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Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

Author

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  • Forcada, Jaume
  • Malone, Donald
  • Royle, J. Andrew
  • Staniland, Iain J.

Abstract

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90–125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12–16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the “escapement” due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management.

Suggested Citation

  • Forcada, Jaume & Malone, Donald & Royle, J. Andrew & Staniland, Iain J., 2009. "Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries," Ecological Modelling, Elsevier, vol. 220(12), pages 1513-1521.
    • Handle: RePEc:eee:ecomod:v:220:y:2009:i:12:p:1513-1521
    DOI: 10.1016/j.ecolmodel.2009.03.020
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    References listed on IDEAS

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    1. Brent A. Coull & Alan Agresti, 1999. "The Use of Mixed Logit Models to Reflect Heterogeneity in Capture-Recapture Studies," Biometrics, The International Biometric Society, vol. 55(1), pages 294-301, March.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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