CCAMLR

This paper details how FOOSA, an operating foodweb model for evaluating spatially-structured harvest strategies for krill, has been implemented within the EPOC modelling framework. It also shows how the parameters developed for use in FOOSA can be adapted for use in EPOC. The paper has three main parts – an outline of the structure of EPOC, consideration of the general FOOSA structure that needs to be implemented and a description of the implementation of FOOSA in EPOC. The latter section includes the methods used for implementing environmental variability, the krill population, generic predators, the krill fishery and the system for setting catch limits. The process of implementing FOOSA in EPOC has been a useful opportunity to consider the functions needed to represent different processes in a minimal realistic model. A number of revised functions are developed as options to reflect different dynamics that may be present in the krill-predator-fishery system in Area 48. Some of these functions and model structures have been generalised to enable more predators to be included in the food web and to provide flexibility in the number of stages of a predator consuming krill. An important step now in the implementation of FOOSA in EPOC is for this implementation to be reviewed by the developers of FOOSA.

We present a generalised spatially explicit Bayesian statistical catch-at-age population dynamics model (SPM) for developing and investigating plausible spatial movement models, and apply a preliminary development version of this model to Antarctic toothfish in the Ross Sea as an age and maturity state spatial movement model. SPM is an aggregate movement model suitable for use with large numbers of areas, and is implemented as a discrete time-step state-space model that represents a cohort-based population age structure in a spatially explicit manner. The model is parameterised by both population processes (i.e., ageing, recruitment, and mortality), as well as movement processes defined as the product of a set of preference functions that are based on known attributes of spatial location. SPM was designed to be flexible, allow for the estimation of both population and movement parameters based on local or aggregated spatially explicit observations, and optimised for speed. Model validation consisted of three types: implementation checking; development-driven unit tests; and comparative software evaluation. Comparisons with expected output from CASAL and movement processes coded in S+/R were essentially identical, and estimates of example parameters for models implemented in both CASAL and SPM gave essentially identical results. We have also developed a preliminary model for Antarctic toothfish in the Ross Sea and describe the spatial and population structure and processes, data, observations, and likelihoods used to estimate movement parameters. The model was a single sex model that categorised fish as immature, mature, or spawning. Observations included within the model were spatially explicit commercial catch proportions-at-age and CPUE indices. While we caution that model results are preliminary, we note that they appeared reasonable, and suggested immature fish were located in the southern Ross Sea on the continental shelf, mature fish were located on the continental slope, and spawning fish were located on the northern banks of the Ross Sea. The results also suggested that parameterising of movement based on latitude, depth and distance provided a significantly better fit to the observations than a model where depth was ignored. However, further development to the SPM model is required, including processes and observation classes to incorporate year class variability, stock recruitment relationships, tag-release and tag-recapture observations, and maturation state observations. Further, the current implementation of the MCMC algorithm in SPM is only partially complete, and there is some further work on parallelisation algorithms for MCMC that could be investigated. And, in order to address the questions of the adequacy of the Antarctic toothfish Ross Sea assessment model, SPM needs to be modified to allow simulation of observations from underlying movement parameters. Finally, once adequate models for Antarctic toothfish in the Ross Sea have been developed using SPM, the current assessment model (Dunn & Hanchet 2007) would need to be evaluated within a simulation-experiment in order to address current assessment model uncertainties.

Measures are developed which aim to summarise the quality of fishing event, catch, and biological sampling data from a fishing trip. In particular these measures aim to quantify the prevalence of position or time reporting errors, the diversity of catch, the extent to which catch data follow Benford's Law for the distribution of the first significant digit, whether length-frequency data have been collected as expected, and the reliability of length-weight measurements. Individually these measures can assist in assessing which data from a trip should be used in an assessment, and can also guide how these data can best be used.The quality of tag data is hard to assess. A methodology is developed to use data quality measures for other data sets to group trips on the basis of their overall data quality. Ongoing development of this method is intended to provide a consistent basis for selecting the tagging data set that is fitted in an assessment model.The data quality measures illustrate sometimes substantial variation in the quality of particular data sets from different trips in the Ross Sea Antarctic toothfish fishery. Cluster analyses suggests two groups of trips, one of which can tentatively be considered to have better data. Tags released by trips in this latter group have been recaptured at a higher rate than tags released by the other group of trips.

nnovative multivariate statistical modelling techniques make it possible to generate spatially comprehensive species distribution layers from discontinuous biological data, by fitting complex and scale-dependent relationship between species abundance and available environmental data. The resulting species-specific distribution layers have many potential applications. We apply one such method, called BRT (Boosted Regression Trees), to data on the distribution of Oithona similis, a small cyclopoid copepod which is abundant through much of near-surface waters of the Southern Ocean. A large dataset (>19 000 records) of abundances of O. similis were measured during the SCAR Southern Ocean Continuous Plankton Recorder (SO-CPR) Survey. We demonstrate that it is possible to obtain a relationship between both the abundance and the probability of presence of O. similis and the long-term, broad-scale environmental conditions of the location where the CPR sample was taken. These fitted relationships were used to estimate abundances of O. similis through the Southern Ocean. We present a number of methods for investigating the robustness of the prediction. (1) Non-spatial cross validation tested the relationship against data withheld from the fitting. We found that the data withholding of data from the model fitting must be done on a tow by tow basis as there is significant within-tow correlation. (2) Spatial cross-validation withheld data from particular geographic regions from the fitting process and used these subsequently to test the predictive accuracy of the model. These cross-validation methods showed that the fitted relationships explained 28–38% of the total variance in abundance (depending on method of cross-validation). The area under the ROC for the model predicting presence was 0.77 indicating good discrimination between presence and absence. (3) Spatially-resolved measures were used to test how well the environmental space of the predicted area was spanned by the environmental characteristics associated with the biological samples. This method was applied to the individual environmental data layers singly and to multivariate space defined by all environmental data layers together. The multivariate statistic was used to create a “mask” which excluded from prediction those geographic areas of the Southern Ocean where environmental conditions were not well represented by the SO-CPR sample locations.

Four Operating Models (OMs) reflecting an “Optimistic”, “Intermediate”, “Less Pessimistic” and a “Pessimistic” current status for the toothfish resource in the Prince Edward Islands region are developed which take account of the different selectivities of past longline and pot fisheries. These models are used for trials of a candidate Management Procedure (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. A specific MP, with its associated control parameter values, is proposed for implementation based upon 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, though does deteriorate in conservation terms if 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.

A new South Georgia bathymetric dataset (SGDB) was compiled from a variety of primary sources including multi-beam swath bathymetry. Seafloor area (km2 <500m depth) within CCAMLR subarea 48.3 was calculated using this new dataset. Total seafloor area within the region closely matched existing estimates derived from nautical charts (and single point sounding data). However, the reliability of existing seafloor area estimates were found to vary spatially and between different depth strata. The new dataset is considered the most accurate and reliable currently available and should be used for future assessments and for assisting with the stratification of surveys.

Reconstruction of size and weight composition of Antarctic toothfish (Dissostichus mawsoni) from the data on processed commercial catches of longliners using conversion factor

Last two years two different approaches were used for stock assessment of Antarctic toothfish in the Ross Sea. One of them, the CASAL model, (Dunn & Hanchet, 2007; Bull et al., 2007) is mostly based on likelihoods and potentially could insure proper mutual weighting of signals from all available sources of information incorporated into the model. The second one, the TISVPA model (Vasilyev, 2005, 2006; Vasilyev et al., 2006, 2007), takes care about robustness of analysis and includes a number of features aiming at consistent assessment using real (that is usually noisy and containing outliers) data. Besides that, some sorts of data, e.g. tagging data, are used in these models in quite different ways. Comparison of the results shows also that the input to the solution from different sources of information was also quite different: while in TISVPA all sources of data gave rather coherent signals about the stock (Vaslilyev et al., 2007), in CASAL the solution was mostly supported by signals from tagging data (Dunn & Hanchet, 2007), especially strong being the influence of fish tagged in 2006 and caught in 2007, driving the stock estimate down.

1. A dataset of all possible combinations of release nation, recapture nation, release year and recapture year for tags released and recaptured in the same SSRUs on the slope of 88.1 was compiled for the years 2003-2006. Recapture rate was expressed as tags captured/tags released/fish scanned (caught), all in numbers. 2. The overall size of the dataset was 734 combinations of release year, recapture year, SSRU, release nation and recapture nation, with 193 recaptures. Despite this size, fishing has not been consistent enough between nations to allow the analysis to be definitive. In many cases, release or recapture nation effects were not significant. In the cases where significant differences existed, recapture rates were usually highest with New Zealand tagged and recaptured fish, although there was some evidence for suggesting that recapture rates are highest when the fleet and tagging fish is the same. 3. This method could be used to identify groups of nations that have similar reporting rates, for inclusion in the Ross Sea stock assessment.

This paper outlines a method of calculating suitable tagging rates and total allowable catches (TACs) that would be expected to yield a pre-specified precision in a resultant abundance estimate. With respect to the tagging-based abundance estimator, we use the Lincoln-Petersen method and derive a formula that gives the expected coefficient of variation of the abundance estimate in terms of the number of releases and recaptures, which can in turn be expressed in terms of the tagging rate per tonne caught, the catch taken and the postulated underlying exploitable biomass. This relationship is shown to be extremely useful in terms of defining suitable catch levels and tagging rates required to obtain a given precision in the Petersen abundance estimate. To show the reliability of the precision relationship we predict the expected abundance precision using the mark and recapture data for Patagonian toothfish (Dissostichus eleginoides) in sub-area 48.3, and compare this to the precision in the abundance predicted by the integrated stock assessment. To show the usefulness of the methodology to new and exploratory fisheries we estimate the required TAC, for a given range of observed tagging rates, that would give us an abundance estimate with a coefficient of variation of 30% for the Patagonian toothfish stock in sub-area 48.4.