Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6296909 | Ecological Modelling | 2014 | 16 Pages |
Abstract
As bivalve aquaculture continues to grow, it is imperative to understand the spatially-explicit interactions between farmed bivalves and the environment. However, the ability of models to represent a large number of bivalve ecophysiology and environmental variables-in 3-D spatially-explicit domains-has been limited by computational constraints. To overcome some of these computational limitations, we developed an optimized hybrid model by two-way coupling a state-of-the-art Eulerian model (Regional Ocean Modeling System; ROMS) that simulates physical, planktonic and sediment dynamics, with an individual-based model (IBM) that simulates shellfish ecophysiology (SHELL-E). The IBM model efficiently represents sparsely-distributed variables that do not occur in every grid cell of the domain, and simplifies the representation of complex life-history and physiological processes, like spawning events. We applied the hybrid model to a mussel farm in Ship Harbour (Eastern Canada) and compared model results against measurements of physical variables, water samples (chlorophyll, nutrients, oxygen and suspended sediments) and mussel size distributions. The hybrid model reproduced the main dynamics of the physical, planktonic and sediment Eulerian variables, as well as the bivalve ecophysiology IBM variables. Prognostic limitations estimated by the model suggested that mussels were temperature-stressed during parts of the summer, and food-limited during parts of the winter. We also used the hybrid model to estimate the production carrying capacity of the farm and we found that the farm is not overstocked. However, we also found that the estimation of carrying capacity strongly depends on the inferred natural mortality, which is difficult to estimate accurately. This work aims to transfer sound and open-source oceanographic tools (i.e. ROMS) into the applied fields of aquaculture research and management.
Related Topics
Life Sciences
Agricultural and Biological Sciences
Ecology, Evolution, Behavior and Systematics
Authors
Diego A. Ibarra, Katja Fennel, John J. Cullen,