The effect of climatic and edaphic factors on soil organic carbon turnover in hummocks based on δ13C on the Qinghai-Tibet Plateau

Li, Hanzhi; Yan, Feng; Tuo, Dengfeng; Yao, Bin; Chen, Junhan

doi:10.1016/j.scitotenv.2020.140141

Cited by 10 publications

(8 citation statements)

References 78 publications

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“…Microbes tend to use lighter 12 C during the decomposition and 13 C component accumulates. Therefore, the combined effects of lower stomatal conductance and lower enzyme activity resulted in a negative correlation between topsoil δ 13 C and temperature (Li et al, 2020;Zhang et al, 2020), and higher topsoil δ 13 C in north and northwest TP (Fig. 4).…”

Section: Spatial Variations Of the Data-driven δ 13 C Across The Tpmentioning

confidence: 99%

“…It is generally accepted that because of the lack of water, vegetation will close stomata to reduce transpiration, leading to an increase in δ 13 C (Farquhar et al, 1989). In the last several decades, the TP suffered from a significant increase in MAT and MAP, which may increase the species, microbial quantities and activities (Papatheodorou et al, 2004), accelerating the decomposition rate of 12 C, enriching soil δ 13 C (Li et al, 2020). In the north TP, precipitation was much lower than in the south TP (Fig.…”

Section: Spatial Variations Of the Data-driven δ 13 C Across The Tpmentioning

confidence: 99%

“…Carbon isotopes (δ 13 C) in soil organics provide reliable insights at the long-term scale into studying soil carbon turnover (Acton et al, 2013;Blagodatskaya et al, 2011;Khan et al, 2008;Li et al, 2020). Because the majority of soil organic matter originates from plant residues, soil δ 13 C can well reflect vegetation-related soil formation and dynamics (Ehleringer et al, 2000).…”

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confidence: 99%

“…However, modelling the spatial patterns of δ 13 C using field observations has not been observed. A better understanding of the spatial variability of soil δ 13 C and its controlling factors at the regional scale is important to understand soil carbon dynamics and potential feedbacks to climate change (Li et al, 2020;Rao et al, 2017;Zhao et al, 2019).…”

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confidence: 99%

“…Site-level studies found that the decomposition rate of SOC accelerates with temperature increase, resulting in the release of stored carbon from the soil into the atmosphere (Chang et al, 2012;Dong et al, 2018;Li et al, 2020). However, regional estimates of the sensitivity of SOC decomposition in the TP are still missing.…”

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confidence: 99%

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A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau

Lai

Shi

et al. 2021

Preprint

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Abstract. Soil carbon isotopes (δ13C) provide reliable insights at a long-term scale for studying soil carbon turnover. The Tibetan Plateau (TP), called “the third pole of the earth” is one of the most sensitive areas to global climate change and exhibits an early warning signal of global warming. Although many studies detected the variability of soil δ13C at site scales, a knowledge gap still exists in the spatial pattern of topsoil δ13C across the TP. To fill the substantial knowledge gap, we first compiled a database of topsoil δ13C with 396 observations from published literatures. Then we applied a Random Forest (RF) algorithm – a machine learning approach, to predict the spatial pattern of topsoil δ13C and β (indicating the decomposition rate of soil organic carbon (SOC), calculated by δ13C divided by logarithmically converted SOC). Finally, two datasets – topsoil δ13C and β with a fine spatial resolution of 1 km across the TP were developed. Results showed that topsoil δ13C varied significantly among different ecosystem types (p < 0.001). Topsoil δ13C was −26.3 ± 1.60 ‰ (mean ± standard deviation) for forests, 24.3 ± 2.00 ‰ for shrublands, −23.9 ± 1.84 ‰ for grasslands, −18.9 ± 2.37 ‰ for deserts, respectively. RF could well predict the spatial variability of topsoil δ13C with a model efficiency of 0.62 and root mean square error of 1.12 ‰, enabling to derive data-driven δ13C and β products. Data-driven topsoil δ13C varied from −28.26 ‰ to −16.95 ‰, with the highest topsoil δ13C in the north and northwest TP and the lowest δ13C in Southeast or South TP, indicating strong spatial variabilities in topsoil δ13C. Similarly, there were strong spatial variabilities in data-driven β, with the lowest β values at the east and middle TP, indicating a higher SOC turnover in the east and middle TP compared that of other regions in the TP. This study was the first attempt to develop a fine resolution product of topsoil δ13C and β across the TP, which could provide an independent data-driven benchmark for biogeochemical cycling models to study SOC turnover and terrestrial carbon-climate feedbacks over the TP under climate change. The data-driven δ13C and β datasets are public available at https://doi.org/10.6084/m9.figshare.16641292.v2 (Tang, 2021).

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Section: Spatial Variations Of the Data-driven δ 13 C Across The Tpmentioning

confidence: 99%

Section: Spatial Variations Of the Data-driven δ 13 C Across The Tpmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau

Lai

Shi

et al. 2021

Preprint

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Response of soil organic carbon to land-use change after farmland abandonment in the karst desertification control

Mu,

Ye,

Xiong

et al. 2024

Plant Soil

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Soil organic carbon stability of vegetation restoration during 11-year-old grassland succession

et al. 2023

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The effect of climatic and edaphic factors on soil organic carbon turnover in hummocks based on δ13C on the Qinghai-Tibet Plateau

Cited by 10 publications

References 78 publications

A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau

A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau

Response of soil organic carbon to land-use change after farmland abandonment in the karst desertification control

Soil organic carbon stability of vegetation restoration during 11-year-old grassland succession

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The effect of climatic and edaphic factors on soil organic carbon turnover in hummocks based on δ13C on the Qinghai-Tibet Plateau

Cited by 10 publications

References 78 publications

A data-driven topsoil δ&lt;sup&gt;13&lt;/sup&gt;C dataset and the drivers of spatial variability across the Tibetan Plateau

A data-driven topsoil δ&lt;sup&gt;13&lt;/sup&gt;C dataset and the drivers of spatial variability across the Tibetan Plateau

Response of soil organic carbon to land-use change after farmland abandonment in the karst desertification control

Soil organic carbon stability of vegetation restoration during 11-year-old grassland succession

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A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau

A data-driven topsoil δ<sup>13</sup>C dataset and the drivers of spatial variability across the Tibetan Plateau