Search NASA⌕ Search

SEARCH · Search NASA

Results for “litter”

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.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Arctic shrub expansion generates regional variation in litter decomposition by altering litter quality and the decomposition environment

Abstract The expansion of deciduous shrubs into the graminoid‐dominated arctic tundra is expected to alter litter decomposition by changing litter quality and local abiotic and biotic conditions. However, it remains unclear how shrub expansion will affect litter decomposition at regional scales, where macroclimate is expected to be the dominant regulator of decomposition. To determine the relative influence of macroclimate and local controls on regional patterns of litter mass loss and nitrogen release, we conducted two hierarchical litter decomposition experiments across spatial scales. We decomposed leaf and root litter from a prominent graminoid ( Eriophorum vaginatum ) and three genera of deciduous shrubs ( Betula , Alnus and Salix ) for 1 year within replicated plots at five sites spanning a 160 km latitudinal gradient in northern Alaska. Using Eriophorum litter as a substrate, we found that macroclimate was the primary regulator of mass loss but had opposing effects on leaf and root litter. As summer temperature increased along the latitudinal gradient (11.9 to 13.9°C), leaf litter mass loss increased by 20% whereas root litter mass loss decreased by 33%. Leaf nitrogen release also increased with summer temperature. Conversely, root nitrogen release was controlled by the vegetation type of the decomposition environment. Using different shrub litters as substrates, we found that litter quality and its interaction with soil microclimate and macroclimate controlled decomposition. Overall, shrub root litters decomposed faster than Eriophorum root litter, losing 53% more mass and 190% more nitrogen across all sites and decomposition environments. For leaf litter, however, patterns varied by litter genus, with Salix losing more mass and Betula and Alnus losing less mass than Eriophorum . Our findings demonstrate that shrub expansion in the Arctic can regulate leaf and root litter decomposition at the regional scale through its effects on local controls, primarily litter quality. Ongoing increases in shrub cover are likely to accelerate the turnover of root litter carbon and nitrogen pools in tundra ecosystems. Therefore, including shrub‐related processes in Earth system models will improve our ability to predict regional‐scale litter decomposition and its effects on carbon and nutrient cycling in a warming Arctic. Read the free Plain Language Summary for this article on the Journal blog.

Vozzo, Justin T. [Department of Natural Resources ↗
DOE OSTI2021

Microbial community composition controls carbon flux across litter types in early phase of litter decomposition

Leaf litter decomposition is a major carbon input to soil, making it a target for increasing soil carbon storage through microbiome engineering. We expand upon previous findings to show with multiple leaf litter types that microbial composition can drive variation in carbon flow from litter decomposition and specific microbial community features are associated with synonymous patterns of carbon flow among litter types. Although plant litter type selects for different decomposer communities, within a litter type, microbial composition drives variation in the quantity of dissolved organic carbon (DOC) measured at the end of the decomposition period. Bacterial richness was negatively correlated with DOC quantity, supporting our hypothesis that across multiple litter types there are common microbial traits linked to carbon flow patterns. Variation in DOC abundance (i.e. high versus low DOC) driven by microbial composition is tentatively due to differences in bacterial metabolism of labile compounds, rather than catabolism of non-labile substrates such as lignin. The temporal asynchrony of metabolic processes across litter types may be a substantial impediment to discovering more microbial features common to synonymous patterns of carbon flow among litters. Overall, our findings support the concept that carbon flow may be programmed by manipulating microbial community composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Reparameterizing Litter Decomposition Using a Simplified Monte Carlo Method Improves Litter Decay Simulated by a Microbial Model and Alters Bioenergy Soil Carbon Estimates

Litter decomposition determines soil organic matter (SOM) formation and plant-available nutrient cycles. Therefore, accurate model representation of litter decomposition is critical to improving soil carbon (C) projections of bioenergy feedstocks. Soil C models that simulate microbial physiology (i.e., microbial models) are new to bioenergy agriculture, and their parameterization is often based on small datasets or manual calibration to reach benchmarks. Here, we reparameterized litter decomposition in a microbial soil C model (CORPSE - Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) using the continental-scale Long-term Inter-site Decomposition Experiment Team (LIDET) dataset which documents decomposition across a range of litter qualities over a decade. Here, we conducted a simplified Monte Carlo simulation that constrained parameter values to reduce computational costs. The LIDET-derived parameters improved modeled C and nitrogen (N) remaining, decomposition rates, and litter mean residence times as compared to Baseline parameters. We applied the LIDET litter decomposition parameters to a microbial bioenergy model (Fixation and Uptake of Nitrogen – Bioenergy Carbon, Rhizosphere, Organisms, and Protection) to examine soil C estimates generated by Baseline and LIDET parameters. LIDET parameters increased estimated soil C in bioenergy feedstocks, with even greater increases under elevated plant inputs (i.e., by increasing residue, N fertilization). This was due to the integrated effects of plant litter quantity, quality, and agricultural practices (tillage, fertilization). Collectively, we developed a simple framework for using large-scale datasets to inform the parameterization of microbial models that impacts projections of soil C for bioenergy feedstocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland

Abstract Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Modeling delayed thermal runaway in nitric acid-soaked cat litter mixed with radioactive waste

Thermal ignition of radioactive waste within a 55-gallon drum was simulated by using a pressure-dependent waste decomposition model (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) calibrated with data from full-scale drum experiments (Parker et al. in The thermolytic response of a surrogate RNS waste mixture at the drum scale. Los Alamos National Laboratory Report LA-UR-16-21760, 2016) and validated with experiments from multiple laboratories (Hobbs et al. in Thermal analysis of aged nitric acid-soaked kitty litter in TRU waste drums-23370.WM2023 Conference, Phoenix, AZ, 2023). The acceleration of nitric acid chemistry reacting with an organic cat litter leading to thermal ignition was likely triggered by a restricted vent in the drum. Here, we address whether the form of the rate equation in (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) is sufficient to extrapolate thermal ignition within aged drums of similar content that have been stored in Texas for over nine years by investigating four different reaction rate forms for waste decomposition. A critical reaction rate reduction analysis is performed on each of these models to determine if delayed thermal runaway within vented aged waste is possible after nine years. We found that a pressure-dependent first-order rate expression not only predicted the accidental ignition of the waste drum, but the form also matches multiple experiments from different laboratories. Even though the waste composition decreases over time, the model predicts that acceleration leading to thermal runaway is possible if the waste is confined, even after 9 years. In conclusion, waste containing oxidizers such as nitric acid should not be mixed with organic adsorbents, especially if the waste is confined.

cookoff↗
DOE OSTI2020

Microbial inputs at the litter layer translate climate into altered organic matter properties

Plant litter chemistry is altered during decomposition but it remains unknown if these alterations, and thus the composition of residual litter, will change in response to climate. Selective microbial mineralization of litter components and the accumulation of microbial necromass can drive litter compositional change, but the extent to which these mechanisms respond to climate remains poorly understood. We addressed this knowledge gap by studying needle litter decomposition along a boreal forest climate transect. Specifically, we investigated how the composition and/or metabolism of the decomposer community varies with climate, and if that variation is associated with distinct modifications of litter chemistry during decomposition. We analyzed the composition of microbial phospholipid fatty acids (PLFA) in the litter layer and measured natural abundance δ 13 CPLFA values as an integrated measure of microbial metabolisms. Changes in litter chemistry and δ 13 C values were measured in litterbag experiments conducted at each transect site. A warmer climate was associated with higher litter nitrogen concentrations as well as altered microbial community structure (lower fungi:bacteria ratios) and microbial metabolism (higher δ 13 CPLFA). Litter in warmer transect regions accumulated less aliphatic-C (lipids, waxes) and retained more O-alkyl-C (carbohydrates), consistent with enhanced 13 C-enrichment in residual litter, than in colder regions. These results suggest that chemical changes during litter decomposition will change with climate, driven primarily by indirect climate effects (e.g. greater nitrogen availability and decreased fungi:bacteria ratios) rather than direct temperature effects. A positive correlation between microbial biomass δ 13 C values and 13 C-enrichment during decomposition suggests that change in litter chemistry is driven more by distinct microbial necromass inputs than differences in the selective removal of litter components. Our study highlights the role that microbial inputs during early litter decomposition can play in shaping surface litter contribution to soil organic matter as it responds to climate warming effects such as greater nitrogen availability.

13C↗
DOE OSTI2022

Litter removal impacts on soil biodiversity and eucalypt plantation development in the seasonal tropics

The little layer of tree plantations provides primary nutrients for uptake, buffers changes in soil moisture, and provides habitat and substrate to soil epigeic fauna. However, this layer in eucalypt plantations is often removed to reduce fuel load during the fire season in the Brazilian savanna (Cerrado). Therefore, it is necessary to quantify the effects of changes in litter dynamics on the function of these plantations, on key nutrient cycling processes and on epigeic fauna diversity and abundance. In two adjacent stands (one juvenile and one mature), the consequences of two years of litter removal were quantified as monthly litterfall, leaf and fine wood litter decomposition, epigeic fauna abundance and diversity, soil biogeochemical variables, and tree diameter and basal area increments. Monthly litterfall rates in juvenile and mature stands did not change with litter removal over the study period. Annual litterfall ranged from 4.1 to 4.9 Mg ha -1 a -1 in litter removal plots and from 3.9 to 4.8 Mg ha -1 a -1 in control plots. Fine wood litter decomposition was slower in litter removal plots compared to controls, while leaf decomposition rates were similar in both. Two years of litter removal in the juvenile stand did not affect topsoil biogeochemical parameters but decreased available phosphorus at 20–40 cm depth relative to controls. In the mature stand, total cation exchange capacity (0–20 cm) was higher in controls (6.4 cmol c dm -3 ) relative to litter removal plots (6.3 cmol c dm -3 ), while soil moisture (0–40 cm depth) was lower in litter removal (25.45 m 3 m -3 ) compared to control plots (26 m 3 m -3 ) in the dry season. A non-metric multidimensional scaling ordination revealed an increased homogeneity in epigeic fauna where litter was removed. Litterfall, decomposition, diameter increment, four soil physical parameters and fourteen chemical parameters at 0–20 and 20–40 cm depth explained the differences in soil epigeic fauna composition between litter removal and control plots. Diameter increment decreased with litter removal only in the juvenile stand, which had reached its growth peak. The results indicate that removing excess litter to decrease fuel volume can alter soil biodiversity and edaphic conditions that negatively affect nutrient cycling and tree growth.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Influence of root- vs needle-derived litter on soil C and N stabilization in a California coniferous forest from 2001 to 2011

How plant inputs from above- versus below-ground affect long term carbon (C) and nitrogen (N) retention and stabilization in soils is not well known. We present results of a decade-long field study that traced the decomposition of 13C- and 15N-labeled Pinus ponderosa needle and fine root litter placed in O or A soil horizons of a sandy Alfisol under a coniferous forest. We measured the retention of litter-derived C and N in particulate (>2 mm) and bulk soil (<2 mm) fractions, as well as in density-separated free light and three mineral-associated fractions. After 10 years, the influence of slower initial mineralization of root litter compared to needle litter was still evident: almost twice as much root litter (44% of C) was retained than needle litter (22–28% of C). After 10 years, the O horizon retained more litter in coarse particulate matter implying the crucial comminution step was slower than in the A horizon, while the A horizon retained more litter in the finer bulk soil, where it was recovered in organo-mineral associations. Retention in these A horizon mineral-associated fractions was similar for roots and needles. Nearly 5% of the applied litter C (and almost 15% of the applied N) was in organo-mineral associations, which had centennial residence times and potential for long-term stabilization. Vertical movement of litter-derived C was minimal after a decade, but N was significantly more mobile. Overall, the legacy of initial litter quality influences total SOM retention; however, the potential for and mechanisms of long-term SOM stabilization are influenced not by litter type but by soil horizon.This dataset comprises (1) litter recovery for each of 5 timepoints in >2mm, <2mm, and density fractions, (2) density fractionation results for the 10-year timepoint, and (3) vertical movement of applied litter.

54 ENVIRONMENTAL 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 OSTI2022

Plant litter traits control microbial decomposition and drive soil carbon stabilization

Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13 C enriched aboveground and belowground litters to soils and traced the fate of the 13 C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modelling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modelling SOC transformations.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Effects of litter addition on ectomycorrhizal associates of a lodgepole pine (Pinus contorta) stand in Yellowstone National Park

Increasing soil nutrients through litter manipulation, pollution, or fertilization can adversely affect ectomycorrhizal (EM) communities by inhibiting fungal growth. In this study, we used molecular genetic methods to determine the effects of litter addition on the EM community of a Pinus contorta stand in Yellowstone National Park that regenerated after a stand-replacing fire. Two controls were used; in unmodified control plots nothing was added to the soil, and in perlite plots perlite, a chemically neutral substance, was added to maintain soil moisture and temperature at levels similar to those under litter. We found that (i) species richness did not change significantly following perlite addition (2.6 +/- 0.3 species/core in control plots, compared with 2.3 +/- 0.3 species/core in perlite plots) but decreased significantly (P < 0.05) following litter addition (1.8 +/- 0.3 species/core); (ii) EM infection was not affected by the addition of perlite but increased significantly (P < 0.001) in response to litter addition, and the increase occurred only in the upper soil layer, directly adjacent to the added litter; and (iii) Suillus granulatus, Wilcoxina mikolae, and agaricoid DD were the dominant organisms in controls, but the levels of W. mikolae and agaricoid DD decreased significantly in response to both perlite and litter addition. The relative levels of S. granulatus and a fourth fungus, Cortinariaceae species 2, increased significantly (P < 0.01 and P < 0.05, respectively) following litter addition. Thus, litter addition resulted in some negative effects that may be attributable to moisture-temperature relationships rather than to the increased nutrients associated with litter. Some species respond positively to litter addition, indicating that there are differences in their physiologies. Hence, changes in the EM community induced by litter accumulation also may affect ecosystem function.

Fungi/classification/growth & development↗
DOE OSTI2022

Castanha et al. 2018: Hopland Lysimeter 13C-Labeled Root Litter Decomposition Study.

The breakdown and decomposition of plant inputs are critical for nutrient cycling, soil development, and climate-ecosystem feedbacks, but uncertainties persist in how the rates and products of litter decomposition are affected by soil temperature, rhizosphere, and depth of input. To elucidate these questions we measured the effects of soil warming (+ 4 °C), rhizosphere, and depth of litter placement on the decomposition of Avena fatua (wild oat grass) root litter in a Mediterranean grassland ecosystem. Field lysimeters were subjected to three environmental treatments (heating, control, and plant removal) and three 13C-labeled root litter addition treatments (to A horizon, to B horizon, and no-addition disturbance control) for each of two harvest time points. We buried root litter in February 2014 and measured loss of 13C in CO2 from the soil surface and in leachate as dissolved organic carbon (DOC) over two growing seasons. At the end of each of the 2014 and 2015 growing seasons we recovered the 13C remaining in the soil. Loss of root litter C occurred almost entirely via heterotrophic respiration, with an estimated < 2% lost as DOC during the initial decay period. The added roots were broken down and incorporated into bulk soil material very quickly; only ~ 30% of added root was visible after 6 months. In the first growing season, decomposition occurred faster in the B than in the A horizon, the latter having greater moisture limitation. Subsequently, there was almost no further decomposition in the B horizon. After two growing seasons, less than 20% of the added root litter C remained in the A or B horizons of all environmental treatments. Heating did not stimulate decomposition, likely because it exacerbated the moisture limitation. However, while plots without plants dried down more slowly than plots with plants, their decomposition rate was not significantly greater, possibly due to the lack of rhizosphere processes such as priming. We conclude that in this Mediterranean grassland ecosystem, soil moisture, which is affected by season, depth, heating, and rhizosphere, plays a dominant role in mediating the effect of those factors on root litter decomposition, which after two seasons did not differ by depth or by treatment.The files in this dataset comprise (1) 13C-labeled litter additions made to each plot, (2) litter recovery after each of 2 growing seasons, (3) periodical soil flux measurements, (4) leachate measurements, and continuously monitored soil (5) temperature and (6) moisture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CORPSE model with litter decomposition parameters derived from the LIDET dataset

This is a version of the CORPSE model (Carbon, Organisms, Rhizosphere and Protection in the Soil Environment, Sulman et al. 2014) that uses litter decomposition parameters derived from a modified Monte Carlo simulation using the LIDET litter decomposition dataset (Long-term Intersite Decomposition Experiment Team, Harmon 2013). The code also includes the Baseline parameters, and the eight other best parameter sets identified in a modified Monte Carlo simulation. 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:The folder "Input Files" contains one folder for each LIDET site with data necessary to run the model. Note that "(site)" in the filenames below indicates where the LIDET site code appears (see Table 1 for site codes). Data streams include: CORPSE_full_spinup_litter.csv, CORPSE_full_spinup_rhizo.csv, CORPSE_full_spinup_bulk.csv, litterbag_init_100g_6spp.csv: initial C and N (kg C or N/m2) pool values for each soil layer, the litterbag_init_100_6spp.csv file is for the litterbag layer and is the same file for all sites. All initial C and N 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 soilT (site) DOY274start.csv: Average daily soil temperature (oC) interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). soilT (site) DOY274start.csv: Average daily soil volumetric water content (VWC) scalar interpolated from previously calculated monthly values used in DayCent LIDET simulations (Bonan et al., 2013). litter production.csv: Average daily litter production values for each site, data sources listed in Table S3 of related publication. litter (site) CN.csv: C:N ratio for each species from LIDET dataset (Table 2, Harmon 2013). (site).csv: Table indicating number of observations for each species decomposed at each site. Instructions: Save the model code ("CORPSE_LIDET.R") and "Input Files" folder in the same folder. Also make a folder for the model output (e.g., "results_Baseline") in the same folder. Set the working directory (setwd) in the model code to the folder with the files saved in step #1. Select the parameter set to use for the litter and litterbag compartments, comment out all other parameter sets. Run code. Output will be saved in the folder made in step 1. Output destination can be changed as necessary in code section called "Running the model." Table 1 LIDET sites and site codes used in model files. Site Code - Site AND - H.J. Andrews Experimental Forest BNZ - Bonanza Creek Experimental Forest BSF - Blodgett Research Forest CDR - Cedar Creek Natural History Area CPR - Central Plains Experimental Range HBR - Hubbard Brook Experimental Forest HFR - Harvard Forest JUN - Juneau KBS - Kellogg Biological Station KNZ - Konza Prairie Research Natural Area NWT - Niwot Ridge/Green Lakes Valley OLY - Olympic National Park OLY Conifer forest SEV - Sevilleta National Wildlife Refuge SMR - Santa Margarita Ecological Reserve UFL - University of Florida VCR - Virginia Coast Reserve Table 2 LIDET species and species codes used in model files (6 common species). Species - Species Code Sugar maple (Acer saccharum) - ACSA Drypetes (Drypetes glauca) - DRGL Red pine (Pinus resinosa) - PIRE Chestnut oak (Quercus prinus) - QUPR Western redcedar (Thuja plicata) - THPL Wheat (Triticum aestivum) - TRAE References:Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957-974. https://doi.org/https://doi.org/10.1111/gcb.12031 Harmon, M. (2013). LTER Intersite Fine Litter Decomposition Experiment (LIDET), 1990 to 2002. Long-Term Ecological Research. Forest Science Data Bank, Corvallis, OR. [Data set]. Accessed http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023. https://doi.org/10.6073/pasta/f35f56bea52d78b6a1ecf1952b4889c5. Sulman, B. N., Phillips, R. P., Oishi, A. C., Shevliakova, E., & Pacala, S. W. (2014). Microbe-driven turnover offsets mineral-mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4, 1099 - 1102. https://doi.org/10.1038/nclimate2436

Juice, Stephanie↗
DOE OSTI2025

Estimating evapotranspiration from deciduous broadleaf forests by considering the effect of foliar litter

Forest litter cover significantly alters the ground surface resistance, which influences the water and energy transfer processes between the land surface and atmosphere. Penman-Monteith (PM) model is widely used to estimate land surface evapotranspiration (ET). However, it was shown to overestimate ET during the period when foliar litter covers the ground surface. Therefore, incorporating the effect of foliar litter on ground surface resistance can potentially improve ET estimates. Here, in this study, we proposed a foliar litter surface resistance model to describe the effect of litter cover on water vapor transport, then incorporated the litter surface resistance into the PM model (noted as PM-EL model). The performance of the PM-EL model was evaluated using observations from 18 deciduous broadleaf forest (DBF) flux sites across global FLUXNET2015 datasets. Results showed that: (1) both the PM model and the PM-EL model are most sensitive to ground surface resistance among resistance parameters; (2) the proposed litter resistance model is capable of describing the seasonal dynamic of litter in DBF ; (3) the PM-EL model, has been shown to improve ET estimates with the coefficient of determination increased by 8.5 %, the mean absolute error and relative root mean square error decreased by 22.1 % and 20.9 %, respectively. The study contributes to our understanding of the effect of litter cover on ET estimation and provides insights into forest ecohydrology and land surface mass and energy transfer processes.

Deciduous Broadleaf Forest↗
DOE OSTI2021

Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".

54 ENVIRONMENTAL SCIENCES↗