NCEAS Project 12482

A graduate seminar network to facilitate synthetic research on context-dependency in the mycorrhizal symbiosis

  • Jason D. Hoeksema
  • James D. Bever

ActivityDatesFurther Information
Meeting23rd—25th April 2010Participant List  

Although mycorrhizal symbioses, in which plants exchange carbohydrates for nutrients with root associated fungal symbionts, are classically considered a mutualism, they can display a high degree of variability in ecological outcomes ranging from mutualism to parasitism. Given the ubiquity and importance of this interaction, understanding the controls on its variability is paramount for basic and applied ecology. One centerpiece activity of a previous NCEAS working group (“Bridging the gap between theory and practice in mycorrhizal management,” 2005-2007) was to initiate an effort to understand this ecological variability through an empirical synthesis of mycorrhizal inoculation experiments. As part of that effort, we created a database of nearly 2000 such experiments, and developed innovative new methods for multi-factor meta-analysis to assess the relative importance of numerous biotic and abiotic factors hypothesized to explain variation among experiments in plant responses to mycorrhizal inoculation. Although important insights were gained from that analysis, it revealed limitations of the approach (detailed below) which prevented the full exploitation of that effort. Through the NCEAS distributed graduate network project proposed here, we plan to address these limitations to answer fundamental questions about context-dependency in the mycorrhizal symbiosis (detailed below). In this process, graduate students will be trained in mycorrhizal ecology, data management/ecoinformatics, and statistical meta-analysis, and will have the opportunity to take the lead in meaningful synthetic ecological science. NCEAS will provide necessary logistical support, staff support, and funding for planning and face-to-face collaboration, without which this project would not be possible.