PhD Courses in Denmark

Single-stock assessment models remain the foundation for fisheries management advice globally. Core management decisions rely on robust, well-documented single-stock assessments estimating stock status, providing catch advice, and evaluating management strategies. At the same time, effective fisheries management faces global challenges due to the complexity of ecological, technical, economic, and sociological interactions which are seldom captured by current advisory frameworks. The single-stock approaches may not account for the broader implications of data-poor stocks, mixed fisheries – with multiple target and bycatch species - or dynamic fleet behavior and ecological interactions. Technological developments, economic incentives, and environmental variability complicate the system, calling for complementary tools addressing multidimensional challenges. These interactions impact the dynamics and development of both stocks, fisheries, and the ecosystem. This course provides students with a solid foundation in modern fisheries management, with focus on the quantitative methods used to assess fisheries systems. Students gain experience with two recognised stock assessment models and learn to validate and interpret assessment results using international good practices. The course also equips students to analyse broader management challenges, including mixed fisheries, bio-economic interactions, and ecosystem-based approaches using new and internationally implemented fisheries, multi-species, and broader ecosystem-based management evaluation models. All models enable assessment of current status, future projections and forecasts, as well as Management Strategy Evaluation (MSE) of different management options. Through lectures, practical exercises, and simulations, students develop the skills to analyse stock dynamics, evaluate management scenarios, consider risks, and understand the ecological, technical, and socio-economic complexities of real-world fisheries systems.

A student who has met the objectives of the course will be able to:

• Describe the development of fisheries and ecosystem based management, including advisory processes, quantitative methods, and institutional frameworks.
• Explain the complexity of fisheries management systems, accounting for multiple objectives, options, and risks.
• Apply state-of-the-art assessment models used by ICES to analyse stock status and characterise stock dynamics.
• Evaluate and validate stock assessments in line with good practice guidelines, benchmark criteria, and methods for quantifying uncertainty.
• Simulate future stock dynamics and fishery yields under alternative harvest control rules and management scenarios using short-and medium-term forecast tools.
• Define homogeneous and mixed fisheries, including technical interactions, and analyse fleet- and stock-specific fishing mortality for target and by-catch species based on fleet-specific effort, efficiency, behavior, and selectivity.
• Use state-of-the art spatially explicit bio-economic and vessel-based management strategy evaluation tools to assess fisheries impacts of scenarios of maritime spatial planning on fleets, stocks and the seabed.
• Evaluate the role of advanced multi-species and ecosystem models in fisheries advice, and evaluate the integrated impacts of fishing, environmental drivers, and species / ecosystem interactions on resource dynamics.
• Design a novel harvest control rule and evaluate its performance by means of management strategy evaluation. Evaluate bio-economic effects of management scenarios, options and strategies under different management systems before

The course introduces students to the principles and practice of modern fisheries management, with a focus on conceptual quantitative fisheries management evaluation methods and their role in scientific management advice. It begins with an overview of the international development of fisheries and ecosystem-based management systems, including their conceptual foundations, institutional frameworks, and advisory processes. It will give understanding of the complexity in fisheries management, decision making processes (policies, governance, stakeholders), and management options and advice in context of multiple objectives and risks with respect to (ecological and socio-economic) sustainable management of the fisheries and their resources. The course provides hands-on training in the application of two advanced single-stock assessment models used within the ICES advisory framework: a surplus production model (SPiCT) and an age-structured stochastic model (SAM). Students will learn to estimate stock abundance, fishing mortality, and stock status relative to reference points such as FMSY and BMSY from time series of catch and survey data. Model diagnostics, uncertainty quantification, and best practices for validating stock assessments are key parts of this training. Beyond single-stock assessments, the course introduces students to simple and advanced methods integrating the complexity of fisheries systems, including mixed fisheries and multi-fleet dynamics. Students will define and analyze technical interactions between target and bycatch species and evaluate fishing mortality by fleet using data on effort, selectivity, and behavior. The course also provides hands-on-training in spatially explicit bio-economic and vessel-based MSE tools, which combine logbook and VMS (satellite tracking) data. These models are used to assess the potential impacts of maritime spatial planning scenarios - such as wind farm closures - on fishing fleets, target stocks, and the seabed according to ecological and economic sustainability. Finally, students are introduced to advanced ecosystem-based evaluation methods that integrate biological interactions, environmental forcing (e.g., climate change, eutrophication), and multi-species dynamics. These components allow students to explore the broader ecological and socio-economic implications of different management strategies before implementation. Throughout the course, students will work with both simple and advanced models in data-rich and data-poor contexts, gaining skills to critically evaluate the trade-offs, risks, and sustainability of alternative management options. This PhD version of the course will furthermore enable the students to design a novel harvest control rule and evaluate its performance by means of MSE.