Temperature sensitivity of soil respiration and its effects on ecosystem carbon budget: nonlinearity begets surprises

Ye, Qi; Xu, Ming; Wu, Jianguo

doi:10.1016/s0304-3800(01)00506-3

Cited by 139 publications

(93 citation statements)

References 35 publications

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“…Many studies have attempted to regress R S against a wide range of biotic and abiotic variables, but the results vary tremendously across ecosystems and biomes (Del Grosso et al, 2005;Raich and Schlesinger, 1992;Reichstein et al, 2003). These correlations also raise the possibility of estimating R S , with an associated error range, from airborne and satellite observations; the lack of such large-scale, observation-driven R S estimates is a major problem in constraining regional-to global-scale C fluxes (Qi et al, 2002;Rayner et al, 2005;Jones et al, 2003).…”

Section: Observed Annual Fluxesmentioning

confidence: 99%

A global database of soil respiration data

2010

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Abstract. Soil respiration -R S , the flux of CO 2 from the soil to the atmosphere -is probably the least well constrained component of the terrestrial carbon cycle. Here we introduce the SRDB database, a near-universal compendium of published R S data, and make it available to the scientific community both as a traditional static archive and as a dynamic community database that may be updated over time by interested users. The database encompasses all published studies that report one of the following data measured in the field (not laboratory): annual R S , mean seasonal R S , a seasonal or annual partitioning of R S into its sources fluxes, R S temperature response (Q 10 ), or R S at 10 • C. Its orientation is thus to seasonal and annual fluxes, not shorter-term or chamberspecific measurements. To date, data from 818 studies have been entered into the database, constituting 3379 records. The data span the measurement years 1961-2007 and are dominated by temperate, well-drained forests. We briefly examine some aspects of the SRDB data -its climate space coverage, mean annual R S fluxes and their correlation with other carbon fluxes, R S variability, temperature sensitivities, and the partitioning of R S source flux -and suggest some potential lines of research that could be explored using these data. The SRDB database is available online in a permanent archive as well as via a project-hosting repository; the latter source leverages open-source software technologies to encourage wider participation in the database's future development. Ultimately, we hope that the updating of, and corrections to, the SRDB will become a shared project, managed by the users of these data in the scientific community.

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Section: Observed Annual Fluxesmentioning

confidence: 99%

A global database of soil respiration data

2010

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“…This has been confirmed by Schindlbacher et al (2010), who measured respiration in incubated soil samples and showed that the Lloyd-Taylor and Gaussian formulations had an increasing temperature sensitivity along elevation gradients in Spain and Austria. Nevertheless, in our study the Exponential formulation was included in the analysis because the usage of Q 10 values is common (Qi et al, 2002).…”

Section: Fit Of the Functionsmentioning

confidence: 99%

Temperature response functions introduce high uncertainty in modelled carbon stocks in cold temperature regimes

2010

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Abstract. Models of carbon cycling in terrestrial ecosystems contain formulations for the dependence of respiration on temperature, but the sensitivity of predicted carbon pools and fluxes to these formulations and their parameterization is not well understood. Thus, we performed an uncertainty analysis of soil organic matter decomposition with respect to its temperature dependency using the ecosystem model LPJ-GUESS.We used five temperature response functions (Exponential, Arrhenius, Lloyd-Taylor, Gaussian, Van't Hoff). We determined the parameter confidence ranges of the formulations by nonlinear regression analysis based on eight experimental datasets from Northern Hemisphere ecosystems. We sampled over the confidence ranges of the parameters and ran simulations for each pair of temperature response function and calibration site. We analyzed both the long-term and the short-term heterotrophic soil carbon dynamics over a virtual elevation gradient in southern Switzerland.The temperature relationship of Lloyd-Taylor fitted the overall data set best as the other functions either resulted in poor fits (Exponential, Arrhenius) or were not applicable for all datasets (Gaussian, Van't Hoff). There were two main sources of uncertainty for model simulations: (1) the lack of confidence in the parameter estimates of the temperature response, which increased with increasing temperature, and (2) the size of the simulated soil carbon pools, which increased with elevation, as slower turn-over times lead to higher carbon stocks and higher associated uncertainties. Our results therefore indicate that such projections are Correspondence to: A. Wolf (annett.wolf@env.ethz.ch) more uncertain for higher elevations and hence also higher latitudes, which are of key importance for the global terrestrial carbon budget.

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“…Aside from its large quantity, SR is exponentially related to soil temperature which has dramatically increased during the last three decades, and will continue to increase in this century (IPCC 2007) in most ecosystems (e.g., Xu and Qi 2001b;Sampson et al 2007). Other factors can also profoundly influence SR, such as soil quality (soil organic carbon), nitrogen deposition, climate conditions and human disturbance (Qi et al 2002;Mo et al 2007). Among all factors, Jones et al (2003) suggested that climate change, particularly rising temperature, was the major cause of increasing SR. Q 10 of SR under temperature T defined as SR T+10 /SR T , where SR T was soil respiration under soil temperature of T°C (Pang et al 2013), was used to describe the sensitivity of SR to temperature, and was usually estimated based on empirical functions (e.g., exponential equation) between soil temperature and SR (Lloyd and Taylor 1994).…”

Section: Introductionmentioning

confidence: 99%

Variation of Q₁₀values in a fenced and a grazed grassland on the loess plateau, northwestern China

Zhang

Xu-dong

Wen

et al. 2015

Soil Science and Plant Nutrition

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Soil respiration (SR) and microbial respiration (MR), which were primarily regulated by soil temperature, can act as a feedback to climate change. Although many studies suggest that global warming will accelerate carbon dioxide (CO 2 ) emissions from soil, the magnitude of this feedback is unknown, mostly due to uncertainty in the temperature sensitivity (Q 10 , increaing ratio of SR and MR after a 10°C increase of temperature) of SR and MR. To investigate the seasonal variation of short-term Q 10 and estimate how grazing impacts temperature sensitivity of SR and MR, we measured SR and MR in a fenced and a grazed grassland on the loess plateau, northwestern China, during 2008China, during -2010. In this semiarid grassland ecosystem, soil temperature was the dominant factor controlling SR and MR during the experimental period. Short-term apparent Q 10 of SR and MR had a clearly seasonal variation, and was significantly and negatively related to soil temperature at 2-cm depth. However, no relationship was found between soil moisture (0-10 cm soil layer) and apparent Q 10 . By decreasing soil organic carbon and root biomass, grazing reduced the long-term Q 10 of SR and MR. In both the short term and the long term, Q 10 of MR was lower than that of SR, suggesting that autotrophic respiration is more sensitive than heterotrophic respiration to temperature. We emphasize the importance of using Q 10 when modeling trajectories of soil carbon stocks under climate change scenarios, and the seasonal variation of Q 10 should also be regarded as a parameter in the global carbon models.

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Temperature sensitivity of soil respiration and its effects on ecosystem carbon budget: nonlinearity begets surprises

Cited by 139 publications

References 35 publications

A global database of soil respiration data

A global database of soil respiration data

Temperature response functions introduce high uncertainty in modelled carbon stocks in cold temperature regimes

Variation of Q₁₀values in a fenced and a grazed grassland on the loess plateau, northwestern China

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Temperature sensitivity of soil respiration and its effects on ecosystem carbon budget: nonlinearity begets surprises

Cited by 139 publications

References 35 publications

A global database of soil respiration data

A global database of soil respiration data

Temperature response functions introduce high uncertainty in modelled carbon stocks in cold temperature regimes

Variation of Q10values in a fenced and a grazed grassland on the loess plateau, northwestern China

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Variation of Q₁₀values in a fenced and a grazed grassland on the loess plateau, northwestern China