Estuarine exchange flow regulates all aspects of estuarine biogeochemical processes, especially residence time. However, the motivation for residence time studies is biogeochemistry, and this can be influenced by much more than the exchange flow, depending on the tracer in question. In this study, we analyzed realistic simulations from a coupled physical-biological model to quantify the volume-integrated budgets of heat, total nitrogen (TN), and dissolved oxygen (DO) in the Salish Sea and its inner basins. The goal was to determine the relative importance of the exchange flow compared to other processes. The three budgets reveal that the exchange flow always plays a leading role, with a clear annual cycle, but is balanced by a different collection of other terms in each case. The heat budget is primarily a balance between the exchange flow cooling and atmospheric heating, with both terms peaking in the summer. The time variation of TN is dominated by the exchange flow, but the annual average is dominated by sources from rivers and wastewater and a sink from benthic denitrification. The DO budget has the most complex set of influences, with sinks due to the exchange flow and respiration, balanced by sources from photosynthesis and air-sea transfer. In all three budgets the difference between the inflow and outflow tracer concentrations, greatly affected by coastal wind conditions, determines the distinct seasonality of the exchange flow budget terms. In contrast, variation of the exchange flow volume transport plays a minor role.

Environmental DNA (eDNA) analysis is a technique for detecting organisms based on genetic material in environments such as air, water, or soil. Observed eDNA concentrations vary in space and time due to biological and environmental processes. Here we investigate variability in eDNA production and loss by sampling water adjacent to a managed population of non-native cetaceans on a near-hourly timescale for 48 hours. We used diverse sampling approaches and modeling methods to describe time variability in observed eDNA concentrations and then compare the magnitude of production and loss mechanisms. We parsed production and loss in a Bayesian process model, and compared biological and physical loss rates using a decay experiment and a physical transport-and-diffusion tracer model. We then evaluated eDNA concentrations along a transect away from the animal enclosure in light of model parameter estimates. We conclude that eDNA production is best conceptualized using a time-varying mixed-state model and biological losses are small relative to physical losses in the marine environment. Because physical loss is unsteady and nonlinear, tracer models are especially helpful tools to estimate it accurately.