Modelling water temperature dynamics for eelgrass (Zostera marina) areas in the nearshore Scotian Shelf.

Water temperature is an important environmental factor for many ecological processes in coastal ecosystems. Here, we study water temperature dynamics at a set of study sites on the Atlantic coast of Nova Scotia where eelgrass beds are found. The central emphasis is to predict temperature on scales relevant to coastal ecosystem processes using a high-resolution nearshore oceanographic model based on the Finite Volume Community Ocean Model (FVCOM). The model predictions were evaluated against observed temperature time series at six sites for three years from 2017-2019; the evaluation indicates that the model was able to replicate the temperature variation on time scales from hours to seasonal. We also used various biologically tailored temperature metrics relevant to eelgrass condition, including mean seasonal values and variability, daily ranges, growing degree day (GDD), and warm events, to validate the model against time series observations to better understand the temperature regime at the study sites. Frequency resolved Willmott skill scores were >0.7, and the temperature metrics were well predicted with the exception of a bias in GDD at some of the shallow sites. The eelgrass sites have a wide range of temperature conditions. Mean water temperature in the summer differed by more than 7°C between the shallowest and the deepest sites, and the rate of heat accumulation was fastest at shallow sites which had ≥ 12 extreme warm events per year. While the amplitude of the temperature variations within the high frequency band (<48 hr) was greater in shallower sites, temperature changes on meteorological time scales (48 hr to 60 days) were coherent at all sites, suggesting the importance of coast-wide processes. The results of this study demonstrated that our high resolution numerical model captured biologically relevant temperature dynamics at different time scales and over a large spatial region, and yet still accurately predicted detailed temperature dynamics at specific nearshore sites. Thus, the model can provide important insights into coastal temperature dynamics that are potentially useful for conservation planning and understanding the implications of future change. [ABSTRACT FROM AUTHOR]