ABSTRACT
Commercial žsheries for abalone and rock lobster (and many other invertebrates) often suffer from the fact that the species concerned are difžcult or impossible to age using readily available technology. Nevertheless, many of these species are the basis of valuable žsheries, and thus require an assessment of some kind to assist with the adequate management of each stock. The use of age-structured models for assessing these species is compromised, so alternatives must be considered. It would be possible to use a surplus production model, which does not require age-structured information (see Example Boxes 8.4 and 8.5 for an example with abalone). However, an alternative that permits the use of more than just catch and catch rate data would be to use a size-or stage-structured model, with the basic form of these models described by Sullivan et al. (1990) and Sullivan (1992); also see Caswell (2001), and a fully developed model for abalone is described by Breen et al. (2003). Such models follow the fate of the numbers in a set of size classes, which contrasts with age-structured models that follow numbers in each age class or cohort through time. A major difference is that the size classes are not related to specižc cohorts, and so the growth of individuals passing from one size class into another is not automatic as the years pass. The transition of animals from size class to size class requires an adequate description of the growth of the species concerned. In particular, this would need to be in terms of the expected growth increment of given sizes of animals, which preadapts the method to use growth estimates derived from tagging studies. In addition, one requires data on catches and catch rates, but one can also include data describing the size distribution of the commercial catch (commonly collected and known as shed or market sampling), as well as žshery-independent surveys of abundance and želd surveys of the size distribution of abalone after žshing. As with the age-structured integrated analysis, it is possible to include different forms of ancillary data once the basic size-based stock assessment model is developed. Size-structured models are relatively complex, and the examples in this chapter will need to be developed in stages (Figure 13.1); we will use
the same western zone abalone data from Tasmania, Australia, as was used in Chapter 8 (Table 8.1). The examples in this chapter use only twelve 10 mm size classes, which is a major simpližcation. With Tasmanian blacklip abalone (Haddon, 2009), seventy-six 2 mm size classes are used to describe the populations being assessed.
