- © The Mineralogical Society Of America
CHARACTERIZING BIOGEOCHEMICAL SYSTEMS
Evidence of connections between microbial activity and the Earth’s biogeochemical cycles is all around us, and motivates our interest in the mechanisms of microbial transformations, their rates, and the distribution of microbial activities across environment types and over Earth history. In general, the approach to investigating a geomicrobiological process begins with biological and geochemical characterization of the environment of interest. Geochemical characteristics constrain available metabolisms (e.g., McCollom and Shock 1997) and patterns can reveal processes not recognized initially to be microbially mediated.
The membership of microbial communities can be assayed through cultivation and cultivation-independent methods. However, this task is not without its challenges. There is little consensus about the ways in which organisms should be grouped into relevant ecological units such as species (Gevers et al. 2005). Even using standard classification techniques, the extent of microbial diversity appears vast, and recent analyses suggest that current estimates may tremendously under predict the amount of genetic diversity in the biosphere. In addition, a single organism type may contain far more genes than expected based on genomic sequencing of an isolate of that species because species populations can exhibit internal heterogeneity. Thus, it seems that comprehensive characterization of the microbial membership of an environment over space and time is a problem of almost incomprehensible magnitude. Furthermore, microbial census taking is only the first step. Beyond documenting the assemblage of organisms present, we need to know how they are distributed, what are they doing, how they are doing it, and the ways that their activities impact the physical and chemical characteristics of their surroundings.
In the near future, the only systems in which it will be plausible to tackle the level of characterization required for relatively comprehensive analyses are the simplest ones. For example, in samples of relatively low geochemical and biological complexity, it …