¬FISH DISTRIBUTIONS IN LAKE ONTARIO’S EASTERN BASIN AND THE UPPER ST. LAWRENCE RIVER: AN ANALYSIS USING GIS AND OCCUPANCY MODELLING TECHNIQUES

Predictive models of species distributions are important tools for fisheries management. Unfortunately, these predictive models can be difficult to perform on large waterbodies where fish are difficult to detect and exhaustive sampling is not possible. In recent years the development of Geographic Information Systems (GIS) and new occupancy modelling techniques has improved our ability to predict distributions across landscapes as well as account for imperfect detection. I surveyed the nearshore fish community at 105 sites between Kingston, Ontario and Rockport, Ontario with the objective of modelling geographic and environmental characteristics associated with littoral fish distributions. Occupancy modelling was performed on Round Goby, Yellow perch, and Lepomis spp. Modelling with geographic and environmental covariates revealed the effect of shoreline exposure on nearshore habitat characteristics and the occupancy of Round Goby. Yellow Perch, and Lepomis spp. occupancy was most strongly associated negatively with distance to a wetland. These results are consistent with past research on large lake systems indicate the importance of wetlands and shoreline exposure in determining the fish community of the littoral zone. By examining 3 species with varying rates of occupancy and detection, this study was also able to demonstrate the variable utility of occupancy modelling.

Subfilter-scale Stress Modelling for Large Eddy Simulations

A subfilter-scale (SFS) stress model is developed for large-eddy simulations (LES) and is tested on various benchmark problems in both wall-resolved and wall-modelled LES. The basic ingredients of the proposed model are the model length-scale, and the model parameter. The model length-scale is defined as a fraction of the integral scale of the flow, decoupled from the grid. The portion of the resolved scales (LES resolution) appears as a user-defined model parameter, an advantage that the user decides the LES resolution. The model parameter is determined based on a measure of LES resolution, the SFS activity. The user decides a value for the SFS activity (based on the affordable computational budget and expected accuracy), and the model parameter is calculated dynamically. Depending on how the SFS activity is enforced, two SFS models are proposed. In one approach the user assigns the global (volume averaged) contribution of SFS to the transport (global model), while in the second model (local model), SFS activity is decided locally (locally averaged). The models are tested on isotropic turbulence, channel flow, backward-facing step and separating boundary layer. In wall-resolved LES, both global and local models perform quite accurately. Due to their near-wall behaviour, they result in accurate prediction of the flow on coarse grids. The backward-facing step also highlights the advantage of decoupling the model length-scale from the mesh. Despite the sharply refined grid near the step, the proposed SFS models yield a smooth, while physically consistent filter-width distribution, which minimizes errors when grid discontinuity is present. Finally the model application is extended to wall-modelled LES and is tested on channel flow and separating boundary layer. Given the coarse resolution used in wall-modelled LES, near the wall most of the eddies become SFS and SFS activity is required to be locally increased. The results are in very good agreement with the data for the channel. Errors in the prediction of separation and reattachment are observed in the separated flow, that are somewhat improved with some modifications to the wall-layer model.