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Marine Ecology Progress Series

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MEPS 466:275-291 (2012)  -  DOI:

Agent-based modeling of the dynamics of mammal-eating killer whales and their prey

J. Ward Testa1,2,*, Kenrick J. Mock3, Cameron Taylor3,4, Heather Koyuk3,5, Jessica R. Coyle3,6, Russell Waggoner3,7

1National Marine Mammal Laboratory, Alaska Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, Washington 98115, USA
2Biological Sciences Department, University of Alaska Anchorage, Anchorage, Alaska 99508, USA
3Department of Mathematical Sciences, University of Alaska Anchorage, Anchorage, Alaska 99508, USA
4Present address: 3604 E 19th Ave, Anchorage, Alaska 99517, USA
5Present address: 12311 32nd Ave, NE #2, Seattle, Washington 98125, USA
6Present address: Department of Biology, University of North Carolina, Chapel Hill, North Carolina 27599, USA
7Present address: 2701 W 32nd #4, Anchorage, Alaska 99517, USA

ABSTRACT: The role of mammal-eating, or transient, killer whales Orcinus orca in the decline of various marine mammal populations in Alaska is controversial and potentially important in their recovery. Classical predator–prey models are insufficient to describe the dynamics of a single predator on the number of prey types known for these predators, and there are few population-level data that could be used to parameterize such models. As an heuristic framework for this more complicated system, we developed an agent-based model of killer whales with plausible energetics and behavior. We calibrated and validated the model using single-prey scenarios (a community of generic ‘Seals’) against published expectations for prey consumption rates, killer whale group dynamics, and demography. We then explored the emergent properties of single-prey models and of 3-prey models using the ‘Seals’ as primary prey, a generic small population of ‘Sea Lions’, and seasonally available large ‘Whales’. The single-prey model gave results that were intuitively reasonable and responsive to underlying parameters but were also sensitive to encounter/killing rates, as expected in classic predator–prey models with similar parameters. However, the dynamics included long time lags (~30 yr) with strong shifts in predator age structure and vital rates. In multi-prey scenarios in which the importance of seasonally available large whale prey was manipulated, large whale prey had the potential to augment killer whale numbers somewhat but had a minimal effect on the overall dynamics, whereas perturbing the carrying capacity of the primary prey created strong numeric shifts in killer whale population size and consequent indirect effects on both alternate prey. No predictive utility is suggested due to the absence of such elements as spatial realism, explicit prey-switching and more realistic prey structure, but the models suggest that we consider more complicated numerical dynamics of killer whales in discussions of their impact on prey.

KEY WORDS: ABM · Individual-based models · IBM · Orcinus orca · Population dynamics · Predator–prey

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Cite this article as: Testa JW, Mock KJ, Taylor C, Koyuk H, Coyle JR, Waggoner R (2012) Agent-based modeling of the dynamics of mammal-eating killer whales and their prey. Mar Ecol Prog Ser 466:275-291.

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