Estimating population size and species distribution is essential for fisheries management and conservation. Traditionally, estimates rely on live-capture and visual surveys; however, these approaches are challenging for low density or elusive species and sensitive habitats. Environmental DNA (eDNA) has shown potential to improve fisheries management, offering a sensitive tool for species detection while reducing some of the unintended harm, uncertainties, and cost of traditional approaches. For eDNA to be incorporated into quantitative population estimates, variability in factors such as DNA shedding and decay must be understood. We assess shedding and decay rates for three developmental stages of muskellunge (Esox masquinongy), a recreational species of social and economic importance and an apex predator of conservation priority in the St. Lawrence River. By housing fish at different biomass levels, we attempt to assess how crowding, and underlying behavioral and/or metabolic responses, affects shedding and decay. Additionally, we collected water from spawning bays and compared eDNA detections to live-capture data. Total eDNA shedding rates for muskellunge were similar to values reported in previous studies of freshwater fishes and ranged from 9.92 × 10 3 copies/h/fish for larvae to 1.32 × 10 6 copies/h/fish for juveniles. Adjusting shedding rates for fish mass revealed no significant difference between larvae and juveniles. eDNA decay rates varied between life stages and experimental aquaria, with coefficients ranging from 0.064 to 0.259. We were unable to detect eDNA from hardened embryos even at high density. Muskellunge DNA was quantified in over 27% of samples from spawning bays, including bays where muskellunge were not captured with traditional approaches. The recovery of muskellunge eDNA in quantifiable levels, often in the absence of live capture, highlights the potential for eDNA approaches to supplement muskellunge monitoring and management. eDNA shedding and decay rates estimated here may also aid in interpretation of future data.