Non-metric dimensional scaling (NMDS) based ordinations for differences among sites and treatments.

<p>Analyses generated from Bray Curtis dissimilarity plus a dummy variable (+d) on Hellinger-transformed relative abundances for all-data at 0% bootstrap (closest match) at the genus (A) and family (B) levels and the re-sampled data at the genus (C) and family (D) levels. 2D stress values were 0.17 (A), 0.18 (B), 0.18 (C), and 0.19 (D).</p

Similarity percentage analysis (SIMPER).

<p>Relative abundances (%) of OTUs at the genus level that contribute to the discrimination between fungal communities in suppressive and non-suppressive soils (solid bar = suppression, hatched bar = non-suppression) in the (A) sowing and (B) in-crop (7 week) samples. Numbers in the right column indicate percent contribution to discrimination by SIMPER analysis (sum = 26.8% (A) and 31.2% (B)). * indicate significant differences between suppressive and non-suppressive fields (t-test, p<0.05). Bold taxa indicate that they are shared between the sowing and in-crop samples.</p

PERMANOVA analysis.

<p>Statistical comparisons of the t-RFLP, the 28S whole dataset, and the 28S re-sampled (4484 sequences per sample) datasets. CV = Component of variation.</p

Soil type and suppression status statistical comparisons.

<p>Significance of differences (main effects only) at different taxonomic levels using ANOSIM two-way crossed analysis for the original dataset and re-sampled dataset.</p

Pathogen abundance and disease incidence.

<p>Note: values within each column followed by the same letter are not statistically significant at P<0.05.</p><p>Amount of pathogen <i>R. solani</i> AG 8 inoculum in the surface soil at sowing and the level of disease incidence measured in 7 week old seedlings from suppressive and non-suppressive fields at Avon and Minnipa with standard errors.</p

Composition of the 20 most abundant genera.

<p>Data from (A) suppressive soils, (B) non-suppressive soils, (C) Avon soil, and (D) Minnipa soil.</p

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of 994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and nonsuppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria, Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression