Senior Honors Projects, 2010-2019

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Date of Graduation

Spring 2017

Document Type

Thesis

Degree Name

Bachelor of Science (BS)

Department

Department of Biology

Advisor(s)

Bruce Wiggins

Christine May

Heather Griscom

Abstract

Agronomic land use and urbanization are the leading causes of water quality decline within streams of the Shenandoah Valley. Implementation of riparian buffer zones is a common, beneficial approach to initiate restoration of negatively affected waterways. In the Commonwealth of Virginia, the Conservation Reserve Enhancement Program (CREP) assists landowners in repairing natural habitat through the provision of cattle fencing and reintroduction of hardwood trees, native warm season grasses, and shrubs. We analyzed seven CREP restored sites of varying time since restoration (5-15 years) to determine the effects of time, land use, and riparian zone characteristics on water quality. The Virginia Stream Condition Index (VA-SCI), Hilsenhoff Biotic Index (HBI), and Shannon Weiner Diversity Index (H) were used to infer water quality through the use of site-specific benthic macroinvertebrate identification. The percent forest, agricultural land, and impervious surfaces in watershed and 100 meter buffer areas for each site was calculated through GIS analysis. Riparian characteristics were determined through in-field assessment of overhanging vegetation, amount woody debris, number of riffles, average number of woody specimens (per m2), and average diameter-at-breast height (DBH). Single variable regressions showed no significant relationships between the macroinvertebrate index scores and the tested variables with the exception of woody debris presence. The amount woody debris was shown to possess a negative relationship with the VA-SCI, with a significant R2 value of 0.669 and p-value of 0.025. Unexpectedly, a lower amount woody debris predicted higher water quality. Through stepwise, multiple variable linear regression tests, we found that varying combinations of riparian characteristics (lower amounts woody debris, greater average DBH of riparian trees, greater time since restoration, and lessor percent impervious surfaces) were significant predictors of macroinvertebrate index scores, all with adjusted R2 values above 0.763. Though the majority of these results were consistent with our predictions, it should be noted that the sample size of this study was small; an increased sample size and more rigorous vegetation assessment may provide more substantial results in the future.

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