CCAMLR

Since 2002, the Working Group on Ecosystem Monitoring and Management has been undertaking a work program to develop a management procedure for krill fisheries. To date, this has primarily focussed on subdividing the region-wide krill catch limit in the southwest Atlantic into small-scale management units through a number of workshops. Computer simulations are being used by WG-EMM to evaluate the costs and benefits to achieving conservation and fishery objectives of the six different strategies for undertaking the subdivision. This paper further elaborates the Ecosystem Productivity, Ocean, Climate modelling framework. In particular, it outlines the general considerations for designing a simulation environment for evaluating the strategies for subdividing the krill catch limit and, on the basis of these considerations, provides an update of the conceptual structure of EPOC and outlines the templates developed for EPOC to facilitate this work.

A useful way of testing assessment methodology and related decisions is through the framework of management strategy evaluation and the simpler form of assessment strategy evaluation. Such a framework uses an operating model of the system to generate data against which the assessment model, or the entire management system can be evaluated against a number of suitably chosen performance measures. This paper defines the term Assessment Strategy Evaluation (ASE) and provides a practical framework for carrying out such an evaluation. The framework is implemented in the R programming language and the technical details and decisions made in the formulation of this framework are included in this paper. Initial testing of this framework with respect to the Patagonian Toothfish Dissostichus Eleginoides Fishery in Division 58.5.2 is described.

An updated version of the Spatial Multi-species Operating Model (SMOM) of krill-predator-fishery dynamics is described. This has been developed in response to requests for scientific advice regarding the subdivision of the precautionary catch limit for krill among 15 small-scale management units (SSMUs) in the Scotia Sea, to reduce the potential impact of fishing on land-based predators. SMOM has been revised from the original version presented in Plagányi and Butterworth (2006a) in three main ways: 1) Accounting for seasonality; 2) Explicitly modelling fish and whales in addition to penguin and seal predators; and 3) Addition of an alternative movement model based on the results from the OCCAM model.
This modelling framework provides an example of a method for bounding some of the uncertainty associated with multi-species models used for management. Results are presented as probability envelopes rather than in point estimate form, giving a truer reflection of the uncertainty inherent in outcomes predicted on the basis of multi-species models as well as highlighting how such probability envelopes could be narrowed given improved data on key parameters such as survival. Results are useful for evaluating different spatial allocations of krill catches. An example is given of how such a framework can be used to develop a management scheme which includes feedback through management control rules.

We modelled the ray population at South Georgia using a surplus production model implemented in a Bayesian framework. Catch and CPUE data were reconstructed for the time series 1985 – 2006 from a variety of sources, and included the consideration that since 2004 the practice of cutting rays off lines at the water surface should have increased survivorship of discarded rays, although this survivorship has been found to decrease as depth of fishing increases. Our analysis is concentrated on catches deeper than 800m, and we have assumed that the majority of catches were of the Amblyraja variant species previously described.
The assessment indicated that the data were informative with respect to carrying capacity but not with respect to r, the intrinsic rate of growth of the ray population. We chose a conservative, low value of r thought to be representative of long-lived rajids, but conducted sensitivity tests with higher and lower values. The assessment suggests that the level of mortality currently experienced by the population is sustainable, and that currently the population is well above Bmsy. Whilst current catches appear not to be significantly impacting the ray population, trends to deeper water fishing and increasing numbers of autoliners (whose catch rates of rays is greater than Spanish gear longliners) should continue to be observed closely. Future analyses should make use of the increasing accuracy and duration of CPUE data and the results of an ongoing mark-recapture experiment for rays at South Georgia.