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Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters
Author(s) -
Menezes Alexandre B.,
PrendergastMiller Miranda T.,
Richardson Alan E.,
Toscas Peter,
Farrell Mark,
Macdonald Lynne M.,
Baker Geoff,
Wark Tim,
Thrall Peter H.
Publication year - 2015
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/1462-2920.12559
Subject(s) - biology , canonical correspondence analysis , woodland , pasture , microbial population biology , community structure , ecology , canonical analysis , agronomy , botany , abundance (ecology) , bacteria , mathematics , statistics , genetics
Summary Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis ( CCA ) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co‐correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function.