Abstract: Norwegian Atlantic salmon aquaculture faces increasingly demanding biological challenges, which may be exacerbated by climate change and rising sea surface temperatures (SSTs). Existing financial literature often simplifies the interdependent and stochastic nature of biological risks, typically modeling important factors such as salmon lice, mortality, and growth as isolated or deterministic variables. Consequently, the economic implications of variability in these biological uncertainties remain less studied than their causes, which are examined extensively within biological literature. This leaves significant gaps in decision making tools available to farmers, investors, and policy makers, both for the current state of the sector, as well as the future under varying climate scenarios. To address these gaps, this thesis builds an SST driven bio-economic model to investigate optimal harvesting strategies and biological impacts for different production areas (PA), under various climate warming scenarios. The framework integrates a stochastic SST process with biological models calibrated to real farm data, representing interdependent variables (growth rates, mortality, lice dynamics) influenced by current farm conditions, such as local SST variations. We employ Least-Squares Monte Carlo (LSM) with Random Forest regression to solve the optimal stopping problem and find the according valuations. Key contributions are threefold. Firstly, the model integrates detailed stochastic biological processes into an economic model for optimal harvesting, which more accurately captures production risk. Secondly, we show that SST driven biological variability is linked to farm profitability and decision making. Thirdly, the research demonstrates substantial economic benefits of monitoring farm conditions and using biological models when evaluating harvesting decisions. Our results indicate that the climate change scenarios considered will have varying economic outcomes for different PAs. Northern and central regions may experience enhanced growth and increased profitability, while southern regions face growth stagnation and extreme mortality, leading to significant economic risks. Despite higher valuations in northern areas, fish welfare mostly decreases along the entire coast under all scenarios. This has further implications for current regulations, which are centered around improving welfare and ecological impacts by dictating mandatory treatments and allowable biomass production based on lice pressure. Our model indicates that increasing salmon mortality levels in southern PAs under climate change may lead to subsequent reduction in lice levels. As such, using only lice pressure to determine regulatory limits may inadequately represent fish welfare and may not effectively support sustainable growth in the industry. Further, although lice related costs due to regulatory treatment constraints increase significantly as the climate changes in norther PAs, valuations increase, indicating that the current regulation might not sufficiently incentivize investments to reduce the lice pressure.

Master’s thesis in Industrial Economics and Technology Management, NTNU
Supervisor: Maria Lavrutich
June 2025

📄 Link on NTNU Open (when available)

Abstract: The severe mortality issues faced by the aquaculture industry, particularly caused by sea lice infestation, restrict growth and value creation. Consequently, the Norwegian Government recently proposed a regulatory change, removing the current framework and introducing a penalty on mortality. The purpose is to more effectively target mortality causes and foster sustainable production and progress by providing more direct incentives and autonomy to each salmon farmer. An alternative production strategy of growing larger smolts on land before transferring to the sea, namely post-smolt production, can potentially be a solution to address the biological challenges. However, there is a need to understand the optimal production strategy and value potential of post-smolt aquaculture. In this thesis, we develop a real options model that incorporates feed price volatility and biological risks in the form of comprehensive mortality dynamics in both the land and sea phases. By considering the impact of stochastic mortality and treatment costs, as well as cost uncertainty, we capture the value of flexibility and upside to uncertainty that traditional valuation methods cannot. Also, through modeling the key tradeoffs between the two phases, we identify that the optimal transfer strategy is at 600 g under most conditions, and the option of dynamic transfer yields a significant value gain of 7.7% per cycle compared to the traditional sea-based farming practice. In response to the recent Government proposal named ”The future of aquaculture: Sustainable growth and food to the world”, the model is designed to handle various penalty scenarios. From the scenario analysis, we conclude that the penalty can be an effective measure to reduce mortality. However, it must be sufficiently strict to enforce the longterm changes in industry practices that policymakers envision.

Master’s thesis in Industrial Economics and Technology Management, NTNU
Supervisor: Maria Lavrutich
June 2025

📄 Link on NTNU Open (when available)