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A New Modeling Approach To Prioritize Riparian Restoration To Reduce Sediment Loading in Two Virginia River Basins

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Abstract

Human impact, particularly land cover changes (e.g., agriculture, construction) increase erosion and sediment loading into streams. Benthic species are negatively affected by silt deposition that coats and embeds stream substrate. Given that riparian buffers are effective sediment filters, riparian restoration is increasingly implemented by conservation groups to protect stream habitats. Limited funding and a multitude of impaired streams warrant the need for cost-effective prioritization of potential restoration actions. We created a decision-support framework for conservation agencies and aquatic resource managers to prioritize riparian restoration efforts. Our framework integrates GIS data and field surveys into a statistical model to predict instream silt from estimates of upland soil loss and riparian filtration capacity. We focus specifically on prioritizing sites in upper sections of the Roanoke and Nottoway river basins (Virginia, US) based on observed records of Roanoke logperch (Percina rex), an imperiled sediment-sensitive species. Our statistical approach examines soil characteristics, land cover, precipitation, topography, and annual soil loss estimates from the empirically derived Revised Universal Soil Loss Equation, combined with land cover-based riparian filtration capacity as potential stream habitat predictors. We found riparian filtration capacity to be a significant predictor of silt cover, while precipitation was a significant predictor of embeddedness. Spatial scale was also a factor, in that spatial variance in silt cover and embeddedness was more accurately predicted at smaller spatial extents. Ultimately, our model can be used as a prioritization tool for mitigating high siltation areas, or for protecting low soil erosion areas.

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Acknowledgements

This project was supported by the Center for the Environment at Plymouth State University and the VDGIF. We thank Zachary Martin from the Department of Fish and Wildlife Conservation at Virginia Tech for largely developing field methodology and surveying stream sites. We also thank undergraduate students that participated in field data collection. We thank Mark Green and two anonymous reviewers for helpful comments on the manuscript. The Virginia Cooperative Fish and Wildlife Research Unit is jointly sponsored by the U.S. Geological Survey, Virginia Polytechnic Institute and State University, VDGIF, and Wildlife Management Institute. Use of trade, firm, or product names does not imply endorsement by the U.S. Government.

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Correspondence to Lisa N. Scott.

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The authors associated with this manuscript certify that they have no affiliations with any entity with financial or non-financial interests in the topics discussed herein.

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Appendix

Appendix

Tables 27.

Table 2 Riparian filtration capacity index adapted from Mayer et al. 2007
Table 3 Soil loss (SL) and riparian filtration capacity (Rip Fil) calculations for all 76 HUC-12s are shown in the table below
Table 4 A list of all 30 field sites is shown along with geospatial coordinates and location descriptions
Table 5 Resulting equations (Eq.s) from our multiple linear regression (MLR) models
Table 6 Annual soil loss calculations in tonnes per hectare per year are shown in the table below
Table 7 Each of our 30 study sites were ranked based on observed silt cover and embeddedness

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Scott, L.N., Villamagna, A.M. & Angermeier, P.L. A New Modeling Approach To Prioritize Riparian Restoration To Reduce Sediment Loading in Two Virginia River Basins. Environmental Management 62, 721–739 (2018). https://doi.org/10.1007/s00267-018-1078-6

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  • DOI: https://doi.org/10.1007/s00267-018-1078-6

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