BEHAVIOURAL ANALYSIS OF MARINE FISH MOVEMENTS IN RELATION TO ENVIRONMENTAL CHANGE

Many of our projects rely on in-depth analysis of large datasets, often comprising many millions of data points. This data is complex since it comprises spatial movements (horizontal and vertical) in relation to changing environmental fields (temperature, light, prey). Software has been developed to support fast throughput of large data for descriptive and statistical analysis. Using these programs, the data retrieved from electronic data-logging tags can be analysed and from this it is possible to identify particular behavioural signals, such as foraging, from complex and noisy data sets. 

Combined with other techniques such as light-level geolocation and other data such as sea temperature it is possible to determine not only where tagged animals are, both geographically and within the water column, but also gain some insight into what they are doing. For this, we also use individual-based simulation programs to test the advantages of empirical movements versus model random walkers or specialised random walk movements.  Detailed insights about how predators view the environment and why they decide to occupy specific habitats over others available, informs conservation efforts as well as adding to the general understanding of the behavioural ecology of economically and ecologically important marine fish such as sharks, rays, tunas and billfish.

People involved: Nick Humphries, Professor David Sims (MBA).

Funding: NERC Oceans 2025.