ArticleFrontiers in microbiology2022
Biogeographic, Driving Factors, Assembly, and Co-occurrence Patterns of Archaeal Community in Biocrusts.
Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 7 citations in OpenAlex.
- Assembly mechanisms, not species pool, shapeFrontiers in microbiology · 2024Article
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5 authors at 2 institutions in 1 country.
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Abstract
Archaea exhibit strong community heterogeneity with microhabitat gradients and are a non-negligible part of biocrust's microorganisms. The study on archaeal biogeography in biocrusts could provide new insights for its application in environmental restoration. However, only a few studies on assembly processes and co-occurrence patterns of the archaeal community in patchy biocrusts have been reported, especially considering the number of species pools (SPs). Here, we comprehensively collected biocrusts across 3,500 km of northern China. Different successional biocrusts from various regions contain information of local climate and microenvironments, which can shape multiple unique archaeal SPs. The archaeal community differences in the same successional stage exceeded the variations between successional stages, which was due to the fact that the heterogeneous taxa tended to exchange between unknown patches driven by drift. We also comparatively studied the driving forces of community heterogeneity across three to ten SPs, and assembly and co-occurrence patterns were systematically analyzed. The results revealed that the impact of spatial factors on biogeographic patterns was greater than that of environmental and successional factors and that impact decreased with the number of SPs considered. Meanwhile, community heterogeneity at the phylogenetic facet was more sensitive to these driving factors than the taxonomic facet. Subgroups 1 (SG1) and 2 (SG2) of the archaeal communities in biocrusts were dominated by Nitrososphaeraceae and Haloarchaea, respectively. The former distribution pattern was associated with non-salinity-related variables and primarily assembled by drift, whereas the latter was associated with salinity-related variables and primarily assembled by homogeneous selection. Finally, network analysis indicated that the SG1 network had a higher proportion of competition and key taxa than the SG2 network, but the network of SG2 was more complex. Our study suggested that the development of the archaeal community was not consistent with biocrusts succession. The dominant taxa may determine the patterns of community biogeography, assembly, and co-occurrence.
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