Diving into fisher experience: Do new entrants and fleet turnover depress catch rates in abalone (Haliotis laevigata and H. rubra) fisheries
Introduction
Individuals often differ in their abilities to locate and catch fish, contributing to some of the variation in catches among fishers (i.e., ‘skipper effect’; Bjarnason and Thorlindsson, 1993; Gatewood, 1984; Pálsson and Durrenberger, 1982). Experience can increase efficiency and effectiveness through greater knowledge and skills, resulting in enhanced productivity (Ericsson et al., 2006; Rice, 2010). A fisher’s experience may therefore influence overall fishing success (Abrahams and Healey, 1990; Mikkonen et al., 2008), and experienced fishers may have higher catches and catch rates than fishers without experience (Chen and Chiu, 2009; Salas and Charles, 2008). Yet, the extent to which catch rates are influenced by experience will likely depend on behavior and consistency within the fleet.
In the fishing industry, relative to new entrants, experienced fishers may have greater knowledge of local fishing grounds (McKenna et al., 2008; Prince and Hilborn, 1998), more efficient fishing practices (Gaertner et al., 1999; Sharma and Leung, 1998), and established relationships and trust within their fishing community (Turner et al., 2014). Individuals that fish more frequently may also have a wider range of skills and greater involvement with equipment (Graefe, 1980), and through experience, fishers have the opportunity to test and implement tactics and innovative technology (Salas and Gaertner, 2004). Fishers with experience ultimately have the advantage of knowing how to respond to changes in resource abundance, environmental conditions, and market demands (Gunderson et al., 1995; Salas and Gaertner, 2004; Sumaila et al., 2011), therefore increasing chances of obtaining optimal and efficient catches and maximizing profit.
Catch rate (i.e., catch per unit effort, CPUE) is one of the primary indicators of abundance used in fisheries stock assessment and can be influenced by fisher behavior and experience (Hilborn and Walters, 1992a; Maunder and Punt, 2004). Fishers with greater relative fishing efficiency, for example, can land catches 2–10 times higher than other fishers (Salas, 2000), and skilled fishers can continue to maintain high catch rates despite declining abundance (i.e., hyperstability; Harley et al., 2001; Hilborn and Walters, 1992a). However, the impact of fisher experience on catch rates may also lessen in situations where both inexperienced and experienced fishers fish optimally, such as fishing grounds with high abundances of target species or fisheries with information sharing (Little et al., 2004; Turner et al., 2014; Van Holt, 2012). The general scientific approach towards removing such biases in catch rates is to standardize CPUE (Giri and Gorfine, 2019). However, nominal catch rates used for stock assessment at fine spatial scales may not be suitable for standardization and alternative methods may need to be developed to reduce biases in catch rates and enable investigation of catch rates for data-poor fisheries (e.g., the South Australian Abalone Fishery; Mayfield et al., 2012).
The impact of experience on fishing capabilities may be particularly strong in fisheries, such as abalone, that require hand-collection and local knowledge to obtain catches. In the Tasmanian Abalone Fishery, entry-level divers had CPUE values of 30 kg/hr with increases to 60–70 kg/hr within five months of experience (Prince and Hilborn, 1998). Furthermore, ∼32−37% of variation in CPUE standardization models for the Victorian Abalone Fishery was due to diver, which reflects differing levels of skill and fishing methods within the fleet (Giri and Gorfine, 2019). The ability of divers to detect and target aggregations of abalone across reefs and to re-locate such aggregations may improve fishing success and result in hyperstable catch rates (Dowling et al., 2004; Hart and Gorfine, 1997; Hilborn and Walters, 1992a). Despite interests in the effects of fisher behavior, market demand, weather, and fishing location on catch rates (Bordalo-Machado, 2006; Gillis and Peterman, 1998; Stobart et al., 2016, 2019), studies on the effects of experience on catch and effort in abalone fisheries are limited (Prince and Hilborn, 1998), and few studies consider or adequately account for the impacts of experience on CPUE (Bishop et al., 2000, 2008; Maunder and Punt, 2004).
In the commercial South Australian Abalone Fisheries (SAAFs), a recent concern is the potential for new entrants, with little experience, to negatively affect CPUE. Fisher concerns over the latter have been augmented by further and recent declines in CPUE (Stobart et al., 2018b, 2019) coinciding with an increased rate of new divers entering the fishery and by the use of CPUE as one of the two key performance indicators in the proposed abalone harvest strategy (PIRSA, 2020; Stobart et al., 2020). CPUE is a logical performance indicator as it is readily available across the entire fishery, is a measure of fishing success, and is widely used as an index of abundance (Hilborn and Walters, 1992a). The second performance indicator in the proposed abalone harvest strategy is legal size abundance obtained from fishery-independent surveys undertaken across key spatial assessment units (SAUs). While these two performance indicators are the core parameters in the harvest strategy, there is also provision for secondary sources of information (e.g., diver experience, weather, market changes) to influence the final total allowable commercial catch (TACC) outcome.
We investigated diver records for greenlip (Haliotis laevigata) and blacklip (Haliotis rubra) abalone fisheries in South Australia to evaluate CPUE and the number of diver entrants among licenses to determine whether diver CPUE increased from entry into the fishery to 10 years post-entry. If entrants improve with experience, we expect 1) CPUE of licenses with new divers to be lower than the fleet average and to become more similar to the fleet average over time (Fig. 1a) and 2) divers to exhibit increasing CPUE with greater experience, particularly within the first twelve months fishing (Fig. 1b). We additionally simulated catch rates for varying levels of fleet turnover in the Western Zone Fishery and applied decision rules, described in the proposed abalone harvest strategy, that enable adjustment of management outcomes based on secondary information when biases in catch rates are shown to be present.
Section snippets
South Australian Abalone Fishery
7 (Fig. 2), with divers having a range of experience of less than one year to over 30 years. The largest commercial greenlip (H. laevigata) and blacklip (H. rubra) abalone fishery is the South Australian Western Zone Fishery (SAWZF) with 22 licenses (reduced from 23 in 2014) and a 2018 catch of 214.5 t greenlip and 171.0 t blacklip (whole weight; Stobart et al., 2019). The smallest fishery is the South Australian Central Zone Fishery (SACZF) with six licenses and a catch of 137.1 t greenlip and
CPUE and experience
Average annual CPUE and the number of entrants varied among licenses (Fig. 3; Table A2). Average catch rates ranged between 96−78 kg/hr in the Southern Zone, 83−65 kg/hr in the Central Zone, and 89−57 kg/hr in the Western Zone (Fig. 3a; Table 2; F34,1357 = 12.88, p < 0.001). The average number of entrants each year ranged from 0.0 to 0.8 individuals, or 0–13 % fleet turnover, but did not differ significantly among licenses (Fig. 3b; Chi square = 0.77, p = 0.943, df = 4). The average number of
Discussion
Experienced divers exhibited higher catch rates than new entrants, with CPUE significantly varying among licenses. Catch rates of licenses with new entrants to the SAAF were on average 3–10 % lower than fleet CPUE. In addition, annual and monthly catch rates were positively correlated to experience, with sole divers exhibiting increases in greenlip and blacklip catch rates from ∼14−22 kg/hr to 20–24 kg/hr, respectively, within one year of experience. However, the number of new entrants into the
CRediT authorship contribution statement
Katherine Heldt: Conceptualization, Investigation, Methodology, Formal analysis, Writing - original draft. Ben Stobart: Methodology, Writing - review & editing. Stephen Mayfield: Conceptualization, Methodology, Writing - review & editing.
Declaration of Competing Interest
The authors declare no conflict of interest.
Acknowledgements
We are grateful to the Information Services Team at the South Australian Research and Development Institute (Aquatic Sciences), especially Angelo Tsolos and Melleessa Boyle, for collating catch and effort data. We also appreciate personal communications with the South Australian Abalone Fishery license holders and fishers that contributed to our understanding of diver experience. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit
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