Environmental DNA (eDNA) analyses allow for the detection of species by isolating and analyzing genetic material shed into the environment. Despite their growing use, eDNA methods remain constrained by uncertain detection probabilities, limited calibration with traditional monitoring, signal variability, and inconsistent methods. This dissertation explores the functional application of eDNA for ecological monitoring and fisheries management across three complementary studies. In Chapter Two, I used eDNA metabarcoding to assess aquatic vertebrate and diadromous fish biodiversity after the Elm Street Dam removal in the Jones River watershed. From 2020 to 2021, species richness declined at downstream sites, while upstream sites gained richness but lost functional diversity. Multivariate statistical analyses revealed significant temporal and spatial differences in community composition, consistent with early-stage ecological restructuring. In Chapter Three, I developed mechanistic and statistical models to estimate river herring abundance across three connected ponds using log-transformed eDNA concentrations from ten synchronized sampling events. A single electronic resistivity fish counter in the most downstream pond served as an anchor for calibration. eDNA concentrations tracked two-day and cumulative fish counts well (site-level R² = 0.94). Predictive accuracy declined in a watershed-scale linear model (R² = 0.58), but improved when a linear mixed model was used that accounted for basin volume and distance from the e-count station (R² = 0.76). I then developed a mechanistic model incorporating site-specific scaling based on hydrological distance, basin surface area, and DNA decay. The best-performing models, using uniform sensitivity-scaled exponents (α = 0.01) at site (R² = 0.98) and watershed (R² = 0.97) scales demonstrated eDNA’s potential to estimate fish abundance at sites unsampled by traditional methods using a single traditional anchor count. In Chapter Four, I compared eDNA quantitative polymerase chain reaction (qPCR) estimates with four traditional fish relative abundance monitoring methods across seven case studies. eDNA aligned closely with resistivity counters, electrofishing, and video surveys, but not fyke nets. A multispecies occupancy model highlighted higher detection certainty for eDNA approaches and exposed traditional method-specific detection biases. Together, these studies demonstrate eDNA’s utility for scalable, quantitative ecological monitoring, advancing data-driven frameworks for biodiversity assessment and resource management in aquatic ecosystems.