Severe undersampling obscures subtle community variation
With the possible exception of AMF, none of the sampling effort curves approached an asymptote meaning that both sampling strategies failed to adequately characterize the microbial communities present (Supporting Information Fig. 2). We found that multiple replicates from a single plant can vary by nearly 80% in FFE SVs, even when extracting from larger amounts (250 mg vs. 30 mg) of tissue. Lindahl et al.(2013) suggests that if duplicate subsamples differ much in community composition then these differences threaten to obscure finer-scale treatment effects and ecological correlations, and that sampling effort should be increased. Indeed, a more robust sampling effort through the use of multiple technical replicates revealed remarkably strong (R2=0.91), and significant host filtering within each individual plant that would have gone unobserved if extracting DNA from just a single replicate per plant. Although we may be able to observe patterns in undersampled data among sites or treatments, it is difficult to train models and make predictions or inferences in regard to the larger microbial population.
As Unterseher et al . (2010) suggests, it is often unnecessary to saturate richness in microbial communities, but this should be carefully considered before developing experiments and testing hypotheses. One must take into account the objectives of the study and the accuracy and precision required to meet those objectives. Although the methods traditionally employed to sample plant-associated microbes may be sufficient to generally observe landscape-scale differences, it is important to recognize that we are not characterizing these communities, rather we are taking a sliver of a ‘snapshot’ of species composition from a single point in time. A large proportion of true microbial diversity for most systems will likely still remain undetected and the specific results may be limited in their replicability.