Global variation of soil microbial carbon-use efficiency in relation to growth temperature and substrate supply

Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE 0 + m ×...

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Published in	Scientific reports Vol. 9; no. 1; p. 5621
Main Authors	Qiao, Yang, Wang, Jing, Liang, Guopeng, Du, Zhenggang, Zhou, Jian, Zhu, Chen, Huang, Kun, Zhou, Xuhui, Luo, Yiqi, Yan, Liming, Xia, Jianyang
Format	Journal Article
Language	English
Published	London Nature Publishing Group UK 04.04.2019 Nature Publishing Group
Subjects	704/158/2445 704/158/855 Biological Phenomena - genetics Biomass Carbon Carbon - metabolism Carbon Cycle - physiology Ecosystem Environmental factors Global Warming Humanities and Social Sciences Markov chains Microbiota - genetics Monte Carlo Method multidisciplinary Multiple regression analysis Science Science (multidisciplinary) Soil - chemistry Soil Microbiology Soil temperature Soils Spatial distribution Temperature Temperature effects
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Abstract	Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE 0 + m × ( T − 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE 0 ) and a temperature response coefficient (i.e., m ). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD ) at the global scale. Then, the key parameters CUE 0 and m in the above equation were estimated as 0.475 and − 0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes.
AbstractList	Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE 0 + m × ( T − 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE 0 ) and a temperature response coefficient (i.e., m ). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD ) at the global scale. Then, the key parameters CUE 0 and m in the above equation were estimated as 0.475 and − 0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes. Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE + m × (T - 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE ) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE and m in the above equation were estimated as 0.475 and -0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes. Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE0 + m × (T − 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE0) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE0 and m in the above equation were estimated as 0.475 and −0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes. Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE0 + m × (T - 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE0) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE0 and m in the above equation were estimated as 0.475 and -0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes.Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a temperature-dependent function in current microbial-explicit soil carbon (C) models. The temperature-dependent function (i.e., CUE = CUE0 + m × (T - 20)) simulates the dynamic CUE based on the specific CUE at a given reference temperature (i.e., CUE0) and a temperature response coefficient (i.e., m). Here, based on 780 observations from 98 sites, we showed a divergent spatial distribution of the soil microbial CUE (0.5 ± 0.25; mean ± SD) at the global scale. Then, the key parameters CUE0 and m in the above equation were estimated as 0.475 and -0.016, respectively, based on the observations with the Markov chain Monte Carlo technique. We also found a strong dependence of microbial CUE on the type of C substrate. The multiple regression analysis showed that glucose influences the variation of measured CUE associated with the environmental factors. Overall, this study confirms the global divergence of soil microbial CUE and calls for the incorporation of C substrate beside temperature in estimating the microbial CUE in different biomes.
ArticleNumber	5621
Author	Zhou, Jian Luo, Yiqi Zhu, Chen Du, Zhenggang Zhou, Xuhui Qiao, Yang Wang, Jing Liang, Guopeng Huang, Kun Yan, Liming Xia, Jianyang
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Snippet	Soil microbial carbon-use efficiency (CUE), which is defined as the ratio of growth over C uptake, is commonly assumed as a constant or estimated by a...
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SubjectTerms	704/158/2445 704/158/855 Biological Phenomena - genetics Biomass Carbon Carbon - metabolism Carbon Cycle - physiology Ecosystem Environmental factors Global Warming Humanities and Social Sciences Markov chains Microbiota - genetics Monte Carlo Method multidisciplinary Multiple regression analysis Science Science (multidisciplinary) Soil - chemistry Soil Microbiology Soil temperature Soils Spatial distribution Temperature Temperature effects
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Title	Global variation of soil microbial carbon-use efficiency in relation to growth temperature and substrate supply
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