scholarly journals Proximal sensing for soil carbon accounting

SOIL ◽  
2018 ◽  
Vol 4 (2) ◽  
pp. 101-122 ◽  
Author(s):  
Jacqueline R. England ◽  
Raphael A. Viscarra Rossel
Keyword(s):  
Bulk Density ◽  
Financial Incentives ◽  
Management Practices ◽  
Near Infrared ◽  
Carbon Accounting ◽  
Soil Organic C ◽  
Proximal Sensing ◽  
Organic C ◽  
Soil C ◽  
Cost Efficient

Abstract. Maintaining or increasing soil organic carbon (C) is vital for securing food production and for mitigating greenhouse gas (GHG) emissions, climate change, and land degradation. Some land management practices in cropping, grazing, horticultural, and mixed farming systems can be used to increase organic C in soil, but to assess their effectiveness, we need accurate and cost-efficient methods for measuring and monitoring the change. To determine the stock of organic C in soil, one requires measurements of soil organic C concentration, bulk density, and gravel content, but using conventional laboratory-based analytical methods is expensive. Our aim here is to review the current state of proximal sensing for the development of new soil C accounting methods for emissions reporting and in emissions reduction schemes. We evaluated sensing techniques in terms of their rapidity, cost, accuracy, safety, readiness, and their state of development. The most suitable method for measuring soil organic C concentrations appears to be visible–near-infrared (vis–NIR) spectroscopy and, for bulk density, active gamma-ray attenuation. Sensors for measuring gravel have not been developed, but an interim solution with rapid wet sieving and automated measurement appears useful. Field-deployable, multi-sensor systems are needed for cost-efficient soil C accounting. Proximal sensing can be used for soil organic C accounting, but the methods need to be standardized and procedural guidelines need to be developed to ensure proficient measurement and accurate reporting and verification. These are particularly important if the schemes use financial incentives for landholders to adopt management practices to sequester soil organic C. We list and discuss requirements for developing new soil C accounting methods based on proximal sensing, including requirements for recording, verification, and auditing.

scholarly journals Proximal sensing for soil carbon accounting

2018 ◽  
Author(s):  
Jacqueline R. England ◽  
Raphael Armando Viscarra Rossel
Keyword(s):  
Bulk Density ◽  
Financial Incentives ◽  
Management Practices ◽  
Ghg Emissions ◽  
Carbon Accounting ◽  
Soil Organic C ◽  
Proximal Sensing ◽  
Organic C ◽  
Soil C ◽  
Cost Efficient

Abstract. Maintaining or increasing soil organic carbon (C) is important for securing food production, and for mitigating greenhouse gas (GHG) emissions, climate change and land degradation. Some land management practices in cropping, grazing, horticultural and mixed farming systems can be used to increase organic C in soil, but to assess their effectiveness, we need accurate and cost-efficient methods for measuring and monitoring the change. To determine the stock of organic C in soil, one needs measurements of soil organic C concentration, bulk density and gravel content, but using conventional laboratory-based analytical methods is expensive. Our aim here is to review the current state of proximal sensing for the development of new soil C accounting methods for emissions reporting and in emissions reduction schemes. We evaluated sensing techniques in terms of their rapidity, cost, accuracy, safety, readiness and their state of development. The most suitable technique for measuring soil organic C concentrations appears to be vis–NIR spectroscopy and for bulk density active gamma-ray attenuation. Sensors for measuring gravel have not been developed, but an interim solution with rapid wet-sieving and automated measurement appears useful. Field-deployable, multi-sensor systems are needed for cost-efficient soil C accounting. Proximal sensing can be used for soil organic C accounting, but the methods need to be standardised and procedural guidelines need to be developed to ensure proficient measurement and accurate reporting and verification. This is particularly important if the schemes use financial incentives for landholders to adopt management practices to sequester soil organic C. We list and discuss the requirements for the development of new soil C accounting methods that are based on proximal sensing, including requirements for recording, verification and auditing.

scholarly journals Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition

2017 ◽  
Vol 51 (10) ◽  
pp. 5630-5641 ◽  
Author(s):  
Raphael A. Viscarra Rossel ◽  
Craig R. Lobsey ◽  
Chris Sharman ◽  
Paul Flick ◽  
Gordon McLachlan
Keyword(s):  
Soil Organic C ◽  
Proximal Sensing ◽  
Organic C ◽  
C Stocks

scholarly journals Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system

2019 ◽  
Vol 10 (2) ◽  
pp. 233-255 ◽  
Author(s):  
Efrén López-Blanco ◽  
Jean-François Exbrayat ◽  
Magnus Lund ◽  
Torben R. Christensen ◽  
Mikkel P. Tamstorf ◽  
...  
Keyword(s):  
The Arctic ◽  
Soil Organic C ◽  
Area Index ◽  
Organic C ◽  
Soil C ◽  
Transit Times ◽  
C Cycle ◽  
C Stocks ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. There is a significant knowledge gap in the current state of the terrestrial carbon (C) budget. Recent studies have highlighted a poor understanding particularly of C pool transit times and of whether productivity or biomass dominate these biases. The Arctic, accounting for approximately 50 % of the global soil organic C stocks, has an important role in the global C cycle. Here, we use the CARbon DAta MOdel (CARDAMOM) data-assimilation system to produce pan-Arctic terrestrial C cycle analyses for 2000–2015. This approach avoids using traditional plant functional type or steady-state assumptions. We integrate a range of data (soil organic C, leaf area index, biomass, and climate) to determine the most likely state of the high-latitude C cycle at a 1∘ × 1∘ resolution and also to provide general guidance about the controlling biases in transit times. On average, CARDAMOM estimates regional mean rates of photosynthesis of 565 g C m−2 yr−1 (90 % confidence interval between the 5th and 95th percentiles: 428, 741), autotrophic respiration of 270 g C m−2 yr−1 (182, 397) and heterotrophic respiration of 219 g C m−2 yr−1 (31, 1458), suggesting a pan-Arctic sink of −67 (−287, 1160) g Cm−2 yr−1, weaker in tundra and stronger in taiga. However, our confidence intervals remain large (and so the region could be a source of C), reflecting uncertainty assigned to the regional data products. We show a clear spatial and temporal agreement between CARDAMOM analyses and different sources of assimilated and independent data at both pan-Arctic and local scales but also identify consistent biases between CARDAMOM and validation data. The assimilation process requires clearer error quantification for leaf area index (LAI) and biomass products to resolve these biases. Mapping of vegetation C stocks and change over time and soil C ages linked to soil C stocks is required for better analytical constraint. Comparing CARDAMOM analyses to global vegetation models (GVMs) for the same period, we conclude that transit times of vegetation C are inconsistently simulated in GVMs due to a combination of uncertainties from productivity and biomass calculations. Our findings highlight that GVMs need to focus on constraining both current vegetation C stocks and net primary production to improve a process-based understanding of C cycle dynamics in the Arctic.

Soil organic matter in rainfed cropping systems of the Australian cereal belt

Soil Research ◽  
2001 ◽  
Vol 39 (3) ◽  
pp. 435 ◽  
Author(s):  
R. C. Dalal ◽  
K. Y. Chan
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Management Practices ◽  
Performance Indicator ◽  
Annual Rainfall ◽  
Soil Productivity ◽  
Organic C ◽  
Soil C ◽  
Eastern Australia

The Australian cereal belt stretches as an arc from north-eastern Australia to south-western Australia (24˚S–40˚S and 125˚E–147˚E), with mean annual temperatures from 14˚C (temperate) to 26˚C (subtropical), and with annual rainfall ranging from 250 mm to 1500 mm. The predominant soil types of the cereal belt include Chromosols, Kandosols, Sodosols, and Vertosols, with significant areas of Ferrosols, Kurosols, Podosols, and Dermosols, covering approximately 20 Mha of arable cropping and 21 Mha of ley pastures. Cultivation and cropping has led to a substantial loss of soil organic matter (SOM) from the Australian cereal belt; the long-term SOM loss often exceeds 60% from the top 0–0.1 m depth after 50 years of cereal cropping. Loss of labile components of SOM such as sand-size or particulate SOM, microbial biomass, and mineralisable nitrogen has been even higher, thus resulting in greater loss in soil productivity than that assessed from the loss of total SOM alone. Since SOM is heterogeneous in nature, the significance and functions of its various components are ambiguous. It is essential that the relationship between levels of total SOM or its identif iable components and the most affected soil properties be established and then quantif ied before the concentrations or amounts of SOM and/or its components can be used as a performance indicator. There is also a need for experimentally verifiable soil organic C pools in modelling the dynamics and management of SOM. Furthermore, the interaction of environmental pollutants added to soil, soil microbial biodiversity, and SOM is poorly understood and therefore requires further study. Biophysically appropriate and cost-effective management practices for cereal cropping lands are required for restoring and maintaining organic matter for sustainable agriculture and restoration of degraded lands. The additional benefit of SOM restoration will be an increase in the long-term greenhouse C sink, which has the potentialto reduce greenhouse emissions by about 50 Mt CO2 equivalents/year over a 20-year period, although current improved agricultural practices can only sequester an estimated 23% of the potential soil C sink.

Douglas-fir soil C and N properties a decade after termination of urea fertilization

2001 ◽  
Vol 31 (12) ◽  
pp. 2225-2236 ◽  
Author(s):  
Peter S Homann ◽  
Bruce A Caldwell ◽  
H N Chappell ◽  
Phillip Sollins ◽  
Chris W Swanston
Keyword(s):  
Mineral Soil ◽  
Cellulase Activity ◽  
Douglas Fir ◽  
Soil Organic C ◽  
Total N ◽  
Organic C ◽  
Soil C ◽  
Second Growth ◽  
Heavy Fractions ◽  
Urea Fertilization

Chemical and microbial soil properties were assessed in paired unfertilized and urea fertilized (>89 g N·m–2) plots in 13 second-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) stands distributed throughout western Washington and Oregon. A decade following the termination of fertilization, fertilized plots averaged 28% higher total N in the O layer than unfertilized plots, 24% higher total N in surface (0–5 cm) mineral soil, and up to four times the amount of extractable ammonium and nitrate. Decreased pH (0.2 pH units) caused by fertilization may have been due to nitrification or enhanced cation uptake. In some soil layers, fertilization decreased cellulase activity and soil respiration but increased wood decomposition. There was no effect of fertilization on concentrations of light and heavy fractions, labile carbohydrates, and phosphatase and xylanase activities. No increase in soil organic C was detected, although variability precluded observing an increase of less than ~15%. Lack of a regionwide fertilization influence on soil organic C contrasts with several site-specific forest and agricultural studies that have shown C increases resulting from fertilization. Overall, the results indicate a substantial residual influence on soil N a decade after urea fertilization but much more limited influence on soil C processes and pools.

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 Soil management effects on organic carbon in isolated fractions of a Gray Luvisol

2006 ◽  
Vol 86 (1) ◽  
pp. 141-151 ◽  
Author(s):  
A. F. Plante ◽  
C. E. Stewart ◽  
R. T. Conant ◽  
K. Paustian ◽  
J. Six
Keyword(s):  
Organic Matter ◽  
Crop Production ◽  
N Fertilization ◽  
Residue Management ◽  
Soil Organic C ◽  
Organic C ◽  
Straw Management ◽  
Soil C ◽  
C Pools

Agricultural management affects soil organic matter, which is important for sustainable crop production and as a greenhouse gas sink. Our objective was to determine how tillage, residue management and N fertilization affect organic C in unprotected, and physically, chemically and biochemically protected soil C pools. Samples from Breton, Alberta were fractionated and analysed for organic C content. As in previous reports, N fertilization had a positive effect, tillage had a minimal effect, and straw management had no effect on whole-soil organic C. Tillage and straw management did not alter organic C concentrations in the isolated C pools, while N fertilization increased C concentrations in all pools. Compared with a woodlot soil, the cultivated plots had lower total organic C, and the C was redistributed among isolated pools. The free light fraction and coarse particulate organic matter responded positively to C inputs, suggesting that much of the accumulated organic C occurred in an unprotected pool. The easily dispersed silt-sized fraction was the mineral-associated pool most responsive to changes in C inputs, whereas the microaggregate-derived silt-sized fraction best preserved C upon cultivation. These findings suggest that the silt-sized fraction is important for the long-term stabilization of organic matter through both physical occlusion in microaggregates and chemical protection by mineral association. Key words: Soil organic C, tillage, residue management, N fertilization, silt, clay

scholarly journals Estimations of soil fertility in physically degraded soils through selective accounting of fine earth

2016 ◽  
Author(s):  
Mavinakoppa S. Nagaraja ◽  
Ajay Kumar Bhardwaj ◽  
G.V. Prabhakara Reddy ◽  
Chilakunda A. Srinivasamurthy ◽  
Sandeep Kumar
Keyword(s):  
Soil Fertility ◽  
Bulk Density ◽  
Land Development ◽  
Soil Mass ◽  
Available Phosphorus ◽  
Soil Organic C ◽  
Fine Earth ◽  
Degraded Lands ◽  
Available Nitrogen ◽  
Organic C

Abstract. Soil fertility and organic carbon (C) stock estimations are crucial to soil management especially that of degraded soils, for productive agricultural use and in soil C sequestration studies. Currently, estimations based on generalized soil mass (hectare-furrow basis) or bulk density (BD) basis are used which may be suitable for normal agricultural soils but not for degraded soils. We measured soil organic C, available nitrogen (N), available phosphorus (P) and available potassium (K), and estimated stocks using three methods: (i) generalized soil mass (GSM, 2 million kg ha−1 furrow soil), ii) bulk density based soil mass (BDSM) and (iii) the proportion of fine earth volume (FEV) method, for soils sampled from physically degraded lands in Eastern Dry Zone of Karnataka State in India. Comparative analyses using these methods revealed that the soil organic C, and N, P and K stocks determined by using BDSM were higher than those by GSM method. The soil organic C values were the lowest in the FEV method compared to the other two methods. The GSM method overestimated soil organic C, N, P and K by 9.3–72.1 %, 9.5–72.3 %, 7.1–66.6 % and 9.2–72.3 %, respectively, compared to FEV based estimations for physically degraded soils. The differences among the three methods of determinations were lower in soils with low gravel content and increased with increase in gravel volume. There was overestimation of soil organic C and soil fertility with GSM and BDSM methods. A reassessment of methods of estimation was, therefore, attempted to provide fair estimates for land development projects in degraded lands.

scholarly journals Assessing the response of soil carbon in Australia to changing inputs and climate using a consistent modelling framework

2021 ◽  
Vol 18 (18) ◽  
pp. 5185-5202
Author(s):  
Juhwan Lee ◽  
Raphael A. Viscarra Rossel ◽  
Mingxi Zhang ◽  
Zhongkui Luo ◽  
Ying-Ping Wang
Keyword(s):  
Global Change ◽  
Future Climate Change ◽  
Natural Environments ◽  
Soil Organic C ◽  
Total N ◽  
Organic C ◽  
Soil C ◽  
Continental Scale ◽  
Modelling Framework ◽  
C Stocks

Abstract. Land use and management practices affect the response of soil organic carbon (C) to global change. Process-based models of soil C are useful tools to simulate C dynamics, but it is important to bridge any disconnect that exists between the data used to inform the models and the processes that they depict. To minimise that disconnect, we developed a consistent modelling framework that integrates new spatially explicit soil measurements and data with the Rothamsted carbon model (Roth C) and simulates the response of soil organic C to future climate change across Australia. We compiled publicly available continental-scale datasets and pre-processed, standardised and configured them to the required spatial and temporal resolutions. We then calibrated Roth C and ran simulations to estimate the baseline soil organic C stocks and composition in the 0–0.3 m layer at 4043 sites in cropping, modified grazing, native grazing and natural environments across Australia. We used data on the C fractions, the particulate, mineral-associated and resistant organic C (POC, MAOC and ROC, respectively) to represent the three main C pools in the Roth C model's structure. The model explained 97 %–98 % of the variation in measured total organic C in soils under cropping and grazing and 65 % in soils under natural environments. We optimised the model at each site and experimented with different amounts of C inputs to simulate the potential for C accumulation under constant climate in a 100-year simulation. With an annual increase of 1 Mg C ha−1 in C inputs, the model simulated a potential soil C increase of 13.58 (interquartile range 12.19–15.80), 14.21 (12.38–16.03) and 15.57 (12.07–17.82) Mg C ha−1 under cropping, modified grazing and native grazing and 3.52 (3.15–4.09) Mg C ha−1 under natural environments. With projected future changes in climate (+1.5, 2 and 5.0 ∘C) over 100 years, the simulations showed that soils under natural environments lost the most C, between 3.1 and 4.5 Mg C ha−1, while soils under native grazing lost the least, between 0.4 and 0.7 Mg C ha−1. Soil under cropping lost between 1 and 2.7 Mg C ha−1, while those under modified grazing showed a slight increase with temperature increases of 1.5 ∘C, but with further increases of 2 and 5 ∘C the median loss of TOC was 0.28 and 3.4 Mg C ha−1, respectively. For the different land uses, the changes in the C fractions varied with changes in climate. An empirical assessment of the controls on the C change showed that climate, pH, total N, the C : N ratio and cropping were the most important controls on POC change. Clay content and climate were dominant controls on MAOC change. Consistent and explicit soil organic C simulations improve confidence in the model's estimations, facilitating the development of sustainable soil management under global change.

scholarly journals From Laboratory to Proximal Sensing Spectroscopy for Soil Organic Carbon Estimation—A Review

2020 ◽  
Vol 12 (2) ◽  
pp. 443 ◽  
Author(s):  
Theodora Angelopoulou ◽  
Athanasios Balafoutis ◽  
George Zalidis ◽  
Dionysis Bochtis
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Management Practices ◽  
Near Infrared ◽  
Wavelength Region ◽  
Soil Condition ◽  
Short Wave ◽  
Proximal Sensing

Rapid and cost-effective soil properties estimations are considered imperative for the monitoring and recording of agricultural soil condition for the implementation of site-specific management practices. Conventional laboratory measurements are costly and time-consuming, and, therefore, cannot be considered appropriate for large datasets. This article reviews laboratory and proximal sensing spectroscopy in the visible and near infrared (VNIR)–short wave infrared (SWIR) wavelength region for soil organic carbon and soil organic matter estimation as an alternative to analytical chemistry measurements. The aim of this work is to report the progress made in the last decade on data preprocessing, calibration approaches, and system configurations used for VNIR-SWIR spectroscopy of soil organic carbon and soil organic matter estimation. We present and compare the results of over fifty selective studies and discuss the factors that affect the accuracy of spectroscopic measurements for both laboratory and in situ applications.

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