Stocks and changes in organic carbon in Danish agricultural soils – role of bulk density and stone fractions

2021 ◽  
Author(s):  
Laura Sofie Harbo ◽  
Jørgen Eivind Olesen ◽  
Zhi Liang ◽  
Lars Elsgaard
Keyword(s):  
Organic Carbon ◽  
Bulk Density ◽  
Management Practices ◽  
Agricultural Soils ◽  
Soil Bulk Density ◽  
Agricultural Management ◽  
Specific Information ◽  
High Productivity ◽  
Soc Estimation ◽  
Sampling Campaign

<p>Soil organic carbon (SOC) is essential for soil fertility and further represents a global carbon stock with potential to control atmospheric CO<sub>2</sub> concentrations. Due to intense agricultural management, SOC is decreasing in many parts of the world, meaning that the soils act as CO<sub>2</sub> sources rather than CO<sub>2</sub> sinks, which they could have the capacity to be. Therefore, it is important to identify pertinent agricultural management practices that allow for high productivity, but at the same time allow for carbon sequestration and increase in SOC.</p><p>In order to document changes in SOC, it is necessary to monitor SOC over decadal time scales, since changes occur slowly and are small as compared with existing stocks. The SOC content in Danish agricultural soils has been monitored at approx. 10-yr intervals (1986, 1997, 2009) since the first systematic national observations in 1986, where soils were sampled from a national 7 km x 7 km grid.</p><p>In 2018, a new sampling campaign was conducted from the national 7 km x 7 km grid and soils were analysed for SOC to 1 m depth. The procedures applied in 2018 allowed for more precise relocation of the sampling points from 2009 as compared to precision obtained during the period from 1986-2009. Further, measurements in 2018 included assessment of soil bulk density and stone content in the upper 0-50 cm, which was not measured previously. Thus, one of the aims of the study was to evaluate how more precise point-specific information on bulk density and stone fractions affected the calculated SOC stocks across different soil types and management practices.</p><p>The point-specific bulk density measured in 2018 were on average lower than the bulk densities used previously, which were retrieved from a database of texture-based soil classes. The volumetric stone fraction in the upper 0-50 cm was found to be <5% for roughly 90% of the soils, whereas <3% of the soils had stone fractions of >10%. On average, the inclusion of point-specific bulk density and stone fractions lead to approx. 5% lower SOC estimation, with equal approximmately contribution from the two variables.</p>

Influence of agricultural management on soil organic carbon: A compendium and assessment of Canadian studies

2003 ◽  
Vol 83 (4) ◽  
pp. 363-380 ◽  
Author(s):  
A. J. VandenBygaart ◽  
E. G. Gregorich ◽  
D. A. Angers
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Management Practices ◽  
Agricultural Management ◽  
Organic Fertilizers ◽  
Published Data ◽  
Native Land ◽  
Soc Stocks ◽  
Long Term Studies

To fulfill commitments under the Kyoto Protocol, Canada is required to provide verifiable estimates and uncertainties for soil organic carbon (SOC) stocks, and for changes in those stocks over time. Estimates and uncertainties for agricultural soils can be derived from long-term studies that have measured differences in SOC between different management practices. We compiled published data from long-term studies in Canada to assess the effect of agricultural management on SOC. A total of 62 studies were compiled, in which the difference in SOC was determined for conversion from native land to cropland, and for different tillage, crop rotation and fertilizer management practices. There was a loss of 24 ± 6% of the SOC after native land was converted to agricultural land. No-till (NT) increased the storage of SOC in western Canada by 2.9 ± 1.3 Mg ha-1; however, in eastern Canada conversion to NT did not increase SOC. In general, the potential to store SOC when NT was adopted decreased with increasing background levels of SOC. Using no-tillage, reducing summer fallow, including hay in rotation with wheat (Triticum aestivum L.), plowing green manures into the soil, and applying N and organic fertilizers were the practices that tended to show the most consistent in creases in SOC storage. By relating treatment SOC levels to those in the control treatments, SOC stock change factors and their levels of uncertainty were derived for use in empirical models, such as the United Nations Intergovernmental Panel on Climate Change (IPCC). Guidelines model for C stock changes. However, we must be careful when attempting to extrapolate research plot data to farmers’ fields since the history of soil and crop management has a significant influence on existing and future SOC stocks. Key words: C sequestration, tillage, crop rotations, fertilizer, cropping intensity, Canada

scholarly journals Soil organic carbon stocks are systematically overestimated by misuse of the parameters bulk density and stone content

2016 ◽  
Author(s):  
Christopher Poeplau ◽  
Cora Vos ◽  
Axel Don
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Bulk Density ◽  
Agricultural Soils ◽  
Soil Layer ◽  
Future Studies ◽  
Soil Organic Carbon Stocks ◽  
Soc Stock ◽  
The Mean ◽  
Soc Stocks

Abstract. Estimation of soil organic carbon (SOC) stocks requires estimates of the carbon content, bulk density, stone content and depth of a respective soil layer. However, different application of these parameters could introduce a considerable bias. Here, we explain why three out of four frequently applied methods overestimate SOC stocks. In stone rich soils (> 30 Vol. %), SOC stocks could be overestimated by more than 100 %, as revealed by using German Agricultural Soil Inventory data. Due to relatively low stone content, the mean systematic overestimation for German agricultural soils was 2.1–10.1 % for three different commonly used equations. The equation ensemble as re-formulated here might help to unify SOC stock determination and avoid overestimation in future studies.

scholarly journals Total and Active Soil Organic Carbon from Long‐term Agricultural Management Practices in West Tennessee

ael ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 180062 ◽  
Author(s):  
Sindhu Jagadamma ◽  
Michael E. Essington ◽  
Sutie Xu ◽  
Xinhua Yin
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Management Practices ◽  
Agricultural Management ◽  
West Tennessee

Organic carbon partitioning in soil and litter in subtropical woodlands and open forests: a case study from the Brigalow Belt, Queensland

2006 ◽  
Vol 28 (2) ◽  
pp. 115 ◽  
Author(s):  
S. H. Roxburgh ◽  
B. G. Mackey ◽  
C. Dean ◽  
L. Randall ◽  
A. Lee ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Bulk Density ◽  
Soil Surface ◽  
Soil Bulk Density ◽  
Carbon Stocks ◽  
Soil Carbon Stocks ◽  
Landscape Scales ◽  
Open Forests

A woodland–open forest landscape within the Brigalow Belt South bioregion of Queensland, Australia, was surveyed for soil organic carbon, soil bulk density and soil-surface fine-litter carbon. Soil carbon stocks to 30 cm depth across 14 sites, spanning a range of soil and vegetation complexes, ranged from 10.7 to 61.8 t C/ha, with an overall mean of 36.2 t C/ha. Soil carbon stocks to 100 cm depth ranged from 19.4 to 150.5 t C/ha, with an overall mean of 72.9 t C/ha. The standing stock of fine litter ranged from 1.0 to 7.0 t C/ha, with a mean of 2.6 t C/ha, and soil bulk density averaged 1.4 g/cm3 at the soil surface, and 1.6 g/cm3 at 1 m depth. These results contribute to the currently sparse database of soil organic carbon and bulk density measurements in uncultivated soils within Australian open forests and woodlands. The estimates of total soil organic carbon stock calculated to 30 cm depth were further partitioned into resistant plant material (RPM), humus (HUM), and inert organic matter (IOM) pools using diffuse mid-infrared (MIR) analysis. Prediction of the HUM and RPM pools using the RothC soil carbon model agreed well with the MIR measurements, confirming the suitability of RothC for modelling soil organic carbon in these soils. Methods for quantifying soil organic carbon at landscape scales were also explored, and a new regression-based technique for estimating soil carbon stocks from simple field-measured soil attributes has been proposed. The results of this study are discussed with particular reference to the difficulties encountered in the collection of the data, their limitations, and opportunities for the further development of methods for quantifying soil organic carbon at landscape scales.

Impact of agricultural management practices on soil organic carbon: simulation of Australian wheat systems

2013 ◽  
Vol 19 (5) ◽  
pp. 1585-1597 ◽  
Author(s):  
Gang Zhao ◽  
Brett A. Bryan ◽  
Darran King ◽  
Zhongkui Luo ◽  
Enli Wang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Management Practices ◽  
Agricultural Management ◽  
Australian Wheat

Land use and management influences on surface soil organic carbon in Tasmania

Soil Research ◽  
2013 ◽  
Vol 51 (8) ◽  
pp. 615 ◽  
Author(s):  
W. E. Cotching ◽  
G. Oliver ◽  
M. Downie ◽  
R. Corkrey ◽  
R. B. Doyle
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Bulk Density ◽  
Management Practices ◽  
Carbon Stocks ◽  
Carbon Accounting ◽  
Continuous Cropping ◽  
Texture Contrast

The effects of environmental parameters, land-use history, and management practices on soil organic carbon (SOC) concentrations, nitrogen, and bulk density were determined in agricultural soils of four soil types in Tasmania. The sites sampled were Dermosols, Vertosols, Ferrosols, and a group of texture-contrast soils (Chromosol and Sodosol) each with a 10-year management history ranging from permanent perennial pasture to continuous cropping. Rainfall, Soil Order, and land use were all strong explanatory variables for differences in SOC, soil carbon stock, total nitrogen, and bulk density. Cropping sites had 29–35% less SOC in surface soils (0–0.1 m) than pasture sites as well as greater bulk densities. Clay-rich soils contained the greatest carbon stocks to 0.3 m depth under pasture, with Ferrosols containing a mean of 158 Mg C ha–1, Vertosols 112 Mg C ha–1, and Dermosols 107 Mg C ha–1. Texture-contrast soils with sandier textured topsoils under pasture had a mean of 69 Mg C ha–1. The range of values in soil carbon stocks indicates considerable uncertainty in baseline values for use in soil carbon accounting. Farmers can influence SOC more by their choice of land use than their day-to-day soil management. Although the influence of management is not as great as other inherent site variables, farmers can still select practices for their ability to retain more SOC.

scholarly journals Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content

2016 ◽  
Vol 20 (9) ◽  
pp. 3859-3872 ◽  
Author(s):  
William Alexander Avery ◽  
Catherine Finkenbiner ◽  
Trenton E. Franz ◽  
Tiejun Wang ◽  
Anthony L. Nguy-Robertson ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Water Content ◽  
Bulk Density ◽  
Soil Water Content ◽  
Cosmic Ray ◽  
Soil Bulk Density ◽  
Local Soil ◽  
Calibration Parameters

Abstract. The need for accurate, real-time, reliable, and multi-scale soil water content (SWC) monitoring is critical for a multitude of scientific disciplines trying to understand and predict the Earth's terrestrial energy, water, and nutrient cycles. One promising technique to help meet this demand is fixed and roving cosmic-ray neutron probes (CRNPs). However, the relationship between observed low-energy neutrons and SWC is affected by local soil and vegetation calibration parameters. This effect may be accounted for by a calibration equation based on local soil type and the amount of vegetation. However, determining the calibration parameters for this equation is labor- and time-intensive, thus limiting the full potential of the roving CRNP in large surveys and long transects, or its use in novel environments. In this work, our objective is to develop and test the accuracy of globally available datasets (clay weight percent, soil bulk density, and soil organic carbon) to support the operability of the roving CRNP. Here, we develop a 1 km product of soil lattice water over the continental United States (CONUS) using a database of in situ calibration samples and globally available soil taxonomy and soil texture data. We then test the accuracy of the global dataset in the CONUS using comparisons from 61 in situ samples of clay percent (RMSE  =  5.45 wt %, R2  =  0.68), soil bulk density (RMSE  =  0.173 g cm−3, R2  =  0.203), and soil organic carbon (RMSE  =  1.47 wt %, R2  =  0.175). Next, we conduct an uncertainty analysis of the global soil calibration parameters using a Monte Carlo error propagation analysis (maximum RMSE  ∼  0.035 cm3 cm−3 at a SWC  =  0.40 cm3 cm−3). In terms of vegetation, fast-growing crops (i.e., maize and soybeans), grasslands, and forests contribute to the CRNP signal primarily through the water within their biomass and this signal must be accounted for accurate estimation of SWC. We estimated the biomass water signal by using a vegetation index derived from MODIS imagery as a proxy for standing wet biomass (RMSE  <  1 kg m−2). Lastly, we make recommendations on the design and validation of future roving CRNP experiments.

scholarly journals Comparison of different models for predicting soil bulk density. Case study – Slovakian agricultural soils

2017 ◽  
Vol 31 (4) ◽  
pp. 491-498 ◽  
Author(s):  
Jarmila Makovníková ◽  
Miloš Širáň ◽  
Beata Houšková ◽  
Boris Pálka ◽  
Arwyn Jones
Keyword(s):  
Organic Carbon ◽  
Bulk Density ◽  
Monitoring System ◽  
Soil Bulk Density ◽  
Pedotransfer Functions ◽  
Research Centre ◽  
Organic Carbon Content ◽  
Joint Research ◽  
Data Set ◽  
Sustainable Resources

Abstract Soil bulk density is one of the main direct indicators of soil health, and is an important aspect of models for determining agroecosystem services potential. By way of applying multi-regression methods, we have created a distributed prediction of soil bulk density used subsequently for topsoil carbon stock estimation. The soil data used for this study were from the Slovakian partial monitoring system-soil database. In our work, two models of soil bulk density in an equilibrium state, with different combinations of input parameters (soil particle size distribution and soil organic carbon content in %), have been created, and subsequently validated using a data set from 15 principal sampling sites of Slovakian partial monitoring system-soil, that were different from those used to generate the bulk density equations. We have made a comparison of measured bulk density data and data calculated by the pedotransfer equations against soil bulk density calculated according to equations recommended by Joint Research Centre Sustainable Resources for Europe. The differences between measured soil bulk density and the model values vary from −0.144 to 0.135 g cm−3 in the verification data set. Furthermore, all models based on pedotransfer functions give moderately lower values. The soil bulk density model was then applied to generate a first approximation of soil bulk density map for Slovakia using texture information from 17 523 sampling sites, and was subsequently utilised for topsoil organic carbon estimation.

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