Differences and influencing factors of microbial carbon use efficiency in forest rhizosphere soils at different altitudes in Taibai Mountain, China

doi:10.17521/cjpe.2022.0090

Abstract

Abstract:

Aims Under the background of changing carbon cycle process in forest ecosystems caused by global environmental change, the microbial carbon use efficiency (CUE) in forest rhizosphere soil is critical to determine the strength of microbial anabolism and catabolism in forest ecosystems. However, the variation and influencing factors of microbial CUE in rhizosphere soils at different altitudes remain undetermined.

Methods Rhizosphere soil at six different altitudes spanning four forest belts in Taibai Mountain was sampled to determine the physical and chemical properties, extracellular enzyme activity, and characteristics of microbial community and vegetation. Based on the stoichiometric ratio, the soil microbial CUE was estimated. Furthermore, the variation in microbial CUE of rhizosphere soil along the altitude gradient was analyzed to quantify the influencing factors of microbial CUE.

Important findings The results showed that the microbial CUE of rhizosphere soil exhibited an overall upward trend with the increase in altitude. The microbial CUE increased by 4.36% from 0.505 at the lowest altitude to 0.527 at the highest altitude, but decreased at 1 603 and 2 405 m. Based on the Mantel analysis, we identified four categories of factors (i.e., altitude, soil matrix, vegetation and microbe) that related to microbial CUE in rhizosphere soil. The variations of microbial CUE in rhizosphere soil are affected by multiple environmental factors, with the dominant factor being soil matrix (such as dissolved organic carbon (DOC) content, ammonium nitrogen (NH⁺₄-N) content), followed by vegetation. Furthermore, the altitude factor and the microbial factor explained 2.6% and 3.1% of the CUE change, respectively. Although the microbial factors exerted no significant impact on microbial CUE, soil matrix, vegetation and microbe jointly explained 47.0% of the microbial CUE change. The variance partitioning analysis (VPA) quantitatively revealed the contribution of environmental factors to the change of microbial CUE, where soil matrix and vegetation explained 17.0% and 5.7% of the variation, respectively. While the interaction between soil matrix and vegetation accounted for 31.9% of the changes in microbial CUE. The above results indicated that the high-altitude rhizosphere soil in Taibai Mountain has a high carbon sequestration potential, and the carbon sequestration of forest rhizosphere soil may decrease with the intensification of global warming. The vertical temperature difference and the vertical differentiation of the vegetation belt induced by altitude gradient will alter the growth and metabolism environment of microorganisms in the rhizosphere soil. The comprehensive effect of multiple environmental factors dominated by soil matrix impacts the CUE of soil microorganisms, and ultimately changes the assimilation and catabolism processes of soil carbon. The results of this study can provide a scientific basis for the carbon assimilation capacity and carbon sequestration potential of forest soil microorganisms in Qinling Mountains, as well as the forest soil carbon cycle under the background of global change.

Key words: rhizosphere soil, microbial carbon use efficiency, altitude gradient, forest ecosystem, Qinling Mountains

ZHANG Yao, CHEN Lan, WANG Jie-Ying, LI Yi, WANG Jun, GUO Yao-Xin, REN Cheng-Jie, BAI Hong-Ying, SUN Hao-Tian, ZHAO Fa-Zhu. Differences and influencing factors of microbial carbon use efficiency in forest rhizosphere soils at different altitudes in Taibai Mountain, China[J]. Chin J Plant Ecol, 2023, 47(2): 275-288.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2022.0090

https://www.plant-ecology.com/EN/Y2023/V47/I2/275

Figures/Tables 10

Table 1 Basic information of soil extracellular enzymes

酶 Enzyme	缩写 Abbreviation	酶编号 Enzyme number	底物 Substrate
纤维二糖水解酶 Cellobiohydrolase	CBH	3.2.1.91	4-甲基伞形酮-β-D-纤维素二糖苷 4-Methylumbelliferyl-β-D-cellobioside
β-1,4-木糖苷酶 β-1,4-xylosidase	BX	3.2.1.37	4-甲基伞形酮酰-β-D-吡喃木糖苷 4-Methylumbelliferyl-β-D-xylopyranoside
β-1,4-葡萄糖苷酶 β-1,4-glucosidase	BG	3.2.1.21	4-甲基伞形酮酰-β-D-吡喃葡糖酸苷 4-Methylumbelliferyl-β-D-glucoside
碱性磷酸酶 Alkaline phosphatase	AKP	3.1.3.1	4-甲基伞形酮磷酸酯 4-Methylumbelliferyl-phosphate
乙酰基氨基葡萄糖苷酶 β-1,4-N-acetylglucosaminidase	NAG	3.2.1.14	4-甲基香豆素-2-乙酰氨基-2-脱氧-β-D-吡喃葡萄糖苷 4-Methylumbelliferyl-2-acetamido-2-deoxy-beta-D-glucopyranoside
亮氨酸氨基肽酶 Leucine aminopeptidase	LAP	3.4.11.1	L-亮氨酰-7-氨基-4-甲基香豆素盐酸盐 L-Leucine-7-amino-4-methylcoumarin hydrochloride

Fig. 1 Physical and chemical properties of rhizosphere soil at different altitudes in Taibai Mountain (mean ± SE). DOC, dissolved organic carbon; DON, dissolved organic nitrogen; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; MBP, microbial biomass phosphorus; NH4+-N, ammonium nitrogen; NO3--N, nitrate nitrogen; SM, soil moisture; SOC, soil organic carbon; ST, soil temperature; TN, total nitrogen; TP, total phosphorus. Different lowercase letters indicate significant difference (p < 0.05).

Table 2 Microbial diversity in rhizosphere soil at different altitudes in Taibai Mountain (mean ± SE)

海拔 Altitude (m)	α多样性 α diversity		β多样性 β diversity
海拔 Altitude (m)	细菌 Bacteria	真菌 Fungi	细菌 Bacteria	真菌 Fungi
1 308	1.37 ± 0.01^d	0.52 ± 0.01^c	0.00 ± 0.00^e	0.00 ± 0.00^c
1 603	1.39 ± 0.01^d	0.60 ± 0.05^bc	0.04 ± 0.01^d	0.05 ± 0.01^bc
1 915	1.57 ± 0.01^a	0.99 ± 0.01^a	0.14 ± 0.01^a	0.38 ± 0.04^a
2 292	1.42 ± 0.00^c	0.32 ± 0.00^d	0.06 ± 0.00^c	0.10 ± 0.01^b
2 405	1.44 ± 0.00^bc	0.62 ± 0.02^b	0.08 ± 0.01^b	0.06 ± 0.03^bc
2 600	1.46 ± 0.01^b	0.61 ± 0.04^b	0.14 ± 0.01^a	0.06 ± 0.00^bc

Fig. 2 Extracellular enzyme activity in rhizosphere soil at different altitudes in Taibai Mountain (mean ± SE). AKP, alkaline phosphatase; BG, β-1,4-glucosidase; BX, β-1,4-xylosidase; CBH, cellobiohydrolase; LAP, leucine aminopeptidase; NAG, β-1,4-N-acetylglucosaminidase. Different lowercase letters indicate significant difference (p < 0.05).

Fig. 3 Plant community diversity characteristics at different altitudes in Taibai Mountain (mean ± SE). Different uppercase letters indicate significant differences between different life forms at the same altitude (p < 0.05), and different lowercase letters indicate significant differences at different altitudes for the same life form (p < 0.05).

Fig. 4 Altitudinal variation of rhizosphere soil microbial carbon use efficiency in Taibai Mountain (mean ± SE). Different lowercase letters indicate significant difference (p < 0.05).

Table 3 Relationship between rhizosphere soil carbon use efficiency and environmental factors in Taibai Mountain

分类 Classification	相关变量 Relevant variable	参数 Parameter
分类 Classification	相关变量 Relevant variable	Mantel分析 Mantel statistic (r)	p
海拔 Altitude	SM, ST	0.17	0.05
土壤基质 Soil substrate	Soil density, pH, DOC, DON, NH₄⁺-N, NO₃^--N, SOC, TN, TP	0.34	<0.01^**
植物多样性 Plant diversity	乔木(丰富度、Simpson多样性、Shannon-Wiener多样性) Tree (richness, Simpson diversity, Shannon-Wiener diversity)
	灌木(丰富度、Simpson多样性、Shannon-Wiener多样性) Shrub (richness, Simpson diversity, Shannon-Wiener diversity)	0.29	0.01^*
	草本(丰富度、Simpson多样性、Shannon-Wiener多样性) Herb (richness, Simpson diversity, Shannon-Wiener diversity)
微生物多样性 Microorganism diversity	α多样性, β多样性 α diversity, β diversity	0.14	0.10

Fig. 5 Variance partitioning analysis of soil microbial carbon use efficiency and environmental factors in Taibai Mountain.

Fig. 6 Linear fitting analysis of soil microbial carbon use efficiency (CUE) and soil matrix in Taibai Mountain. DOC, dissolved organic carbon; DON, dissolved organic nitrogen; NH4+-N, ammonium nitrogen; NO3--N, nitrate nitrogen; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.

Fig. 7 Linear fitting analysis of soil microbial carbon use efficiency and α diversity of plant communities in Taibai Mountain. R2 is corrected, represents the fitting dagree of linear fitting analysis, and its negative value represents poor fitting degree.

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