Multi-level statistical soil profiles for assessing regional soil organic carbon stocks

Ottoy, Sam; Beckers, Véronique; Jacxsens, Paul; Hermy, Martin; Orshoven, Jos Van

doi:10.1016/j.geoderma.2015.04.001

Cited by 15 publications

(20 citation statements)

References 37 publications

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“…Legacy data are, in contrast to recent inventories, often characterized by more vertical detail. Therefore, historical soil profile descriptions provide a valuable source of information on the assumed invariant sequence of horizons and their historical SOC contents (Ottoy et al ., ), and so are essential for model calibration (Sleutel et al ., ; Mestdagh et al ., ). Legacy datasets are important sources of information, in particular for LUs with an anomalous distribution of SOC with depth.…”

Section: Discussionmentioning

confidence: 99%

“…In the second half of the 20th century, a large number of soil profiles were described and their horizons analysed on various key soil properties in the context of intensive soil sampling campaigns to produce soil maps in several countries and regions. Such legacy soil profile descriptions are a valuable resource for extending the information content of soil maps with quantitative data on historical SOC stocks (Ottoy et al, 2015). Moreover, these datasets also contain reference data about the dependence of the SOC content with depth and can be used to calibrate vertical extrapolation functions (Sleutel et al, 2003;Mestdagh et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…The SMUs are often generalized spatially to achieve complete cover of the vertical sequence of horizons, their thickness and SOC content (Lettens et al, 2004). In earlier research we were able to attach at least one historical profile to 18 731 of 18 809 land units (defined as a combination of SMU and land cover type) or 98.7% of the non-built-up area in Flanders, Belgium, based on a multi-level generalization approach from which we derived regional SOC stocks for the upper 100 cm (Ottoy et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An exponential change decline function to estimate soil organic carbon stocks and their changes from topsoil measurements

Ottoy

Elsen²,

Vreken

et al. 2016

European J Soil Science

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Soil organic carbon (SOC) stocks and their changes are important indicators in ecosystem service assessments. Routine soil inventories are often limited to the topsoil, even though a non‐negligible fraction of SOC is known to be stored in deeper horizons. To assess SOC stocks and their changes in the upper metre of the soil profile, vertical extrapolation of topsoil SOC measurements is necessary. The commonly used exponential decline function is not valid, however, for soil types in which subsurface horizons with a larger SOC content (‘anomalies’) occur. Here, we propose an exponential change decline function to account for these profile anomalies. Therefore, we applied the exponential decline function to the difference between the recent (2008–11) and historical (1947–74) SOC contents in the topsoil and compared the results with those derived by the original method. We applied the exponential change decline function to 54 041 agricultural land units (7159 km2) in Flanders (Belgium) and were able to model specific profile characteristics such as spodic horizons, plaggic topsoil and peat substrates. For these particular land units, the exponential decline function underestimated SOC stocks; therefore, it compromised an in‐depth assessment of changes in SOC stocks over time. This study shows that the exponential change decline function is promising for certain soil types and will contribute to the more accurate assessment of ecosystem service indicators. In addition, we emphasize the need for more detailed descriptions of subsoil reference profiles, sampled by pedogenetic horizon rather than by fixed depth interval to optimize calibration of the decline functions. Highlights When recent soil sampling is limited to the topsoil, extrapolation is needed to assess subsoil SOC stocks. We modified the exponential decline function to model SOC‐rich subsurface horizons with the integration of legacy data. An appropriate extrapolation approach is essential for in‐depth SOC assessments. Detailed subsoil data are needed to optimize the calibration of the decline functions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An exponential change decline function to estimate soil organic carbon stocks and their changes from topsoil measurements

Ottoy

Elsen²,

Vreken

et al. 2016

European J Soil Science

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“…As a case in point, Ottoy et al (2015), assess regional soil organic carbon stocks, related to climate mitigation. Their work reveals that even within this limited focus, some ambiguity is associated with the assessment, associated with a strong methoddependence in the spatial interpolation between map and profile data.…”

Section: Using Soil Maps and Pedotransfer Functionsmentioning

confidence: 99%

“…Their work reveals that even within this limited focus, some ambiguity is associated with the assessment, associated with a strong methoddependence in the spatial interpolation between map and profile data. Working in the same region and with the same original data set as two previous groups of researchers (Lettens et al, 2005;Meersmans et al, 2008) who used different upscaling techniques, Ottoy et al (2015) predicted a value for the total carbon stock down to a reference depth of 1 m that was 12% lower than the estimate based on the individual profile approach of Lettens et al (2005), and 10% lower than with the linear modeling approach of Meersmans et al (2008).…”

Section: Using Soil Maps and Pedotransfer Functionsmentioning

confidence: 99%

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Baveye

Gowdy

2016

Front. Environ. Sci.

305

168

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Understanding large‐extent controls of soil organic carbon storage in relation to soil depth and soil‐landscape systems

Mulder¹,

Lacoste

Martín³

et al. 2015

Global Biogeochemical Cycles

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In this work we aimed at developing a conceptual framework in which we improve our understanding of the controlling factors for soil organic carbon (SOC) over vast areas at different depths. We postulated that variability in SOC levels may be better explained by modeling SOC within soil-landscape systems (SLSs). The study was performed in mainland France, and explanatory SOC models were developed for the sampled topsoil (0-30 cm) and subsoil (>30 cm), using both directed and undirected data-mining techniques. With this study we demonstrated that there is a shift in controlling factors both in space and depth which were mainly related to (1) typical SLS characteristics and (2) human-induced changes to SLSs. The controlling factors in relation to depth alter from predominantly biotic to more abiotic with increasing depth. Especially, water availability, soil texture, and physical protection control deeper stored SOC. In SLSs with similar SOC levels, different combinations of physical protection, the input of organic matter, and climatic conditions largely determined the SOC level. The SLS approach provided the means to partition the data into data sets that were having homogenous conditions with respect to this combination of controlling factors. This information may provide important information on the carbon storage and sequestration potential of a soil.

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Multi-level statistical soil profiles for assessing regional soil organic carbon stocks

Cited by 15 publications

References 37 publications

An exponential change decline function to estimate soil organic carbon stocks and their changes from topsoil measurements

An exponential change decline function to estimate soil organic carbon stocks and their changes from topsoil measurements

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Understanding large‐extent controls of soil organic carbon storage in relation to soil depth and soil‐landscape systems

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