New, rapid techniques to quantify the different pools of soil organic matter (SOM) are needed to improve our understanding of the dynamics and spatio-temporal variability of SOM in terrestrial ecosystems. In this study, total organic carbon (TOC) and oxidizable organic carbon (OCWB) fraction were calibrated and predicted by mid- and near-DRIFT spectroscopy in combination with partial least squares (PLS) regression method. PLS regression is a multivariate calibration method that can decompose spectral data (X) and soil property data (Y) into a new smaller set of latent variables and their scores that best describe all the variance in the data. Oxidizable organic carbon content was measured by a modified Walkley-Black method, and total organic carbon was measured by the carbon analyzer. The floodplain and Blackland Prairie soils in Texas were used for prediction of TOC and OCWB using mid- and near-DRIFT spectroscopy. Floodplain soil is mainly composed of quartz and kaolinite, whereas Blackland Prairie soils contain high concentrations of smectitic clays and low to high concentrations of carbonate minerals. The total organic carbon of 68 soil samples from two Texas sites varied between 0.19 and 4.36 wt.% C, and the oxidizable organic carbon of 26 samples from floodplain soils was in the range of 0.05 to 1.33 wt.% C. TOC and OCWB of soil were successfully calibrated and predicted by the PLS regression method using mid- and near-DRIFT spectroscopy. The correlation using mid-IR spectra for TOC (r = 0.96, RMSEV = 0.32 for calibration; r = 0.93, RMSEP = 0.44 for prediction) was about the same as the near-IR result (r = 0.95, RMSEV = 0.37; r = 0.93, RMSEP = 0.42). Therefore, we can also use mid-infrared region for quantification of total organic carbon in soils. The PLS1 regression model (r = 0.92) for prediction of OCWB using mid-IR spectra was more accurate than the PLS2 regression model (r = 0.90). PLS models showed better correlation with spectral data than the univariate least square regression method(r = 0.83) with TOC measured by the carbon analyzer. This study shows that the partial least squares (PLS1) method using mid-and near-IR spectra of neat soil samples can be used to predict both total organic carbon and oxidizable carbon fraction as a fast and routine quantitative method.

Recalcitrant soil carbon is a poorly understood component of total soil organic carbon (SOC). Although the turnover rate of the recalcitrant fraction is slow, warming temperatures are expected to speed the decomposition of recalcitrant SOC resulting in an increase of atmospheric CO₂ in the future. Several studies show that the oldest SOC is associated with the smallest mineral particles (clays), making direct spectroscopic analysis of old carbon difficult. To overcome the difficulty of analyzing natural samples, we created synthetic soils to examine the association between clay surfaces and specific biomolecules based on the hypothesis that clays with higher surface charge will more strongly bond organic molecules, and also that certain molecules will be better stabilized by clay. We used kaolinite, montmorillonite, or quartz (sand) as a synthetic soil inside 12 mL septum-capped vials, added either dissolved glucose or vanillic acid to each mineral, inoculated with soil microbes, and then purged the vials with a CO₂-free atmosphere. We incubated them and measured the concentration and [delta]¹³C of CO₂ that accumulated in the vials. Respiration rates were significantly higher in experiments containing vanillic acid than in those containing glucose. Respiration rates were lowest in experiments containing montmorillonite. We repeated the experiment using dilute H₂O₂ as an oxidant, and adding vanillic acid, glucose, or glycine. Vials with montmorillonite showed lower rates of CO₂ accumulation than kaolinite, and both glycine- and glucose-containing experiments had less CO₂ than vanillic acid-experiments. We conclude that the montmorillonite protected the organic matter from oxidation better than sand or kaolinite. Both clays protected organic matter better than sand. In all experiments with clay, the respired CO₂ had lower [delta]¹³C values than bulk substrate. This carbon isotope fractionation is likely due to preferential desorption, followed by oxidation, of 12C- as opposed to 13C- bearing organic molecules. The mineral-organic interaction is a strong bond that explains the old age of labile organic compounds in soils. These results indicate that the clay fraction of soils must be considered for accurate prediction of future land-atmosphere carbon fluxes. / text

As the largest carbon reservoir in ecosystems, soil accounts for more than twice as much carbon storage as that of vegetation biomass or the atmosphere. The goal of this study is to examine spatial patterns of soil organic carbon (SOC) in Canadian forest area at an eco-region scale and to explore its relationship with different ecological variables. In this study, the first Canadian forest soil database published in 1997 by the Canada Forest Service was analyzed along with other long-term eco-climatic data (1961 to 1991) including precipitation, air temperature, Normalized Difference Vegetation Index (NDVI), slope, aspect, and elevation. Additionally, an eco-region framework established by the Environment Canada was adopted in this study for SOC distribution assessment. Exploratory spatial data analysis techniques, with an emphasis on spatial autocorrelation analysis, were employed to explore how forest SOC was spatially distributed in Canada. Correlation analysis and spatial regression analysis were applied to determine the most dominant ecological factors influencing SOC distribution in different eco-regions. At the national scale, a spatial error model was built up to adjust for spatial effects and to estimate SOC patterns based on ecological and ecosystem property factors. Using the significant variables derived in the spatial error model, a predictive SOC map in Canadian forest area was generated. Findings from this study suggest that high SOC clusters tend to occur in coastal areas, while low SOC clusters occur in western boreal eco-region. In Canadian forest area, SOC patterns are strongly related to precipitation regimes. Although overall SOC distribution is influenced by both climatic and topographic variables, distribution patterns are shown to differ significantly among eco-regions, thus verifying the eco-region classification framework for SOC zonation mapping in Canada.

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No description available.

Paleosols contain information about the rates of soil organic carbon turnover when the soil was actively forming. However, this temporal information is often difficult to interpret without tight stratigraphic control on the age of the paleosol. Here we apply ramped pyrolysis/oxidation (Ramped PyrOx) C-14 analyses to evaluate age spectra of transgressive early Holocene paleosols from the Mississippi Delta in southeastern Louisiana, USA. We find C-14 age spectra from soil organic matter (SOM) in both paleosols and overlying basal peats that represent variability in age that is close to, or only slightly greater than, analytical uncertainty of C-14 measurements, despite different sources of carbon with likely disparate ages. Such age spectra have not previously been observed in the sedimentary record. Here they indicate vigorous soil carbon turnover prior to burial, which homogenized C-14 ages within SOM across the entire thermochemical spectrum. The weighted bulk C-14 ages from Ramped PyrOx of paleosols and overlying peats are identical within analytical and process-associated uncertainty, and corroborate C-14 ages from charcoal fragments and plant macrofossils from the overlying peat. The youngest ages from Ramped PyrOx age spectra may also potentially be applied as chronometers for stratigraphic burial ages. Our results suggest rapid turnover (<<300 years) of carbon in these soils relative to input of allochthonous carbon, indicating that the C-14 age of different soil components is decoupled from thermochemical stability and instead reflects vigorous turnover processes. The concurrence of paleosol and peat C-14 ages also suggests that pedogenic processes were linked with the development of coastal marshes, and that the priming effect potentially masked the signal of allochthonous carbon inputs during sea level rise.

Through appropriate soil and crop residue management, soil can function as a sink for carbon (C) and nitrogen (N) for the mitigation of greenhouse gases (GHG). No research has yet investigated the potential of intercrop agroecosystems to reduce emissions of GHG to the atmosphere. This research evaluates whether maize-soybean intercrop agroecosystems sequester more C and N and emit fewer GHG than maize and soybean sole crop agroecosystems. An experiment was conducted at Balcarce, Argentina using four treatments: a maize sole crop, a soybean sole crop, and two intercrops with either 1:2 or 2:3 rows of maize to soybean. The objectives were to quantify soil organic carbon (SOC) and soil total nitrogen (TN) at 0-10, 10-20, 20-40, 40-80 and 80-120 cm depths, rates of decomposition of maize and soybean crop residue after 312 days, crop residue C- and N-input at harvest, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Significant decreases in SOC were observed with depth in all treatments after 40 cm, and significant decreases in TN were observed with depth in all treatments after 20 cm. Crop residue from maize had the greatest input of C and N to the soil, but the slowest rate of decomposition. Soybean biomass had the least input of C and N to the soil and the fastest rate of decomposition. The 1:2 and 2:3 intercrop agroecosystems had moderate crop residue inputs of C and N and intermediate rates of decomposition. No significant differences in GHG emissions were detected between treatments throughout the growing season. The major influences on GHG emissions were weather events, soil temperature and moisture, and crop residue input. Annual GHG emissions were determined; the CH4 sink in the 1:2 intercrop and the soybean sole crop was significantly greater (P < 0.05) than the 2:3 intercrop and the maize sole crop. Emissions of CO2 were inversely proportionate to N2O, with the greatest C sink in the 1:2 intercrop.

Through appropriate soil and crop residue management, soil can function as a sink for carbon (C) and nitrogen (N) for the mitigation of greenhouse gases (GHG). No research has yet investigated the potential of intercrop agroecosystems to reduce emissions of GHG to the atmosphere. This research evaluates whether maize-soybean intercrop agroecosystems sequester more C and N and emit fewer GHG than maize and soybean sole crop agroecosystems. An experiment was conducted at Balcarce, Argentina using four treatments: a maize sole crop, a soybean sole crop, and two intercrops with either 1:2 or 2:3 rows of maize to soybean. The objectives were to quantify soil organic carbon (SOC) and soil total nitrogen (TN) at 0-10, 10-20, 20-40, 40-80 and 80-120 cm depths, rates of decomposition of maize and soybean crop residue after 312 days, crop residue C- and N-input at harvest, and emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Significant decreases in SOC were observed with depth in all treatments after 40 cm, and significant decreases in TN were observed with depth in all treatments after 20 cm. Crop residue from maize had the greatest input of C and N to the soil, but the slowest rate of decomposition. Soybean biomass had the least input of C and N to the soil and the fastest rate of decomposition. The 1:2 and 2:3 intercrop agroecosystems had moderate crop residue inputs of C and N and intermediate rates of decomposition. No significant differences in GHG emissions were detected between treatments throughout the growing season. The major influences on GHG emissions were weather events, soil temperature and moisture, and crop residue input. Annual GHG emissions were determined; the CH4 sink in the 1:2 intercrop and the soybean sole crop was significantly greater (P < 0.05) than the 2:3 intercrop and the maize sole crop. Emissions of CO2 were inversely proportionate to N2O, with the greatest C sink in the 1:2 intercrop.

In the past years considerable attention has been given to soil organic carbon (SOC) stored in permafrost-affected soils in periglacial terrain. Studies have shown that these soils store around half the global SOC pool, making them a key component of the global carbon cycle. Much of the SOC presently stored in these soils has accumulated since the Pleistocene and is protected from decomposition and erosion by low temperatures close to or below the freezing point. This makes it vulnerable to remobilization under a warming climate. This thesis provides new data on SOC storage in three study areas in Siberian periglacial terrain. A high-resolution land cover classification (LCC) for each study area is used to perform detailed vertical and spatial partitioning of SOC. The results show that the vast majority (&gt;86%) of the ecosystem carbon is stored in the top meter of soil. Low relative storage of carbon in plant phytomass indicates limited uptake potential by vegetation and emphasises the vulnerability of the SOC pool to geomorphic changes. Peat formation as well as cryoturbation are identified as the two main pedogenic processes leading to accumulation of SOC. Presence or absence of ice-rich Yedoma deposits determine soil formation and SOC storage at landscape scale. At local scale, periglacial landforms dominate SOC allocation in the tundra, while forest ecosystem dynamics and catenary position control SOC storage in the taiga. A large diversity of soil types is found in these environments and soil properties within pedons can be highly variable with depth. High-resolution satellite imagery allows upscaling of the SOC storage at unprecedented detail, but replication of soil pedons is a limiting factor for mapping of SOC in remote periglacial regions. Future research must look beyond traditional LCC approaches and investigate additional data-sources such as digital elevation models. The concept of state factors of soil formation is advocated as a framework to investigate present day and future SOC allocation in periglacial terrain.

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