Interdisciplinary Faculty Seed Grant Program

Overview

Each year, the Global Change Center (GCC) at Virginia Tech accepts proposals from GCC faculty to support interdisciplinary research that will lead to collaborative proposals submitted to extramural funding sources. We are seeking projects that link multiple faculty programs and take advantage of unique combinations of expertise at VT, have societal implications and/or a policy component, deal with emerging global change issues that have regional significance, and have high potential to eventually leverage external resources.

FUNDED PROPOSALS

Global Change Science

Water Resources

Water & Health

How does current water quality management align with ecological health and human well-being?

Community Ecology

Biological Invasions

Spatio-temporal dynamics of fish reproductive mutualism and linkages to the spread of invasive

Sustainability

Energy & Water

Integrating economic models with watershed & energy models using a system-of-systems approach

Climate Mitigation

Carbon & Energy

Climate mitigation from biofuels: Is loblolly or switchgrass more beneficial in the southeast?

Land Use Changes

Public Health

How does environmental landscape change shape community and ecological health in Appalachia?

Climate Change

Drinking Water

Managing human needs and ecosystem services in drinking water reservoirs confronted with global change.

Global Change

Avian Health

Poison Ivy and migrating birds: exploring a mutualistic relationship in the face of climate change.

Land Use Changes

Carbon Fluxes

Surface-subsurface connectivity in karst landscapes: implications for terrestrial water and carbon fluxes.

Land Use Changes

Stream Salinity

Microbial diversity response to a coal-mining induced salinity gradient in Appalachian streams.

Wildlife Disease

Birdfeeding Dynamics

The coupled social and ecological dynamics of backyard bird feeding.

Invasive Species

Parasite Spillover

Parasite spillover from invasive to native species

Climate Change

Health Outcomes

A synthetic population approach to modeling human health and the environment: A tool for adaptation planning