Date of Award

8-2025

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Forestry and Environmental Conservation

Committee Chair/Advisor

Althea Hagan

Committee Member

Kyle Barrett

Committee Member

Debabrata Sahoo

Committee Member

Calvin Sawyer

Abstract

For many years, the United States Army Corps of Engineers (USACE) used the Guidelines for Preparing a Compensatory Mitigation Plan worksheets to guide pre-restoration evaluation and determine post-restoration mitigation credits in South Carolina. Recently, the USACE in South Carolina transitioned to the Stream Quantification Tool (SQT), which provides a more comprehensive assessment framework. Our first objective was to compare these assessment methodologies across different landscape types to determine what the SQT adds to mitigation calculations that were not considered in prior worksheets. We evaluated 16 streams in the Piedmont of South Carolina, with four replicates each of forested, suburban, urban, and agricultural land use types. I calculated Pearson correlation coefficients between the raw SQT and USACE scores, finding strong positive correlation when analyzing all streams collectively (r=0.756, p< 0.001). However, landscape-specific analysis revealed distinct patterns. Forested streams showed strong correlation between methods (r=0.740, p>0.1), confirming both tools similarly assess minimally impaired systems. In contrast, developed landscapes showed weak or negative correlations: urban streams (r=0.178), suburban streams (r=-0.297), and agricultural streams (r=-0.295), with no statistical significance due to small sample sizes but consistent patterns. A consistent pattern emerged across more developed landscapes: the USACE worksheet frequently assigned relatively higher scores to more developed streams compared to the SQT. These differences can be attributed to the SQT's more comprehensive measurement approach and inclusion of parameters not assessed by the USACE methodology, particularly those related to water quality, macroinvertebrates, and detailed hydrological measurements. To isolate the influence of methodological differences, I compared SQT geomorphology scores with total USACE scores, focusing on similar parameter categories. The correlation remained weak and non-significant (r=0.392, p>0.05), with notable outliers including Hunnicutt Creek (urban) and George Creek (urban) that deviated substantially from the expected relationship. This finding suggests that fundamental differences between quantitative measurements and visual assessment persist even when comparing similar parameter categories. Our second objective examined how the physicochemical parameters of the SQT relate to salamander abundance as potential bioindicators of stream health. Some salamanders are sensitive to pollution, with populations flourishing in healthy environmental conditions and declining in the presence of environmental stressors. We sampled salamanders in the same 16 streams where the SQT was implemented, identifying 6 species across 14 streams for a total of 394 individuals. We used N-mixture models to analyze factors influencing abundance while accounting for detection probability. Contrary to my hypothesis that composite SQT physicochemical scores would best predict salamander abundance, individual parameters proved more reliable. Turbidity was the strongest single predictor, with the next best model having a delta AIC of 2.82 and showing significant negative effects. Summer daily maximum temperature also negatively affected abundance. For two-lined salamanders specifically, the combination of nitrogen and turbidity formed the best-supported model. When I removed Three & Twenty Creek (a consistently turbid agricultural stream) from analysis, model rankings changed substantially. The null model became top-ranked, followed by nitrogen, total SQT physicochemical score, and temperature, with much more even support across parameters. This demonstrated how extreme values can drive overall patterns and highlighted the importance of multiple water quality factors when extreme turbidity is absent. Our findings have significant implications for stream assessment and restoration practices. The differences observed between assessment tools suggest that reliance solely on visual assessment methodologies might underestimate restoration needs or mitigation requirements, particularly in developed watersheds. The SQT's greater sensitivity to impairment in human-altered landscapes provides more comprehensive evaluation of stream quality. For salamander conservation, management practices should prioritize erosion control, sedimentation reduction, and preservation of riparian shading to maintain suitable conditions. We recommend that stream assessment method selection be context-dependent, based on land use type and application of results. For salamander monitoring as part of the SQT's biology component, we suggest focusing particularly on turbidity and temperature as critical parameters affecting salamander abundance. As human modification of landscapes continues to increase, the ability to accurately assess stream conditions across diverse settings becomes increasingly critical for effective environmental management and conservation.

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