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.