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Harvard Forest Symposium Abstract 2009

  • Title: Using neighborhood models to examine the role of ecto- and arbuscular mycorrhizal forest communities on Eastern hemlock seedling establishment
  • Primary Author: Michael O'Brien (SUNY College of Environmental Science and Forestry)
  • Additional Authors: Thomas Horton (SUNY College of Environmental Science and Forestry)
  • Abstract:

    Neighborhood models were adapted to examine the influence of plant community assemblage and spatial distribution on soil mycorrhizal inoculum potential. The objective of the study was to quantify the role of mycorrhizal plant communities on the ectomycorrhizal (EM) colonization of root tips, survival, and growth of first-year hemlock seedlings. Contrasting EM Eastern hemlock and arbuscular mycorrhizal (AM) sugar maple dominated communities at Harvard, Hubbard Brook, and Bartlett forests in the northeastern US were used as an in situ setting for developing and testing the model. Hemlock seeds were sown into 120 plots (60 hemlock dominated and 60 sugar maple dominated) in May 2008. Three treatments at each plot were used to alter the mycorrhizal soil inoculum: (i) an undisturbed control with limited soil mixing, (ii) a disturbed soil treatment with extraction, homogenization, and replacement, and (iii) swapped soil treatment from the alternate community type. Emergent seedlings were harvested and assessed for EM root tip colonization, survival, and total biomass after 5 months. Initial results showed that models with mycorrhizal neighborhood functions performed poorly in predicting colonization, survival, and growth of first-year seedlings when compared to null models based on site characteristics and neighborhood models with no plant mycorrhizal type delineation. The model was incapable of distinguishing biotic interactions within the rhizosphere at the early stage of seedling establishment. Longer study periods, extensive sample sizes, and larger variability in canopy openness will be required to improve the goodness-of-fit.

  • Research Category: Ecological Informatics and Modelling, Physiological Ecology, Population Dynamics, and Species Interactions