Modelling water temperature dynamics for eelgrass (Zostera marina) areas in the nearshore Scotian Shelf
- Aidin Jabbari,
- Yongsheng Wu,
- Melisa Wong,
- Mike Dowd
Yongsheng Wu
Fisheries and Oceans Canada, Bedford Institute of Oceanography
Melisa Wong
Fisheries and Oceans Canada, Bedford Institute of Oceanography
Mike Dowd
Department of Mathematics and Statistics, Dalhousie University
Abstract
Water temperature is an important environmental factor for the growth of eelgrass (Zostera marina) beds, which provide important nearshore ecosystem services. Here, we study water temperature dynamics in eelgrass beds off the Atlantic coast of Nova Scotia using a highresolution nearshore oceanographic model based on the Finite Volume Community Ocean Model (FVCOM). The model has been evaluated against the observed temperature at six sites for three years from 2017-2019; the evaluation indicates that the model is able to replicate the temperature variation on time scales from hours to seasonal. We also use various temperature metrics relevant to eelgrass condition, including mean seasonal values and variability, daily ranges, growing degree day, and warm events, to both validate the model and better understand the temperature regime at the study sites. Our analyses showed that eelgrass inhabit a wide range of temperature conditions that have previously been shown to influence their performance. The mean water temperature during the summer growing period differs by more than 7°C between the shallowest and the deepest sites. The rate of heat accumulation was faster at shallow sites, and they experienced ≥ 12 extreme warm events year-1. 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 demonstrate that our high resolution numerical model can capture biologically relevant temperature dynamics at different time scales and over a large spatial region and yet still capture detailed temperature dynamics at specific nearshore sites. It therefore has the potential to contribute to conservation planning and prediction of eelgrass response to future climate changes.23 Jan 2024Submitted to ESS Open Archive 24 Jan 2024Published in ESS Open Archive