Predicting eastern oyster (Crassostrea virginica) settlement using growing degree days along the north shore of Nova Scotia, Canada

Abstract

The supply of oyster spat is crucial for the sustainability and development of the oyster aquaculture industry. While hatcheries worldwide are increasing spat production, wild spat collection remains prevalent in Atlantic Canada. Existing monitoring programs aid in wild spat collection but are costly and labour-intensive, relying on fieldwork and expert personnel. To complement monitoring programs, mathematical models with varying complexity have been used to predict the settlement of commercially valuable bivalves. These models consider various environmental parameters such as temperature, winds, tides, and food concentrations. In this study, we explore the prediction of settlement in Eastern oysters (Crassostrea virginica) using a simple Growing Degree Day (GDD) model, which considers only one parameter, temperature. The GDD model estimates Larval Development Time (LDT) based on accumulated heat units (°C·day) above a species-specific minimum temperature threshold for growth. By calibrating the model with literature data and validating it with field observations from four estuaries in Nova Scotia, we aimed to provide a tool for farmers to predict the onset of oyster settlement based on observed seawater temperature. The model effectively predicted the onset of oyster settlement based on observed seawater temperature. The GDD model is a simple and easily implementable tool that can enhance the success of wild spat collection efforts and contribute to the robustness of the oyster aquaculture industry.