APPLYING ENVIRONMENTAL FILTERING TO COLLECT AND FUNCTIONALLY COMPARE MICROBIAL ASSEMBLAGES WITH DIFFERENT ECOLOGICAL TRAITS

agriculture tends to reduce biodiversity relative to environments that are not directly managed by humans. in general, this leads to a decrease in specialist organisms that survive under a narrow range of conditions, and promotes generalists that are able to tolerate a broader range of conditions. we do not know whether this occurs among soil microorganisms (e.g. bacteria and fungi), but certain management practices (e.g. nutrient applications) impose pressures that occur in cycles that may repeat seasonally or annually. microorganisms must contend with these changes, and those that can thrive under a wider range of conditions can potentially remain active for a longer period each year. it is often assumed that many functions can be performed equally well by many different microorganisms, but some functions are not widespread, and studies of larger organisms (e.g. birds) suggest that specialist organisms in their home environment often outperform generalists. as a result, if human-imposed pressures cause soil communities to become dominated by generalist organisms, this could have consequences for microbial functions across landscapes.in this project, i will transfer communities between soil environments under different conditions in order to collect pools of microorganisms with different ecological traits. we will assess whether this selection leads to functional changes in these pools, with our main goal being to understand whether generalists can replace the function of specialists. a microorganism could be a generalist with respect to many aspects of the environment, but here we focus on microbes that thrive across a broad range of 1) temperatures, 2) resources, and 3) habitat types, which are all relevant to agriculture.in aim 1, we will select pools of generalists or generalists + specialists by either maintaining a consistent environment (i.e. conditions do not change), or by imposing low or high degrees of environmental variability. in aim 2, we will compare the function selected pools through assays of microbial growth, respiration, metabolism, and enzyme activity. in aim 3, we will determine whether filtering for ecological types of microorganisms alters the pool that can be captured through culturing in the lab, and ultimately used for microbial product development.our overall goals are to increase functional and ecological annotations of abundant sequence data, and to better inform microbial management in agriculture.