scholarly journals Pedogenic Carbonates and Radiocarbon Isotopes of Organic Carbon at Depth in the Russian Chernozem

Geosciences ◽  
2018 ◽  
Vol 8 (12) ◽  
pp. 458 ◽  
Author(s):  
Elena Mikhailova ◽  
Ray Bryant ◽  
John Galbraith ◽  
Yang Wang ◽  
Christopher Post ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Carbon ◽  
Soil Profile ◽  
Biosphere Reserve ◽  
Radiocarbon Age ◽  
Pedogenic Carbonates ◽  
Native Grasslands ◽  
Native Grassland ◽  
Ap Horizon ◽  
Diagnostic Horizons

Conversion of native grasslands to agricultural sites has resulted in remarkable changes in soil carbon at depth, but its impact on soil diagnostic horizons is unknown. This study was conducted to radiocarbon date the soil organic carbon (SOC) and quantify pedogenic carbonates in the Russian Chernozem at depth at three sites: a native grassland field (not cultivated for at least 300 years), an adjacent 50-year continuous fallow field in the V.V. Alekhin Central-Chernozem Biosphere State Reserve in the Kursk region of Russia (UNESCO—MAB Biosphere Reserve), and a cropland in the Experimental Station of the Kursk Institute of Agronomy and Soil Erosion Control. All sampled soils were classified as Fine-silty, mixed, frigid Pachic Hapludolls (Haplic Chernozem). The radiocarbon age (14C date, y BP) of SOC was highly variable: in the native grassland field, it varied from post-bomb (A-horizon) to 8011 ± 54 y BP (C-horizon); in the continuous fallow, it varied from 1569 ± 41 y BP (Ap-horizon) to 11,380 ± 180 y BP (C1-horizon); and in the cropland, it varied from 1055 ± 38 y BP (Ap-horizon) to 11,805 ± 68 y BP (Ck-horizon). Cultivation resulted in morphological/diagnostic changes in the soil profile (conversion of A to Ap; conversion of Bw to Bk horizon) over a 50-year period. These changes are supported by radiocarbon dating of SOC and pedogenic carbonate distribution within the soil profile. The proportion of pedogenic carbonates was highly variable: in the native grassland, it was 27% (C-horizon); in the continuous fallow, it varied from 53% (Bk1-horizon) to 72% (C2-horizon); and in the cropland, it varied from 85% (A-horizon) to 10% (Ck-horizon). The radiocarbon age differences with depth among the soils reflect changes in the soil carbon dynamics resulting from cultivation.

Whole-soil profile carbon dynamic in response to climate change modulated by vertical carbon transport

2021 ◽  
Author(s):  
Mingming Wang ◽  
Zhongkui Luo
Keyword(s):  
Organic Carbon ◽  
Soil Carbon ◽  
Soil Profile ◽  
Soil Layer ◽  
Vital Role ◽  
Sensitivity Analyses ◽  
Data Sets ◽  
Organic Carbon Content ◽  
Global Pattern ◽  
Carbon Transport

<p>Vertical carbon transport along the soil profile redistributes soil carbon fractions in soil layers, which may have significant consequences on whole-soil profile organic carbon (SOC) dynamics. We developed three varieties of vertically resolved SOC models to simulate SOC dynamics (down to 2 m). The three models took into account mechanisms underpinning the increased persistence of SOC in deeper soil layer depths by explicitly simulating microbial processes and the interactions between old and new carbon pools. Model sensitivity analyses indicated that vertical carbon transport must to be considered; otherwise the profile distribution of SOC stock cannot be captured by the models. The models were further constrained by global data sets of whole-soil profile observations of vertical distribution of SOC stocks and carbon inputs, and then were used to predict the spatial pattern of the depth-specific amount of vertically transported organic carbon (<em>V</em>, g C m<sup>-2</sup> yr<sup>-1</sup>) across the globe. The <em>V</em> showed great variability across the globe as well as across different depths. Precipitation was the most important for influencing the global pattern of <em>V</em>; and soil texture and organic carbon content for the profile pattern. Applying the models across the global, we assessed the response of SOC to 2℃ global warming at the resolution of 1 km. The results suggested that without considering the vertical carbon transport, SOC loss under warming would be underestimated by 10%, particularly in the deeper layers. In wetter areas or areas with stronger soil profile disturbance such as bioturbation and cryoturbation, SOC was more sensitive (i.e., more SOC loss) to climatic warming due to the stronger vertical carbon transport and/or carbon-mixing. Our modelling demonstrates the vital role of vertical carbon transport in controlling whole-soil carbon dynamics, which is a key determinant of whole-soil profile SOC persistence under warming.</p>

scholarly journals Soil degradation due to the conversion of native grassland into cropland in the Pampa biome – (Southern Brazil) and impact on suspended sediment supply to the rivers

2020 ◽  
Author(s):  
Rafael Ramon ◽  
Olivier Evrard ◽  
Tales Tiecher ◽  
Sylvain Huon ◽  
Felipe Bernardi ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Suspended Sediment ◽  
Sediment Source ◽  
Southern Brazil ◽  
Unpaved Roads ◽  
Native Grasslands ◽  
Pampa Biome ◽  
Native Grassland ◽  
Fallout Radionuclide

<p>The conversion of the natural grasslands of the Pampa biome (Southern Brazil) into cropland may lead to an increase in soil erosion rates and sediment delivery to the rivers. Grasslands represent a significant sink of carbon, and according to the literature, 59% of the soil organic carbon (SOC) is lost when pastures are converted into cropland. It makes soils even more vulnerable to water and land degradation. This study aims to evaluate the impact of land use change on the river sediment composition by calculating the sediment contribution of each potential sediment source using organic matter composition, ultra-violet and visible (UV-VIS) spectra derived parameters and fallout radionuclide activities, as potential tracers in a sediment fingerprinting approach. The study site (Ibirapuitã river basin – 5,942 km²) is located in the Pampa biome, Southern Brazil, were sandy and shallow soils predominate, occupied mainly by native grasslands that are gradually being converted to cropfields, especially soybean. Potential sediment sources were sampled, which include croplands (n=36), native grasslands (n=31), unpaved roads (n=31) and subsurface sources (channel banks (n=18) and gullies (n=16)). Samples were taken from the soil surface layer of croplands and grasslands, as well as from the top layer of exposed sites of gullies, channel banks and unpaved roads. Samples were oven dried (50 °C), gently disaggregated and dry sieved to 63 mm to avoid particle size effects prior to further analysis. Suspended sediment samples were collected using time integrated samplers deployed in the bottom of the river, and during rainfall runoff events at the outlet of the catchment. Organic matter parameters (total organic carbon - TOC, total nitrogen - TN, δ<sup>13</sup>C and δ<sup>15</sup>N) were measured using a continuous flow isotope ratio mass spectrometry (EA-IRMS). Diffuse reflectance spectra in the UV-VIS wavelengths was measured using a Cary 5000 UV-VIS-NIR spectrophotometer, and 33 parameters were derived from the spectra. Fallout radionuclide (<sup>137</sup>Cs and <sup>210</sup>Pb<sub>xs</sub>) activities were measured by gamma spectrometry using low-background high-purity germanium detectors. Tracers were selected following a three step procedure, including: (i) a conservative range test, (ii) a Kruskal–Wallis H-test, and (iii) a linear discriminant function analysis. The selected tracers were introduced into a mass balance mixing model to estimate the source contributions to in-stream sediment by minimizing the sum of square residuals. TOC and TN show significant differences between cropland and native grassland, while the isotopes δ<sup>13</sup>C and δ<sup>15</sup>N, presented a lower discrimination potential. TOC and UV-VIS derived parameters did not present a good discriminant potential when they were tested in isolation, although they increased the source discrimination when combined with organic matter parameters. Fallout radionuclides have a good discriminant potential between surface and subsurface sources, but also between native grasslands and croplands. Croplands are the main sediment source in the Ibirapuitã river catchment (36%), followed by the native grasslands (33%). However, the area occupied by croplands is approximately eight times smaller, demonstrating that erosion processes have been intensified by the conversion of native grasslands into croplands and/or croplands are better connected to the river network.</p>

scholarly journals Long-Term Nitrogen Addition Decreases Soil Carbon Mineralization in an N-Rich Primary Tropical Forest

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 734
Author(s):  
Xiankai Lu ◽  
Qinggong Mao ◽  
Zhuohang Wang ◽  
Taiki Mori ◽  
Jiangming Mo ◽  
...  
Keyword(s):  
Microbial Biomass ◽  
Organic Carbon ◽  
Tropical Forest ◽  
Soil Carbon ◽  
Tropical Forests ◽  
Carbon Mineralization ◽  
N Deposition ◽  
Soil Carbon Mineralization ◽  
N Additions

Anthropogenic elevated nitrogen (N) deposition has an accelerated terrestrial N cycle, shaping soil carbon dynamics and storage through altering soil organic carbon mineralization processes. However, it remains unclear how long-term high N deposition affects soil carbon mineralization in tropical forests. To address this question, we established a long-term N deposition experiment in an N-rich lowland tropical forest of Southern China with N additions such as NH4NO3 of 0 (Control), 50 (Low-N), 100 (Medium-N) and 150 (High-N) kg N ha−1 yr−1, and laboratory incubation experiment, used to explore the response of soil carbon mineralization to the N additions therein. The results showed that 15 years of N additions significantly decreased soil carbon mineralization rates. During the incubation period from the 14th day to 56th day, the average decreases in soil CO2 emission rates were 18%, 33% and 47% in the low-N, medium-N and high-N treatments, respectively, compared with the Control. These negative effects were primarily aroused by the reduced soil microbial biomass and modified microbial functions (e.g., a decrease in bacteria relative abundance), which could be attributed to N-addition-induced soil acidification and potential phosphorus limitation in this forest. We further found that N additions greatly increased soil-dissolved organic carbon (DOC), and there were significantly negative relationships between microbial biomass and soil DOC, indicating that microbial consumption on soil-soluble carbon pool may decrease. These results suggests that long-term N deposition can increase soil carbon stability and benefit carbon sequestration through decreased carbon mineralization in N-rich tropical forests. This study can help us understand how microbes control soil carbon cycling and carbon sink in the tropics under both elevated N deposition and carbon dioxide in the future.

scholarly journals Can Agricultural Management Induced Changes in Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?

2021 ◽  
Vol 13 (12) ◽  
pp. 2265
Author(s):  
Jonathan Sanderman ◽  
Kathleen Savage ◽  
Shree Dangal ◽  
Gabriel Duran ◽  
Charlotte Rivard ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Diffuse Reflectance Spectroscopy ◽  
Low Cost ◽  
Soil Survey ◽  
Mid Infrared ◽  
Mir Spectroscopy ◽  
Induced Changes ◽  
Carbon Change

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg Soil Survey Laboratory MIR spectral library. Overall, MIR-based estimates of SOC%, with samples scanned on a secondary instrument, were excellent with the root mean square error ranging from 0.10 to 0.33% across the seven sites. In all but two instances, the same statistically significant (p < 0.10) management effect was found using both the lab-based SOC% and MIR estimated SOC% data. Despite some additional uncertainty, primarily in the form of bias, these results suggest that large existing MIR spectral libraries can be operationalized in other laboratories for successful carbon monitoring.

On human blood, rock art and calcium oxalate: further studies on organic carbon content and radiocarbon age of materials relating to Australian rock art

Antiquity ◽  
1997 ◽  
Vol 71 (272) ◽  
pp. 430-437 ◽  
Author(s):  
Richard Gillespie
Keyword(s):  
Organic Carbon ◽  
Calcium Oxalate ◽  
Human Blood ◽  
Ancient Dna ◽  
Rock Art ◽  
Field Studies ◽  
Organic Carbon Content ◽  
Radiocarbon Age ◽  
Archaeological Materials ◽  
Supplementary Report

Minute biological traces, with their prospect of recovering even ancient DNA, are the most attractive of archaeological materials to work with. This supplementary report on field studies of rock-art first published in ANTIQUITY further explores how these studies may in truth be carried out.

Subsoil organic carbon turnover is dominantly controlled by soil properties in grasslands across China

2021 ◽  
Author(s):  
Yuehong Shi ◽  
Xiaolu Tang ◽  
Peng Yu ◽  
Li Xu ◽  
Guo Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Soil Properties ◽  
Soil Carbon ◽  
Carbon Turnover ◽  
Area Index ◽  
Important Indicator ◽  
Environmental Controls ◽  
Biogeochemical Models ◽  
Soc Stock

&lt;p&gt;Soil carbon turnover time (&amp;#964;, year) is an important indicator of soil carbon stability, and a major factor in determining soil carbon sequestration capacity. Many studies investigated &amp;#964; in the topsoil or the first meter underground, however, little is known about subsoil &amp;#964; (0.2 &amp;#8211; 1.0 m) and its environmental drivers, while world subsoils below 0.2 m accounts for the majority of total soil organic carbon (SOC) stock and may be as sensitive as that of the topsoil to climate change. We used the observations from the published literatures to estimate subsoil &amp;#964; (the ratio of SOC stock to net primary productivity) in grasslands across China and employed regression analysis to detect the environmental controls on subsoil &amp;#964;. Finally, structural equation modelling (SEM) was applied to identify the dominant environmental driver (including climate, vegetation and soil). Results showed that subsoil &amp;#964; varied greatly from 5.52 to 702.17 years, and the mean (&amp;#177; standard deviation) subsoil &amp;#964; was 118.5 &amp;#177; 97.8 years. Subsoil &amp;#964; varied significantly among different grassland types that it was 164.0 &amp;#177; 112.0 years for alpine meadow, 107.0 &amp;#177; 47.9 years for alpine steppe, 177.0 &amp;#177; 143.0 years for temperate desert steppe, 96.6 &amp;#177; 88.7 years for temperate meadow steppe, 101.0 &amp;#177; 75.9 years for temperate typical steppe. Subsoil &amp;#964; significantly and negatively correlated (p &lt; 0.05) with vegetation index, leaf area index and gross primary production, highlighting the importance of vegetation on &amp;#964;. Mean annual temperature (MAT) and precipitation (MAP) had a negative impact on subsoil &amp;#964;, indicating a faster turnover of soil carbon with the increasing of MAT or MAP under ongoing climate change. SEM showed that soil properties, such as soil bulk density, cation exchange capacity and soil silt, were the most important variables driving subsoil &amp;#964;, challenging our current understanding of climatic drivers (MAT and MAP) controlling on topsoil &amp;#964;, further providing new evidence that different mechanisms control topsoil and subsoil &amp;#964;. These conclusions demonstrated that different environmental controls should be considered for reliable prediction of soil carbon dynamics in the top and subsoils in biogeochemical models or earth system models at regional or global scales.&lt;/p&gt;

Prediction and digital mapping of soil carbon storage in the Lower Namoi Valley

Soil Research ◽  
2006 ◽  
Vol 44 (3) ◽  
pp. 233 ◽  
Author(s):  
Budiman Minasny ◽  
Alex. B. McBratney ◽  
M. L. Mendonça-Santos ◽  
I. O. A. Odeh ◽  
Brice Guyon
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Carbon ◽  
Carbon Storage ◽  
Environmental Data ◽  
Pedotransfer Functions ◽  
Soil Carbon Storage ◽  
Depth Function ◽  
Terrain Attributes ◽  
Organic Carbon Storage

Estimation and mapping carbon storage in the soil is currently an important topic; thus, the knowledge of the distribution of carbon content with depth is essential. This paper examines the use of a negative exponential profile depth function to describe the soil carbon data at different depths, and its integral to represent the carbon storage. A novel method is then proposed for mapping the soil carbon storage in the Lower Namoi Valley, NSW. This involves deriving pedotransfer functions to predict soil organic carbon and bulk density, fitting the exponential depth function to the carbon profile data, deriving a neural network model to predict parameters of the exponential function from environmental data, and mapping the organic carbon storage. The exponential depth function is shown to fit the soil carbon data adequately, and the parameters also reflect the influence of soil order. The parameters of the exponential depth function were predicted from land use, radiometric K, and terrain attributes. Using the estimated parameters we map the carbon storage of the area from surface to a depth of 1 m. The organic carbon storage map shows the high influence of land use on the predicted storage. Values of 15–22 kg/m2 were predicted for the forested area and 2–6 kg/m2 in the cultivated area in the plains.

Is soil carbon disappearing? The dynamics of soil organic carbon in Java

2010 ◽  
Vol 17 (5) ◽  
pp. 1917-1924 ◽  
Author(s):  
BUDIMAN MINASNY ◽  
YIYI SULAEMAN ◽  
ALEX B. MCBRATNEY
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon
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