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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.15550
|2 doi
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|a pubmed25n1070.xml
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|a (DE-627)NLM321197054
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|a (NLM)33559308
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Wang, Chao
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Large-scale importance of microbial carbon use efficiency and necromass to soil organic carbon
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|c 2021
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| 336 |
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 23.04.2021
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|a Date Revised 23.04.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2021 John Wiley & Sons Ltd.
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|a Optimal methods for incorporating soil microbial mechanisms of carbon (C) cycling into Earth system models (ESMs) are still under debate. Specifically, whether soil microbial physiology parameters and residual materials are important to soil organic C (SOC) content is still unclear. Here, we explored the effects of biotic and abiotic factors on SOC content based on a survey of soils from 16 locations along a ~4000 km forest transect in eastern China, spanning a wide range of climate, soil conditions, and microbial communities. We found that SOC was highly correlated with soil microbial biomass C (MBC) and amino sugar (AS) concentration, an index of microbial necromass. Microbial C use efficiency (CUE) was significantly related to the variations in SOC along this national-scale transect. Furthermore, the effect of climatic and edaphic factors on SOC was mainly via their regulation on microbial physiological properties (CUE and MBC). We also found that regression models on explanation of SOC variations with microbial physiological parameters and AS performed better than the models without them. Our results provide the empirical linkages among climate, microbial characteristics, and SOC content at large scale and confirm the necessity of incorporating microbial biomass and necromass pools in ESMs under global change scenarios
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| 650 |
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4 |
|a Journal Article
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| 650 |
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4 |
|a carbon use efficiency
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| 650 |
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4 |
|a microbial necromass
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| 650 |
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4 |
|a microbial physiological parameters
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| 650 |
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4 |
|a microbial turnover rate
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| 650 |
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4 |
|a modeling
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| 650 |
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4 |
|a soil carbon storage
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| 650 |
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7 |
|a Soil
|2 NLM
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| 650 |
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7 |
|a Carbon
|2 NLM
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| 650 |
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7 |
|a 7440-44-0
|2 NLM
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| 700 |
1 |
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|a Qu, Lingrui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Yang, Liuming
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Dongwei
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Morrissey, Ember
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Miao, Renhui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Ziping
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Wang, Qingkui
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Fang, Yunting
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Bai, Edith
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Global change biology
|d 1999
|g 27(2021), 10 vom: 01. Mai, Seite 2039-2048
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnas
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| 773 |
1 |
8 |
|g volume:27
|g year:2021
|g number:10
|g day:01
|g month:05
|g pages:2039-2048
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| 856 |
4 |
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|u http://dx.doi.org/10.1111/gcb.15550
|3 Volltext
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