There are three ways in which microbial composition might not matter to ecosystem functioning in the face of disturbance. First, microbial communities might be resistant to change. However, we find that microbial composition is, in the majority of cases that we reviewed, sensitive to elevated CO2, mineral fertilization, temperature changes, and C amendments. Second, microbial composition might be resilient and quickly return to its original state. The literature suggests that, at least over the timescale of a few years, microbial composition usually still differs from that of undisturbed communities. Third, even if microbial composition changes, the new community might be functionally similar to the original. Although this hypothesis is currently difficult to test, recent studies suggest that the taxa in many microbial communities are probably not functionally redundant and different communities are not functionally similar.
How can the information that microbial composition affects ecosystem functioning be used to improve predictions of ecosystem process rates under disturbance? The simple model we presented in the previous section highlights two lacking pieces of information. First, more data are needed on the responses of microbial taxa to disturbance, in addition to knowledge about physiological traits. Microbial taxa may vary in their responses to different disturbances, and these taxa may not correspond to functional groups defined by physiological traits.
Second, it would be useful to know the relationship among microbial phylogeny, physiological traits, and response curves. Although it is clear that phylogenetic relationships of taxa are not perfect predictors of microbial physiology (Achenbach and Coates, 2000; Konstantinidis and Tiedje, 2005), there are phylogenetic signals of physiological traits [e.g., Fierer et al., 2007]. The genetic scale at which these traits are clustered would guide modelers in aggregating microbial taxa for their models. Similarly, we know of no studies that address the relationship between phylogeny and microbial responses to disturbance. For instance, perhaps the response of microbial taxa to particular C amendments are predictable at very fine phylogenetic scales (e.g., >99% 16S rDNA similarity), whereas the responses of taxa to temperature changes can be aggregated at a broader scale (such as at >95% similarity).
In sum, there has been increasing recognition that microbes are relevant to ecosystem processes and enormous progress in characterizing the response of microbial composition to disturbance, particularly in soils. Despite these advances, the field of microbial ecology lacks a strong predictive framework to interpret the functional consequences of changes in microbial composition. Much more empirical work is needed to define