Soil aggregate fraction-based 14C analysis and its application in the study of soil organic carbon turnover under forests of different ages

Tan, Wenbing; Zhou, Liping; Liu, Kexin

doi:10.1007/s11434-012-5660-7

Cited by 28 publications

(18 citation statements)

References 106 publications

(113 reference statements)

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“…The TT of RecalcitF ranged from hundreds to thousands of years (Table ). These results are consistent with previous observations (Kleber, Mikutta, Torn, & Jahn, ; Tan et al, ). LightF consists of root exudates, fresh plant litter, and residues of microbial cells.…”

Section: Discussionsupporting

confidence: 94%

“…TT will be underestimated or overestimated using this method, because each isolated fraction still remains a mixture of multiple functional pools with various turnover rates (Torn et al, ). Therefore, a combination of comprehensive fractionation methods, which separate the functional pools with specific protection mechanisms, should be applied in studying SOC turnover (Marzaioli et al, ; Tan, Zhou, & Liu, ).…”

Section: Introductionmentioning

confidence: 99%

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Temperature sensitivity of decomposition of soil organic matter fractions increases with their turnover time

et al. 2020

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Soil organic carbon (SOC) is an indicator of soil fertility. Global warming accelerates SOC decomposition, consequently, resulting in land degradation. Characterization of the response of SOC decomposition to temperature is important for predicting land development. A simulation model based on temperature sensitivity (Q10) of SOC decomposition has been used to predict SOC response to climate warming. However, uncertain Q10 leads to substantial uncertainties in the predictions. A major uncertainty comes from the interference of rainfall. To minimize this interference, we sampled surface (0–5 cm) soils along an isohyet across a temperature gradient in the Qinghai–Tibetan Plateau. The Q10 of bulk soil and the four soil fractions, such as light fraction (LightF), particulate organic matter (POM), hydrolyzable fraction (HydrolysF), and recalcitrant fraction (RecalcitF), were studied by 14C dating. Turnover time follows the order: LightF < POM < bulk soil < HydrolysF < RecalcitF. The Q10 follows the order: LightF (1.0) = POM (1.0) < HydrolysF (3.63) < bulk soil (5.93) < RecalcitF (7.46). This indicates that stable fractions are much more sensitive to temperature than labile fractions. We also suggest that protection mechanisms rather than molecular composition regulate SOC turnover. A new concept 'protection sensitivity' of SOC decomposition was proposed. Protection sensitivity relates to protection type and primarily controls Q10 variation. A simulation model based on the Q10 of individual fractions predicted SOC change and land development in the Qinghai–Tibetan Plateau in the next 100 years much effectively as compared to simulations based on one‐pool model (Q10 = 2) or bulk soil (Q10 = 5.93).

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Section: Discussionsupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Temperature sensitivity of decomposition of soil organic matter fractions increases with their turnover time

et al. 2020

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“…Variation in C turnover times results from different SOC protection mechanisms associated with soil particles as well as inconsistent methods used to estimate C turnover times (Bird et al, 2002;Tan et al, 2013;Yonekura et al, 2013;Beniston et al, 2014). Physically fractionated soil particles are often obtained according to soil aggregate size or soil texture.…”

Section: Introductionmentioning

confidence: 99%

Methodological uncertainty in estimating carbon turnover times of soil fractions

Feng

Shi

Jiang

et al. 2016

Soil Biology and Biochemistry

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C 14 C Incubation Fraction a b s t r a c t Improving predictions of soil organic carbon (SOC) dynamics by multi-compartment models requires validation of turnover times of different SOC pools. Techniques such as laboratory incubation and isotope analysis have been adopted to estimate C turnover times, yet no studies have systematically compared these techniques and assessed the uncertainties associated with them. Here, we tested whether C turnover times of soil fractions were biased by methodology, and how this changed across soil particle sizes and ecosystems. We identified 52 studies that quantified C turnover times in different soil particles fractionated either according to aggregate size (e.g., macro-versus micro-aggregates) or according to soil texture (e.g., sand versus silt versus clay). C turnover times of these soil fractions were estimated by one of three methods: laboratory incubation (16 studies), d 13 C shift due to C 3 eC 4 vegetation change (25 studies), and 14 C dating (19 studies). All methods showed that C turnover times of soil fractions generally increase with decreasing soil particle size. However, estimates of C turnover times within soil fractions differed significantly among methods, with incubation estimating the shortest turnover times and 14 C the longest. The short C turnover times estimated by incubation are likely due to optimal environmental conditions for microbial decomposition existing in these studies, which is often a poor representation of field conditions. The 13 C method can only be used when documenting a successive C 3 versus C 4 vegetation shift. C turnover times estimated by 14 C were systematically higher than those estimated by 13 C, especially for fine soil fractions (i.e., silt and clay). Overall, our findings highlight methodological uncertainties in estimating C turnover times of soil fractions, and correction factors should be explored to account for methodological bias when C turnover times estimated from different methods are used to parameterize soil C models.

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“…To establish an empirical relationship that can yield an unbiased estimator of the SOC turnover time over a wide range of mean annual air temperatures, a data set that covers a large climate gradient is needed. We conducted a meta‐analysis by incorporating our result with 50 14 C‐based studies from the Tibetan Plateau and elsewhere that covers a variety of vegetation types such as Arctic tundra [ Frank et al , ; Hicks Pries et al , ], alpine meadow [ Wang et al , ; Tao et al , ; Leifeld and Fuhrer , ; Budge et al , ; Tan et al , ], boreal forests [ Frank et al , ; Tan et al , ], temperate grasslands [ Trumbore et al , ; Frank et al , ], temperate forests [ Trumbore et al , ; Gaudinski et al , ; Wang et al , ; Koarashi et al , ; Frank et al , ], and subtropical‐tropical forests [ Townsend et al , ; Ding et al , ; Frank et al , ]. Clearly, the inventory‐weighted mean turnover time of the mineral SOC in the active carbon pool of the alpine ecosystem is negatively correlated with mean annual air temperature (Figure ).…”

Section: Discussionmentioning

confidence: 99%

Depth heterogeneity of soil organic carbon dynamics in a heavily grazed alpine meadow on the northeastern Tibetan Plateau: A radiocarbon-based approach

Cheng

et al. 2017

J. Geophys. Res. Biogeosci.

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A deep understanding of soil organic carbon (SOC) dynamics on the Tibetan Plateau is crucial for predicting the response of the alpine carbon pool to future climate changes. Here we present information about SOC stocks and turnover time in a heavily grazed alpine meadow on the Tibetan Plateau based on radiocarbon (14C) measurements and inverse modeling. Our results reveal that the alpine meadow soil is composed of three distinct carbon pools. The topsoil represents the active carbon pool, which has a carbon inventory‐weighted mean turnover time of 64 years. The CO2 efflux due to the mineral soil respiration from this pool is approximately 48.45 g C m−2 yr−1, accounting for 91% of the total heterotrophic soil respiration. The intermediate carbon pool has an inventory‐weighted mean turnover time of 780 years, and the rate of mineral soil respiration in this pool is an order of magnitude lower than that in the active carbon pool. The parental materials feature the passive carbon pool, which has millennia‐long turnover time and the mineral soil respiration is trivial. Comparing our results with other 14C‐based studies suggests that grazing intensity may alter not only the SOC stocks but also the soil respiration rate in the alpine grassland ecosystem. The heavily grazed alpine meadow broadly fits the exponential relationship between turnover time and mean annual air temperature identified by meta‐analysis of published data from the Tibetan Plateau, alpine grassland, and forest sites elsewhere.

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Soil aggregate fraction-based 14C analysis and its application in the study of soil organic carbon turnover under forests of different ages

Cited by 28 publications

References 106 publications

Temperature sensitivity of decomposition of soil organic matter fractions increases with their turnover time

Temperature sensitivity of decomposition of soil organic matter fractions increases with their turnover time

Methodological uncertainty in estimating carbon turnover times of soil fractions

Depth heterogeneity of soil organic carbon dynamics in a heavily grazed alpine meadow on the northeastern Tibetan Plateau: A radiocarbon-based approach

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