The role of clay content and mineral surface area for soil organic carbon storage in an arable toposequence

Schweizer, Steffen A.; Mueller, Carsten W.; Höschen, Carmen; Иванов, П. В.; Kögel‐Knabner, Ingrid

doi:10.1007/s10533-021-00850-3

Cited by 76 publications

(68 citation statements)

References 104 publications

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“…In contrast, areas with sandy soil texture had a low SOC content. High surface area of clay soils provide more surfaces to bind SOC, and aggregation preserves organic matter from decomposition [ 77 ].…”

Section: Resultsmentioning

confidence: 99%

Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and mapping of soil organic carbon

Kılıç

Gündoğan²,

Günal³

et al. 2022

PLoS ONE

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This study aimed to produce a soil organic carbon (SOC) content map with high accuracy and spatial resolution using the most effective factors in the model. The spatial SOC estimation success of Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Empirical Bayesian Kriging (EBK), Multi-Layered Perception Network (MLP) and MLP-OK Hybrid models were compared to obtain the most reliable model in estimating the SOC content. The study area was located in Besni district in the Southeastern Anatolia Region of Turkey. Total of 132 surface (0–30 cm) soil samples were collected from the covers 1330 km2 land and analyzed for SOC, lime, clay and sand content and soil reaction included in the estimation models. Mean annual precipitation and temperature, elevation, compound topographic index, enhanced vegetation and normalized difference vegetation index, were also used as the inputs in the modelling. The spatial distribution of SOC was determined using a MLP and a two-stage ensemble model (MLP-OK) combining the estimation of OK residuals. Soil surveys and covariates were used to train and validate the MLP-OK hybrid model. The MLP-OK model provided a more accurate estimation of SOC content with minimal estimation errors (ME: -0.028, 45 MAE: 0.042, RMSE: 0.066) for validation points compared to the other models. The MLP-OK model outperformed other models by 75.09 to 77.92%. The MLP-OK model estimated the lower and upper limits of the estimated and the measured values in a consistent manner compared to the other models. The spatial distribution map of SOC content obtained by ANN-kriging approach was significantly affected by ancillary variables, and revealed more detail than other interpolation methods in the northern, central, southwestern and southeastern parts of the study area. The results revealed that the assembling of MLP with OK model can contribute to obtain more reliable regional, national and global spatial soil information.

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Section: Resultsmentioning

confidence: 99%

Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and mapping of soil organic carbon

Kılıç

Gündoğan²,

Günal³

et al. 2022

PLoS ONE

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“…Fine mineral particles have a relatively larger specific surface area (SSA), which implies more potential surface interaction with other particles and also OM. Consequently, high clay soils are usually connected with enhanced OC storage and aggregate formation (Schweizer et al, 2021; Souza et al, 2017; Stewart et al, 2008). The distribution of OM has been shown to be heterogeneous at the microscale (Keiluweit et al, 2012; Schweizer et al, 2018; Vogel et al, 2014; Wilhelm et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Explicit spatial modeling at the pore scale unravels the interplay of soil organic carbon storage and structure dynamics

Zech

Schweizer

Bucka

et al. 2022

Global Change Biology

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The structure of soil aggregates plays an important role for the turnover of particulate organic matter (POM) and vice versa. Analytical approaches usually do not disentangle the continuous re-organization of soil aggregates, caught between disintegration and assemblage. This led to a lack of understanding of the mechanistic relationship between aggregation and organic matter dynamics in soils. In this study, we took advantage of a process-based mechanistic model that describes the interaction between the dynamic (re-)arrangement of soil aggregates, based on dynamic image analysis data of wet-sieved aggregates, to analyze the turnover of POM, and simultaneous soil surface interactions in a spatially and temporally explicit way. Our novel modeling approach enabled us to unravel the temporal development of aggregate sizes, organic carbon (OC) turnover of POM, and surface coverage as affected by soil texture, POM input, and POM decomposition rate comparing a low and high clay soil (18% and 33% clay content). Our results reveal the importance of the dynamic re-arrangement of soil structure on POM-related turnover of OC in soils. Firstly, aggregation was largely determined by the POM input fostering aggregates through additional gluing joints outweighing soil texture at lower decomposition rate, whereas at higher decomposition rate, soil texture had a higher influence leading to larger aggregates in the high clay soil.Secondly, the POM storage increased with clay content, showing that surface interactions may delay the turnover of OC into CO 2 . Thirdly, we observed a structural priming effect in which the increased input of POM induced increased structural re-arrangement stimulating the mineralization of old POM. This work highlights that the dynamic re-arrangement of soil aggregates has important implications for OC turnover and is driven by underlying surface interactions where temporary gluing spots stabilize larger aggregates.

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“…Additionally, we examined the specific surface area of mineral-associated organic matter. Before the analysis, we removed organic matter by hypochlorite oxidation (five times with 1 M NaClO) 82 . After that, these treated samples were first degassed with helium at 325 °C for 4 h 83 .…”

Section: Methodsmentioning

confidence: 99%

Divergent changes in particulate and mineral-associated organic carbon upon permafrost thaw

et al. 2022

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Permafrost thaw can stimulate microbial decomposition and induce soil carbon (C) loss, potentially triggering a positive C-climate feedback. However, earlier observations have concentrated on bulk soil C dynamics upon permafrost thaw, with limited evidence involving soil C fractions. Here, we explore how the functionally distinct fractions, including particulate and mineral-associated organic C (POC and MAOC) as well as iron-bound organic C (OC-Fe), respond to permafrost thaw using systematic measurements derived from one permafrost thaw sequence and five additional thermokarst-impacted sites on the Tibetan Plateau. We find that topsoil POC content substantially decreases, while MAOC content remains stable and OC-Fe accumulates due to the enriched Fe oxides after permafrost thaw. Moreover, the proportion of MAOC and OC-Fe increases along the thaw sequence and at most of the thermokarst-impacted sites. The relatively enriched stable soil C fractions would alleviate microbial decomposition and weaken its feedback to climate warming over long-term thermokarst development.

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The role of clay content and mineral surface area for soil organic carbon storage in an arable toposequence

Cited by 76 publications

References 104 publications

Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and mapping of soil organic carbon

Accuracy Assessment of Kriging, artificial neural network, and a hybrid approach integrating spatial and terrain data in estimating and mapping of soil organic carbon

Explicit spatial modeling at the pore scale unravels the interplay of soil organic carbon storage and structure dynamics

Divergent changes in particulate and mineral-associated organic carbon upon permafrost thaw

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