期刊
GEODERMA
卷 409, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.geoderma.2021.115644
关键词
Carbon mineralization; Microbial biomass; Nitrogen mineralization; pH; Soil organic carbon; Water stress
类别
资金
- INRA
- AEI-MICIU [RYC-2018-024536-I]
- European Social Fund [RYC-2018-024536-I]
The sensitivity of C and N mineralization to water potential in soil varies significantly between sites, and can be accurately predicted by specific soil properties. This suggests the potential for improving soil and soil-crop models to better predict water stress on C and N mineralization, particularly in the context of climate change.
The sensitivity of C and N mineralization in soil to water potential is mostly described in simulation models as a linear function independent of the pedoclimatic conditions. We hypothesized that water sensitivity could be sitespecific and dependent of climate or soil properties. In this study, we characterized the responses of C and N mineralization to water stress in ten soils representing a range of French arable cropping systems and evaluated whether the responses differ between soils and pedoclimatic contexts. C and N mineralization kinetics were quantified in laboratory incubations at four soil water potentials (pF) ranging from pF = 2.0 (~field capacity) to 4.2 (~permanent wilting point). The C and N mineralization rates, calculated by curve fitting, were linearly correlated with pF or relative water content (RWC). The slope of the linear regression, representing the sensitivity to water potential, differed significantly between sites, ranging from 0.12 to 0.35 pF-1 for C mineralization and 0.20 to 0.44 pF-1 for N mineralization. The sensitivity of C or N mineralization rate to pF or RWC could be well predicted by a couple of two soil properties: either microbial quotient (ratio of microbial biomass-C to total organic C) and soil pH or soil organic C:N ratio and soil pH. The sensitivity of soil to water stress was more accurately predicted by these site-specific variables than a model common to all pedoclimatic conditions. These results open the possibility of improving soil and soil-crop models for a more accurate prediction of water stress on C and N mineralization particularly in the context of climate change.
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