Parameterization of an optical model to refine seagrass habitat requirements in an urbanized coastline

Accurate simulation of the underwater light climate is a requirement to understanding and predicting the ecological benefits from initiatives to manage land-derived inputs of nutrients and suspended solids to the coast. The goal of this work was to derive an empirical light model to be used in the water quality module of a coupled physical-biogeochemical model, developed to estimate habitat suitability for seagrasses in a metropolitan region (Adelaide, South Australia) affected by wastewater and stormwater discharges. Paired measurements of water quality and the vertical attenuation coefficient (K_d) obtained at six fixed sites between summer and winter were used in a multiple regression analysis to optimize local specific attenuation coefficients for coloured dissolved organic matter (CDOM) (2.623 cm m⁻¹, measured as absorption at 254 nm), chlorophyll a (0.071 m² mg⁻¹), suspended solids (SS) < 63 μm (0.032 m² g⁻¹) and >63 μm (0.001 m² g⁻¹). The fitted relation explained 65% of the variability in K_d, with a standard error of 0.10 m^-1. This error is small considering a mean K_d value of 0.35 m^-1, varying between 0.12 and 0.89 m^-1. Fine SS contributed on average 6 times more light attenuation (34%) than coarse SS (6%). CDOM was the second largest contributor to K_d (36%). The contribution of chlorophyll a to K_d (13%) was only marginally higher than the background imparted by seawater (12%). In shallow waters (3–5 m), K_d values were >0.4 m^-1 and heavily influenced by sediment resuspension. In deeper waters (12–15 m), K_d values decreased and were dominated by CDOM. The light climate in the north of the study region was also heavily influenced by CDOM inputs, not only from point sources but also from mangroves and seagrass beds. This analysis suggests the control of fine SS as the most powerful management option to deter further nearshore seagrass losses in the region, and promote seagrass restoration.