Predator-prey relationships in Alaska fisheries management
In the world of fisheries management systems, many do not account for predator-prey interactions that scientists know can have big impacts on the dynamics and available biomass of commercially targeted species.
For his dissertation work as part of the Gulf Of Alaska Climate Integrated Modeling Project (GOA-CLIM), Grant Adams from the Punt Lab at SAFS, has been developing multi-species population dynamics models for the Gulf of Alaska. Focusing on four species of commercially important fish in this region – cod, pollock, arrowtooth flounder and pacific halibut – Grant has been examining their predator-prey interactions in the Gulf of Alaska.
The model is in the similar sphere to the Atlantis model worked on by Alberto Rovellini but is relatively more simple in terms of being able to use observed data from NOAA and the International Pacific Halibut Commission (IPHC) in the region to inform the model.
So which species are prey, and which are predators? Pollock has been observed as the main prey species among the four, and researchers are interested about the impacts of predation on this very important fishery and how the different species interact with each other. The Alaska pollock fishery is one of the most valuable in the world, worth $383 million in 2021.
The first half of Grant’s work was geared towards developing the model for the Gulf of Alaska and understanding predator-prey interactions more deeply, including the implications on future dynamics of pollock, as their population is heavily impacted by how many predators are in the system. The model used is called CEATTLE (Climate-Enhanced, Age-based model with Temperature-specific Trophic Linkages and Energetics), first developed for the Bering Sea by Kirstin Holsman at the NOAA Alaska Fisheries Science Center.
The second part of his work focused on fisheries management and how these models can be used to evaluate how robust the current management system is to predator-prey dynamics and how management advice from multi-species models compares.
Using a simulation approach called Management Strategy Evaluation, this involves simulating data from multi-species models accounting for predator-prey interactions, applying the current management system used, which in this case, does not consider predator-prey relationships, and then evaluating management performance.
This sheds insight into how biased the perception and management of fisheries are. How many fish do we think are in the system, is it productive or less productive, is over or under-harvesting in the fishery taking place as a result?
The next step in the process is to incorporate external factors such as climate change into these models, and see what projections are made for the future for fish abundance. One of the key aims of developing multi-species models that include interactions like predator-prey relationships is to evaluate if such models can better achieve management objectives under climate change. Leaving enough fish in the system for other animals, sustaining fisheries, ensuring reliable catches without too much variability, and securing enough catch to maintain local communities, are all things at stake.
Previously working in Peru with the Peace Corps, Grant was inspired to work in fisheries management when he observed the big impacts of El Nino and other climate factors on fisheries in that region. Enjoying working with the quantitative side and the use of data and statistics, his journey brought him to SAFS where he it’s exciting to work in a field that combines fisheries and climate, and is likely to have an important impact in the future.