Fish production is influenced by many interacting biological, environmental, social, and economic factors. Robust climate impact assessment at a marine cage site must include the complexities, inter relationships and trade-offs between different natural processes and human interventions. As the fish respond to acute or chronic changes in environmental variables, such as water temperature, pH, dissolved oxygen, salinity, and pathogens , they become stressed. Also, farm operations like delousing and net cleaning can increase stress. However, m ost studies consider each or a couple of stressors in isolation due to methodological challenges. Stress causes reduced feed intake and increased metabolism , leading to depressed growth potential, poor disease resistance or mortality of farmed fish. Climate change further challenges production through stressors such as increased temperatures and storms. T here is a need to better understand how multiple stressors (climate, environment, and production) could impact salmon production in the future .
The present study uses system dynamics to model salmon production in the marine environment . Our model is based on one-dimensional, box modelling approach, divided into three components namely, water quality , fish growth and h ealth & w elfare sub-models. The first component deals with dissolved oxygen dynamics, formulated with photosynthesis and air-sea flux as source terms and water column respiration as the ma jor sink term. Three forcing functions drive the dynamics: light and heat from the Sun and wind regime. These are time-dependent inputs with a 1-hour simulation time step to account for daily and seasonal dynamics of the model variables. A baseline simulation of this sub-model describes normal condition of the farm environment in terms of water temperature, dissolved oxygen level , current velocity, etc . Based on this, scenarios of climate-related stressful conditions can be created.
The second and third model components serve together as the response model . Both components interact with each other and with the water quality model and calibrated with farm production data. A flexible nonlinear formulation for fish growth and disease susceptibility is used to allow effective coupling of the three model components. Most growth models of f armed salmon are a function of temperature and body weight, and only few studies have attempted to incorporate the effect o f multiple stressors. W e aim to leverage on the power of system dynamics to capture complex interrelationships in marine aquaculture system for better assessment of climate change impacts and evaluation of adaptation strategies.