A fundamental model for oxygen consumption of Atlantic salmon.

Predicting oxygen availability in Atlantic salmon farms is challenging, but digital simulations that couple bioenergetics and hydrodynamics show great promise. Robust simulations depend on reliable estimates of oxygen demand, yet previous empirical models offer limited accuracy. Here, we present a refined fundamental model for Atlantic salmon oxygen consumption rate (MO2) as a function of three readily measurable parameters: body weight, water temperature, and relative swimming speed. Retaining the established framework of Grøttum and Sigholt (1998), we refined the model through an improved coefficient estimation approach and a methodologically rigorous dataset derived from group swim tunnel respirometry measurements on 718 fish across seven experiments. Model coefficients were re-estimated using log-linear regression fitted via nonlinear mixed-effects, substantially improving parameterisation and yielding a model that explains 80% of the observed variation in MO2:[Formula: see text], where MO2 is oxygen consumption rate (mg O2 kg− 1 h− 1), W is body weight (kg), T is water temperature (°C), and U is relative swimming speed (body lengths s− 1). Our model delivers reliable estimates of Atlantic salmon oxygen demand across relevant farming conditions (0.2–3.4 kg, 3–18 °C, 0.3–2.8 body lengths s− 1). With broad utility in both research and industry, our model supports the development of more precise, data-driven strategies for modern salmon aquaculture.