Current status, uncertainty and future needs in soil organic carbon monitoring

Increasing human demands on soil-derived ecosystem services requires reliable data on global soil resources for sustainable development. The soil organic carbon (SOC) pool is a key indicator of soil quality as it affects essential biological, chemical and physical soil functions such as nutrient cycling, pesticide and water retention, and soil structure maintenance. However, information on the SOC pool, and its temporal and spatial dynamics is unbalanced. Even in well-studied regions with a pronounced interest in environmental issues information on soil carbon (C) is inconsistent. Several activities for the compilation of global soil C data are under way. However, different approaches for soil sampling and chemical analyses make even regional comparisons highly uncertain. Often, the procedures used so far have not allowed the reliable estimation of the total SOC pool, partly because the available knowledge is focused on not clearly defined upper soil horizons and the contribution of subsoil to SOC stocks has been less considered. Even more difficult is quantifying SOC pool changes over time. SOC consists of variable amounts of labile and recalcitrant molecules of plant, and microbial and animal origin that are often operationally defined. A comprehensively active soil expert community needs to agree on protocols of soil surveying and lab procedures towards reliable SOC pool estimates. Already established long-term ecological research sites, where SOC changes are quantified and the underlying mechanisms are investigated, are potentially the backbones for regional, national, and international SOC monitoring programs. © 2013 Elsevier B.V.

Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

Variation in soil organic carbon and thickness of soil horizons within a boreal forest stand - effect of trees and implications for sampling

Summary

Changes in Soil Organic Carbon Fractions in Response to Cover Crops in an Orange Orchard

ABSTRACT The cultivation of cover crops intercropped with fruit trees is an alternative to maintain mulch cover between plant rows and increase soil organic carbon (C) stocks. The objective of this study was to evaluate changes in soil total organic C content and labile organic matter fractions in response to cover crop cultivation in an orange orchard. The experiment was performed in the state of Bahia, in a citrus orchard with cultivar ‘Pera’ orange (Citrus sinensis) at a spacing of 6 × 4 m. A randomized complete block design with three replications was used. The following species were used as cover crops: Brachiaria (Brachiaria decumbes) – BRAQ, pearl millet (Pennisetum glaucum) – MIL, jack bean (Canavalia ensiformis) – JB, blend (50 % each) of jack bean + millet (JB/MIL), and spontaneous vegetation (SPV). The cover crops were broadcast-seeded between the rows of orange trees and mechanically mowed after flowering. Soil sampling at depths of 0.00-0.10, 0.10-0.20, and 0.20-0.40 m was performed in small soil trenches. The total soil organic C (SOC) content, light fraction (LF), and the particulate organic C (POC), and oxidizable organic C fractions were estimated. Total soil organic C content was not significantly changed by the cover crops, indicating low sensitivity in reacting to recent changes in soil organic matter due to management practices. Grasses enabled a greater accumulation of SOC stocks in 0.00-0.40 m compared to all other treatments. Jack bean cultivation increased LF and the most labile oxidizable organic C fraction (F1) in the soil surface and the deepest layer tested. Cover crop cultivation increased labile C in the 0.00-0.10 m layer, which can enhance soil microbial activity and nutrient absorption by the citrus trees. The fractions LF and F1 may be suitable indicators for monitoring changes in soil organic matter content due to changes in soil management practices.

Particulate soil organic carbon and stratification ratio increases in response to crop residue decomposition under no-till

In soils under no-tillage (NT), the continuous crop residue input to the surface layer leads to carbon (C) accumulation. This study evaluated a soil under NT in Ponta Grossa (State of Paraná, Brazil) for: 1) the decomposition of black oat (Avena strigosa Schreb.) residues, 2) relation of the biomass decomposition effect with the soil organic carbon (SOC) content, the particulate organic carbon (POC) content, and the soil carbon stratification ratio (SR) of an Inceptisol. The assessments were based on seven samplings (t0 to t6) in a period of 160 days of three transects with six sampling points each. The oat dry biomass was 5.02 Mg ha-1 at t0, however, after 160 days, only 17.8 % of the initial dry biomass was left on the soil surface. The SOC in the 0-5 cm layer varied from 27.56 (t0) to 30.07 g dm-3 (t6). The SR increased from 1.33 to 1.43 in 160 days. There was also an increase in the POC pool in this period, from 8.1 to 10.7 Mg ha-1. The increase in SOC in the 0-5 cm layer in the 160 days was mainly due to the increase of POC derived from oat residue decomposition. The linear relationship between SOC and POC showed that 21 % of SOC was due to the more labile fraction. The results indicated that the continuous input of residues could be intensified to increase the C pool and sequestration in soils under NT.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Prediction of soil organic carbon for Ethiopian highlands using soil spectroscopy

Soil spectroscopy was applied for predicting soil organic carbon (SOC) in the highlands of Ethiopia. Soil samples were acquired from Ethiopia’s National Soil Testing Centre and direct field sampling. The reflectance of samples was measured using a FieldSpec 3 diffuse reflectance spectrometer. Outliers and sample relation were evaluated using principal component analysis (PCA) and models were developed through partial least square regression (PLSR). For nine watersheds sampled, 20% of the samples were set aside to test prediction and 80% were used to develop calibration models. Depending on the number of samples per watershed, cross validation or independent validation were used.The stability of models was evaluated using coefficient of determination (R2), root mean square error (RMSE), and the ratio performance deviation (RPD). The R2 (%), RMSE (%), and RPD, respectively, for validation were Anjeni (88, 0.44, 3.05), Bale (86, 0.52, 2.7), Basketo (89, 0.57, 3.0), Benishangul (91, 0.30, 3.4), Kersa (82, 0.44, 2.4), Kola tembien (75, 0.44, 1.9),Maybar (84. 0.57, 2.5),Megech (85, 0.15, 2.6), andWondoGenet (86, 0.52, 2.7) indicating that themodels were stable. Models performed better for areas with high SOC values than areas with lower SOC values. Overall, soil spectroscopy performance ranged from very good to good.

Managing Soil Organic Carbon: A Farm Perspective

Farming practices that lead to declining returns and inputs of carbon to soils pose a threat to key soil functions. The EU FP 7 interdisciplinary project Smart SOIL is using scientific testing and modeling to identify management practices that can optimize soil carbon storage and crop productivity. A consultation with advisors and policymakers in six European case study regions seeks to identify barriers to, and incentives for, uptake of such practices. Results from preliminary interviews are reported. Overall advisor and farmer awareness of management practices specifically directed towards soil carbon. is low. Most production- related decisions are taken in the short term, but managing soil carbon needs a long- term approach. Key barriers to uptake of practices include: perceived scientifi c uncertainty about the effi cacy of practices; lack of real life ?best practice? examples to show farmers; diffi culty in demonstrating the positive effects of soil carbon management practices and economic benefi ts over a long time scale; and advisors being unable to provide suitable advice due to inadequate information or training. Most farmers are unconvinced of the economic benefi ts of practices for managing soil carbon. Incentives are therefore needed, either as subsidies or as evidence of the cost effectiveness of practices. All new measures and advice should be integrated into existing programmes to avoid a fragmented policy approach.

Comparison of the particulate organic carbon and permanganate oxidation methods for estimating labile soil organic carbon

Forty-four soils from under native vegetation and a range of management practices following clearing were analysed for ‘labile’ organic carbon (OC) using both the particulate organic carbon (POC) and the 333 mm KmnO4 (MnoxC) methods. Although there was some correlation between the 2 methods, the POC method was more sensitive by about a factor of 2 to rapid loss in OC as a result of management or land-use change. Unlike the POC method, the MnoxC method was insensitive to rapid gains in TOC following establishment of pasture on degraded soil. The MnoxC method was shown to be particularly sensitive to the presence of lignin or lignin-like compounds and therefore is likely to be very sensitive to the nature of the vegetation present at or near the time of sampling and explains the insensitivity of this method to OC gain under pasture. The presence of charcoal is an issue with both techniques, but whereas the charcoal contribution to the POC fraction can be assessed, the MnoxC method cannot distinguish between charcoal and most biomolecules found in soil. Because of these limitations, the MnoxC method should not be applied indiscriminately across different soil types and management practices.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.

Increase in soil organic carbon by agricultural intensification in northern China

Acknowledgements. This research was supported by National Natural Science Foundation of China (no. 31370527 and 31261140367) and the National Science and Technology Support Program of China (no. 2012BAD14B01-2). The authors gratefully thank the Huantai Agricultural Station for providing of the Soil Fertility Survey data. We also thank Zheng Liang from China Agricultural University for the soil sampling and analysis in 2011. Thanks are extended to Jessica Bellarby for helpful discussion and suggestions.

Is land condition a useful indicator of soil organic carbon stock in Australia?

The grazing lands of northern Australia contain a substantial soil organic carbon (SOC) stock due to the large land area. Manipulating SOC stocks through grazing management has been presented as an option to offset national greenhouse gas emissions from agriculture and other industries. However, research into the response of SOC stocks to a range of management activities has variously shown positive, negative or negligible change. This uncertainty in predicting change in SOC stocks represents high project risk for government and industry in relation to SOC sequestration programs. In this paper, we seek to address the uncertainty in SOC stock prediction by assessing relationships between SOC stocks and grazing land condition indicators. We reviewed the literature to identify land condition indicators for analysis and tested relationships between identified land condition indicators and SOC stock using data from a paired-site sampling experiment (10 sites). We subsequently collated SOC stock datasets at two scales (quadrat and paddock) from across northern Australia (329 sites) to compare with the findings of the paired-site sampling experiment with the aim of identifying the land condition indicators that had the strongest relationship with SOC stock. The land condition indicators most closely correlated with SOC stocks across datasets and analysis scales were tree basal area, tree canopy cover, ground cover, pasture biomass and the density of perennial grass tussocks. In combination with soil type, these indicators accounted for up to 42% of the variation in the residuals after climate effects were removed. However, we found that responses often interacted with soil type, adding complexity and increasing the uncertainty associated with predicting SOC stock change at any particular location. We recommend that caution be exercised when considering SOC offset projects in northern Australian grazing lands due to the risk of incorrectly predicting changes in SOC stocks with change in land condition indicators and management activities for a particular paddock or property. Despite the uncertainty for generating SOC sequestration income, undertaking management activities to improve land condition is likely to have desirable complementary benefits such as improving productivity and profitability as well as reducing adverse environmental impact.

Changes in soil organic carbon storage under different agricultural management systems in the Southwest Amazon Region of Brazil

The Cerrado and Amazon regions of Brazil are probably the largest agricultural frontier of the world, and Could be a sink or source for C depending on the net effect of land use change and subsequent management on soil organic C pools. We evaluated the effects of agricultural management systems on soil organic C (SOC) stocks in the Brazilian states of Rondonia and Mato Grosso, and derived regional specific factors for soil C stock change associated with different management systems. We used 50 observations (data points) in this study, including 42 dealing with annual cropping practices and 8 dealing with perennial cropping, and analyzed the data in linear mixed-effect models. No tillage (NT) systems in Cerrado areas increased SOC Storage by 1.08 +/- 0.06 relative to SOC stocks under native conditions, while SOC storage increased by a modest factor of 1.01 +/- 0.17 in Cerradao and Amazon Forest conditions. Full tillage (FT) had negative effect on SOC storage relative to NT, decreasing SOC stocks by a factor of 0.94 +/- 0.04. but did not significantly reduce SOC stocks relative to native levels when adopted in the Cerrado region. Perennial cropping had a minimal impact on SOC stocks, estimated at a factor Value of 0.98 +/- 0.14, suggesting these systems maintain about 98% of the SOC stock found under native vegetation. The results Suggest that NT adoption may be increasing SOC with land use change from native vegetation to cropland management in the Cerrado region of Brazil. (C) 2009 Elsevier B.V. All rights reserved.

Soil organic carbon and fertility interactions affected by a tillage chronosequence in a Brazilian Oxisol

No-till (NT) adoption is an essential tool for development of sustainable agricultural systems, and how NT affects the soil organic C (SOC) dynamics is a key component of these systems. The effect of a plow tillage (PT) and NT age chronosequence on SOC concentration and interactions with soil fertility were assessed in a variable charge Oxisol, located in the South Center quadrant of Parana State, Brazil (50 degrees 23`W and 24 degrees 36`S). The chronosequence consisted of the following six sites: (i) native field (NF); (ii) PT of the native field (PNF-1) involving conversion of natural vegetation to cropland; (iii) NT for 10 years (NT-10); (iv) NT for 20 years (NT-20); (v) NT for 22 years (NT-22); and (vi) conventional tillage for 22 years (CT-22) involving PT with one disking after summer harvest and one after winter harvest to 20 cm depth plus two harrow disking. Soil samples were collected from five depths (0-2.5; 2.5-5; 5-10; 10-20; and 20-40 cm) and SOC, pH (in H(2)O and KCl), Delta pH, potential acidity, exchangeable bases, and cation exchangeable capacity (CEC) were measured. An increase in SOC concentration positively affected the pH, the negative charge and the CEC and negatively impacted potential acidity. Regression analyses indicated a close relationship between the SOC concentration and other parameters measured in this study. The regression fitted between SOC concentration and CEC showed a close relationship. There was an increase in negative charge and CEC with increase in SOC concentration: CEC increased by 0.37 cmol(c) kg(-1) for every g of C kg(-1) soil. The ratio of ECEC:SOC was 0.23 cmol(c) kg(-1) for NF and increased to 0.49 cmol(c) kg(-1) for NT-22. The rates of P and K for 0-10 cm depth increased by 9.66 kg ha(-1) yr(-1) and 17.93 kg ha(-1) yr(-1), respectively, with NF as a base line. The data presented support the conclusion that long-term NT is a useful strategy for improving fertility of soils with variable charge. (C) 2008 Elsevier B.V. All rights reserved.

Soil Organic Carbon Stocks of Rio Grande do Sul, Brazil

Robust and accurate regional estimates of C storage in soils are currently an important research topic because of ongoing debate about human-induced changes in the terrestrial C cycle. Widely available geoprocessing tools were applied to estimate native soil organic C (SOC) stocks of Rio Grande do Sul state in southern Brazil to a depth of 30 cm from previously sampled soil pedons under undisturbed vegetation. The study used a statewide comprehensive soil survey comprising a small-scale soil map, a climate map, and a soil pedon database. Soil organic C stocks under native vegetation were calculated with two different approaches: the Tier 1 method of the Intergovernmental Panel on Climate Change (IPCC) and a refined method based on actual field measurements derived from soil profile data. Highest SOC stocks occurred in Neossolos Quartzarenico hidromorfico (Aquents), Organossolos Tiomorficos (Hemists), Latossolos Brunos (Udox), and Vertissolos Ebanicos (Uderts) soil classes. Before human use of soils, most C was stored in the Latossolos Vermelhos (Udox) and Neossolos Regoliticos (Orthents), which occupy a large area of Rio Grande do Sul. Generally, IPCC default reference SOC stocks compared well with SOC stocks calculated from soil pedons. The total SOC stock of Rio Grande do Sul was estimated at 1510.3 Tg C (5.8 kg C m(-2)) by the IPPC method and 1597.5 +/- 363.9 Tg C (7.4 +/- 1.9 kg C m(-2)) calculated from soil pedons. The SOC digital map and SOC database developed in this study provide crucial background information for state-level contemporary assessment of C stocks and soil C sequestration programs and initiatives.