Publication Date

10-2024

Series Number

Fisheries Research Report No. 331

Publisher

Department of Primary Industries and Regional Development, Western Australia

City

Perth

ISBN

978-1-925415-02-5 (Print), 978-1-925415-03-2 (Online)

ISSN

1035-4549 (Print), 2202-5758 (Online)

Abstract

Marine waters along the Western Australian coastline are characterised by low ecosystem productivity and high species diversity of fishes. With over 3,000 known species comprising estuarine, nearshore, demersal and pelagic fishes in the region, many contribute to important commercial and recreational fisheries (Lenanton et al. 1991; Molony et al. 2011; Newman et al. 2018). As it is logistically and economically infeasible to conduct intensive monitoring and high-level stock assessments of all exploited fish species in Western Australia, indicator species are used to assess the sustainability of suites of species of biological and ecological similarity, for optimal use of available resources (Newman et al. 2018).

In recent years, there has been increased demand for quantitative stock assessments of a greater number of species to meet national reporting in the Status of Australian Fish Stocks Reports (SAFS; www.fish.gov.au), used to inform Australia’s progress against UN Sustainable Development Goal 14.4.1, on the proportion of fish stocks within biological sustainable levels. The types of assessment analyses that can be applied to provide stock status estimates for a species vary depending on a range of factors including; the identified level of sustainability risk, species biology, characteristics of the fishery, data availability and level of resourcing for conducting quantitative assessments. There are five levels of stock assessment methodology of increasing complexity that are used by the Department of Primary Industries and Regional Development (DPIRD), from Level 1 (L1) which comprises a relatively simple simulation (i.e. Catch-MSY) to Level 5 (L5), which involves a dynamic, integrated stock assessment model (see Newman et al. (2023)). For many species however, no long-term reliable abundance indices and/or age composition data are available that would allow age-based equilibrium assessment approaches (L3, age-based catch curve and per recruit analysis) or dynamic assessment approaches (L4, biomass dynamics models, or L5, integrated models). Length data are available, however, for many of these species.

Compared to collecting age data, obtaining length data requires far less resourcing and thus is highly cost effective. However, the utility of length information (without catch and abundance indices) for providing stock status estimates can be limited, depending on factors such as reliability of available life history information, species biology and the dynamics of the fishery targeting the stocks of interest. As with all data used for assessment, it is also important to evaluate how representative the available length data are of the overall stock.

Unlike for commercial logbooks, Tour operator returns (charter logbooks) contain self-reported length measurements. These data, which first started being recorded in 2001/02 by charter operators from all four bioregions, provide an opportunity to raise the level of assessment for a number of fish species in Western Australia from catch only (L1) to length-based equilibrium assessment models (L3, length-based catch curve and per recruit analysis), and thereby provide more robust scientific advise for those species.

In this study, several length-based empirical analyses and models were applied to test the applicability of these methods and the available length data in charter logbooks for providing stock status information for fish species targeted by charter operators. The assessment methods include: empirical length-based indicators (Froese 2004), length-converted catch curves (Pauly 1990), length-based catch Fisheries Research Report [Western Australia] No. 331 | Page vi curve (Hesp 2023), mean length mortality estimators (Gedamke and Hoenig 2006), the length-based spawning potential ratio method (Hordyk et al. 2015a) and Bayesian biomass estimators (Froese et al. 2018).

Number of Pages

381

Keywords

stock assessments, Western Australia, marine waters, Status of Australian Fish Stocks Reports, UN Sustainable Development Goal, biological sustainable levels, age data, length data

Disciplines

Aquaculture and Fisheries | Environmental Monitoring | Marine Biology

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