Term of Award

Spring 2024

Degree Name

Master of Science in Biology (M.S.)

Document Type and Release Option

Thesis (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Biology

Committee Chair

James Roberts

Committee Member 1

Elizabeth Hunter

Committee Member 2

J. Checo Colón-Gaud

Abstract

Human manipulation of river systems has long been a known contributor to the loss of freshwater biodiversity. By accounting for environmental causes of hydrologic variation among rivers, we can better understand how ecoregion mediates flow regimes and forecast species that may be at risk. Presumably, natural variation associated with ecoregion boundaries exerts strong influence on flow regimes, and may mediate relationships between other features (e.g., land use, dam operations) and hydrology. However, such between-ecoregion variation is poorly investigated, particularly at fine spatial and temporal scales. I characterized 10 hydrologic metrics, representing the five key dimensions of the flow regime (magnitude, frequency, duration, timing, and rate-of-change) using 30+ years of daily streamflow data collected at 375 real-time monitoring gages in streams spanning mountain (MT), Piedmont (PD), and coastal plain (CP) ecoregions of the southeastern U.S. Random forest and redundancy analysis models were used to rank the relative importance of stream-size, land-cover, climatic, physiographic, and impoundment conditions in upstream watersheds for predicting downstream flow characteristics, and to assess the transferability of these relationships across ecoregions. Stream size was the “master variable” that consistently influenced flow conditions across all ecoregions and dimensions, whereas the influences of other factors varied considerably among ecoregions. For example, watershed urbanization and topography tended to be the most important predictors of flow conditions in PD streams, whereas carbonitic geology and annual climate conditions tended to be the most important predictors in MT streams, with wetland land cover, climate, and topography tended to be most strongly associated with flow conditions in CP streams. Anthropogenic influences like land use and dams had stronger influences on flow duration, predictability, and rate-of-change than on magnitude or frequency. Notably, duration, predictability, and rate-of-change profoundly influence riverine biota but are not addressed by common streamflow regulations like minimum- or mean-flow management standards. Contrary to predictions, PD streams were not hydrologically intermediate to MT and CP streams. Rather, they exhibited the most-variable base-flow magnitudes, most-frequent yet shortest-lasting high-flow events, and flashiest hydrographs of any ecoregion. My results suggest that attempts to model and manage flow should account for all five flow dimensions, given their presumably strong influence on fish ecology and evolution, but should also account for substantial differences in landscape-flow-ecology relationships among ecoregions.

Research Data and Supplementary Material

No

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