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91 results for “soil chemistry”
Chemistry from thermokarst impacted soils, lakes, and streams near Toolik Lake Alaska, 2008-2011.
This file contains data collected from thermokarst impacted soils, lakes, and streams near Toolik Lake Alaska. Data are also presented for experimental manipulations of water (e.g., time course experiments). Sample descriptors include a unique sortchem #, site, date, time, depth, distance, elevation, treatment, date-time, category, and water type (e.g., lake, surface, soil). Physical/chemical measures collected in the field include temperature, conductivity, and pH. Chemical analyses performed later include alkalinity; dissolved inorganic and organic carbon (DIC and DOC); inorganic and total dissolved nutrients (NH4, PO4, NO3, TDN, TDP); particulate carbon, nitrogen, and phosphorus (PC, PN, and PP); cations (Ca, Mg, Na, K, and Si); anions (SO4 and Cl); chlorophyll a, and oxygen. Note that archived data from before the NSF ARCSS-Thermokarst project started in 2009, and funded by NSF from 1988-2008 (e.g., by the NSF ARC LTER), are included in this dataset.
Water chemistry of leachates prepared from permafrost soils collected from the North Slope of Alaska in the summers of 2015 and 2018
Soils were collected from the frozen permafrost layer (greater than 60 cm below the surface) at six sites underlying tussock or wet sedge vegetation, and on three glacial surfaces on the North Slope of Alaska during the summers of 2015 and 2018. Dissolved organic carbon (DOC) was leached from each permafrost soil and the water chemistry was analyzed.
Soil Water (Lysimeter) Chemistry for Mature Balsam Poplar and White Spruce for BCEF
This dataset includes soil water samples (lysimeter samples) collected from mature balsam poplar (BP1, BP2 and BP3) and white spruce (FP4A, FP4B, FP4C) stands during 2000 and 2001. Five Lysimeter were installed at 12 cm and four at the 40 cm in each stand type. Water from the Tanana River and small, non-silt, streams on the eastern portion of the floodplain were collected during many sampling periods.
Soil chemistry along the canopy gradient from 1997 to 1999
Resin bags were buried at 10 plots on three canopy gradient sites at Coweeta Hydrologic Laboratory and the resin bag extracts were analyzed for nitrate (NO3), ammonium (NH4) and phosphate (PO4). Values will be compared with throughfall chemistry and frass weights to determine if there are any correlations due to canopy herbivory. For more information see Reynolds and Hunter, 2001 in Publications section below. We tested whether inputs from canopy herbivores would affect soil processes such as respiration, nutrient cycling, and decomposition along an elevation gradient. The five treatments we used were frass additions, throughfall additions, removal of all litter that fell during the study, removal of greenfall that fell during the study, and controls.
Measurements of Soil Water Chemistry at the Coweeta Terrestrial Gradient Sites
This project is part of a larger examination of site productivity along an elevational gradient. Five tension lysimeters were placed at each of two depths, 15 cm and bottom of Bt soil horizon, along two transects running parallel to the contour of each 40 × 20 m terrestrial gradient plot. Soil water was collected weekly and composited at the end of each month. Values are the mean value for each site/month.
Riparian study: soil water chemistry (lysimeters) yearly data (1993 to 1997) at the Coweeta Hydrologic Laboratory
These measurements are a part of a near-stream vegetation manipulation experiment conducted on WS 56 at Coweeta. The purpose of the project is to determine the effect of removal of streamside Rhododendron maximum on the export of nutrients and organic matter, on microbial community function, on downslope coarse woody debris transport, on seedling regeneration, and on microclimatic variables such as soil temperature and soil moisture. Two experimental hillslope transects that span topographic flowpaths from a local highpoint to the stream were instrumented with lysimeters in two soil horizons, the BA (20-25 cm deep) and the B (40-50 cm deep). The vegetation cut was conducted on the "treatment slope" in Aug 1995. Shortly thereafter, Oct 1995, hurricane Opal blew down a significant number of canopy trees on the "control slope." Due to this natural disturbance, the project was adjusted to contrast the effects of natural vs human disturbance - a bank of lysimeters above the cut area was unaffected and now serve as the control data for the project. The treatment slope has been renamed the "cut slope" and the hurricane impact slope has been renamed the "storm slope." The project uses a terrain-fitted hillslope hydrology model (TAPES-C, IHDM4 hybrid) to account for water flux and nutrient loading from the hillslope before and after the cut and storm impacts.
Hubbard Brook Experimental Forest: Watershed 3 Lateral Weathering Soil Chemistry
Chemical analyses were performed on sieved and dried soil samples collected for the Lateral Weathering project within Watershed 3, Hubbard Brook Experimental Forest, Woodstock, NH, USA from 2018-2020. Chemical information corresponds to horizons described in dataset HBR361, which were collected from pits described in the same dataset. Analyses include pH, C, N, exchangeable ions, secondary metals from citrate dithionite and ammonium oxalate in the dark, and total elemental content. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Soil interstitial water chemistry data for Green Lakes Valley, 1987 - 1992.
Soil interstitial water samples were collected from tension and zero-tension samplers at various locations within the Green Lakes Valley in the City of Boulder Watershed. Chemical analyses were performed on the samples in order to characterize soil solution concentrations and estimate fluxes of important chemical constituents. Samples were collected at several depths from within several soil types and topographic situations in this alpine/subalpine environment.
Soil chemistry dataset from the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica"
<p>Bases sum, H+Al (potential acidity), pH, phosphorous, remaining P (P-rem), sodium and total organic carbon distribution in Antarctic soils modeled and predicted through Machine Learning approaches, legacy soil data and environmental covariates. The quantile and prediction interval data represent the spatial uncertainty of the predictions.</p> <p>As soon as the work "Modelling and prediction of major soil chemical properties with Random Forest: machine learning as tool to understand soil-environment relationships in Antarctica" is published, the paper will be cited here. </p> <p>The .zip file contains the following folders:</p> <p>1) soil_chemistry_antarctica: data containing the soil chemical attributes distribution</p> <p>2) soil_chemistry_prediction_interval: uncertainty from the prediction interval 90% (Q95% - Q5%) of the soil attributes prediction</p> <p>4) soil_texture_quantile05: quantile 5% of the soil attributes prediction</p> <p>5) soil_texture_quantile95: quantile 95% of the soil attributes prediction</p>
Water and soil chemistry and molecular composition data of dissolved organic matter from soils in the central Amazon rainforest, 2019-2021
This dataset was created based on sampling campaigns in the central Amazon rainforest. It covers four field sites in vicinity of the Amazon Tall Tower Oberservatory project (ATTO). The field sites are comprised of pristine, old-growth rainforest with distinct forest types: terra firme forest (Plateau and Terrace sites) and white-sand forest (Campina and Campinarana sites). Freely percolating soil porewater was sampled repeatedly in soil profiles from 0 to 30 cm in the wet seasons (October to May) of 2019, 2020 and 2021. Solid soil samples were taken in vicinity to the plots in October 2017. The datasets include chemical and texture (particle size fractions) and chemical (metals, cation exchange capacities and pH) data from soil samples. Soil porewater samples were measured for pH, electrical conductivity and dissolved organic carbon (DOC) concentrations. There are some missing values for these data, particularly for DOC concentrations. Soil porewater samples were used for solid-phase extraction of dissolved organic matter (DOM). The molecular composition was measured by ultra-high resolution mass spectrometry (Orbitrap Elite MS). The detected masses were used to assign molecular formulas. The data include the assigned molecular formulas and sum-normalized intensites of all samples. This data is associated with a Ph.D. dissertation chapter (Lange, 2025) and a journal article (Lange et al., accepted).
Effects of stem canker disease on N fixation inputs by Alnus tenuifolia to early-successional floodplains in interior and south-central Alaska. I. Nitrogen fixation rates, leaf chemistry and soil chemistry.
This dataset contains data on nitrogen fixation rates, leaf chemistry, soil temperature and moisture, and soil chemistry on trees selected for studying disease-mediated declines in N-fixation inputs by Alnus tenuifolia to early-successional floodplains in interior and south-central Alaska
Ecological Survey of Central Arizona: soil chemistry and soil properties in the greater Phoenix metropolitan area and surrounding Sonoran desert, survey year 2000
The Ecological Survey of Central Arizona (ESCA) is an extensive field survey and integrated inventory designed to capture key ecological indicators of the CAP LTER study area consisting of the urbanized, suburbanized, and agricultural areas of metropolitan Phoenix, and the surrounding Sonoran desert. The survey is conducted every five years at approximately 200 sample plots (30m x 30m) that were located randomly using a tessellation-stratified dual-density sampling design. Study plots cover habitats throughout the CAP LTER study area ranging from native Sonoran desert sites to residential yards to an airport tarmac. Measurements include an inventory of all plants (identified to the lowest possible taxonomic unit, typically species), plant biovolume, soil coring for physicochemical properties, arthropod sweep-net sampling, photo documentation, and a visual survey of site and area characteristics. The objectives of the survey are to (1) characterize patches in terms of key biotic, physical, and chemical variables, and (2) examine relationships among land use, general plant diversity, native plant diversity, plant biovolume, soil nutrient status, and social-economic indices along an indirect urban gradient. This data set focuses specifically on soil chemistry and soil properties assessed during the 2000 survey year. Investigators interested in soil data from more recent surveys or other measured variables should search the data catalog for 'ecological survey of central arizona' or 'survey 200' to locate those and other data related to the CAP LTER's ESCA.
Porous tension-cup lysimeter depths and soil water chemistry from 9 Hillslope Project sites in Macon County, North Carolina, within the Upper Little Tennessee River Basin
Porous tension-cup lysimeters were installed at 9 sites throughout Macon County beginning in 2011. Sites represented a gradient of land use, including relatively undisturbed forests, valley bottomlands in agriculture, and mountain developments. Eighteen lysimeters were placed at each site - 9 were shallow lysimeters located in the A horizon and 9 were deep lysimeters located in the B horizon. Collections were made every other week and samples were composited monthly for chemistry. The depths of the lysimeters were noted.
Soil Chemistry for the Hubbard Brook Valley Plots, 1997 - 1998 Survey Data
The valley-wide plots are a grid of 431 sites along fifteen N–S transects established at 500-m intervals spanning the entire Hubbard Brook Valley. Multiple above- and below- ground attributes were measured between 1995 and 1998. This dataset includes soil chemistry data; tree inventory, additional soil data and other measurements are presented in separate datasets. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Nitrogen in Soil Water Chemistry on the Main Cropping System Experiment at the Kellogg Biological Station, Hickory Corners, MI (1995 to 2019)
Open the record for dataset details and reuse information.
Soil lysimeter chemistry data from various locations on Niwot Ridge and in the Green Lakes Valley 1994 - 2013.
Water was collected from soil lysimeters at key sites across Niwot Ridge and the Green Lakes Valley in the tundra and subalpine forest. Zero-tension soil lysimeters in the City of Boulder Watershed were deployed in the mid-1980’s. Additional zero-tension lysimeters were installed at Subnivean and Soddie sites in 1997. At c1 in 2010, 12 Tension lysimeters (Soil Moisture Equipment Corp Model 1900 Soil Water Sampler ) were installed at C1.SO, C1.ST and C1.SW sites, with four lysimeters at each site. In 2012, 15 additional zero tension lysimeters were installed in the City of Boulder Watershed at Gl5, Arikaree, and D1 locations (with 5 lysimeters at each site).
Soil and litter chemistry, soil microbial communities and litter decomposition from tropical forest and oil palm
<b>Description: </b><p>A study examining the interactions between soil chemistry, litter chemistry and soil microbial decomposers as controls on rates of litter decomposition across a tropical land use disturbance gradient. Co-located soil and litter samples were collected from old growth forest, moderately logged forest, heavily logged forest and oil palm plantations. Soil and litter were chemically characterised and soil bacterial and fungal community composition and abundance were measured. These were then combined in fully factorial ex-situ microcosms and measured litter decomposition rates at 3 time points during different stages of decomposition.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/124"><b>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Quantifying biogeochemistry across forest disturbance gradients in Sabah</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>UK NERC-funded Biodiversity And Land-use Impacts on Tropical Ecosystem Function (BALI) consortium (Standard grant, NE/K016377/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/2 JLD.5 (20))</li><li>Sabah Biodiversity Centre (Export licence JKM/MBS.1000-2/3 JLD.2 (70))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3929632">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_Dataset.xlsx</p><p><b>SAFE_Dataset.xlsx</b></p><p>This file contains dataset metadata and 5 data tables:</p><ol><li><p><b>Soil_Properties</b> (described in worksheet Soil_Properties)</p><p>Description: Basic measured soil properties</p><p>Number of fields: 9</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Plot</b>: Plot name corresponding to the GEM Carbon plot where soils were sampled (Field type: id)</li><li><b>Plot_ID</b>: Plot ID indicating land use as referenced in the Frontiers in forests and global change publication "Soil microbial community and litter quality controls on decomposition across a tropical forest disturbance gradient" (Field type: categorical)</li><li><b>location_name</b>: Name of subplot where soils were collected (Field type: location)</li><li><b>gravimetric moisture content</b>: Soil moisture content at the time of sample collection (Field type: numeric)</li><li><b>soil_pH</b>: Soil pH measured on fresh soils (Field type: numeric)</li><li><b>soil_N</b>: Total soil Nitrogen (Field type: numeric)</li><li><b>soil_C</b>: Total soil Carbon (Field type: numeric)</li><li><b>soil_C.N</b>: Soil carbon to nitrogen ratio (Field type: numeric)</li><li><b>soil_P</b>: soil inorganic phosphorus (Field type: numeric)</li></ul></li><li><p><b>Litter_Chemistry</b> (described in worksheet Litter_Chemistry)</p><p>Description: Litter chemistry data of mixed forest floor litter, collected, sorted to remove humified material, woody debris and dried</p><p>Number of fields: 20</p><p>Number of data rows: 40</p><p>Fields: </p><ul><li><b>Plot</b>: Plot name corresponding to the GEM Carbon plot where soils were sampled (Field type: id)</li><li><b>Plot_ID</b>: Plot ID indicating land use as referenced in the Frontiers in forests and global change publication "Soil microbial community and litter quality controls on decomposition across a tropical forest disturbance gradient" (Field type: categorical)</li><li><b>location_name</b>: Name of subplot where soils were collected (Field type: location)</li><li><b>Pretreatment</b>: Whether the litter sample was sterilised by autoclaving or not (Field type: categorical)</li><li><b>leaf_K</b>: leaf potassium concentration (Field type: numeric)</li><li><b>leaf_Ca</b>: leaf Calcium concentration (Field type: numeric)</li><li><b>leaf_Mg</b>: leaf Magnesium concentration (Field type: numeric)</li><li><b>leaf_Al</b>: leaf aluminium concentration (Field type: numeric)</li><li><b>leaf_P</b>: leaf phosphorus concentrations (Field type: numeric)</li><li><b>solubles</b>: leaf soluble cell content (Field type: numeric)</li><li><b>hem_pro_cel_lig_rec</b>: leaf hemicellulose, proteins, cellulose, lignin and recalcitrant fibres (Field type: numeric)</li><li><b>hem_pro</b>: leaf hemicellulose and proteins (Field type: numeric)</li><li><b>cel_lig_rec</b>: leaf cellulose, lignin and recalcitrant fibres (Field type: numeric)</li><li><b>cel</b>: leaf cellulose (Field type: numeric)</li><li><b>lig_rec</b>: leaf lignin and recalcitrants (Field type: numeric)</li><li><b>leaf_N</b>: leaf nitrogen concentration (Field type: numeric)</li><li><b>leaf_C</b>: leaf carbon concentration (Field type: numeric)</li><li><b>c.n</b>: leaf carbon to nitrogen ration (Field type: numeric)</li><li><b>d13c</b>: leaf carbon stable isotope ratio (Field type: numeric)</li><li><b>d15n</b>: leaf nitrogen stable isotope ratio (Field type: numeric)</li></ul></li><li><p><b>PLFA_Concentrations</b> (described in worksheet PLFA_Concentrations)</p><p>Description: Phospolipid Fatty Acid (PLFA) concentrations as biomarkers of soil bacteria and fungi. Extracted from freeze dried soils prior to the microcosm experiment</p><p>Number of fields: 10</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Plot</b>: Plot name corresponding to the GEM Carbon plot where soils were sampled (Field type: id)</li><li><b>Plot_ID</b>: Plot ID indicating land use as referenced in the Frontiers in forests and global change publication "Soil microbial community and litter quality controls on decomposition across a tropical forest disturbance gradient" (Field type: categorical)</li><li><b>location_name</b>: Name of subplot where soils were collected (Field type: location)</li><li><b>Total_PLFA</b>: Total PLFA concentrations extracted from soil samples (Field type: numeric)</li><li><b>Fungal_PLFA</b>: Fungal PLFA biomarker concentrations extracted from soils (Field type: numeric)</li><li><b>Bacteria_PLFA</b>: Bacteria PLFA biomarkers extracted from soils (Field type: numeric)</li><li><b>Fungal:Bacteria</b>: Ratio of fungal to bacteria PLFAs (Field type: numeric)</li><li><b>Gram_Pos_PLFA</b>: Gram Positive PLFA Biomarker concentrations extracted from soil (Field type: numeric)</li><li><b>Gram_Neg_PLFA</b>: Gram Negative PLFA Biomarker concentrations extracted from soil (Field type: numeric)</li><li><b>GramPos:GramNeg</b>: Gram positive to Gram negative PLFA ratios (Field type: numeric)</li></ul></li><li><p><b>Soil_Microbial_Communities</b> (described in worksheet Soil_Microbial_Communities)</p><p>Description: Summary diversity statistics from bacterial 16S and fungal ITS biomarker microbial sequencing. DNA extracted from soils prior to microcosm experiment</p><p>Number of fields: 9</p><p>Number of data rows: 20</p><p>Fields: </p><ul><li><b>Plot</b>: Plot name corresponding to the GEM Carbon plot where soils were sampled (Field type: id)</li><li><b>Plot_ID</b>: Plot ID indicating land use as referenced in the Frontiers in forests and global change publication "Soil microbial community and litter quality controls on decomposition across a tropical forest disturbance gradient" (Field type: categorical)</li><li><b>location_name</b>: Name of subplot where soils were collected (Field type: location)</li><li><b>Bacteria_Richness</b>: Number of observed bacterial taxa from sequencing of 16S marker genes from soil samples (Field type: numeric)</li><li><b>Bacteria_Shannon</b>: Bacterial Shannon diversity from 16S Marker gene sequencing (Field type: numeric)</li><li><b>Fungal_Richness</b>: Number of observed fungal taxa from sequencing of 16S marker genes from soil samples (Field type: numeric)</li><li><b>Fungal_Shannon</b>: Fungal Shannon diversity from 16S Marker gene sequencing (Field type: numeric)</li><li><b>Saprotrophic_Fungal_Richness</b>: Number of observed saprotrophic fungal taxa from sequencing of 16S marker genes from soil samples (Field type: numeric)</li><li><b>Saprotrophic_Fungal_Shannon</b>: Saprotrophic Fungal Shannon diversity from 16S Marker gene sequencing (Field type: numeric)</li></ul></li><li><p><b>Ex_Situ_Litter_Decomposition</b> (described in worksheet Ex_Situ_Litter_Decomposition)</p><p>Description: Fully factorial litter decomposition experiment. 16 unique soil and litter combinations (4x4) were incubated in petri dishes at constant temperature and moisture and mass loss measured after 31, 105 and 398 days.</p><p>Number of fields: 8</p><p>Number of data rows: 240</p><p>Fields: </p><ul><li><b>location_name</b>: Name of subplot where soils were collected (Field type: location)</li><li><b>Soil_ID</b>: Soil ID indicating which land use soil was collected from (Field type: categorical)</li><li><b>Litter_Location</b>: Location of which GEM carbon plot the litter was collected from. Litter was collected from the 5 carbon subplots as per soil collection and homogenised into one composite sample per carbon plot (Field type: location)</li><li><b>Litter_ID</b>: Litter ID indicating which land use litter was collected from (Field type: categorical)</li><li><b>Experimental_Block</b>: Which experimental block the microcosm was assigned to. N= 5 (Field type: replicate)</li><li><b>Timepoint</b>: At what timepoint the litter was harvested from each microcosm (Field type: categorical)</li><li><b>Mass_Loss</b>: The mass loss of litter relative to the starting mass of 1g (Field type: numeric)</li><li><b>home_away</b>: Descriptor for whether the soil and litter combination in microcosm (Field type: categorical)</li></ul></li></ol><p><b>Date range: </b>2014-10-01 to 2018-09-01</p><p><b>Latitudinal extent: </b>4.6402 to 4.9539</p><p><b>Longitudinal extent: </b>117.4518 to 117.7942</p>
Belowground fungi, soil, and root chemistry in tropical landuse systems
<p>The data were collected in the humid tropical climate on Sumatra (Indonesia) in rain forests, in jungle rubber (rubber planted into forests), in rubber, and oil palm plantations. A total of 44 plots were sampled. The data set consists of two tables. The table Environmental_data contains plot information, geographic coordinates of the plots, and data on soil properties (pH, nitrogen, carbon, C/N, potassium, calcium, magnesium, manganese, iron, phosporous, soil resource index, soil PC1, soil PC2) and on root traits (biomass, nitrogen, carbon, C/N, potassium, calcium, magnesium, manganese, iron, phosporous, root resource index, root PC1, soil PC, root vitality). Table 2 contain abundance data (OTU counts) for fungi associated with roots or with soil and their phylogenetic and functional assignments.</p>
Converting conventional agriculture to poplar bioenergy crops: soil chemistry
<p>Woody bioenergy is a viable source of alternative energy; however, questions remain on how purpose-grown bioenergy feedstock production management impact surface soil chemistry. In order to understand the soil processes under poplar (<i>Populus spp.</i>) trees and adjacent agricultural sites, surface (0-15 cm) soil samples were collected from four northwestern United States locations over a four-year period. Initial and final surface soil samples were analyzed for various soil chemical parameters, including organic matter, pH, cation exchange capacity and nutrient concentrations. Fields selected to compare poplar and agricultural management initially differed in some key soil chemical parameters. Many soil chemical parameters changed over time and the magnitude of change often depended on location; however, initial differences between management types within any one location did not change over time for most soil chemical variables. Consistent in-location differences between management types over time show poplar did not alter soil chemical parameters relative to agricultural management during the study period. Together all observations indicate that little of the overall soil chemistry was impacted by introduction of poplar in the traditionally agricultural fields.</p>
Plant litter chemistry controls coarse-textured soil carbon dynamics
<p>1. As soils store more carbon (C) than the Earth's atmosphere and terrestrial biomass together, the balance between soil C uptake in the form of soil organic matter and release as CO2 upon its decomposition is a critical determinant in the global C cycle regulating our planet's climate. Although plant litter is the predominant source of C fueling both soil C build-up and losses, the issue of how litter chemistry influences this balance remains unresolved.</p> <p>2. As a contribution to solving that issue, we traced the fate of C during near-complete decomposition of 13C-labelled leaf and root litters from 12 plant species in a coarse-textured soil. We separated the soil organic carbon (SOC) into mineral-associated organic matter (MAOM) and particulate organic matter (POM) pools, and investigated how 14 litter chemical traits affected novel SOC formation and native SOC mineralization (i.e., the priming effect) in these soil fractions.</p> <p>3. We observed an overall net increase in SOC due to the addition of litter, which was stronger for root than for leaf litters. The presumed stable MAOM-C pool underwent both substantial stabilization and mineralization, whereas the presumably less stable POM-C pool showed substantial stabilization and reduced mineralization. Overall, the initial increase in soil C mineralization was fully counterbalanced by a later decrease in native soil C mineralization. POM-C formation as well as MAOM-C formation and mineralization were positively related to the initial litter lignin concentration and negatively to that of the nitrogen leachates, whereas the opposite was observed for POM-C mineralization.</p> <p>4. Synthesis. Our results highlight the importance of litter chemical traits for SOC formation, and stabilization, destabilization, and mineralization. In our coarse-textured soil, the amount of MAOM-C did not change despite large C fluxes through this pool. The litter chemical traits that drove these processes differed from those frequently reported for fine-textured soils far from mineral-associated C saturation. To account for these discrepancies, we propose an integrative perspective in which litter quality and soil texture interactively control soil C fluxes by modulating several SOC stabilization and destabilization mechanisms. Irrespective, our results open new critical perspectives for managing soil C pools globally.</p>
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