INFLUENCE OF WIND AND SWELL ON CATCH RATES IN A DIVE FISHERY: A CASE STUDY FROM THE SOUTH AUSTRALIAN ABALONE FISHERY BEN STOBART, 1 * STEPHEN MAYFIELD 2 AND JONATHAN CARROLL 2 1 South Australian Research and Development Institute, SARDI Aquatic Sciences, PO Box 1511, Port Lincoln, SA 5606, Australia; 2 South Australian Research and Development Institute, PO Box 120, Henley Beach, SA 2022, Australia ABSTRACT Catch per unit effort (CPUE) is widely used as an index of abundance in the assessment of abalone fisheries even though it has often been considered unreliable. This is because, it is susceptible to hyperstability and influenced by factors other than stock abundance such as increased fishing efficiency, market demand for particular product, weather, diver habits, and putative rotation of fishing grounds. These factors introduce uncertainty to the use of CPUE as an index of relative stock abundance, with some of these factors causing hyperdepletion of the index. In the western and southern zones (WZ and SZ) of South Australia, commercial fishers recently suggested that declining CPUE in 2014 was attributed to a fishing season with poor weather, and in particular higher than average swell, rather than to declines in stock abundance. To evaluate the effect of weather on CPUE in the SZ and WZ daily, logbook catch and effort data were linked with swell and wind observations. Analysis demonstrates that, although the observations of extrinsic factors were correct, fishers avoided diving on days with unsuitable weather conditions. Consequently, the observed decrease in CPUE is not likely to have been affected by weather-related hyperdepletion, and therefore managers should not rule out interpreting recent declines in CPUE as reflecting decreases in stock abundance. This highlights the independence of CPUE to the effects of the extrinsic factors evaluated and challenges some of the reasoning provided for it not being a reliable index of abundance. Further exploration of the effects of other factors that may affect CPUE, as well as the link between this index and fishery-independent estimates of abundance, are needed to determine the weighting it should receive in the stock assessment process. KEY WORDS: catch per unit effort, abundance index, abalone, fishery management INTRODUCTION Catch per unit effort (CPUE) is the most common index of abundance used for stock assessments of commercial and recreational fisheries, yet the use of CPUE as an index of abundance relies on the assumption that catchability (the fraction of abundance captured by a unit of effort) is a constant (Maunder & Punt 2004). This has been demonstrated not to be the case, as a suite of factors that often vary among fisheries are known to affect catchability. Among others, these include changes in vessel size and power, fishing gear, fisher behavior, target species behavior, weather, and the spatial distribution of fishing (Bordalo-Machado 2006). All of these factors affect the proportionality between CPUE and abundance, most com- monly leading to CPUE remaining high while abundance declines (‘‘hyperstability’’; Hilborn & Walters 1992), although the opposite, ‘‘hyperdepletion,’’ may also occur (Harley et al. 2001). Despite this deficiency, CPUE commonly remains the index of choice because it is relatively cheap to obtain from fishing records and often available across entire fisheries (Maunder & Punt 2004, Cotter & Pilling 2007). The uncertainty associated with using CPUE as a relative index of abundance has been well documented in abalone fisheries (Harrison 1983, Sloan & Breen 1988, Breen 1992, Prince & Shepherd 1992, Prince & Guzman del Proo 1993, Officer et al. 2001). In particular, CPUE has often been criticized due to the combined effect of the aggregating nature of abalone and the highly efficient searching behavior of abalone divers targeting aggregations, both helping maintain catch rates under circumstances of declining abundance and causing hyperstability in CPUE (Prince & Guzman del Proo 1993, Shepherd & Rodda 2001, Dowling et al. 2004). Adding to the complication, CPUE may be affected by numerous other factors that can lead to either hyperstability or hyperdepletion. For example, hyperstability may occur because fishers can maintain their catch, or increase their expected levels of catch for a range of plausible reasons that may include technological changes in the fishing fleet (e.g., trends to larger or smaller vessels, increased use of motorized dive cages), increasing fishing efficiency (effort creep), rotation of fishing grounds by divers, and changes in diver demographics (Gorfine & Dixon 2001, Stobart et al. 2014). In contrast, hyperdepletion may occur as a result of adverse weather conditions, diver preference and habits (e.g., trends toward operating with two divers per vessel in Tasmania), and convenience and market demands for particular product types (e.g., larger size abalone). In spite of these uncertainties, CPUE remains one of the primary performance indicators for assessing stock status across abalone fisheries in Australia (South Australia—Stobart et al. 2014, Tasmania—Tarbath et al. 2014, Victoria—Gorfine et al. 2002, and Western Australia—Hart et al. 2009). This is because, CPUE estimates are (1) readily available across entire fisheries; (2) cheaper to obtain than alternatives such as fishery- independent (FI) surveys (Maunder & Punt 2004, Cotter & Pilling 2007); and (3) provide a meaningful measure of stock status, providing they are assessed in context with complemen- tary data (Dowling et al. 2008, Smith et al. 2009, Burch et al. 2011, Tarbath & Gardner 2011, Tarbath et al. 2014). For example, one of the ways to assist the interpretation of CPUE trends is to include an independent measure of stock abun- dance, such as FI surveys, in stock assessments. This is the case in South Australia, where management of the greenlip (Haliotis laevigata) and blacklip (Haliotis rubra) abalone fisheries relies *Corresponding author. E-mail: ben.stobart@sa.gov.au DOI: 10.2983/035.035.0315 Journal of Shellfish Research, Vol. 35, No. 3, 685–694, 2016. 685