ESA/SER Joint Meeting (August 5 -- August 10, 2007)

PS 41-17 - The response of gross nitrogen mineralization and nitrification to long and short-term changes in moisture and temperature: The relative roles of soil climate, chemistry, and microbes

Wednesday, August 8, 2007
Exhibit Halls 1 and 2, San Jose McEnery Convention Center
Damon C. Bradbury, University of California, Berkeley and Mary K. Firestone, Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA

Microorganisms mediate several transformations of nitrogen in soils critical for plant nutrition as well as retention or loss of N from soils.  Temperature and water are also important environmental drivers of these transformations.  Some experiments manipulate climate and measure the impact of the new conditions on a community or process.  Other studies measure the short-term response of a process to a change in moisture or temperature that can be indicative of the physiological response of soil microorganisms.  Both are examined in this study.  Soils were reciprocally transplanted along a latitudinal gradient in coastal redwood forests between three sites that differ in climate, soil characteristics, and microbial community composition and then harvested after 1 year.  In additional experiments, soils from two sites were incubated across a range of moisture or temperature for 48 hours. In addition to measuring gross rates of N mineralization and nitrification, some soil characteristics (dissolved organic carbon and nitrogen, water potential, pH, particle size) and microbial biomass and community composition were also determined.  Transplanting impacted pools, process rates, and community composition.  Manipulations of temperature had a strong impact on gross N mineralization.  Gross nitrification responded more to the short-term manipulation of moisture than mineralization.  The variability in process rates is related to the variability in substrate pools, soil characteristics and community composition using simple linear regression multivariate ordination, and classification and regression trees.  These experiments assess the impact of soil climate and chemistry, and microbial community composition, abundance and physiology on process rates.