fine-root systems being rudimentarily treated. As accelerated empirical advances in the last two decades establish clearly functional differentiation conferred by the hierarchical structure of fine-root orders and associations with mycorrhizal fungi, a need emerges to embrace this complexity to bridge the data-model gap in still extremely uncertain models. In this work, we propose a three-pool structure comprising transport and absorptive fine roots with mycorrhizal fungi (TAM) to model vertically resolved fine-root systems across organizational and spatial–temporal scales. Emerging from a conceptual shift away from arbitrary homogenization, TAM builds upon theoretical and empirical foundations as an effective and efficient approximation that balances realism and simplicity. A proof-of-concept demonstration of TAM in a big-leaf model both conservatively and radically shows robust impacts of differentiation within fine-root systems on simulating carbon cycling in temperate forests. Theoretical and quantitative support warrants exploiting its rich potentials across ecosystems and models to confront uncertainties and challenges for a predictive understanding of the biosphere. Echoing a broad trend of embracing ecological complexity in integrative ecosystem modeling, TAM may offer a consistent framework where modelers and empiricists can work together toward this grand goal.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

SPRUCE Climate Warming and Elevated CO2 Rapidly Alter Peatland Soil Carbon Sources and Stability: Supporting Data

This data set reports a suite of complementary biogeochemical analyses of peat samples from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment. Results were collected using quantitative molecular analysis of bulk soil carbon to assess the stability of soil organic carbon following whole-ecosystem warming and exposure to elevated carbon dioxide concentrations (eCO2). Targeted soil organic carbon components include solvent-extractable compounds (alkanoic acids, alkanols, alkanes, steroids, and terpenoids), ester-bound hydrolysable biopolymers (cutin and suberin markers), lignin phenols, and pyrogenic carbon. Bulk peat samples were analysed by Soxhlet extraction and solid phase separation for solvent-extractable compounds, alkaline hydrolysis to extract hydrolysable biopolymers, copper (II) oxide oxidation to extract lignin phenols and benzene polycarboxylic acids (BPCAs) as an approximation of pyrogenic carbon. Samples were analysed by gas chromatography (GC) equipped with a flame ionization detector (GC-FID) and compound identification was performed on GC coupled to mass selective detector (MS) for solvent-extractable compounds, ester-bound hydrolysable biopolymers and lignin phenols, and high-performance liquid chromatograph (HPLC) for pyrogenic carbon. Results are presented in Ofiti et al. (accepted). The experimental work was conducted on samples collected in August 2018 at the SPRUCE climate manipulation experiment in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). Samples were collected and later analysed in a 10 cm increments over 0 to 50 cm depth and 25 cm intervals from 50 to 75 cm. Samples were analyzed for lignin phenols over 0 to 30 cm depth. This data set contains one file in comma separate (*.csv) format. This dataset contains data used to produce: Ofiti, N.O.E., Schmidt, M.W.I., Abiven, S., Hanson, P.J., Iversen, C.M., Wilson, R.M., Kostka, J.E., Wiesenberg, G.L.B., Malhotra, A. 2023. Climate warming and elevated CO2 rapidly alter peatland soil carbon sources and stability. Nat Commun 14, 7533. https://doi.org/10.1038/s41467-023-43410-z.

SPRUCE experiment, Marcell Experimental Forest, so↗

DOE OSTI2022

Spatial patterns of snow distribution in the sub-Arctic

Abstract. The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017–2019; ∼ 2.5 km2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (> 22 000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86 % of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Evaluating alternative ebullition models for predicting peatland methane emission and its pathways via data–model fusion

Abstract. Understanding the dynamics of peatland methane (CH4) emissions and quantifying sources of uncertainty in estimating peatland CH4 emissions are critical for mitigating climate change. The relative contributions of CH4 emission pathways through ebullition, plant-mediated transport, and diffusion, together with their different transport rates and vulnerability to oxidation, determine the quantity of CH4 to be oxidized before leaving the soil. Notwithstanding their importance, the relative contributions of the emission pathways are highly uncertain. In particular, the ebullition process is more uncertain and can lead to large uncertainties in modeled CH4 emissions. To improve model simulations of CH4 emission and its pathways, we evaluated two model structures: (1) the ebullition bubble growth volume threshold approach (EBG) and (2) the modified ebullition concentration threshold approach (ECT) using CH4 flux and concentration data collected in a peatland in northern Minnesota, USA. When model parameters were constrained using observed CH4 fluxes, the CH4 emissions simulated by the EBG approach (RMSE = 0.53) had a better agreement with observations than the ECT approach (RMSE = 0.61). Further, the EBG approach simulated a smaller contribution from ebullition but more frequent ebullition events than the ECT approach. The EBG approach yielded greatly improved simulations of pore water CH4 concentrations, especially in the deep soil layers, compared to the ECT approach. When constraining the EBG model with both CH4 flux and concentration data in model–data fusion, uncertainty of the modeled CH4 concentration profiles was reduced by 78 % to 86 % in comparison to constraints based on CH4 flux data alone. The improved model capability was attributed to the well-constrained parameters regulating the CH4 production and emission pathways. Our results suggest that the EBG modeling approach better characterizes CH4 emission and underlying mechanisms. Moreover, to achieve the best model results both CH4 flux and concentration data are required to constrain model parameterization.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Whole-Ecosystem Warming Increases Plant-Available Nitrogen and Phosphorus in an Ombrotrophic Bog

Warming is expected to increase the net release of carbon from peatland soils, contributing to future warming. This positive feedback may be moderated by the response of peatland vegetation to rising atmospheric [CO 2 ] or to increased soil nutrient availability. We asked whether a gradient of whole-ecosystem warming (from + 0 °C to + 9 °C) would increase plant-available nitrogen and phosphorus in an ombrotrophic bog in northern Minnesota, USA, and whether elevated [CO 2 ] would modify the nutrient response. We tracked changes in plant-available nutrients across space and through time and in comparison with other nutrient pools, and assessed whether nutrient warming responses were captured by a point version of the land-surface model, ELM-SPRUCE. We found that warming exponentially increased plant-available ammonium and phosphate, but that nutrient dynamics were unaffected by elevated [CO 2 ]. The warming response increased by an order of magnitude between the first and fourth year of the experimental manipulation, perhaps because of dramatic mortality of Sphagnum mosses in the surface peat of the warmest treatments. However, neither the magnitude nor the temporal dynamics of the responses were captured by ELM-SPRUCE. Here, relative increases in plant-available ammonium and phosphate with warming were similar, but the response varied across raised hummocks and depressed hollows and with peat depth. Plant-available nutrient dynamics were only loosely correlated with inorganic and organic porewater nutrients, likely representing different processes. Future predictions of peatland nutrient availability under climate change scenarios must account for dynamic changes in nutrient acquisition by plants and microbes, as well as microtopography and peat depth.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

NGEE Arctic LANL Overview [Slides]

The Next-Generation Ecosystem Experiments (NGEE Arctic) project has a goal to "deliver a process-rich ecosystem model, extending from bedrock to the top of the vegetative canopy/atmospheric interface, in which the evolution of Arctic ecosystems in a changing climate can be modeled at the scale of a high resolution Earth System Model (ESM) grid cell." LANL works across multiple NGEE Arctic science questions, such as: Q1. How does the structure and organization of the landscape control permafrost evolution and associated carbon and nutrient fluxes in a changing climate? Q5. Where, when, and why will the Arctic become wetter or drier, and what are the implications for climate forcing? and Q6. What controls the vulnerability of Arctic ecosystems to disturbance, and how do disturbances alter the structure and function of these ecosystems? This report features LANL's research summaries.

54 ENVIRONMENTAL SCIENCES↗