. "8 Resistance, Resilience, and Redundancy in Microbial Communities--STEVEN D. ALLISON and JENNIFER B. H. MARTINY." In the Light of Evolution, Volume II: Biodiversity and Extinction. Washington, DC: The National Academies Press, 2008.
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In the Light of Evolution: Volume II—Biodiversity and Extinction
lish because it requires detailed knowledge about the microbial populations that perform a specific process. Furthermore, organisms that are functionally redundant under one set of conditions may not be under different conditions. In general, we know little about the distribution of functional traits across microbial taxa despite years of recognition of this need (Schimel, 2001).
Nonetheless, a growing body of literature has begun to address the more basic question of whether microbial composition matters to ecosystem processes to any degree versus whether the members of a functional group are completely redundant. To address this question, one needs to manipulate microbial composition while controlling for the abiotic environment. This is because any differences in process rates can then be attributed directly to compositional differences and not simply to physiological responses of the original community under new environmental conditions. In plant communities, composition and diversity can be manipulated directly by sowing and weeding plots in the field. Although this is not an easy task, it is much more feasible than manipulating microbial community composition in the field.
A number of approaches can be used to disentangle compositional versus environmental effects on ecosystem processes. In one approach, process rates are measured before and after a disturbance manipulation but before microbial composition changes. This measurement gives some idea about the direct effect of the disturbance on process rates independent of community composition. Schimel and Gulledge (1998) review studies that subject microbial communities from different habitats to parallel short-term, environmental treatments and compare the communities’ process rates. For instance, Gulledge et al. (1997) found that rates of methane consumption by methanotroph communities in response to ammonium fertilization varied depending on whether the communities were associated with paper birch or white spruce taiga forests. This result suggests that differences in methanotroph composition are responsible for differences in the physiological responses.
Although they may not mimic natural communities, bioreactors are useful model systems for linking microbial functional groups with process rates. Community composition can be manipulated directly to test the functional contribution of different microbial taxa. In addition, the communities can be perturbed and monitored for function and composition over time. For example, Fernandez et al. (2000) constructed two different methanogenic bioreactor communities that functioned similarly before disturbance with a glucose pulse. After the pulse, the communities metabolized glucose using different pathways and regained prepulse function at different rates. The authors were able to attribute these differences to specific groups of bacteria that showed different metabolic functions.