Krill Predator Fishery Model

AERD and International Colleagues Collaborate to Help Manage the Antarctic Krill Fishery

FOOSA Paper Graphic

AERD scientists and colleagues from around the world have invested in a long-term effort to help manage the Antarctic krill fishery by modeling how the major components of the Scotia Sea ecosystem, including predators (baleen whales, penguins, fur seals, and fishes), their main prey (Antarctic krill), and the krill fishery, respond to proposed fishery management actions. The proposed management actions seek to allocate the catch of krill across space in a way that minimizes local impacts on major predator and prey groups, but enables a viable fishery. A major hurdle in understanding the impacts of proposed management actions on the ecosystem is a high degree of uncertainty in the population dynamics of predators and prey on the scale of the Scotia Sea and the mechanisms that link fishery catch to observable predator responses. Our approach to confront this uncertainty was to bookend plausible extremes of the parameterizations for the dynamics of predators and prey and then to measure the risk that specific objectives relating to the productivity of the ecosystem (krill population abundance), the health of the ecosystem (relative abundance of predators), the resilience of the ecosystem (the ability of population to recover after the cessation of fishing), and the ecosystem services to humans (the catch of krill) would not be met for each of the fishing management actions. The results demonstrate that, even under conditions of substantial uncertainty, ecosystem models can help identify management actions that are robust to uncertainty.

The result of this international effort is a paper accepted to the journal Ecological Applications, describing the benefits of ecosystem models in managing fisheries (see abstract below). The code for this model is also available; please click here to download the zipped file.

Published in Ecological Applications (Ecol Appl. 2013 Jun;23(4):710-25):

Decision making for ecosystem based management: evaluating options for a krill fishery with an ecosystem dynamics model

G.M. Wattersa, S.L. Hillb,1, J.T. Hinkea, J. Matthewsb, K. Reidb,2

Abstract. Decision makers charged with implementing Ecosystem Based Management (EBM) rely on scientists to predict the consequences of decisions for multiple, potentially conflicting, objectives. The inherent uncertainty in such predictions can be a barrier to decision making. The Convention on the Conservation of Antarctic Marine Living Resources requires managers of Southern Ocean fisheries to sustain the productivity of target stocks, the health and resilience of the ecosystem, and the performance of the fisheries themselves. The managers of the Antarctic krill fishery in the Scotia Sea and southern Drake Passage have requested advice on candidate management measures consisting of a regional catch limit and options for subdividing this amongst smaller areas. We developed a spatially resolved model that simulates krill-predator-fishery interactions and reproduces a plausible representation of past dynamics. We worked with experts and stakeholders to identify (1) key uncertainties affecting our ability to predict ecosystem state; (2) illustrative reference points that represent the management objectives; and (3) a clear and simple way of conveying our results to decision makers. We developed four scenarios that bracket the key uncertainties and evaluated candidate management measures in each of these scenarios using multiple stochastic simulations. The model emphasises uncertainty and simulates multiple ecosystem components relating to diverse objectives. Nonetheless, we summarise the potentially complex results as estimates of the risk that each illustrative objective will not be achieved (i.e., of the state being outside the range specified by the reference point). This approach allows direct comparisons between objectives. It also demonstrates that a candid appraisal of uncertainty, in the form of risk estimates, can be an aid, rather than a barrier, to understanding and using ecosystem model predictions. Management measures that reduce coastal fishing, relative to oceanic fishing, apparently reduce risks to both the fishery and the ecosystem. However, alternative reference points could alter the perceived risks, so further stakeholder involvement is necessary to identify risk metrics that appropriately represent their objectives.

aAntarctic Ecosystem Research Division, NOAA Southwest Fisheries Science Center, 3333 North Torrey Pines Court, La Jolla, CA 92037-1023, USA.

bBritish Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge, CB3 0ET, UK.

1Corresponding author email:

2Current address: CCAMLR Secretariat, P.O. Box 213, Hobart 7000, Tasmania, Australia