Spatial heterogeneity of subsoil organic carbon turnover times in forest ecosystems across China

2021 ◽  
Author(s):  
Peng Yu ◽  
Xiaolu Tang ◽  
Yuehong Shi ◽  
Chunju Cai ◽  
Yuxuan Han ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Heterogeneity ◽  
Soil Carbon ◽  
Forest Ecosystems ◽  
Carbon Turnover ◽  
Soil Environment ◽  
Forest Types ◽  
Broadleaf Forest ◽  
Biogeochemical Models

<p>Soil organic carbon turnover time (τ, year) is an important indicator of soil carbon stability and sequestration capacity. However, our understanding of the spatial heterogeneity of subsoil τ still was poorly qualified over a large scale, even though subsoil organic carbon below 0.2 m accounts for the majority of total soil organic carbon. We compiled a dataset that consisted of 630 observations in subsoil (0.2 - 1 m) from published literatures to investigate the spatial heterogeneity of subsoil τ (defined as the ratio of soil carbon stock and net primary production) and explore its main environmental drivers using structural equation modelling (SEM) in forest ecosystems across China.<strong> </strong>Results indicated that mean (± standard deviation) subsoil τ was 72.4 ± 68.6 years with a large variability ranging from 2.3 to 896.2 years. Subsoil τ varied significantly with forest types that mean subsoil τ was the longest in deciduous broadleaf forest (82.9 ± 68.7 years), followed by evergreen needleleaf forest (77.6 ± 60.8 years), deciduous needleleaf forest (75.3 ± 78.6 years) and needleleaf and broadleaf mixed forest (71.3 ± 80.9 years), while the shortest τ in evergreen broadleaf forest (59.9 ± 40.7 years). SEM suggested that soil environment was the most important factor in predicting subsoil τ. However, the dominant driver differed with forest types, i.e. soil environment for evergreen broadleaf forest and climate for evergreen needleleaf forest. This study highlights the different dominant controlling factors in subsoil τ and improve our understanding of biogeographic variations of subsoil τ. These findings are essential to better understand (and reduce uncertainty) in biogeochemical models of subsoil carbon dynamics at regional scales.</p>

Subsoil organic carbon turnover is dominantly controlled by soil properties in grasslands across China

2021 ◽  
Author(s):  
Yuehong Shi ◽  
Xiaolu Tang ◽  
Peng Yu ◽  
Li Xu ◽  
Guo Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Soil Properties ◽  
Soil Carbon ◽  
Carbon Turnover ◽  
Area Index ◽  
Important Indicator ◽  
Environmental Controls ◽  
Biogeochemical Models ◽  
Soc Stock

<p>Soil carbon turnover time (τ, year) is an important indicator of soil carbon stability, and a major factor in determining soil carbon sequestration capacity. Many studies investigated τ in the topsoil or the first meter underground, however, little is known about subsoil τ (0.2 – 1.0 m) and its environmental drivers, while world subsoils below 0.2 m accounts for the majority of total soil organic carbon (SOC) stock and may be as sensitive as that of the topsoil to climate change. We used the observations from the published literatures to estimate subsoil τ (the ratio of SOC stock to net primary productivity) in grasslands across China and employed regression analysis to detect the environmental controls on subsoil τ. Finally, structural equation modelling (SEM) was applied to identify the dominant environmental driver (including climate, vegetation and soil). Results showed that subsoil τ varied greatly from 5.52 to 702.17 years, and the mean (± standard deviation) subsoil τ was 118.5 ± 97.8 years. Subsoil τ varied significantly among different grassland types that it was 164.0 ± 112.0 years for alpine meadow, 107.0 ± 47.9 years for alpine steppe, 177.0 ± 143.0 years for temperate desert steppe, 96.6 ± 88.7 years for temperate meadow steppe, 101.0 ± 75.9 years for temperate typical steppe. Subsoil τ significantly and negatively correlated (p < 0.05) with vegetation index, leaf area index and gross primary production, highlighting the importance of vegetation on τ. Mean annual temperature (MAT) and precipitation (MAP) had a negative impact on subsoil τ, indicating a faster turnover of soil carbon with the increasing of MAT or MAP under ongoing climate change. SEM showed that soil properties, such as soil bulk density, cation exchange capacity and soil silt, were the most important variables driving subsoil τ, challenging our current understanding of climatic drivers (MAT and MAP) controlling on topsoil τ, further providing new evidence that different mechanisms control topsoil and subsoil τ. These conclusions demonstrated that different environmental controls should be considered for reliable prediction of soil carbon dynamics in the top and subsoils in biogeochemical models or earth system models at regional or global scales.</p>

Does soil disturbance result in soil carbon losses? – A case study on bioturbation effects of wild boar

2020 ◽  
Author(s):  
Axel Don ◽  
Christina Hagen ◽  
Erik Grüneberg ◽  
Cora Vos
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Wild Boar ◽  
Forest Floor ◽  
Mineral Soil ◽  
Soil Disturbance ◽  
Carbon Stocks ◽  
No Tillage ◽  
Carbon Turnover

<p>Soil disturbance and disruption is assumed to enhance mineralisation and cause losses of soil organic carbon. Therefore, no tillage is promoted as soil carbon sequestration measure. However, the experimental evidence of enhanced carbon turnover due to soil disturbance is rare.  We investigated soil disturbance in forest ecosystems with simulated bioturbation of wild boar. Wild boar are effective at mixing and grubbing in the soil and wild boar populations are increasing dramatically in many parts of the world. In a six-year field study, we investigated the effect of wild boar bioturbation on the stocks and stability of soil organic carbon in two forest areas at 23 plots. The organic layer and mineral soil down to 15 cm depth were sampled in the disturbed plots and adjacent undisturbed reference plots.</p><p>No significant changes in soil organic carbon stocks were detected in the bioturbation plots compared with non-disturbed reference plots. However, around 50% of forest floor carbon was transferred with bioturbation to mineral soil carbon and the stock of stabilised mineral-associated carbon increased by 28%. Thus, a large proportion of the labile carbon in the forest floor was transformed into more stable carbon. Carbon saturation of mineral surfaces was not detected, but carbon loading per unit mineral surface increased by on average 66% due to bioturbation. This indicates that mineral forest soils have non-used capacity to stabilise and store more carbon.</p><p>Our results indicate that soil disturbance and bioturbation alone does not affect soil carbon turnover and stocks, but only change the distribution of carbon in the soil profile. This is in line with results from no-tillage experiments. The prevailing effect is a redistribution of carbon in the soil profile with no changes in total soil carbon stocks. We discuss these findings in the light of soils as potential sinks for carbon.</p><p> </p>

Plant carbon inputs through shoot, root, and mycorrhizal pathways affect soil organic carbon turnover differently

2021 ◽  
pp. 108322
Author(s):  
Junsheng Huang ◽  
Weixing Liu ◽  
Sen Yang ◽  
Lu Yang ◽  
Ziyang Peng ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Turnover

scholarly journals Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks

2021 ◽  
Vol 7 (9) ◽  
pp. eaaz5236 ◽  
Author(s):  
Umakant Mishra ◽  
Gustaf Hugelius ◽  
Eitan Shelef ◽  
Yuanhe Yang ◽  
Jens Strauss ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Heterogeneity ◽  
Surface Air Temperature ◽  
Spatially Explicit ◽  
Soil Profiles ◽  
Permafrost Region ◽  
Environmental Predictors ◽  
Soil Organic Carbon Stocks ◽  
Soc Stocks

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

scholarly journals Effects of Urban Forest Types and Traits on Soil Organic Carbon Stock in Beijing

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 394
Author(s):  
Xinhui Xu ◽  
Zhenkai Sun ◽  
Zezhou Hao ◽  
Qi Bian ◽  
Kaiyue Wei ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Stock ◽  
Urban Forest ◽  
Coniferous Forest ◽  
Predictor Variable ◽  
Urban Forests ◽  
Least Squares Regression ◽  
Forest Types ◽  
Organic Carbon Stock

Forests can affect soil organic carbon (SOC) quality and distribution through forest types and traits. However, much less is known about the influence of urban forests on SOC, especially in the effects of different forest types, such as coniferous and broadleaved forests. Our objectives were to assess the effects of urban forest types on the variability of SOC content (SOC concentration (SOCC) and SOC density (SOCD)) and determine the key forest traits influencing SOC. Data from 168 urban forest plots of coniferous or broadleaved forests located in the Beijing urban area were used to predict the effects of forest types and traits on SOC in three different soil layers, 0–10 cm, 10–20 cm, and 20–30 cm. The analysis of variance and multiple comparisons were used to test the differences in SOC between forest types or layers. Partial least squares regression (PLSR) was used to explain the influence of forest traits on SOC and select the significant predictors. Our results showed that in urban forests, the SOCC and SOCD values of the coniferous forest group were both significantly higher than those of the broadleaved group. The SOCC of the surface soil was significantly higher than those of the following two deep layers. In PLSR models, 42.07% of the SOCC variance and 35.83% of the SOCD variance were explained by forest traits. Diameter at breast height was selected as the best predictor variable by comparing variable importance in projection (VIP) scores in the models. The results suggest that forest types and traits could be used as an optional approach to assess the organic carbon stock in urban forest soils. This study found substantial effects of urban forest types and traits on soil organic carbon sequestration, which provides important data support for urban forest planning and management.

scholarly journals Can Agricultural Management Induced Changes in Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?

2021 ◽  
Vol 13 (12) ◽  
pp. 2265
Author(s):  
Jonathan Sanderman ◽  
Kathleen Savage ◽  
Shree Dangal ◽  
Gabriel Duran ◽  
Charlotte Rivard ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Diffuse Reflectance Spectroscopy ◽  
Low Cost ◽  
Soil Survey ◽  
Mid Infrared ◽  
Mir Spectroscopy ◽  
Induced Changes ◽  
Carbon Change

A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg Soil Survey Laboratory MIR spectral library. Overall, MIR-based estimates of SOC%, with samples scanned on a secondary instrument, were excellent with the root mean square error ranging from 0.10 to 0.33% across the seven sites. In all but two instances, the same statistically significant (p < 0.10) management effect was found using both the lab-based SOC% and MIR estimated SOC% data. Despite some additional uncertainty, primarily in the form of bias, these results suggest that large existing MIR spectral libraries can be operationalized in other laboratories for successful carbon monitoring.

Is soil carbon disappearing? The dynamics of soil organic carbon in Java

2010 ◽  
Vol 17 (5) ◽  
pp. 1917-1924 ◽  
Author(s):  
BUDIMAN MINASNY ◽  
YIYI SULAEMAN ◽  
ALEX B. MCBRATNEY
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon

scholarly journals The use of radiocarbon <sup>14</sup>C to constrain carbon dynamics in the soil module of the land surface model ORCHIDEE (SVN r5165)

2018 ◽  
Author(s):  
Marwa Tifafi ◽  
Marta Camino-Serrano ◽  
Christine Hatté ◽  
Hector Morras ◽  
Lucas Moretti ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Soil Carbon ◽  
Land Surface ◽  
Carbon Stock ◽  
Land Surface Model ◽  
Carbon Dynamics ◽  
Total Carbon ◽  
Soil Parameters ◽  
Surface Model

Abstract. Despite the importance of soil as a large component of the terrestrial ecosystems, the soil compartments are not well represented in the Land Surface Models (LSMs). Indeed, soils in current LSMs are generally represented based on a very simplified schema that can induce a misrepresentation of the deep dynamics of soil carbon. Here, we present a new version of the IPSL-Land Surface Model called ORCHIDEE-SOM, incorporating the 14C dynamic in the soil. ORCHIDEE-SOM, first, simulates soil carbon dynamics for different layers, down to 2 m depth. Second, concentration of dissolved organic carbon (DOC) and its transport are modeled. Finally, soil organic carbon (SOC) decomposition is considered taking into account the priming effect. After implementing the 14C in the soil module of the model, we evaluated model outputs against observations of soil organic carbon and 14C activity (F14C) for different sites with different characteristics. The model managed to reproduce the soil organic carbon stocks and the F14C along the vertical profiles. However, an overestimation of the total carbon stock was noted, but was mostly marked on the surface. Then, thanks to the introduction of 14C, it has been possible to highlight an underestimation of the age of carbon in the soil. Thereafter, two different tests on this new version have been established. The first was to increase carbon residence time of the passive pool and decrease the flux from the slow pool to the passive pool. The second was to establish an equation of diffusion, initially constant throughout the profile, making it vary exponentially as a function of depth. The first modifications did not improve the capacity of the model to reproduce observations whereas the second test showed a decrease of the soil carbon stock overestimation, especially at the surface and an improvement of the estimates of the carbon age. This assumes that we should focus more on vertical variation of soil parameters as a function of depth, mainly for diffusion, in order to upgrade the representation of global carbon cycle in LSMs, thereby helping to improve predictions of the future response of soil organic carbon to global warming.

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