ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on September 20, 2007
ICES Journal of Marine Science: Journal du Conseil 2007 64(9):1710-1722; doi:10.1093/icesjms/fsm146
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A method for evaluating the impacts of fishing mortality and stochastic influences on the demography of two long-lived shark stocks
1 Department of Fisheries, Government of Western Australia, Western Australian Fisheries and Marine Research Laboratories, PO Box 20, North Beach, WA 6920, Australia and Centre for Ecosystem Management, School of Natural Sciences, Edith Cowan University, 100 Joondalup Drive, Joondalup, WA 6027, Australia
2 School of Earth and Environmental Sciences, James Cook University, Townsville, QLD 4811, Australia
3 School of Biological Sciences and Biotechnology, Murdoch University, Murdoch, Western Australia 6150, Australia
Correspondence to R. B. McAuley: tel: +61 8 9203 0210; fax: +61 8 9203 0111; e-mail: rory.mcauley{at}fish.wa.gov.au
McAuley, R. B., Simpfendorfer, C. A., and Hall, N. G. 2007. A method for evaluating the impacts of fishing mortality and stochastic influences on the demography of two long-lived shark stocks. — ICES Journal of Marine Science, 64.
Stochastic demographic models were developed for Carcharhinus obscurus and C. plumbeus populations off the west coast of Australia by resampling the input parameters for life tables from empirical biological data collected from commercial target fisheries and fishery-independent surveys. The models were used to examine the effects of multiple scenarios of age-specific survival, derived from the fishing mortality rates estimated from a tagging study on sharks and indirect estimates of natural mortality. In the absence of fishing, median estimates of the rates of intrinsic population increase (r) were 0.025 for both species. Inclusion of the age-specific fishing mortality rates estimated for C. obscurus recruits born in 1994 and 1995 resulted in the median estimates of r declining to 0.007 and 0.012, respectively, suggesting that recent harvest levels of mainly neonates by the target fishery were probably sustainable. However, the model also suggested that the population was more susceptible to exploitation of older sharks than was previously believed. The C. plumbeus model indicated that fishing mortality between 2001 and 2004 was probably unsustainable. The increasingly negative trend in median r estimates (from –0.032 to –0.049), and the population’s apparently limited capacity for density-dependent compensation through changes in fecundity, somatic growth and longevity, suggests that management intervention is necessary to prevent continued stock depletion.
Keywords: Carcharhinus obscurus, Carcharhinus plumbeus, demographic analysis, fishing mortality, gauntlet fishery, stochastic
Received 16 February 2007; accepted 22 August 2007; advance access publication 20 September 2007.
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Introduction |
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 Top Introduction MethodsResultsDiscussionReferences |
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The dusky shark (Carcharhinus obscurus) and the sandbar shark (C. plumbeus) are relatively abundant medium to large carcharhinids that share similar circumglobal distributions in tropical and temperate coastal and adjacent oceanic waters (Compagno, 1984; Last and Stevens, 1994). Both species are distributed along the east and west coasts of Australia (Last and Stevens, 1994), but neither is seemingly common north of 16°S or in southeastern Australian waters (Last and Stevens, 1994; McAuley et al., 2005, 2007a). Therefore, each species is considered to be represented by two distinct regional populations. Western Australian populations of C. obscurus and C. plumbeus co-occur throughout most of their ranges and both exhibit similar size-segregated structure, juveniles being most common in temperate latitudes and adults in warmer northern latitudes (McAuley and Simpfendorfer, 2003; McAuley et al., 2007a).
Because of their occurrence nearshore and their high-quality flesh and fins, both species support significant commercial and artisanal shark fisheries around the world (Bonfil, 1994; Joung and Chen, 1995; Castro et al., 1999; Chan A Shing, 1999; Fowler et al., 2005; McVean et al., 2006). Neonate and young juvenile C. obscurus have been the primary target of a demersal gillnet fishery in southwestern Australian waters since at least the 1970s (Heald, 1987; Simpfendorfer and Donohue, 1998; Simpfendorfer, 1999a, b). Their catches by that fishery escalated rapidly from under 100 t (estimated live weight) per year in the late 1970s to a peak of just under 600 t in 1988/1989 before management restrictions reduced and stabilized catches at 
300 t year–1 (McAuley, 2006a). Juvenile C. plumbeus are also caught by that fishery, particularly off the lower west coast, but they were not heavily targeted until the mid- to late 1990s (McAuley and Simpfendorfer, 2003). Demersal gillnet catches of C. plumbeus more than doubled between 1994/1995 and 2003/2004, to >200 t year–1 (McAuley, 2006a). In addition to the growth in the temperate gillnet fishery’s catch, the concurrent development of a demersal longline shark fishery off the northwest coast of Australia during the late 1990s resulted in a similar escalation of C. plumbeus catches from the northern part of the stock’s range. By 2003/2004, reported longline catches by this northern fishery had also exceeded 200 t year–1, resulting in a combined C. plumbeus catch by these two target fisheries of 415 t in that year (McAuley 2006b). Although the northern shark longline fishery has a known bycatch of C. obscurus (McAuley et al., 2005), it is poorly identified in reported catches, though the catch is thought to be reasonably small (McAuley, 2006b).
Owing to their slow rates of growth, high ages at maturity (Natanson et al., 1995; Sminkey and Musick, 1995; Natanson and Kohler, 1996; Simpfendorfer et al., 2002; McAuley et al., 2006) and low fecundity (Bass et al., 1973; Castro, 1983; McAuley et al., 2007a), both C. obscurus and C. plumbeus are highly susceptible to overfishing and are likely to require many decades to recover from periods of overexploitation (Hoff, 1990; Sminkey and Musick, 1996; Cortés, 1998, 1999, 2002; Smith et al., 1998; Simpfendorfer, 1999a; Brewster-Geisz and Miller, 2000). The difficulties associated with sustainably harvesting K-selected fishery resources such as these are indicated by the long history of rapid overexploitation of targeted shark fisheries around the world (Ripley, 1946; Parker and Stott, 1965; Holden, 1968, 1974, 1977; Casey et al., 1978). Severe declines in C. obscurus and C. plumbeus abundance indices in the western North Atlantic and Gulf of Mexico (Musick et al., 1993; Ulrich, 1996; Fowler et al., 2005) and highly pessimistic predictions of continuing stock depletion (Sminkey and Musick, 1996; Cortés, 1999; Brewster-Geisz and Miller, 2000; Cortés et al., 2006; NOAA/NMFS, 2006), emphasize the importance of carefully managing these low-productivity shark resources to avoid the need for drastic conservation responses and associated economic loss to fisheries.
An often cited obstacle to the successful assessment and management of fisheries exploiting long-lived shark stocks is that available time-series of fishery data (i.e. catches, fishing effort, and catch rates) are typically noisy and insufficient in duration to reflect trends in stock abundance (Anderson, 1990; Punt and Smith, 1999; Simpfendorfer, 1999a, b, 2005; Stevens et al., 2000; Bonfil, 2005). These data limitations, as well as the generally low economic value of shark catches, usually preclude the use of dynamic modelling techniques in assessing the effects of fishing on shark stocks. Although there are some notable examples of the application of dynamic assessment techniques to shark stocks (Walker, 1992; Punt and Walker, 1998; Punt et al., 2000; Simpfendorfer et al., 2000; Apostolaki et al., 2006), a more conventional approach to evaluating the potential resilience of shark stocks to fishing pressure is via demographic analysis (Cailliet et al., 1992; Sminkey and Musick, 1996; Smith et al., 1998; Brewster-Geisz and Miller, 2000; Mollet and Cailliet, 2002; Simpfendorfer, 2005; Cortés, 2007). Although demographic models, which rely on more readily obtainable life history parameters to estimate a population’s potential growth rate, have provided useful information on the relative productivities of shark populations and, hence, on their relative vulnerabilities to fishing pressure, they have typically not been used for direct assessment of the effects of fishing. The incorporation of exploitation rates in demographic analysis is relatively straightforward, but reliable estimates of fishing mortality are generally lacking for shark stocks. Therefore, demographic analysis has so far proved to be of limited use in providing explicit fishery management advice and in the development of robust and defensible harvest strategies.
A major advance in demographic analyses of shark populations over the past decade has been the introduction of stochastic parameter-estimation techniques (Cortés, 1999, 2002; Beerkircher et al., 2003). Unlike earlier studies, which relied on assessment of deterministic input parameters and sensitivity analysis of discrete changes in their values, stochastic methods can more adequately reflect the inherent variability in the life histories of wild populations. By evaluating many simultaneous and disproportionate changes in age, growth, reproduction, and survival parameters, the results obtained from stochastic demographic models allow for a more probabilistic evaluation of populations’ potential demographic rates. Moreover, if input parameters are drawn from adequately representative ranges of their possible values, the extent to which potential changes in populations demographic rates may be constrained by these parameters can also be examined.
The aim of this study was to develop stochastic demographic models for Western Australian populations of C. obscurus and C. plumbeus, with which to examine the effects of empirically derived, age-specific rates of fishing mortality and variability in observed life history data. In addition to providing comprehensive baseline assessments of the sustainability of these populations under current levels of fishing pressure, the study also sought to demonstrate the viability of stochastic demographic techniques as an alternative fisheries assessment tool, for situations where estimates of fishing mortality are available but where time-series of stock abundance data are insufficient to develop dynamic assessment models.
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Methods |
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TopIntroductionMethodsResultsDiscussionReferences |
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Age-structured demographic models were developed for female C. obscurus and C. plumbeus, using life table techniques (e.g. Krebs, 1985), validated estimates of age and growth, and empirical reproductive data from the study populations (Simpfendorfer et al., 2002; McAuley et al., 2005, 2006, 2007a). Models were used to estimate the generation time (G), proportion reaching maturity (PM), net reproductive rate (R0), intrinsic growth rate (r), and doubling time (tx2) for each population under multiple scenarios of empirically estimated age-specific rates of fishing mortality. To account for observed levels of variability in the empirical biological data (Table 1) and uncertainty in the rates of natural mortality, a stochastic approach was used to incorporate these vital rates into the models, according to the methods described below. For each scenario of fishing mortality, 1000 sets of results were estimated by randomly resampling (with replacement) independent estimates of age, growth, and reproductive parameter values and the rates of natural mortality derived from those values. Confidence intervals (95%) were determined from the 2.5 and 97.5 percentiles of the results.
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Estimating the rate of natural mortality
As no empirical natural mortality rate estimates were available for either study population, values of Mx were instead estimated by five commonly used indirect age-independent methods and two age-dependent methods for each set of variables (Table 2). The age-specific rates of natural mortality used for demographic analysis were then drawn with uniform probability from within the ranges of the maximum and minimum estimates of all seven methods. The von Bertalanffy growth parameters of L
and k used in the Pauly (1980) method, and to derive t0 for the Chen and Watanabe (1989) method from the length at birth (L0) of each species, were drawn from combinations of the bootstrapped estimates of L and k reported by McAuley et al. (2005, 2006). As in those studies, lengths at birth were fixed at 75.3 cm fork length (LF) for C. obscurus (Simpfendorfer et al., 2002) and 42.5 cm LF for C. plumbeus (McAuley et al., 2006, 2007a). Values of age at maturity (tmat) used in the Jensen (1996) and Chen and Watanabe (1989) methods were derived from bootstrapped estimates of the length at which 50% of sharks were expected to be mature (L0.5) reported by McAuley et al. (2005, 2007a), using the modified form of the von Bertalanffy growth equation: |
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and k are the same resampled estimates as described earlier.
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Values of the maximum age variable (
) used in the Hoenig (1983) equations (which refer to as tmax) were assumed to have a distribution with discrete probability function p(j), in which j ranged from min to max, i.e. j = 1, 2, ..., max–min + 1, and where the values of p(j) were assumed to decline linearly from a maximum at min towards zero at max + 1. Thus, the assumed probability function was |
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n) = 
j=1np(j). On the basis of the conclusions of Simpfendorfer et al. (2002) and McAuley et al. (2006), min and max were assumed to be 40 and 55 years, respectively, for C. obscurus and 30 and 40 years, respectively, for C. plumbeus. In both cases, min was based on direct observations of maximum age. The decision to resample from declining probability distributions was based on the assumption that maximum ages were more likely closer to their maximum observed ages than towards their reported potential maxima (max). Random values of maximum age were drawn using the inverse transform method, i.e. by determining the random value of as the minimum value of n, such that u
D(n), where u was randomly selected from the uniform distribution ranging from 0 to 1. As suggested by Cortés (2002) and Beerkircher et al. (2003), live weight was used instead of dry weight for the Peterson and Wroblewski (1984) method, because the latter resulted in inconsistently high estimates of Mwt. Live weight-at-age was estimated from each species’ mean length-at-age (Simpfendorfer et al., 2002; McAuley et al., 2006) and the female relationships between length and live weight given by McAuley and Simpfendorfer (2003).
Estimating the rate of fishing mortality
Age-specific fishing mortality rates for the two species were estimated from tag-recapture data from two independent tagging studies, details of which are given in Simpfendorfer et al. (1996) and McAuley et al. (2005). The first tagging study was conducted between March 1994 and December 1995, when 1572 juvenile (mainly neonate) C. obscurus were tagged in waters between Geraldton and Eucla (Figure 1a). During the second study, 1759 C. plumbeus were tagged in temperate and tropical waters between Cape Leveque and Cape Leeuwin between August 2000 and June 2004 (Figure 1b). Juvenile C. obscurus were sourced only from commercial catches made by demersal gillnet shark fishing vessels, and juvenile and adult C. plumbeus were tagged on-board commercial gillnet and longline shark fishing vessels and during fishery-independent longline fishing surveys. In both studies, sharks were tagged with Jumbo Rototags in the first dorsal fin, and a subsample of C. obscurus was also tagged with a nylon-headed dart tag in the dorsal musculature for estimating the rates of tag shedding. Ages of tagged sharks at release were estimated from their measured lengths at that time and the parameters of the fitted von Bertalanffy curves reported by Simpfendorfer et al. (2002) and McAuley et al. (2006).
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As the survival of sharks that were sluggish, unable to swim away, or bleeding excessively at release (C. obscurus, n = 47; C. plumbeus, n = 88) may have been compromised by their capture and handling, they were not included in estimating the rates of fishing mortality. To ensure tagged sharks had been allowed adequate time to re-mix into the populations after release, those at liberty for <90 d (C. obscurus, n = 115; C. plumbeus, n = 9) were also excluded from further analysis. Unlike the two tagged C. obscurus caught by recreational fishers, which were reported to have been retained, the four recreationally caught tagged sandbar sharks were also excluded from analysis because they were either reported or assumed to have been released alive because of their large size. Subsequent analyses of fishing mortality, based on the recaptures of 277 tagged C. obscurus and 62 tagged C. plumbeus, were therefore assumed to be unaffected by tagging-induced mortality or behavioural effects. Additionally, as tagging and tag recaptures were throughout the ranges of the target fisheries and over most of the stocks’ distributions, it was also assumed that the 1410 tagged C. obscurus and 1658 tagged C. plumbeus included in these analyses were representative of the stock components assessed.
To account for the fishing mortality caused by unreported tag recaptures, commercial shark fishers’ tag-reporting behaviour was quantified separately for four regions corresponding to the management zones (Figure 1) of the commercial shark fisheries, using the method of Simpfendorfer (1999a). Fishers were classified as either reporters or non-reporters on the basis of whether they returned any tag information within a financial year (July–June inclusive). For each species, regional annual non-reporting rates were estimated as the proportion of each region’s annual catch taken by the non-reporting fleet. Annual catches for the regions south of Northwest Cape (regions 1, 2 and 3; Figure 1) were taken from the data reported by McAuley (2006a) and for the region north and east of North West Cape (region 4) reported by McAuley (2006b). The estimated number of captures (
) of tagged sharks from each age group during each month (t) was then calculated as
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The number of sharks of age group x tagged that were present in the population at the start of month t (nx,t) was calculated as
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For each of the resampled values of Mx,T, the Baranov catch equation (Ricker, 1975),
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x,T and nx,T were derived from discrete monthly time-steps of tagged shark survival, values of Fx,T calculated from this equation were approximations of instantaneous rates of fishing mortality. However, as survival schedules were estimated for relatively short time-steps with continuous rates of natural mortality and tag shedding, such an approximation was considered to be reasonably accurate. Different approaches were taken to incorporate fishing mortality schedules into the demographic models for each species. As 92% of tagged C. obscurus were estimated to be <1 year old at the time of their release, the rates of fishing mortality could not be determined directly for all age classes during the study period. Therefore, the rates of fishing mortality experienced by the two C. obscurus cohorts tagged in 1994 and 1995 were calculated separately for each cohort up to 10 years of age, at which stage F was assumed to be zero. Unlike the first tagging study, estimated ages of C. plumbeus tagged in the second tagging study ranged from 0+ to 24+ years, so it was possible to estimate annual rates of fishing mortality directly for most age classes. However, as estimation of fishing mortality for some C. plumbeus year classes was affected by relatively small numbers of tag releases, it was necessary to pool data into 3-year age classes from 0+ to 17+ years of age, and for all sharks aged between 18+ and 24+ years. As suggested by the decreasing frequency of sharks larger than the estimated length at 24+ years of age in observed commercial catches (McAuley et al., 2005, 2006), fishing mortality was assumed to decrease linearly each year from the rate estimated for the 18–24+ age group to zero for sharks aged >30+ years.
Demographic analysis
Life tables were based on the Euler–Lotka equation (Lotka, 1959):
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is the maximum age (as derived for natural mortality estimation), lx the proportion of female sharks surviving to age x, r the intrinsic population growth rate, and mx the annual number of female offspring produced by females of age x. Age-specific survival (lx) schedules were derived from the survival equation: |
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x) was estimated as the expected proportion of mature sharks at the fork length of the midpoint of age class x (xL), determined from the point estimates of the parameters of the fitted von Bertalanffy curves reported by Simpfendorfer et al. (2002) and McAuley et al. (2006), using the logistic function |
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Results |
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Rates of natural mortality
The use of multiple indirect relationships for estimating the rates of natural mortality resulted in relatively disparate values of Mx for each species (Table 3). The highest age-independent estimates for each species were provided by Hoenig’s (1983) relationship for combined mollusc, teleost and cetacean data [method (iii)]. Pauly’s (1980) method resulted in the most variable rates, whereas the lowest and least variable estimates were derived from the Jensen (1996) method. The age-dependent natural mortality schedules estimated by the Peterson and Wroblewski (1984) method declined from 0.13 and 0.22 year–1 in the youngest age class to 0.04 and 0.08 year–1 at maximum ages of 55 and 40 for C. obscurus (Figure 2a) and C. plumbeus (Figure 2b), respectively. The Chen and Watanabe (1989) method also yielded high mean estimates of natural mortality in the youngest age groups and low rates in intermediate age groups, but produced substantially larger estimates for the oldest age groups than were derived from the Peterson and Wroblewski (1984) method (Figures 2a and 2b). Resampling estimates of Mx from within the ranges calculated by the individual methods provided age-specific natural mortality schedules that retained the characteristics of the age-dependent methods, i.e. higher mortality in the youngest and oldest age groups. However, the more extreme values of Mx estimated by the age-dependent methods for the youngest and oldest age groups were moderated by the generally lower rates estimated for these age classes by the age-independent methods (Figures 2c and 2d).
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Rates of fishing mortality
Before 2002/2003, non-reporting rates were fairly consistent within each region (Table 4). During that period, mean annual non-reporting rates of C. obscurus captures were lowest in region 1 (Di,T = 0.22, s.d. = 0.07), followed by region 3 (Di,T = 0.35, s.d. = 0.17) and region 2 (Di,T = 0.55, s.d. = 0.09). During the second tagging study, the estimated mean non-reporting rates of tagged C. plumbeus captures were lowest in region 2 (Di,T = 0.15, s.d. = 0.07), followed by region 3 (Di,T = 0.55, s.d. = 0.11) and region 4 (Di,T = 0.59, s.d. = 0.23). However, the estimated rates of non-reporting increased substantially in regions 3 and 4 during 2002/2003 and 2003/2004.
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Rates of fishing mortality of juvenile C. obscurus were highest for the 0+ age class, with mean estimates of 0.21 and 0.17 year–1 for the 1994 and 1995 cohorts, respectively (Figure 3). These declined to 0.14 and 0.09 year–1 for the 1+ age classes, and to 0.05 and 0.04 year–1 for the 2+ age classes, then continued to decline to the assumed value of 0 at 10 years of age. The compounding variability of natural mortality estimates over the 10 years that tagged C. obscurus were at liberty caused increasing uncertainty in the estimates of F with age of shark. The coefficient of variation in F estimates increased from 0.03 in the 0+ age groups to 0.13 in the 9+ age classes of both cohorts.
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The highest annual rates of C. plumbeus fishing mortality were experienced by the 6–9-year age class in 2001/2002 (0.19 year–1) and 2003/2004 (0.28 year–1) and by the 3–6-year age class (0.10 year–1, followed closely by the 6–9 year-old group) in 2002/2003 (Figure 4). Apart from the 3–6-year-old age class, the rates of fishing mortality of all juvenile age classes <16 years for females (McAuley et al., 2007a) were estimated to be lower in 2002/2003 than in other years of the study.
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Demographic analyses
Carcharhinus obscurus
There was little variation in estimates of the generation time (G) of the C. obscurus population under the different schedules of fishing mortality tested in the demographic model (Table 5). Median values were 31.8 and 32.0 years, with 95% of estimates between 30.0 and 34.8 years. Median estimates of the proportion of C. obscurus recruits reaching maturity (PM) declined from 7.9% in the absence of fishing, to 4.5% and 5.2% under the rates of fishing mortality estimated for the 1994 and 1995 cohorts, respectively. The upper confidence intervals of PM estimates indicate that it was highly unlikely that any more than 7.5% of C. obscurus born in 1994 and 1995 would survive to reproductive age (between 26.7 and 34.7 years old, Table 1). As a consequence of F-induced reductions in PM, median estimates of the net reproductive rate per generation (R0) declined from 2.2 offspring per generation in the absence of fishing to 1.3 in the 1994 cohort, and to 1.5 in the 1995 cohort.
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In the absence of fishing, the median estimate of r for the C. obscurus population was 0.025 year–1, with 95% confidence intervals of –0.007 to 0.052 year–1. However, the small proportion (5.7%) of negative estimates of r resulting from the assumption of zero fishing mortality indicated that some combinations of life history parameter values used in the model were biologically unrealistic, and that these were not entirely excluded by 95% confidence intervals. Application of the estimated rates of C. obscurus fishing mortality (Figure 3) resulted in 66% and 51% declines in median estimates of r for the 1994 and 1995 cohorts, respectively (Table 5). Although median estimates of r remained positive under these rates of fishing mortality, 30.2% of estimates for the 1994 cohort and 19.9% of estimates for the 1995 cohort were negative.
Estimates of the C. obscurus population’s doubling time (tx2) were highly variable for all scenarios of fishing mortality (Table 5). This caused a contradictory higher median estimate of tx2 for the 1995 cohort than for the 1994 cohort, despite the higher rates of fishing mortality and the concomitant lower rate of intrinsic population growth experienced by the 1994 cohort.
Carcharhinus plumbeus
Median estimates of the C. plumbeus population’s generation time were slightly more variable than those determined for the C. obscurus population, but 95% confidence intervals of these estimates only varied by 2.4–2.6 years (or 10.9–11.3% of the respective median values; Table 5). Despite the maximum rates of fishing mortality being lower than those determined for C. obscurus, there were greater reductions in the proportion of C. plumbeus reaching maturity PM because of the exposure of more juvenile age classes to fishing (Figure 4). Median estimates of PM declined from 13.4% in the absence of fishing to 4.1% under the 2001/2002 schedule of F, to 6.9% under the 2002/2003 schedule, and to 3.8% under the 2003/2004 schedule. The 95% confidence intervals of PM estimates indicated that as few as 3.0% and no more than 8.2% of female C. plumbeus were likely to survive to maturity under such rates of fishing mortality. Because of the combined effects of these reductions in PM as well as the exposure of adult C. plumbeus to fishing mortality during 2002/2003 and 2003/2004, median estimates of the net reproductive rate (R0) declined by between 52% in 2002/2003 and 78% in 2003/2004 of the population’s unfished rate of 2.0. Under the most severe schedule of F (2003/2004), the model predicted that, even at the upper 95% confidence interval of R0 estimates, the number of female offspring produced was insufficient to replace those being lost to the combined effects of fishing and natural mortality.
In the absence of fishing, the median estimate of r (0.025 year–1) was equal to that estimated for C. obscurus, but there was slightly more variation in these estimates than for C. obscurus (Table 5). Moreover, the proportion of negative r estimates (10.4%) was also greater than that obtained for C. obscurus. Median estimates of r were negative under all three schedules of C. plumbeus fishing mortality, indicating that the population did not have the reproductive capacity to offset the additional mortality caused by fishing in those years and would therefore decline. Furthermore, under the estimated schedules of fishing mortality, between 66.0% (in 2002/2003) and 99.4% (in 2003/2004) of r estimates were negative. As with C. obscurus, estimates of tx2 were highly variable. Nonetheless, the majority (between 66% and 99% in 2002/2003 and 2003/2004, respectively) predicted that the C. plumbeus population could not double in size, irrespective of time.
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Discussion |
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TopIntroductionMethodsResultsDiscussionReferences |
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Results from this study confirm that C. obscurus and C. plumbeus have among the lowest intrinsic rates of population increase of any shark species yet evaluated. In the absence of fishing mortality, median estimates of intrinsic population growth rates for the two species (r = 0.025) were similar to those derived from previous deterministic demographic analyses of C. obscurus (Cortés, 1998, r = 0.028; Smith et al., 1998, r2M = 0.020–0.029) and C. plumbeus (Smith et al., 1998, r2M = 0.028–0.039), but are noticeably different from those reported for C. obscurus by Simpfendorfer (1999a; r = 0.042) and by Hoff (1990; r = 0.18), Sminkey and Musick (1996; r = 0.062), Cortés (1998; r < 0.003), and Cortés (1999; r = 0.013) for C. plumbeus. Nevertheless, only one of these estimates (Sminkey and Musick, 1996; r = 0.062) lay outside the 95% confidence intervals of current estimates. Therefore, although previous estimates of these species’ intrinsic rates of population increase generally appear to be reasonable, given the variability evident in the empirical biological data used in this study, they only provide limited descriptions of the species’ potential demographic rates.
Comparing the results from the current study with previous demographic analysis of the Western Australian C. obscurus population (Simpfendorfer, 1999a) highlights the importance of obtaining locally derived empirical biological data. As empirical estimates of age at maturity and reproductive period were not available when the previous analysis was carried out, it relied on invalidated estimates from South African C. obscurus (Natanson, 1990) and an assumed reproductive frequency of 3 years. Although reproductive period remains uncertain (and was therefore randomly selected as either 2 or 3 years in the current study), subsequently collected reproductive data from 66 maturing and mature females (McAuley et al., 2005) and validated estimates of age and growth (Simpfendorfer et al., 2002) indicate that age at maturity in this population (27–35 years) is substantially higher than the 14–21 years previously calculated. Nonetheless, further data are required to resolve the uncertainty in reproductive period and to improve estimates of size at maturity, litter size, and embryonic sex ratios for this population.
Although these results confirm that the rates of fishing mortality experienced by C. obscurus born in 1994 and 1995 were sustainable, they also suggest that the stock is more susceptible to overfishing than indicated by the previous deterministic study. In particular, the previous conclusion that up to 4.3% of each age class could be sustainably harvested each year (equivalent to F = 0.041 year–1; Simpfendorfer, 1999a), appears overly optimistic. Using the revised biological parameters and age-specific rates of fishing mortality, the stochastic demographic model indicated that, with an additional fishing mortality of between 1% and 2% year–1 applied to C. obscurus >10 years old, there was a 55% probability that r would be negative and that the stock would decline. This lower sustainable threshold of older juvenile and adult fishing mortality helps to explain the apparent decline in neonate recruitment that has been inferred from the declining trend in catch rates in the target demersal gillnet fishery since the last analysis was conducted (McAuley, 2006a). Despite the 22% effort reduction in the target gillnet fishery between 1994/1995 and 2001/2002 (McAuley, 2006a), it now appears probable that an additional unquantified fishing mortality of older sharks outside the target fisheries has caused a slow decline in both stock biomass and recruitment. Of equal but longer term concern is that, given the longer time-lag between birth and reproductive maturity expected from the higher estimates of age at maturity, the impacts of the peak in C. obscurus catches during the mid- to late 1980s (which were up to 35% higher than in 1994/1995) will not be evident for at least another decade.
Although the maximum rates of fishing mortality experienced by the C. plumbeus stock were lower than those estimated for C. obscurus, tagging data indicated that all but the oldest age classes were subject to fishing pressure during the second study period (Figure 4). This was particularly so in 2002/2003 and 2003/2004, when the estimated rates of fishing mortality on adult age classes increased by between 108% (in the 15–18-year-old age class) and 172% (in the 18–24-year-old age class) in response to substantial increases in targeted demersal longline fishing effort in regions 3 and 4 (McAuley, 2006a, b). The 42% decline in median estimates of r for C. plumbeus between 2001/2002 and 2003/2004, corresponded to a 76% increase in the overall reported catch by the target fisheries (McAuley, 2006a, b), suggesting that the escalation in catches was depleting the stock at an increasing rate. As the application of estimated fishing mortality rates resulted in mostly (66.0–99.4%) negative estimates of r, the model suggested that even with the highest assessed survival rates and the most favourable combinations of biological characteristics, fishing was unsustainable throughout this study. Given this, the reported 265% increase in the 2004/2005 catch by the northwestern (region 4) demersal longline fishery (McAuley, 2006b) is a cause for huge concern, especially given that the majority of C. plumbeus caught in the region are of adult size sharks.
The median estimate of r = –0.009 in 2002/2003 was, however, inconsistent with the overall declining trend in r estimates during the 3 years for which tag-recapture data were available. Considering that the combined C. plumbeus catch by the target fisheries in 2002/2003 of 258 t (live weight) was similar to the previous year’s catch of 235 t, this result appears anomalous (McAuley, 2006a, b). There are many plausible explanations for this unexpected result. First, juvenile C. plumbeus are highly mobile (McAuley et al., 2005), and widely distributed in deeper Western Australian continental shelf waters where the nearshore gillnet fishery does not operate regularly (McAuley et al., 2007a), and the distribution of fishing effort is very patchy throughout the species’ range. Therefore, the simplest explanation is that there could have been a temporary variation in the distribution of tagged sharks with respect to the distribution of fishing effort during that year, which led to a coincidentally low rate of capture.
It is also possible that the method used to estimate non-reporting rates of tag recaptures could have caused biases in the estimated rates of fishing mortality, leading to underestimation of F in 2002/2003 and/or overestimation in other years. Although this method does have some potential to bias results by classifying fishers who would have reported tag recaptures but caught no tagged sharks by chance as non-reporters, this is only likely to be significant when the average number of tags caught by each fisher is low. For example, when the mean rate of tag recapture per fisher is 1.0, the expected probability of fishers reporting no tags (even if everyone reports honestly) from an assumed Poisson distribution is e–1.0 = 37%. However, during the 3-year tagging study, more than 97% of the reported C. plumbeus catch was landed by just 17 shark fishing vessels (RBM, unpublished data), ten of which reported recapturing tagged sharks. Therefore, the resulting average recapture rate of 3.7 tags per "target" vessel gives a 98% probability that non-reporting fishers did actually recapture tagged sharks (i.e. p = 1–e–3.7), suggesting that any bias caused by this method was likely negligible.
Alternatively, despite pooling tag-recapture data into multiyear age classes, sample sizes were relatively small, and annual rates of instantaneous fishing mortality were sensitive to small variations in the numbers of reported recaptures. It is therefore also possible that a genuinely low rate of reported tag recaptures in 2002/2003 could have led to underestimating the rates of fishing mortality that year. Although it also holds that the small annual sample sizes could equally have caused overestimation of F in the other years, this seems less likely owing to the similarities between the rates estimated for 2001/2002 and 2003/2004, once increases in the reported catch and non-reporting rates are taken into consideration. Moreover, whatever the cause or, more likely, causes for the lower-than-expected rates of F in 2002/2003, the relationship between the increasing trends in estimates of the rate of fishing mortality and reported catches between 2001/2002 and 2003/2004 strongly suggests that F was underestimated in 2002/2003 and that resulting estimates of r for that year (although still overwhelmingly negative) were therefore overly optimistic.
The sustainability of such high rates of C. obscurus fishing mortality has previously been attributed to the "gauntlet" characteristics of the Western Australian gillnet fishery (Stevens et al., 1997; Walker, 1998; Simpfendorfer, 1999a; Prince, 2005), whereby older juvenile age classes are largely immune to exploitation because of their distribution outside of the fishery’s operational area, and the size-selective nature of catches from the mesh sizes permitted in the fishery (165–178 mm stretched mesh; Simpfendorfer and Unsworth, 1998; McAuley et al., 2007b). However, because of their smaller size-at-age, a greater proportion of C. plumbeus age classes appears vulnerable to the same mesh sizes (McAuley et al., 2005, 2007b). Also, unlike C. obscurus, older juvenile and adult C. plumbeus were subject to targeted exploitation by the less size-selective longline fisheries operating in regions 3 and 4 (McAuley et al., 2005, 2007a). Therefore, despite the maximum estimated rates of C. plumbeus fishing mortality being lower than those for C. obscurus, the application of fishing mortality across a much broader range of C. plumbeus age classes contributed to the highly pessimistic estimates of the potential growth rates of this population. As the two study populations share broadly similar biological characteristics and equivalent intrinsic rates of increase, the contrast in r estimates under the two very different scenarios of fishing mortality demonstrate distinct benefits in restricting the exploitation of K-selected shark stocks such as these to a small number of juvenile age classes.
Results from this study also suggest that within the ranges of estimated and observed parameter values, the Western Australian C. obscurus and C. plumbeus populations’ potential for increased population growth, in response to reductions in population density, for example, is severely constrained. Even though there is very little empirical evidence that either somatic growth rates or fecundity of shark populations are influenced by density-dependence, both have been proposed as possible compensatory mechanisms (Holden, 1977; Wood et al., 1979; Sminkey and Musick, 1995; Walker, 1998, 2007). Although greater than tested levels of variation in growth rates, age at maturity, maximum age, and fecundity are possible, the low variability in the absolute magnitude of r estimates for both populations suggests that substantial changes in one or more of these parameters would be required to effect appreciable increases in population growth. The validated age and growth estimates and observed reproductive data from which input parameters were derived exhibited relatively little variation, but it was not possible to verify empirically the accuracy of the estimates of natural mortality used in the models. Therefore, as other authors have noted, there would appear greater potential for density-dependent compensation in these populations via changes in natural mortality than through variation in age, growth, and rates of reproduction (Walker, 1992, 1998; Au and Smith, 1997; Punt and Walker, 1998; Smith et al., 1998).
Given these results, the introduction of management measures to address the currently unsustainable levels of C. plumbeus exploitation by the target fisheries and the high risk to sustainability of unquantified but inferred catches of older C. obscurus by other Western Australian fishing sectors should not be delayed. We also conclude that, in the absence of suitably long indices of relative abundance, where reliable biological data and estimates of fishing mortality are available, stochastic demographic analysis can provide a tool for assessing the efficacy of existing and alternative fishery management strategies. This approach has also proven very useful for determining defensible baseline estimates of sustainable harvest levels for Western Australian fisheries (McAuley, 2006b), at least until sufficiently long time-series of fishery and abundance data for developing dynamic fishery assessment models can be collected.
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We are grateful to the Fisheries Research and Development Corporation for co-funding this and related research, to the skippers and crews of the Western Australian shark fisheries on whose vessels most of these data were collected, and to the other commercial and recreational fishers who reported tag recaptures. In particular, we acknowledge the considerable assistance of the skipper and crew of the RVs "Flinders" and "Naturaliste". We also thank Rick Allison, Ryan Ashworth, Justin Chidlow, Dennyse Newbound, and Ben Sale for their assistance with the collection and preparation of biological samples and data, and Rod Lenanton, Steve Newman, Peter Stephenson, and Dan Gaughan from the WA Fisheries and Marine Research Laboratory, Glenn Hyndes at Edith Cowan University, and Carl Walters from the University of British Columbia for their advice on these analyses. We also acknowledge the constructive comments of Helen Dobby and Gregor Cailliet on an earlier version of this paper. All sampling was conducted according to the relevant laws of Australia and the State of Western Australia, and with the approval of Edith Cowan University’s Animal Ethics Committee.
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  R. B. McAuley, C. A. Simpfendorfer, and I. W. Wright Gillnet mesh selectivity of the sandbar shark (Carcharhinus plumbeus): implications for fisheries management ICES J. Mar. Sci., December 1, 2007; 64(9): 1702 - 1709. [Abstract] [Full Text] [PDF]
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