MCA: A Meta-analytic approach to resolving mechanisms of plant-soil-herbivore interactions

Information

  • NSF Award
  • 2120677
Owner
  • Award Id
    2120677
  • Award Effective Date
    8/15/2021 - 3 years ago
  • Award Expiration Date
    7/31/2024 - 6 months ago
  • Award Amount
    $ 241,421.00
  • Award Instrument
    Standard Grant

MCA: A Meta-analytic approach to resolving mechanisms of plant-soil-herbivore interactions

Plants and their associated soils are in a close bidirectional relationship, and this relationship is affected by organisms such as herbivores that consume plants. Feeding by herbivores may influence the numbers and species of plants present in the ecosystem. However, consistent relationships between feeding by herbivores does and the composition or functioning of the soil community have not yet been described. The resolution of this paradox is a fascinating ecological question because indirect effects among organisms are tricky to resolve, but it is also important from a human perspective due to the potential implications to soil properties. For example, changes in soil functioning can influence agricultural success or carbon storage for climate mitigation. In addition, human demographic patterns and shifts in land use have markedly changed the distribution of wild herbivores and livestock, making this a more urgent problem. Therefore, the need to define the role of herbivory on soils and their functioning is profound. This research will tease apart and define the effect of herbivory on soil community composition and functioning as it occurs across varied environments. <br/><br/>Interactions among herbivores, plants, and soils are driven by gradients of multi-variate factors, both biotic and abiotic, and establishing controlled and repeatable experiments to capture these factors is expensive and challenging. Modern and diverse data sets from prior manipulative and observational herbivore experiments are abundant. However, when considered in isolation, individual experiments typically reveal inconsistent and weak responses in the soil. This research will compile and analyze a large number of experimental and observational data sets, thus revealing the full continuum of biotic and abiotic influences of herbivores on the soil. Specifically, the methods will include a regression based and multi-variate meta-analytic approach. In so doing, the following research goals will be addressed: First, meta-analytic regression will capture non-linear or indirect effects of herbivory on soil functioning. Second, multivariate herbivore effects will be explored with respect to both abiotic environmental variables and community level interaction variables, i.e. nutrient flux via dung, trampling or seed dispersal. In partnership with a world expert in meta-analysis, this research will gather diverse data sets to resolve the most elusive mechanisms explaining the link between herbivory and soil ecosystem functioning. The outcome of this work will be a substantial and publicly available database in addition to student training and numerous scientific publications and presentations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Kendra McLauchlankmclauch@nsf.gov7032922217
  • Min Amd Letter Date
    7/22/2021 - 3 years ago
  • Max Amd Letter Date
    7/22/2021 - 3 years ago
  • ARRA Amount

Institutions

  • Name
    Montclair State University
  • City
    Montclair
  • State
    NJ
  • Country
    United States
  • Address
    1 Normal Avenue
  • Postal Code
    070431624
  • Phone Number
    9736556923

Investigators

  • First Name
    Jennifer
  • Last Name
    Krumins
  • Email Address
    kruminsj@mail.montclair.edu
  • Start Date
    7/22/2021 12:00:00 AM

Program Element

  • Text
    Cross-BIO Activities
  • Code
    7275
  • Text
    Ecosystem Science
  • Code
    7381

Program Reference

  • Text
    MCA-Mid-Career Advancement
  • Text
    COVID-Disproportionate Impcts Inst-Indiv