Despite the large contribution of rangeland and pasture to global soil organic carbon (
The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (
- NSF-PAR ID:
- 10047284
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 24
- Issue:
- 3
- ISSN:
- 1354-1013
- Page Range / eLocation ID:
- p. 1394-1404
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Temperature sensitivity of soil organic carbon (
SOC ) decomposition is one of the major uncertainties in predicting climate‐carbon (C) cycle feedback. Results from previous studies are highly contradictory with old soil C decomposition being more, similarly, or less sensitive to temperature than decomposition of young fractions. The contradictory results are partly from difficulties in distinguishing old from youngSOC and their changes over time in the experiments with or without isotopic techniques. In this study, we have conducted a long‐term field incubation experiment with deep soil collars (0–70 cm in depth, 10 cm in diameter ofPVC tubes) for excluding root C input to examine apparent temperature sensitivity ofSOC decomposition under ambient and warming treatments from 2002 to 2008. The data from the experiment were infused into a multi‐pool soil C model to estimate intrinsic temperature sensitivity ofSOC decomposition and C residence times of threeSOC fractions (i.e., active, slow, and passive) using a data assimilation (DA ) technique. As activeSOC with the short C residence time was progressively depleted in the deep soil collars under both ambient and warming treatments, the residences times of the wholeSOC became longer over time. Concomitantly, the estimated apparent and intrinsic temperature sensitivity ofSOC decomposition also became gradually higher over time as more than 50% of activeSOC was depleted. Thus, the temperature sensitivity of soil C decomposition in deep soil collars was positively correlated with the mean C residence times. However, the regression slope of the temperature sensitivity against the residence time was lower under the warming treatment than under ambient temperature, indicating that other processes also regulated temperature sensitivity ofSOC decomposition. These results indicate that oldSOC decomposition is more sensitive to temperature than young components, making the old C more vulnerable to future warmer climate. -
Abstract Earth system models (
ESM s) rely on the calculation of canopy conductance in land surface models (LSM s) to quantify the partitioning of land surface energy, water, andCO 2fluxes. This is achieved by scaling stomatal conductance,g w, determined from physiological models developed for leaves. Traditionally, models forg whave been semi‐empirical, combining physiological functions with empirically determined calibration constants. More recently, optimization theory has been applied to modelg winLSM s under the premise that it has a stronger grounding in physiological theory and might ultimately lead to improved predictive accuracy. However, this premise has not been thoroughly tested. Using original field data from contrasting forest systems, we compare a widely used empirical type and a more recently developed optimization‐typeg wmodel, termedBB andMED , respectively. Overall, we find no difference between the two models when used to simulateg wfrom photosynthesis data, or leaf gas exchange from a coupled photosynthesis‐conductance model, or gross primary productivity and evapotranspiration for aFLUXNET tower site with theCLM 5 communityLSM . Field measurements reveal that the key fitted parameters forBB andMED ,g 1Bandg 1M,exhibit strong species specificity in magnitude and sensitivity toCO 2, andCLM 5 simulations reveal that failure to include this sensitivity can result in significant overestimates of evapotranspiration for high‐CO 2scenarios. Further, we show thatg 1Bandg 1Mcan be determined from meanc i/c a(ratio of leaf intercellular to ambientCO 2concentration). Applying this relationship withc i/c avalues derived from a leaf δ13C database, we obtain a global distribution ofg 1Bandg 1M, and these values correlate significantly with mean annual precipitation. This provides a new methodology for global parameterization of theBB andMED models inLSM s, tied directly to leaf physiology but unconstrained by spatial boundaries separating designated biomes or plant functional types. -
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