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Sardine Sardinops sagax distributed off the west and south coasts of South Africa have traditionally been assumed to comprise a single well-mixed stock for assessment and management purposes. New research, however, lends weight to the possibility of two stocks in this region. A precautionary management approach thus needs to consider the impact of management decisions on the hypothesised two individual stocks as well as on the resource as a whole. As a first step in this process, Bayesian assessments of South African sardine are presented, which compare results for the traditional single-stock hypothesis with those that follow from a new two-mixing-stock hypothesis. Recruits from the west stock are assumed to move to and remain part of the south stock in annual pulses of varying size. This movement is estimated to be appreciable, and to take place from a substantially more productive west stock to the south stock. This immigration makes a greater contribution to the south-stock biomass than do years of above-average south-stock recruitment. Importantly, this two-mixing-stock hypothesis is shown to be consistent with the data available. Further alternative sardine stock-structure hypotheses suggested by the most recent data are discussed.Keywords: assessment, multiple stocks, Sardinops sagax, stock structure, two-mixing-stock hypothesis

The status of the toothfish resource in the Prince Edward Islands region is unclear because CPUE data suggest considerable depletion, whereas catch-at-length information indicates that past catches have had relatively little impact on abundance. A Management Procedure (MP) approach is proposed to provide a sound scientific basis to recommend future TACs in the face of this appreciable uncertainty. Four Operating Models (OMs) reflecting ‘Optimistic’, ‘Intermediate’, ‘Less Pessimistic’ and a ‘Pessimistic’ current status for the resource are developed which take account of the different selectivities of past longline and pot fisheries. These OMs are used for trials of a candidate generic MP which could provide future TAC recommendations for this resource. The MP uses two data sources: the recent trend in longline CPUE and the mean length of the catches made. An MP with control parameter values specified is proposed for implementation based on the results of the trials. Given the importance of an adequate catch rate for the economic viability of the fishery, the choice of control parameter values focused primarily on a reasonable probability of securing a catch rate increase, whatever the current resource status. MP performance is reasonably robust across a range of sensitivity tests, although it does deteriorate in conservation terms if the stock-recruitment curve steepness h is low. These tests also indicate that monitoring of future catch-at-length information would be necessary to guard against a change in selectivity towards greater catches of older fish.

Environmental indices that provide short-term predictions of recruitment have the potential to improve the average yield from highly productive resources that sustain recruit fisheries without an associated increase in risk (of resource ‘collapse'). This is particularly true for cases where a measurement of recruitment is not available until after substantial fishing on this recruitment has already taken place. The South African anchovy Engraulis encrasicolus resource reflects such a situation, and forms the basis for a simulation study to investigate the benefits of using environmental indices to set appropriate Total Allowable Catches (TACs). Simulations, based on a ‘management procedure' (sensu the International Whaling Commission), investigate how such benefits are related to the proportion of variation in recruitment explained by the environmental index. Furthermore, they evaluate to what extent these benefits are compromised by uncertainties related to the degrees of freedom effect (over-fitting data), the selection of explanatory variables (danger of spurious correlations), and errors in the values of explanatory variables (including measurement error). Five recruitment prediction models that incorporate increasing numbers of these uncertainties are investigated. These predictions are used to adjust TACs depending on whether they indicate forthcoming recruitment to be in the top or bottom third of the distribution of possible recruitment values. Results indicate that an environmental index needs to explain roughly 50&#37 or more of the total variation in recruitment (r2 &#8805 0.5) before the management procedure starts showing benefits in terms of the summary performance statistics for risk and average catch. Comparable benefits are possible at a lower r2 value when TAC constraints are removed, but there is then a large associated increase in interannual catch variation. When r2 is low, performance in terms of average catch may prove worse if attempting to take account of an environmental variable in setting the TAC than ignoring it.

Aspects of the potential application of multispecies/ecosystem modelling to advise the management of South African fisheries are discussed. In general, reliable predictive ability from such models is likely to be achieved sooner for top predators, because relatively fewer links need to be modelled. Accordingly, discussion concentrates on the deliberations of scientific workshops on modelling marine mammal – fisheries interactions held by two international marine mammal commissions during 2002. Five questions are posed, and some responses suggested, relating to the development of a framework for multispecies/ecosystem modelling to contribute to South African fisheries management: (1) should such models be used for testing or making decisions; (2) do they appreciably reduce uncertainties associated with single-species models; (3) are whole ecosystem or minimum realistic models more appropriate; (4) what computer software is best suited to implement such approaches; (5) what are the overall cost implications? Caution is expressed that general scientific acceptance of predictive reliability for such models (as required for their use for management) is unlikely in the short term, and will probably require considerable data collection and complex analysis at not insubstantial cost.Afr. J. mar. Sci. 26: 53–61

As a first step in investigating the major predator–prey interactions in the Antarctic, a model describing blue whales Balaenoptera musculus, minke whales Balaenoptera acutorostrata and krill Euphausia superba is developed. Blue and minke whales feed mainly on krill, and they share a similar feeding area near the Antarctic ice edge. In the early 20th century, the large baleen whales in the Antarctic were heavily harvested, some to near extinction. Blue whales were taken for almost 60 years, before being officially protected in 1964. Harvesting of the smaller minke whales commenced only in the 1970s, and the population probably increased during the mid 20th century, likely in response to increased krill abundance following the depletion of the large baleen whales. Recent studies show recoveries of some of these large baleen whale species in response to protection, and also a possible recent decrease in the stock of minke whales as the larger whales recover. This work investigates whether the abundance trends indicated by surveys and other information for these species can be explained by considering only harvesting and the predator–prey interactions between the two whale species and krill. Using historical catch data for blue and minke whales, a simple age-aggregated model including species interactions is fitted to survey abundance estimates. Uncertainties in the abundance estimates and the biological parameters are taken into account in the process by considering plausible ranges for their alues. Abundance trends for the species can broadly be replicated by the model, provided the parameter values show certain features, including (i) that blue whales are able to maintain their birth and krill consumption rates until krill abundance drops to relatively low levels, and (ii) that both minke and blue whales show relatively fast rates of growth if krill is abundant, but that minke growth rate falls more rapidly as krill abundance drops. The model suggests two interesting features of the dynamics of these species. First, a substantial decrease in krill biomass from the 1970s to the 1990s as a result of the preceding rapid increase in minke whale abundance, and hence krill consumption, following the depletion of the larger baleen whales. Second, a recovery of blue whales despite the impact of minke whales on krill abundance and its resultant decrease, because blue whales are better able to tolerate decreased krill abundance. Future projections show a gradual increasing trend in blue whale abundance and a gradual decrease in minke abundance, with large amplitude oscillations superimposed. Long-term monitoring of biological parameters and abundance are essential to provide a basis for verification or otherwise of such predictions. Results presented here should be viewed qualitatively rather than quantitatively. However, for the future, refinement of the model structure and incorporation of age structure, data on some other major predator species that feed on krill and some spatial structure, is under consideration.Afr. J. mar. Sci. 26: 245–259

Ecosystem-orientated thinking is increasingly incorporated into fishery management. Given the complexity of ecosystem processes, there is a need to evaluate the tools used to steer this thinking critically. ECOPATH with ECOSIM (EwE), an aggregate system-modelling package, is currently the most widely employed approach to assess the ecosystem effects of fishing. The basic equations and assumptions, strengths and weaknesses, and the potential of this approach to contribute to practical fisheries management advice are reviewed. Strengths include the structured parameterization framework, the inclusion of a well-balanced level of conceptual realism, a novel representation of predator-prey interaction terms, and the inclusion of a Bayes-like approach (ECORANGER) to take account of the uncertainty associated with values for model inputs. Weaknesses in model structure include the constraining nature of the mass-balance assumption (of ECOPATH) for initiating projections, the questionable handling of life history responses such as compensatory changes in the natural mortality rates of marine mammals, overcompensatory stock-recruit relationships that result from default parameter settings, possible problems in extrapolating from the microscale to the macroscale, as well as some (not too far-reaching) mathematical inconsistencies in the underlying equations. There is a paucity of systematic and stepwise investigations into model behaviour and properties, and users are cautioned against non-critical use of the default settings. An important limitation related to the predominant use of EwE as a “black-box” modelling tool is that some users fail to consider a range of alternative interaction representations. As with all multispecies approaches, the major limitation in applying the EwE approach lies in the quality and quantity of available data. Current EwE applications generally do not adequately address uncertainty in data inputs and model structure. Prudent EwE applications that utilize good data and are based upon rigorous statistical analyses can complement the quantitative predictions of traditional single-species models. They could be particularly useful in some contexts if output in the form of probability distributions encompassing a range of likely ecosystem responses were to be coupled with attempts to extend Operational Management Procedure (OMP) approaches to fisheries management beyond the singlespecies level. In particular, such applications could serve as the operating models of the underlying dynamics that are used for computer simulation testing of OMPs.