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- ItemRestrictedConditioning SMOM using the agreed calendar of observed changes in predator and krill abundance: a further step in the development of a management procedure for krill fisheries in area 48(2008) Plagányi, Éva E; Butterworth, Doug SThe updated version of the Spatial Multi-species Operating Model (SMOM) of krill-predatorfishery dynamics described in an accompanying paper is conditioned using the WG-SAM set of reference observations for Area 48 (the SAM calendar). Results are presented for two implementations of SMOM, one with the time series of krill abundance fixed on input, and the other incorporating an explicit model of krill dynamics. Additional versions of SMOM that may need to be conditioned are discussed. In general the two SMOM implementations are broadly successful in reproducing the direction and timing of observed changes in predator abundance. The main method of conditioning involved estimating a shape parameter (the “steepness”) of the predator-prey interaction formulation. The steepness values estimated suggest that penguins respond sooner than other predators to decreasing levels of krill abundance. Given data on fish catches, the model estimates the starting (1970) fish abundance level, with results suggesting that fish populations in several of the SSMUs are much reduced compared to their 1970 levels. The conditioned operating models presented here constitute a further step towards the development of a spatially-structured Management Procedure (MP) for the krill fishery by contributing to the set of such operating models to be used to simulation test candidate MPs for robust performance. The next step involves agreeing the relative plausibilities (weights) for the different operating models. An outline of suggested future steps in the MP development process is discussed.
- ItemOpen AccessAn integrated approach for the estimation of abundance through a random-effects model(2007) Kitakado, T; Butterworth, Doug S; Okamura, HLet Nay be the true abundance in the a-th survey block in the year y, and let Nˆ ay (P) and Nˆ ay (C) denote estimates of Nay obtained from passing-mode and closing-mode surveys respectively. If abundance estimates in different blocks or years include common parameters such as effective search half-width, then any two of them are correlated, and the method following takes this into account.