Faculty Seed Grant Project


Developing a predictive model for in-stream embeddedness to link physical processes with biotic responses 


Excess fine sediment is a chronic, widespread, and major cause of impairment in streams across the U.S. Fine sediment within pore spaces of a streambed degrades habitat quality for benthic macroinvertebrates and fishes by reducing streambed porosity, interparticle flow, and surfaces for biological production. Embeddedness (Fig. 1) can facilitate declines in local biodiversity and invasion by silt-tolerant species. Embeddedness is manually measured to assess habitat quality and there are currently no methods available that directly translate remotely sensed or continuously measured stream variables into a prediction of embeddedness.

The purpose of this GCC seed grant is to (1) demonstrate that we can predict embeddedness from river channel and flow characteristics alone, and by extension (2) show that embeddedness can predict crayfish invasion. This work is a first step toward achieving our long-term goal of developing predictive aquatic ecosystems models via embeddedness; linking physical processes directly with biotic responses. 

Project objectives:

  1. To assemble known data on stream embeddedness in Virginia and North Carolina. This includes looking for data in the literature and compiling data already collected by the PIs.  
  2. Show that embeddedness (and siltation generally) mediates changes in biotic communities by harming silt-intolerant species and helping silt-tolerant species. 

We anticipate that embeddedness can be predicted from river channel and flow characteristics alone. This outcome is important for linking physical processes with biotic responses because embeddedness is a key predictor of habitat quality, species diversity and abundance, and invasive species. Therefore, this work would allow us to predict embeddedness and crayfish invasions directly for any river given measures of channel geometry and streamflow; allowing unprecedented insight for aquatic ecosystem managers. 

Fig. 1. Embeddedness is the percent of a particle surrounded by a finer substrate. Embeddedness at a site is averaged over many particles. Image courtesy of Jon Czuba.
Faxonius cristavarious, the spiny stream crayfish. Photo courtesy of Bryan Brown.

Reference citations for project proposal description available upon request.