Estimating nitrogen loading and far-field dispersal potential from background sources and coastal finfish aquaculture: A simple framework and case study in Atlantic Canada

Far-field nutrient impacts associated with finfish aquaculture have been identified as a topic of concern for regulators, managers, scientists, and the public for over two decades but disentangling aquaculture impacts from those caused by other natural and anthropogenic sources has impeded the development of monitoring metrics and management plans. We apply a bulk, steady-state nitrogen loading model (NLM) framework to estimate the annual input of Total Dissolved Nitrogen (TDN) from point and non-point sources to the watershed surrounding Port Mouton Bay, Nova Scotia (Canada). We then use the results of the NLM together with estimates of dissolved inorganic nitrogen (DIN) loading from a sea-cage trout farm in the Bay and progressive vector diagrams to illustrate potential patterns of DIN dispersal from the trout farm. Our estimated anthropogenic nitrogen contribution to Port Mouton Bay from all terrestrial and atmospheric sources is ∼211,703 kg TDN/year with atmospheric deposition accounting for almost all (98.6%). At a stocking level of ∼400,000 rainbow trout, the Port Mouton Bay sea-cage farm increases the annual anthropogenic TDN loading to the bay by 14.4% or 30,400 kg. Depending on current flow rates, nitrogen flux from the trout farm can be more than double the background concentrations of TDN near the farm site. Although it is unlikely that nitrogen loading from this single fish farm is saturating the DIN requirements of the entire bay, progressive vector diagrams suggest that the dispersal potential may be insufficient to mitigate potential symptoms of eutrophication associated with nitrogen fluxes. We present an accessible and user-friendly tool for managers to estimate baseline nutrient loading in relation to aquaculture and our use of progressive vector diagrams illustrate a practical and simple method for characterizing potential nutrient dispersal based on local conditions and spatial scales. Our study joins numerous studies which have highlighted the need for more effective monitoring and assessment methods to improve the detection of aquaculture effects at far-field scales and to assess those effects in relation to other natural and anthropogenic factors impacting coastal habitats.