Soil microbial community structures are shaped by agricultural systems revealing little temporal variation.

Many studies in soil microbial ecology are undertaken with a single sampling event, with the influence of temporal progression rarely being considered. Under field conditions, soil samples were taken from different agricultural systems; a sown grassland to maize rotation (MC), an intensively managed permanent grassland (INT), as well as extensively managed permanent grasslands with high (EXT_HP), low to sufficient (EXT_LP) and deficient available P (EXT_DP), six times throughout the 2017 growing season. Thus, this study aimed to determine if any differences in soil microbiome structures between both sharply contrasting (MC - INT - EXT), slightly differing (EXT_HP - EXT_DP) and quite similar (EXT_HP - EXT_LP and EXT_LP - EXT_DP) agricultural systems persist through changing growth conditions within the growing season. For both fungal and bacterial community structure, the influence of agricultural system (CV = 0.256, P < 0.001 and CV = 0.145, P < 0.01, respectively) was much greater than that of temporal progression (√CV = 0.065 and 0.042, respectively, both P < 0.001). Importantly, nearly all agricultural systems persistently harbored significantly distinct fungal community structures across each of the six sampling events (all at least P < 0.05). There were not as many pairwise differences in bacterial community structure between the agricultural systems, but some did persist (MC and EXT_HP ∼ EXT_DP, all P < 0.001). Additionally, persistent indicator fungal OTUs (IndVal >0.7, P ≤ 0.05) associated to each agricultural system (except EXT_LP) were found in each of the six sampling events. These results highlight the temporal stability of pairwise differences in soil microbiome structures between established agricultural systems through changing plant growth conditions, even between those with a comparable management regime. This is a highly relevant finding in informing the sampling strategy of studies in soil microbial ecology as well as for designing efficient soil biodiversity monitoring systems.