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整合微生物群落特性、生物量和死有机物质以预测农田土壤有机碳。

Integrating microbial community properties, biomass and necromass to predict cropland soil organic carbon.

作者信息

Wang Chao, Wang Xu, Zhang Yang, Morrissey Ember, Liu Yue, Sun Lifei, Qu Lingrui, Sang Changpeng, Zhang Hong, Li Guochen, Zhang Lili, Fang Yunting

机构信息

CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110016, China.

Key Laboratory of Terrestrial Ecosystem Carbon Neutrality, Liaoning Province, Shenyang, 110016, China.

出版信息

ISME Commun. 2023 Aug 23;3(1):86. doi: 10.1038/s43705-023-00300-1.

DOI:10.1038/s43705-023-00300-1
PMID:37612426
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10447565/
Abstract

Manipulating microorganisms to increase soil organic carbon (SOC) in croplands remains a challenge. Soil microbes are important drivers of SOC sequestration, especially via their necromass accumulation. However, microbial parameters are rarely used to predict cropland SOC stocks, possibly due to uncertainties regarding the relationships between microbial carbon pools, community properties and SOC. Herein we evaluated the microbial community properties (diversity and network complexity), microbial carbon pools (biomass and necromass carbon) and SOC in 468 cropland soils across northeast China. We found that not only microbial necromass carbon but also microbial community properties (diversity and network complexity) and biomass carbon were correlated with SOC. Microbial biomass carbon and diversity played more important role in predicting SOC for maize, while microbial network complexity was more important for rice. Models to predict SOC performed better when the microbial community and microbial carbon pools were included simultaneously. Taken together our results suggest that microbial carbon pools and community properties influence SOC accumulation in croplands, and management practices that improve these microbial parameters may increase cropland SOC levels.

摘要

通过调控微生物来增加农田土壤有机碳(SOC)仍然是一项挑战。土壤微生物是SOC固存的重要驱动因素,特别是通过它们的坏死物质积累。然而,微生物参数很少用于预测农田SOC储量,这可能是由于微生物碳库、群落特性与SOC之间关系存在不确定性。在此,我们评估了中国东北468个农田土壤中的微生物群落特性(多样性和网络复杂性)、微生物碳库(生物量和坏死物质碳)以及SOC。我们发现,不仅微生物坏死物质碳,而且微生物群落特性(多样性和网络复杂性)以及生物量碳都与SOC相关。微生物生物量碳和多样性在预测玉米的SOC方面发挥了更重要的作用,而微生物网络复杂性对水稻更为重要。当同时纳入微生物群落和微生物碳库时,预测SOC的模型表现更好。综合来看,我们的结果表明,微生物碳库和群落特性影响农田SOC积累,改善这些微生物参数的管理措施可能会提高农田SOC水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/1f323ecf5def/43705_2023_300_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/2552c124f52c/43705_2023_300_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/f1e328cd9ac6/43705_2023_300_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/e9a73501559f/43705_2023_300_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/1c199663df5c/43705_2023_300_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/aa2940137178/43705_2023_300_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/1f323ecf5def/43705_2023_300_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/2552c124f52c/43705_2023_300_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/f1e328cd9ac6/43705_2023_300_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/e9a73501559f/43705_2023_300_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/1c199663df5c/43705_2023_300_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/aa2940137178/43705_2023_300_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05c7/10447565/1f323ecf5def/43705_2023_300_Fig6_HTML.jpg

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本文引用的文献

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Microbial carbon use efficiency promotes global soil carbon storage.微生物碳利用效率促进全球土壤碳储存。
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Fungal necromass increases soil aggregation and organic matter chemical stability under improved cropland management and natural restoration.
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DNA metabarcode analyses reveal similarities and differences in plant microbiomes of industrial hemp and medicinal in China.DNA条形码分析揭示了中国工业大麻和药用大麻植物微生物群的异同。
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在改良农田管理和自然恢复条件下,真菌坏死物质可增强土壤团聚作用并提高有机物质的化学稳定性。
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