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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Belowground plant allocation regulates rice methane emissions from degraded peat soils

Carbon-rich peat soils have been drained and used extensively for agriculture throughout human history, leading to significant losses of their soil carbon. One solution for rewetting degraded peat is wet crop cultivation. Crops such as rice, which can grow in water-saturated conditions, could enable agricultural production to be maintained whilst reducing CO 2 and N 2 O emissions from peat. However, wet rice cultivation can release considerable methane (CH 4 ). Water table and soil management strategies may enhance rice yield and minimize CH 4 emissions, but they also influence plant biomass allocation strategies. It remains unclear how water and soil management influences rice allocation strategies and how changing plant allocation and associated traits, particularly belowground, influence CH 4 -related processes. We examined belowground biomass (BGB), aboveground biomass (AGB), belowground:aboveground ratio (BGB:ABG), and a range of root traits (root length, root diameter, root volume, root area, and specific root length) under different soil and water treatments; and evaluated plant trait linkages to CH 4 . Rice (Oryza sativa L.) was grown for six months in field mesocosms under high (saturated) or low water table treatments, and in either degraded peat soil or degraded peat covered with mineral soil. We found that BGB and BGB:AGB were lowest in water saturated conditions where mineral soil had been added to the peat, and highest in low-water table peat soils. Furthermore, CH 4 and BGB were positively related, with BGB explaining 60% of the variation in CH 4 but only under low water table conditions. Our results suggest that a mix of low water table and mineral soil addition could minimize belowground plant allocation in rice, which could further lower CH 4 likely because root-derived carbon is a key substrate for methanogenesis. Minimizing root allocation, in conjunction with water and soil management, could be explored as a strategy for lowering CH 4 emissions from wet rice cultivation in degraded peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Agile Allocation in the Tundra: A Single Growing Season of Warming Increases Nutrient Availability While Decreasing Fine-Root Length

The majority of plant biomass is located belowground in Arctic ecosystems and plant roots are responsible for the uptake of the nutrients that constrain plant growth in these infertile ecosystems. Despite performing a crucial role connecting primary producers to the soil, roots are relatively understudied in the Arctic and their functional response to a rapidly warming and increasingly variable climate is unknown. Here, we assessed whether one growing season with elevated temperatures would have an impact on nutrient uptake and allocation by applying a warming technique that increased daily air temperatures by 3.2 °C. Destructive sampling was performed at the peak of the growing season to quantify biomass pools of carbon (C) and nitrogen (N), root traits, and uptake of a 15 N tracer ( 15 NH 4 + ) for the dominant plant species, Arctagrostis latifolia. We found that soil nutrient availability increased with short-term warming, but A. latifolia NH 4 + uptake remained unchanged. Fine-root length density and root biomass within the soil profile, however, were both reduced by warming. N allocation patterns across plant tissues were also altered by warming. NH 4 + uptake was best fit with a logistic model that captured the spatial relationship between roots and soil (NH 4 + uptake expressed per length fine root and NH 4 + availability expressed per unit soil volume) rather than a traditional Michaelis–Menten model. Our results indicate that short-term experimental warming can shift plant–soil interactions, suggesting that the tundra’s belowground response to elevated temperatures may be more dynamic than previously recognized.

15N tracer↗
DOE OSTI2022

Annual Herbaceous Plants Exhibit Altered Morphological Traits in Response to Altered Precipitation and Drought Patterns in Semiarid Sandy Grassland, Northern China

The frequency and intensity of extreme precipitation events and severe drought are predicted to increase in semiarid areas due to global climate change. Plant morphological traits can reflect plant responses to a changing environment, such as altered precipitation or drought patterns. In this study, we examined the response of morphological traits of root, stem, leaf and reproduction meristems of annual herbaceous species to altered precipitation and drought patterns in a semiarid sandy grassland. The study involved a control treatment (100% of background precipitation) and the following six altered precipitation treatments: (1) P(+): precipitation increased by 30%, (2) P(++): precipitation increased by 60%, (3) P(-): precipitation decreased by 30%, (4) P(--): precipitation decreased by 60%, (5) drought 1 (D1): 46-day drought from May 1st to June 15th, and (6) drought 2 (D2): 46-day drought from July 1st to August 15th. P(++) significantly increased root length, flower length-to-width ratio, both P(+) and P(++) significantly increased stem length and flower number in the plant growing seasons, while all of them decreased under P(-) and P(--). The annual herbaceous plants marginally increased the number of second-level stem branches and stem diameter in order to better resist the severe drought stress under P(--). P(+) and P(++) increased the root, stem, leaf, and flower dry weight, with the flower dry weight accounting for a larger proportion than the other aboveground parts. Under D2, the plants used the limited water resources more efficiently by increasing the root-to-shoot ratio compared with P(-), P(--) and D1, which reflects biomass allocation to belowground increased. The linear mixed-effects models and redundancy analysis showed that the root-to-shoot ratio and the dry weight of various plant components were significantly affected by morphological traits and altered precipitation magnitude. Our results showed that the herbaceous species have evolved morphological trait responses that allow them to adapt to climate change. Such differences in morphological traits may ultimately affect the growing patterns of annual herbaceous species, enhancing their drought-tolerant capacity in semiarid sandy grassland during the ongoing climate change.

Sun, Shan-Shan↗
DOE OSTI2023

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

Among many agricultural practices proposed to cut carbon emissions in the next 30 years is the deposition of carbon in soils as plant matter. Adding rooting traits as part of a sequestration strategy would result in significantly increased carbon sequestration. Integrating these traits into production agriculture requires a belowground phenotyping method compatible with high-throughput breeding (i.e., rapid, inexpensive, reliable, and non-destructive). However, methods that fulfill these criteria currently do not exist. We hypothesized that ground-penetrating radar (GPR) could fill this need as a phenotypic selection tool. In this study, we employed a prototype GPR antenna array to scan and discriminate the root and rhizome mass of the perennial sorghum hybrid PSH09TX15. B-scan level time/discrete frequency analyses using continuous wavelet transform were utilized to extract features of interest that could be correlated to the biomass of the subsurface roots and rhizome. Time frequency analysis yielded strong correlations between radar features and belowground biomass (max R −0.91 for roots and −0.78 rhizomes, respectively) These results demonstrate that continued refinement of GPR data analysis workflows should yield an applicable phenotyping tool for breeding efforts in contexts where selection is otherwise impractical.

Wolfe, Matthew↗
DOE OSTI2024

A Test of Functional Balance Theory for Wetland Biomass Allocation in a Global Change Experiment

Abstract Forecasts of root growth and carbon sequestration under global change are compromised by uncertainty in how plants will allocate biomass between above and belowground pools. Here, we develop a simple model to assess whether functional balance theory can explain a complex biomass allocation response observed in a brackish marsh under experimental warming and elevated CO 2 . Our model shows how treatment‐driven changes in nitrogen supply and demand can explain divergent observations of root growth (i.e., maximum responses under intermediate warming and elevated CO 2 ). The model also reveals a surprising interaction between warming and eutrophication, where enhanced N loading to coastal marshes may reduce adverse impacts of warming on root growth. Our findings provide a mechanistic basis for incorporating biomass allocation into forecast models of marsh evolution. They also provide a general example of using ecological theory to decompose complex net responses observed in multi‐factor global change experiments into constituent processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data for Aboveground rather than belowground productivity drives variability in Miscanthus x giganteus net primary productivity

This dataset contains the data used for the publication “Aboveground rather than belowground productivity drives variability in Miscanthus x giganteus net primary productivity”. This dataset contains Miscanthus x giganteus biomass, carbon, and nitrogen tissue data for aboveground and belowground plant parts collected in 2021 for three different sites in Iowa with three different nitrogen application rates. Data at the Iowa sites were collected via biometric hand harvesting, belowground excavations, and soil coring both in-clump and beside-clump. Data were collected at two collection timepoints to calculate the contributions of belowground parts to Miscanthus x giganteus net primary productivity. This dataset also includes Miscanthus x giganteus and Switchgrass soil coring and excavation data collected in 2012 at the University of Illinois Urbana Champaign Energy Farm.

Belowground Biomass↗
DOE OSTI2021

Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations

Abstract Accurate simulations of high‐latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO 2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Many such models represent high‐latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine Arctic‐specific PFTs. The newly developed PFTs include: (1) nonvascular mosses and lichens, (2) deciduous and evergreen shrubs of various height classes, including an alder PFT, (3) graminoids, and (4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario and constant PFT fractional areas showed alder‐dominated plant communities gaining more biomass and lichen‐dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Data from: "Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine"

This data package contains data that were used to support conclusions drawn in “Growth strategies and threshold responses to water deficit modulate effects of warming on tree seedlings from forest to alpine”, by Lazarus, Castanha et al. 2017. Data were collected at field sites within the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA, and at the U.S. Geological Survey laboratory located in Boise, Idaho. This archive contains comma-separated-values (.csv) files, as well as the same files in Microsoft Excel (.xlsx) format, which can be opened by either Microsoft Excel, R, or any simple text editor program. There are two types of geospatial data files: .kml and ESRI shapefiles (.shp). The kml files contain placemarks, which can be opened by Google Earth, or Google Maps. The ESRI shapefiles can be opened by any geographic information system application that can read shapefiles, including ESRI's entire ArcGIS suite, and QGIS. We asked whether and how tree species differences in response to water deficit relates to their establishment along the gradient from forest to alpine. To do this, we compared growth and moisture stress responses in first-year seedlings of three species planted in common gardens subject to a factorial of heating and watering treatments below, at, and above tree line. This combination of an elevation gradient alongside warming and watering treatments enabled us to observe species differences in seedling responses to a broad set of climatic conditions.Entire seedlings were harvested at c. 3- and again at 9 weeks of age following germination/emergence in the experimental plots, and we then measured dry mass (DM) of above and belowground parts, root length, root mass fraction (RMF), relative growth rates (RGRs) from seed to 3 weeks and from 3 to 9 weeks, turgor-loss point (TLP), and photosynthetic WUE (as δ13C). Also included in this dataset (but not described in the manuscript) are measures of specific leaf area (SLA) and other variables generated by pressure-volume curves (saturated water content, osmotic potential at full turgor, elastic modulus).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

BOREAS TE-6 NPP For The Tower Flux, Carbon Evaluation, and Auxiliary Sites

The BOREAS TE-6 team collected several data sets to examine the influence of vegetation, climate, and their interactions on the major carbon fluxes for boreal forest species. This data set contains estimates of the biomass produced by the plant species at the TF, CEV, and AUX sites in the SSA and NSA for a given year. Temporally, the data cover the years of 1985 to 1995. The plant biomass production (i.e., aboveground, belowground, understory, litterfall), spatial coverage, and temporal nature of measurements varied between the TF, CEV, and AUX sites as deemed necessary by BOREAS principal investigators. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
DOE OSTI2024

Biomass Carbon Removal and Storage (BiCRS)

To achieve the ambitious net-zero emission goal by 2050, it is vital to explore practical approaches for removing carbon dioxide from the air. One promising method is Biomass Carbon Removal and Storage (BiCRS). BiCRS combines the natural ability of plants to convert carbon dioxide into biomass with human engineering to store the biomass, or derived products (char), belowground where it won't decompose. By securely storing these materials underground, we can trap the carbon dioxide absorbed by the plants during their growth, thus aiding in carbon removal from the atmosphere. BiCRS not only addresses carbon emissions but also has co-benefits such as wildfire risk reduction by utilizing forest residues. It is essential to establish best practices to ensure accurate measurements of net carbon dioxide removed by BiCRS for policymakers, businesses and communities. Presently, there is a lack of consistent methods for calculating these removals, considering variables like plant type, storage conditions, and conditions for converting the biomass to other products for storage like char. This project develops guidelines for monitoring and reporting BiCRS activities, offering a dependable framework for measuring carbon dioxide removal, enabling adoption of transparent BiCRS approaches for making significant contributions to reducing carbon dioxide levels in the atmosphere.

biomass carbon removal and storage↗
DOE OSTI2025

Unraveling the influence of microbial necromass on subsurface microbiomes: metabolite utilization and community dynamics

The role of microbial necromass (nonliving microbial biomass), a significant component of belowground organic carbon, in nutrient cycling and its impact on the dynamics of microbial communities in subsurface systems remains poorly understood. It is currently unclear whether necromass metabolites from various microbes are different, whether certain groups of metabolites are preferentially utilized over others, or whether different microbial species respond to various necromass metabolites. In this study, we aimed to fill these knowledge gaps by designing enrichments with necromass as the sole nutrient source for subsurface microbial communities. We used the soluble fraction of necromass from bacterial isolates belonging to Arthrobacter, Agrobacterium, and Pseudomonas genera, and our results indicate that metabolite composition of necromass varied slightly across different strains but generally included amino acids, organic acids, and nucleic acid constituents. Arthrobacter-derived necromass appeared more recalcitrant. Necromass metabolites enriched diverse microbial genera, particularly Massilia sp. responded quickly regardless of the necromass source. Despite differences in necromass utilization, microbial community composition converged rapidly over time across the three different necromass amendments. Uracil, xanthine, valine, and phosphate-containing isomers were generally depleted over time, indicating microbial assimilation for maintenance and growth. However, numerous easily assimilable metabolites were not significantly depleted, suggesting efficient necromass recycling and the potential for necromass stabilization in systems. This study highlights the dynamic interactions between microbial necromass metabolites and subsurface microbial communities, revealing both selective utilization and rapid community and necromass convergence regardless of the necromass source.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The physiological acclimation and growth response of Populus trichocarpa to warming

Plant metabolic acclimation to thermal stress remains underrepresented in current global climate models. Gaps exist in our understanding of how metabolic processes (i.e., photosynthesis, respiration) acclimate over time and how aboveground versus belowground acclimation differs. We measured the thermal acclimation of Populus trichocarpa, comparing aboveground versus belowground physiology over time. Ninety genetically identical ramets were propagated in mesocosms that separated root and microbial components. After establishment at 25°C for 6 weeks, 60 clones were warmed +4 or +8°C and monitored for 10 weeks, measuring photosynthesis (A), leaf respiration (R), soil respiration (R s ), root plus soil respiration (R s+r ), and root respiration (R r ). We observed thermal acclimation in both A and R, with rates initially increasing, then declining as the thermal photosynthetic optimum (T opt ) and the temperature-sensitivity (Q 10 ) of respiration adjusted to warmer conditions. Photosynthetic acclimation was constructive, based on an increase in both T opt and peak A. Belowground, R s+r decreased linearly with warming, while R s rates declined abruptly, then remained constant with additional warming. Plant biomass was greatest at +4°C, with 30% allocated belowground. Rates of mass-based R r were similar among treatments; however, root nitrogen declined at +8°C leading to less mass nitrogen-based R r in that treatment. The Q 10 -temperature relationship of R r was affected by warming, leading to differing values among treatments. Aboveground acclimation exceeded belowground acclimation, and plant nitrogen-use mediated the acclimatory response. Results suggest that moderate climate warming (+4°C) may lead to acclimation and increased plant biomass production but increases in production could be limited with severe warming (+8°C).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rapid in situ nutrient element distribution in plants and soils using laser-induced breakdown spectroscopy ($\mathrm{LIBS}$)

The aim of this study is to develop and test the applicability of a rapid in situ plant chemistry profiling technique to determine elemental composition of small-volume plant and soil samples obtained from a woody bioenergy crop species, Populus trichocarpa. Expanding the research tools available to characterize the nutrient element correlations among plant tissue types and soil depths is a critical need in the path of understanding productivity and adaptation of plants to variations in external abiotic and biotic factors and developing sustainable perennial bioenergy crops that are co-optimized for biomass valorization aboveground and carbon sequestration belowground. Several plant root, stem, and soil samples were tested using laser-induced breakdown spectroscopy (LIBS) to evaluate the presence and distribution of nutrient elements. Samples were tested as collected and after being dried and cross sectioned to evaluate the effectiveness of using LIBS for in situ analysis on plant samples. The collected LIBS spectra show the elemental peaks were the same in both the as collected and prepared samples for roots and stems. Qualitative amounts of elements such as H, C, N, O, Li, Na, Mg, K, Ca, Fe, Al, and Si were able to be identified rapidly in raw samples. Here in this report we demonstrate suitability of LIBS in obtaining rapid, in situ, elemental distribution in plant and soil samples, utilizing only small sample volumes and minimal sample preparation. This demonstration opens up a new rapid phenotyping avenue necessary to fill the asymmetrical knowledge gaps in belowground performance of plant systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Beyond carbon flux partitioning: Carbon allocation and nonstructural carbon dynamics inferred from continuous fluxes

Carbon (C) allocation and nonstructural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here, in this work, we propose a framework where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO 2 exchange, soil CO 2 efflux, and allometry-based biomass and net primary production) by a simple mass balance model to derive ecosystem-level NSC dynamics (NSC i ), C translocation (dC i ), and the biomass production efficiency (BPE i ) in above- and belowground plant (i = agp and bgp) compartments. We applied this framework to two long-term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale, whereas the mature stand stored a near-constant proportion of new assimilates as NSC every year under normal conditions, which was comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post drought. The above- and belowground dC i and BPE i varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPE bgp differed the most between the young and mature stands and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve biomass production estimation, which reveals the variations resulting from droughts. Overall, these quantified ecosystem-scale dynamics were consistent with existing evidence from tree-based manipulative experiments and measurements and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models and offers new insights into observed variability in soil–plant–climate interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Life cycle greenhouse gas emissions of ethanol produced via fermentation of sugars derived from shrub willow (Salix ssp.) hot water extraction in the Northeast United States

Abstract Background The amount of carbon dioxide in the atmosphere has been on the rise for more than a century. Bioenergy crops are seen by the Intergovernmental Panel on Climate Change as an essential part of the solution to addressing climate change. To understand the potential impact of shrub willow ( Salix spp . ) crop in the northeast United States, effective and transparent life cycle assessment of these systems needs to occur. Results Here we show, ethanol produced from the fermentation of sugars from hot water extract of willow grown on cropland can sequester 0.012 ± 0.003 kg CO 2eq MJ −1 for a supply system incorporating summer harvest and storage. Despite decreases in soil organic carbon when willow is instead grown on grassland, the produced fuel still can provide significant climate benefits compared to gasoline. Conclusions Shrub willow converted to ethanol can be a carbon negative source of transportation fuel when the electricity and heat required for the conversion process are generated from renewable biomass. The sequestration of carbon in the belowground portion of the plants is essential for the negative GHG balance for cropland and low GHG emissions in grassland.

10 SYNTHETIC FUELS↗
DOE OSTI2021

Variation in hyphal production rather than turnover regulates standing fungal biomass in temperate hardwood forests

Abstract Soil fungi link above‐ and belowground carbon (C) fluxes through their interactions with plants and contribute to C and nutrient dynamics through the production, turnover, and activity of fungal hyphae. Despite their importance to ecosystem processes, estimates of hyphal production and turnover rates are relatively uncommon, especially in temperate hardwood forests. We sequentially harvested hyphal ingrowth bags to quantify the rates of Dikarya (Ascomycota and Basidiomycota) hyphal production and turnover in three hardwood forests in the Midwestern United States, where plots differed in their abundance of arbuscular (AM)‐ vs. ectomycorrhizal (ECM)‐associated trees. Hyphal production rates increased linearly with the percentage of ECM trees and annual production rates were 66% higher in ECM‐ than AM‐dominated plots. Hyphal turnover rates did not differ across the mycorrhizal gradient (plots varying in their abundance of AM vs. ECM trees), suggesting that the greater fungal biomass in ECM‐dominated plots relates to greater fungal production rather than slower fungal turnover. Differences in hyphal production across the gradient aligned with distinctly different fungal communities and activities. As ECM trees increased in dominance, fungi inside ingrowth bags produced more extracellular enzymes involved in degrading nitrogen (N)‐bearing relative to C‐bearing compounds, suggesting greater fungal (and possibly plant) N demand in ECM‐dominated soils. Collectively, our results demonstrate that shifts in temperate tree species composition that result in changes in the dominant type of mycorrhizal association may have strong impacts on Dikarya hyphal production, fungal community composition and extracellular enzyme activity, with important consequences for soil C and N cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

FUN-BioCROP model with litter decomposition parameters derived from the LIDET dataset

This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023

Juice, Stephanie↗
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.

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