Non-parametric multivariate comparisons of soil fungal composition: Sensitivity to thresholds and indications of structural redundancy in T-RFLP data

Complex soil microbial data produced by molecular profiling techniques, such as terminal restriction fragment length polymorphism (T-RFLP), are often analysed using multivariate statistical methods. Despite this, there has been little evaluation of the sensitivity of multivariate methods to routine data manipulations such as the application of noise thresholds. We examine effects of three percentage area thresholds (0.1%, 0.5% and 1.0%; i.e. ranging from low to commonly applied) on non-metric multidimensional scaling (NMDS) ordinations of soil fungal T-RFLP profiles. We then interpret threshold effects by introducing the concept of structural redundancy in T-RFLP data.NMDS ordinations compared 20 soil samples (encompassing seven sites, two forest types, and three locations) for T-RFLP presence/absence data, which were produced using primers specific to the rDNA internal transcribed spacer (ITS) region, and three separate restriction enzymes (HinfI, AluI and TaqI). Increasing thresholds from 0.1% to 1.0% led to decreases in average number of detected reproducible fragments per site of 57% (HinfI), 75% (AluI), and 69% (TaqI). However, despite the removal of many fragments unique to site/forest type/location, the application of increasing thresholds did not significantly change NMDS patterns for any enzyme in both the complete data and in a more weakly structured sub-group (involving one forest type and two locations). Thus, our data indicate that application of area thresholds up to 1.0% would have minimal impact on NMDS-based comparisons of soil fungal composition.Robustness of NMDS patterns to considerable fragment loss with increasing threshold suggested a degree of ‘structural redundancy’ in our T-RFLP data – that is, multiple fragments per soil sample were interchangeable in the way they contributed to between-sample NMDS patterns. Indeed, for each restriction enzyme, we found 3–4 peels of data (i.e. mutually exclusive sub-sets) that were capable of reproducing overall patterns in presence/absence data at the 0.1% threshold. Despite potential in the T-RFLP method for production of more than one fragment per fungal species/phylotype, we present arguments to support at least some translation of structural redundancy in T-RFLP data to structural redundancy in fungal community comparisons (i.e. the between-soil similarity patterns can be explained by, or are imprinted in, multiple groups of fungal phylotypes). Our analyses highlight structural redundancy as an efficient method for identifying key phylotypes responsible for differences in community composition among soils, and as a promising starting point for improved understanding of many aspects of spatial soil ecology.