Evidence map›Paper›PMID 36760496›Full record

ArticleFrontiers in microbiology2023

Grass-microbial inter-domain ecological networks associated with alpine grassland productivity.

Yingcheng Wang, Ning Dang, Kai Feng, Junbang Wang, Xin Jin, Shiting Yao, Linlin Wang, Songsong Gu, Hua Zheng, Guangxin Lu and 1 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Yingcheng WangCollage of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Ning DangInstitute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China.
Kai FengCAS Key Laboratory for Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (CAS), Beijing, China.
Junbang WangNational Ecosystem Science Data Center, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Xin JinCollage of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Shiting YaoCollage of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Linlin WangCAS Key Laboratory for Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (CAS), Beijing, China.
Songsong GuCAS Key Laboratory for Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (CAS), Beijing, China.
Hua ZhengState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China.
Guangxin LuCollage of Agriculture and Animal Husbandry, Qinghai University, Xining, China.
Ye DengCAS Key Laboratory for Environmental Biotechnology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences (CAS), Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Associations between grasses and soil microorganisms can strongly influence plant community structures. However, the associations between grass productivity and diversity and soil microbes, as well as the patterns of co-occurrence between grass and microbes remain unclear. Here, we surveyed grass productivity and diversity, determined soil physicochemical, and sequenced soil archaea, bacteria and fungi by metabarcoding technology at 16 alpine grasslands. Using the Distance-decay relationship, Inter-Domain Ecological Network (IDEN), and Mantel tests, we investigated the relationship between grass productivity, diversity and microbial diversity, and the patterns of co-occurrence between grass and microbial inter-domain network in alpine grassland. We found the archaea richness, bacteria richness and Shannon, and fungi α-diversity were significantly negatively correlation with grass diversity, but archaea and bacteria diversity were positively correlation with grass productivity. Moreover, an increase in microbial β-diversity was observed along with increased discrepancy in grass diversity and productivity and soil variables. Variance partitioning analysis suggested that the contribution of grass productivity on microbial community was higher than that of soil variables and grass diversity, which implies that microbial community was more related to grass productivity. Inter-Domain Ecological Network showed that the grass species formed complex and stable ecological networks with some bacterial, archaeal, and fungal species, and the grass-fungal ecological networks showed the highest robustness, which indicated that soil fungi could better co-coexist with aboveground grass in alpine grasslands. Besides, the connectivity degrees of the grass-microbial network were significantly positively correlated with grass productivity, suggesting that the coexistence pattern of grasses and microbes had a positive feedback effect on the grass productivity. The results are important for establishing the regulatory mechanisms between plants and microorganisms in alpine grassland ecosystems.

Indexed as

alpine grasslandbipartite networkgrass-microbe associationsgrass productivitysoil microbialThree-Rivers Headwaters region

Identifiers

PMID36760496
PMCPMC9905801

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.