NSF-SNSF: A theoretical understanding of feasible energy limits in ecological communities

Information

  • NSF Award
  • 2436069
Owner
  • Award Id
    2436069
  • Award Effective Date
    9/1/2024 - 4 months ago
  • Award Expiration Date
    8/31/2028 - 3 years from now
  • Award Amount
    $ 385,312.00
  • Award Instrument
    Standard Grant

NSF-SNSF: A theoretical understanding of feasible energy limits in ecological communities

The composition of ecological communities (group of interacting populations in a given place and time) exhibits feedbacks with the physical and chemical environment, reinforcing or weakening the planetary life-support systems. These feedbacks are expected to be regulated by the availability of energy in the environment and both the capacity and efficiency of populations to use such energy. Thus, understanding the feasible limits of energy expenditures in ecological communities becomes instrumental to explain and predict the possibility of observing a community in nature, the response of such communities to random external perturbations, as well as changes in community composition and environmental conditions. Using mathematical models, this project will set out to answer how ecological and evolutionary processes drive energy limits (energy intake, energy requirements, productivity, efficiency, storage, distribution, and tolerance to random changes in the amount and rate of energy supply) in sustainable and unsustainable ecological communities. This knowledge is paramount to establish successful interventions in the conservation and restoration of ecosystems. This project will also provide training to graduate students.<br/><br/>Organisms are not isolated units, but they form ecological communities, affecting the availability of useful energy and resources. At this other level of living matter organization, it is unclear whether the energy limits operating at the organismal level are conserved at the community level and lead to feasible ecological communities, or whether feasible conditions at the community level constrain organismal energy limits. While metabolic scaling theory has provided theoretical and empirical platforms to study energy limits at the organismal level, it remains unclear what are the feasible energy limits in ecological communities leading to sustainable systems. From an evolutionary point of view, efforts have concentrated on understanding the role of trait evolution (e.g., body mass, life span) on community-wide properties (e.g., emergence of communities through branching events and productivity). In fact, it has been shown that co-evolution cannot continuously increase feasibility; on the contrary, it will be limited by limits in energy intake. Moreover, this work points to unknown trade-offs operating at the community level, as well as feasible energy limits that should be expected to be different from a scaled-up version of the organismal/population limits. For example, under which contexts co-evolutionary pressures at the organismal level can increase/decrease the feasible limits of energy expenditures in communities? The goal of this project is to provide a testable theoretical platform to understand how fundamental ecological and evolutionary processes drive the limits of energy expenditures in feasible communities.<br/><br/>This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland.<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
    Andrea Porras-Alfaroaporrasa@nsf.gov7032922944
  • Min Amd Letter Date
    7/23/2024 - 6 months ago
  • Max Amd Letter Date
    7/23/2024 - 6 months ago
  • ARRA Amount

Institutions

  • Name
    Massachusetts Institute of Technology
  • City
    CAMBRIDGE
  • State
    MA
  • Country
    United States
  • Address
    77 MASSACHUSETTS AVE
  • Postal Code
    021394301
  • Phone Number
    6172531000

Investigators

  • First Name
    Serguei
  • Last Name
    Saavedra
  • Email Address
    sersaa@mit.edu
  • Start Date
    7/23/2024 12:00:00 AM

Program Element

  • Text
    Population & Community Ecology
  • Code
    112800

Program Reference

  • Text
    International Partnerships
  • Text
    U.S. NSF-Swiss Resrch Corp
  • Text
    SWITZERLAND
  • Code
    5950