Fish Stock Dynamics and Management
DTU Aqua's research develops models and solutions to support the sustainable use of fish resources within an ecosystem-based management framework.
Research in fish stock dynamics and management
Human pressures and climatic and environmental changes are driving shifts in the distributions and productivity of fish, making adaptive ecosystem-based management essential.The research area Fish Stock Dynamics and Management works to strengthen the foundation for healthy self-sustaining fish stocks by developing innovative data-driven solutions to support ecosystem-based fisheries management and conservation efforts across sectors in coastal as well as offshore ecosystems.
Contact
The multiple stressors on aquatic ecosystems make adaptive ecosystem-based management crucial. Ecosystem-based management is an integrated approach that incorporates the entire ecosystem and all types of stressors into management decisions to safeguard marine ecosystems and ensure the sustainable use of marine resources.
How the transition to ecosystem-based fisheries management should be realized in practice is a huge scientific and societal challenge, and this is the main focus of the research area Fish Stock Dynamics and Management at DTU Aqua.
Some of the underlying challenges are to reconcile fisheries management with broader conservation goals while addressing data gaps, especially for coastal habitats, non-target species, and vulnerable ecosystems and habitats. Also, the increased use of closed areas at sea is likely to conflict with conventional stock assessment-based advice, calling for new solutions that are both ecologically sound and usable for decision-making.
Our work combines models, statistical data analysis, and field studies to address complex challenges within fisheries management and conservation. We integrate ecological processes such as species interactions, species-habitat associations, and environmental change into analyses, and we quantify uncertainties to ensure the robustness of our advice to authorities.
Multispecies Models
Multispecies models consider several species simultaneously, their interactions, and the food web, rather than assessing the status of a single fish stock in isolation. An example is models of predator–prey interactions. We continuously enhance the multispecies and food-web models by improving their applicability, transparency, and integration of biological drivers. This lays the groundwork for developing multispecies reference points which can help us move away from the single stock approaches and towards an ecosystem-approach to managing fish stocks.Contact
Nis Sand Jacobsen Senior Researcher nsja@aqua.dtu.dk
Spatiotemporal Models and Tools
Spatiotemporal models address the movement of fish stocks in the sea, connectivity, and shifting distributions. This knowledge is used, among other things, to support spatial management advice, including decisions on area closures and other forms of human use. The work also addresses challenges related to vulnerable and data-poor species and combining diverse spatial data sources, such as surveys, fisheries data, oceanographic information, and habitat maps.Contact
Tobias Mildenberger Researcher tobm@aqua.dtu.dk
Management Strategy Evaluations
The management of fisheries and marine ecosystems must be evaluated to determine whether the results are as intended. Therefore, we develop and apply tailored Management Strategy Evaluations (MSEs) to explore trade-offs and uncertainties in harvest strategies, area closures, and ecosystem changes. This includes developing dynamic reference points that respond to productivity drivers, such as climate, habitat quality, population structure, and population connectivity.Contact
Mollie Elizabeth Brooks Senior Researcher molbr@aqua.dtu.dk
Coastal Fish and Their Habitats
Coastal marine habitats are key nursery areas and feeding grounds for many fish. We study the environmental and ecological drivers shaping the coastal ecosystems and their links to adjacent offshore waters. This includes examining how ecosystem processes should shape the way fish populations are understood and managed to ensure that the limited coastal space and living resources are not overexploited. However, fish data from coastal areas are often scarce. To address this, we examine how data from trawl surveys, fisheries, citizen science, and cameras can be used to monitor fish species and their habitats. We also draw on historical datasets to tackle shifting baselines.Contact
Ole Henriksen Researcher ohen@aqua.dtu.dk
Elliot John Brown Researcher elbr@aqua.dtu.dk
Internationally, we contribute to a wide range of working groups under ICES (International Council for the Exploration of the Sea) and advisory bodies at global (FAO), European and regional (HELCOM) levels. Our work supports the implementation of the EU Common Fisheries Policy, the ecosystem-based management agenda, and broader EU fisheries and water frameworks.
Nationally, our research provides advice to authorities, mainly the Ministry of Environment, through model development, reference point evaluations, scenario testing, requested topic reviews, and recommendations.
Furthermore, engaging with stakeholders of all sorts and effectively communicating data, assessments, and insights to broader audiences form a vital foundation of this research area.
External collaboration
The research area Fish Stock Dynamics and Management is strongly engaged in research collaboration with other researchers nationally and internationally, particularly in the EU, Scandinavia, and the US and to a lesser extent with countries in other parts of the world, i.e., Tanzania, Australia, and New Zealand.
These collaborations take place via projects and working groups hosted by international advisory bodies such as ICES-FAO workshops.
Internal collaboration
Internally at DTU Aqua, we mainly collaborate with the following research areas:
- Population Genetics
- Modelling of Aquatic Living Systems
- Fish Biology
- Population Dynamics and Stock Assessments
Projects, publications & people
Organization
The research area is organizationally affiliated with:
