A fishery-independent survey of juvenile shortfin mako (Isurus oxyrinchus) and blue (Prionace glauca) sharks in the Southern California Bight, 1994–2013

Fisheries Research 183 (2016) 233–243

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A fishery-independent survey of juvenile shortfin mako (Isurus oxyrinchus) and blue (Prionace glauca) sharks in the Southern California Bight, 1994–2013 Rosa Runcie a,∗ , David Holts b , James Wraith b , Yi Xu c , Darlene Ramon b , Rand Rasmussen b , Suzanne Kohin b a Ocean Associates, Inc. Under Contract to the Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, CA 92037, USA b Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, CA 92037, USA c National Research Council Affiliated with the Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, CA 92037, USA

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Article history: Received 20 January 2016 Received in revised form 9 June 2016 Accepted 9 June 2016 Handled by A.E. Punt Keywords: Pelagic shark longline survey Catch-per-unit-effort (CPUE) Shark size sampling Northeast Pacific Ocean Blue shark Shortfin mako shark

a b s t r a c t A fishery-independent abundance survey was initiated by the National Marine Fisheries Service (NMFS) and the California Department of Fish and Game (CDFG) in 1994 to track the relative abundance and size of juvenile shortfin mako (Isurus oxyrinchus) and blue (Prionace glauca) sharks in the Southern California Bight (SCB). The survey was designed based on data from an experimental commercial shark longline fishery that operated in the SCB during 1988–1991. Survey sets were conducted annually during the summer months within seven 10 × 10 min spatial blocks in the SCB close to the California Channel Islands. Between 1994 and 2013, survey effort totaled 460 sets. The standardized catch-per-unit-effort (CPUE) of shortfin mako showed a generally declining trend from 1994 through 2010 with increases during the final years to a level similar to those of the mid-1990s. For blue sharks, the standardized CPUE showed a generally declining trend throughout the time series with the lowest values in 2012 and 2013, and an anomalously high CPUE in 2000. Catch rates varied across the survey area with fewer, larger sharks caught in the more northern blocks of the survey. Sharks of age classes 0–2 represented the majority of those caught in the survey (approximately 81% of blue sharks and 58% of makos), yet there was variability in the sizes of blue and mako sharks caught by year. The sex ratio of age-0 sharks caught was not different from 1:1 for shortfin makos, but skewed toward females for blue sharks. Although the survey area is relatively small and results show interannual and spatial variability in CPUE that is not fully understood, these data represent the first and only fishery-independent survey that has targeted these shark species in the SCB. The results of the survey and associated data provide useful information regarding regional relative abundance, size- and sex-compositions, and spatial distributions of shortfin mako and blue sharks, all of which are essential for stock assessments and fisheries management. © 2016 Elsevier B.V. All rights reserved.

1. Introduction Juvenile shortfin mako (Isurus oxyrinchus; hereafter referred to as mako) and blue sharks (Prionace glauca) inhabit the highly productive waters of the Southern California Bight (SCB) during the summer months (Hanan et al., 1993; Holts and Bedford, 1993; O’Brien and Sunada, 1994). Both species are important components

∗ Corresponding author. E-mail address: [email protected] (R. Runcie). http://dx.doi.org/10.1016/j.fishres.2016.06.010 0165-7836/© 2016 Elsevier B.V. All rights reserved.

of the pelagic ecosystem and co-occur throughout the California Current and offshore with many other large pelagic fish such as swordfish and tunas. While not specifically targeted in U.S. west coast commercial fisheries, makos caught incidentally are considered valuable and are marketed on the West Coast and elsewhere (PFMC, 2013, 2016). Recreational angling for makos is also popular because it is among the fastest swimming and most acrobatic of large pelagic fish, and is prized by anglers for the challenge of the fight (Stevens, 2008). Like makos, blue sharks are caught incidentally in high numbers in U.S. west coast commercial fisheries and are thus important to monitor as a bycatch species. However, they

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have low market value in the U.S. and most caught off California are discarded at sea (O’Brien and Sunada, 1994; Holts et al., 1998; James et al., 2015). Fisheries along the U.S. West Coast that catch mako and blue sharks have been monitored and managed since the late 1970s by state or federal fisheries managers (PFMC, 2013, 2016). Historically these have included drift and set gillnet, hook and line, longline, and harpoon fisheries. The only U.S. west coast fishery to target these species began in the late 1980s when California issued a limited number of permits for an experimental pelagic longline fishery in the SCB. The fishery operated from 1988 through 1991 (O’Brien and Sunada, 1994) and was opened to exploit the large number of these sharks that come into the Bight during the summer months, and to develop a market for shark. The fishery catch was almost exclusively mako and blue sharks, the majority of which were juveniles. During 1990, the California Fish and Game Commission imposed a minimum landing requirement of 40,000 pounds for blue sharks for all the vessels operating in the experimental fishery with hope to develop a market for their meat, skin and other products. However, when buyers were not interested in blue shark, the minimum landing requirement was removed. After the 1991 season, the experimental fishery was terminated because of low profits and concerns over the high take of juvenile sharks (O’Brien and Sunada, 1994). Between 2000 and 2014, an annual average of 43 mt of makos was landed commercially on the U.S. West Coast, with approximately 56% taken in the pelagic drift gillnet fishery for swordfish and smaller proportions taken in the pelagic longline, set gillnet and nearshore small mesh drift gillnet fisheries (PFMC, 2016). For blue sharks, an annual average of 4 mt was landed on the U.S. West Coast over the same period, and an additional estimated 1470 (approximately 15 mt) blue sharks were discarded annually from the pelagic drift gillnet fishery (NMFS, 2015; PFMC, 2016). Many shark species are vulnerable to heavy fishing pressure due to their K-selected life history characteristics of slow growth, long lives, late maturity and low fecundity (Hoenig and Gruber, 1990; Smith et al., 1998; Musick et al., 2000). In addition, many shark species, including mako and blue sharks, segregate by size and/or sex (Nakano, 1994; Nakano and Seki, 2003; Mucientes et al., 2009) making them vulnerable to different fisheries across their lifetimes. Based on the proportionately high catches of young-ofthe-year and juvenile mako and blue sharks in the SCB relative to subadults and adults, the area is considered a nursery for these species (Hanan et al., 1993; O’Brien and Sunada, 1994; Holts et al., 1998). While there is some evidence that for long-lived, low fecundity sharks, protecting subadults and adults is more beneficial for population sustainability than protecting young sharks, the benefits vary depending upon both the life history characteristics of the stocks and the extent of the nursery areas (Kinney and Simpfendorfer, 2009). Collecting information on mako and blue sharks off the U.S. West Coast in this nursery area is challenging due to the lack of target fisheries, thus life history information, fishery catch, catch/effort and catch at size data that provide the basis for fish population assessments are limited. The NMFS Southwest Fisheries Science Center (SWFSC) and California Department of Fish and Game (CDFG) initiated a fisheryindependent survey for juvenile mako and blue sharks in the SCB in 1994 to monitor trends in their relative abundance and to study aspects of their biology to inform fishery managers of their status. This survey has been conducted annually since 1994 (with the exception of 1998 and 1999). The short-lived experimental shark fishery (O’Brien and Sunada 1994) provided baseline data from which a survey to track relative abundance was designed. Having been conducted for 20 years, the survey now provides relative abundance indices, size and sex composition trends, and spatial dis-

tribution information that provide information to regional fishery managers and is useful for stock assessments of these species. 2. Materials and methods 2.1. Fishery-independent survey The CDFG created numbered fishery reporting blocks used to describe general locations of fishing activity on logsheets and landing receipts (CDFG, 1944). Seven fishing blocks (707, 723, 742, 805, 828, 846, and 848; each 10 × 10 min) in the SCB were selected for the survey (Fig. 1). In the former experimental shark longline fishery, consistently high catch-per-unit-effort (CPUE) and low variability were observed in the seven selected blocks during the months of June through August (O’Brien and Sunada, 1994; CDFG, pers. comm.) relative to other areas in the Bight where the fishery operated, demonstrating that these blocks fell within the core abundance area of the juvenile sharks. Since 1994, five vessels have been used to conduct the annual survey: NOAA R/V David Starr Jordan, California State University R/V Yellowfin, California Department of Fish and Game R/V Mako, and the chartered commercial F/Vs Ventura II and Southern Horizon. During the survey, efforts were made to sample each of the seven selected fishing blocks four times during the months of June through August. The sampling was conducted in two consecutive stages, with sampling conducted twice in each block during the first stage of 7–10 days, followed by resampling of each of the blocks during the latter 7–10 days. Two sets were conducted in each block during each stage, generally one in the morning and one in the afternoon. Locations within the block were selected without regard to local conditions (i.e., there was no effort to “target” sharks within the block) and such that the beginning set locations were separated by at least 8 km. This resulted in both greater temporal and spatial coverage of the sets within each block for any given year, and for the analyses, each set was thus considered an independent observation. The survey was not conducted during 1998 and 1999 due to funding and scheduling conflicts. The fishing methods used during the survey sets replicated those of the former experimental longline fishery for sharks (as diagramed in O’Brien and Sunada 1994). The gear used was a 3.7 km (2 nmi) stainless steel mainline rigged with 180–210 stainless steel leaders of about 5 m (2–3 fm) length. Leaders were attached at 15 m (50 ft) intervals, and each was terminated with a 9/0 J-style hook baited with whole mackerel (Scomber japonicus). Buoys with approximately 5 m (2–3 fm) polypropylene leaders were placed after every fifth hook to maintain a relatively shallow fishing depth. The gear was allowed to drift with one end affixed to the vessel for three to four hours from the time the first hook entered the water to the time the first hook was retrieved (calculated soak time). During most sets, hooks were retrieved in reverse order, with the last hook set hauled first. Survey sets were conducted during daylight hours; the first baited hook entered the water no earlier than 5:30 am, and retrieval of the gear was initiated no later than 7:00 pm Occasionally, ancillary sets using similar survey methods with slight variations in gear configuration, set timing, or bait were completed either within or outside the survey blocks to meet other research objectives. At the time of each set, environmental observations were recorded including wind direction, swell height and direction, Beaufort sea state, sea surface temperature (SST), bottom depth, bottom type, kelp presence, water color and cloud cover. 2.2. Shark handling In the first four years of the study (1994 through 1997), sharks were either kept in the water with sizes estimated or pulled aboard

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Fig. 1. Map illustrating the research survey area within the Southern California Bight. The seven CDFG blocks surveyed are shown as colored squares. Survey (n = 460) and ancillary (n = 293) sets conducted during the survey cruises are shown with blue and red dots, respectively.

and measured on a small portable measuring board. Beginning in 2000, provided a captured shark was not too large and the conditions were not too dangerous, it was brought alongside the boat and pulled into a cradle designed to support the shark above the waterline. In the cradle, sharks were sexed and measured to the nearest cm (either straight fork length (FL) or straight total length (TL), or both). All live sharks and other live fish caught were released with or without tags. Sharks that did not survive the longline capture were retained for other studies. 2.3. Nominal and standardized CPUE Nominal CPUE was calculated for the two target pelagic shark species and for pelagic rays (Pteroplatytrygon violacea), the third most commonly caught species. Ancillary sets, i.e. those sets conducted during survey cruises that addressed other research objectives, were not included in the CPUE analysis unless otherwise noted. The following equation was used to calculate a nominal CPUE in number of fish per 100 hook-hours for each set: [numbercaught/(numberofhooks × soaktimeinhours)] × 100 Means and standard errors of the nominal CPUE by year and block were calculated and compared using ANOVAs and Tukey tests to examine abundance trends and variability over time and space. In order to statistically determine whether the vessel, or any temporal, spatial or environmental conditions affected the nominal CPUE, a boosted regression tree analysis (BRT, Elith et al., 2008) was used to study changes in nominal CPUE with respect to all pos-

sible factors (e.g., vessel, month, block, Beaufort sea state, water color, etc.). We examined the relationship between the nominal CPUE and the detected important factors using general linear models (GLMs) with Gaussian error distribution. We initially examined several models with error distributions including gamma, Gaussian and delta-lognormal. The GLM with Gaussian error distribution was finally selected because it explained more of the variability in nominal CPUE. Because some sets had zero catch, a constant value of 1 was added before log transforming the data for the analyses. We tested the sensitivity of adding 0.1 and 0.01 instead of 1 to the CPUE term and found that the model was robust as long as a constant was chosen, which was consistent with prior studies (Porch and Scott, 1994; Maunder and Punt, 2004). For each species, GLMs that included the important factors as found through the BRT analyses were fit using models of the form: ln(CPUEi + 1) = ˇo + ˇ1 Xi1 + ˇ2 Xi2 + ˇ3 Xi3 +. . . + εi Throughout the rest of the paper, “logCPUE” is used to represents the ln(CPUEi + 1) term. The standardized CPUE indices for each year t (It ) were calculated as:



It = exp

␴t 2 ␣ ˆt + 2



where ␣ ˆ t is the year factor estimated from the GLM, and ␴t is the standard error of ␣ ˆ t . This population marginal mean calculation (Searle et al., 1980) is widely used in CPUE standardization models. GLMs without block as a factor were conducted to study the potential auto-correlation between temperature and/or year and block,

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Table 1 Summary of the shark abundance survey cruises conducted off the Southern California Bight between 1994 and 2013. Year

1994 1995 1995 1996 1997 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

Start

End

Number of Sets

Month

Day

Month

Day

7 6 7 8 7 6 6 6 6 6 7 6 7 6 7 7 6 6 7

11 19 24 10 23 19 18 18 21 18 7 26 3 9 29 14 24 20 3

7 6 8 8 8 7 7 7 7 7 7 7 8 6 8 8 7 7 7

23 30 24 28 11 16 14 7 6 7 23 15 2 26 27 12 13 18 22

as well as GLMs that included the survey and ancillary sets to see if CPUE was consistent across the other gears, areas and times fished. 2.4. Size and sex ratios To standardize size measurements over the course of the survey, linear relationships to convert TL to FL for mako and blue sharks were determined using data from sharks for which both were available from all survey and ancillary sets. Once all lengths were converted to FL, the sizes of mako and blue sharks caught during the survey cruises were examined by year and survey block using ANOVAs. Sex-specific length frequencies in 5 cm length bins for each species were compared using a two-sample KolmogorovSmirnov test. The proportion of males caught (sex ratio) for each 10 cm length bin was also calculated and tested for departures from 1:1 using a Chi-Square Goodness of Fit test. Mako sharks were considered young-of-the-year (age-0) if they were smaller than 100 cm FL (Wells et al., 2013; Pratt and Casey, 1983). Blue sharks were considered young-of-the-year if they were smaller than 90 cm FL (Cailliet and Bedford, 1983; Blanco-Parra et al., 2008; Stevens, 1975). All statistical analyses were conducted in R for Windows (R Development Team, version 2.15.2; http://www.R-project.org/). 3. Results 3.1. Effort and catch Nineteen survey cruises were conducted during the 20-year period (Table 1). Survey effort totaled 460 pelagic longline sets comprising 1677 h of effort during which 88,141 hooks were set (Table 2). An additional 293 sets were conducted during these cruises to meet other research goals. Fig. 1 shows the locations of all the survey and ancillary longline sets conducted during the survey cruises. Catch during the survey sets totaled 1726 makos, 2749 blue sharks and 456 pelagic rays. Ninety four percent of the mako and blue sharks caught during the survey cruises were released alive. Other species including opah (Lampris guttatus), thresher shark (Alopias vulpinus), Pacific mackerel (Scomber japonicus), Barred sand bass (Paralabrax nebulifer) and common mola (Mola mola), were also caught during the survey and ancillary research sets, but in relatively low numbers compared to blue and mako sharks and pelagic rays.

22 17 35 44 36 55 49 35 31 38 28 41 51 34 58 51 37 56 35

Cruise Number

Vessel Name

LL-JM-0004 95-M-07 YF-CA-95 LL-JM-0009 YF-CA-97 LL-JM-0013 LL-JM-0014 LL-JM-0015 LL-JM-0016 LL-JM-0017 LL-JS-0018 LL-JS-0019 LL-JS-0020 LL-JS-0021 LL-JS-0022 LL-JS-0023 LL-JS-0024 LL-JS-0025 LL-JS-0026

DAVID STARR JORDAN MAKO YELLOWFIN DAVID STARR JORDAN YELLOWFIN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN DAVID STARR JORDAN VENTURA II SOUTHERN HORIZON VENTURA II VENTURA II VENTURA II VENTURA II

3.2. CPUE The average annual nominal CPUE in numbers of fish per 100 hook-hours for mako sharks ranged from 0.06 to 1.43 (Table 2). The highest nominal CPUEs occurred during 1994 and 1996 and the lowest nominal CPUEs occurred in 2008 and 2010. There was a gradual decline in the 1990s reaching a low level by 2000 that was maintained until the last few years when the CPUE again approached a level comparable to those of the mid 1990s (Table 2). There was considerable variation by set in the nominal CPUE data. The results of the BRT analyses showed that for mako sharks, only year, block, and SST were important factors. The effects of the rest of the factors were considered negligible (i.e., the percent of variation in nominal CPUE explained by each factor was <1%; Appendix A in Supplementary material). The standardized CPUE, based on the final model, logCPUE ∼ Year + Temperature + Block, showed a trend similar to the nominal CPUE (Fig. 2a). Detailed GLM output for the final model for mako sharks is shown in Appendix B. GLM models without block as a factor as well as including both survey and ancillary sets showed similar results with higher but variable CPUE through 2001 followed by a gradually declining CPUE to a low point in 2010, and an increasing trend beginning in 2011 (Appendix Fig. B.1 in Supplementary material). For mako sharks, CPUE varied across blocks (ANOVA, F = 3.918, p < 0.001) and was generally higher in the survey blocks to the southeast of Santa Catalina Island and east of San Clemente Island (blocks 805, 828, 846, and 848; Table 3, Appendix B in Supplementary material). For blue sharks, the average annual nominal CPUE in numbers of fish per 100 hook-hours ranged from 0.06 to 7.19 (Table 2). The highest blue shark nominal CPUE occurred during 2000 and the lowest nominal CPUEs occurred in 2010 and 2013. Higher nominal catch rates were generally observed prior to 2001. More recently, a relatively high nominal catch rate of 1.41 blue sharks per 100 hook-hours was observed in 2006 after which there has been a declining trend in nominal CPUE to the lowest observed level in 2013 (Table 2). As observed for mako sharks, there was considerable variation by set in the nominal CPUE data. The results of the BRT analyses showed that for blue sharks, only year and block were important factors. Unlike for mako sharks, temperature was not found to have a significant effect on nominal CPUE (Appendix Fig. A.1 in Supplementary material). The standardized CPUE, based on the final model, logCPUE ∼ Year + Block, showed a trend similar to the nominal CPUE (Fig. 2b). Detailed GLM out-

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Table 2 Number of survey sets, hooks, soak time and shortfin mako, blue shark and pelagic ray catch, nominal CPUE (catch per 100 hook-hours), and standard error by year. Year

Number of Survey Sets

Number of Hooks

1994 1995 1996 1997 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013

4 28 23 18 27 27 28 28 29 26 27 28 28 27 29 27 28 28

673 4433 3720 2953 4444 4613 5054 5635 5649 5312 5527 5759 5807 5575 5956 5493 5592 5946

Total

460

88,141

Soak Time (HR)

Mako Catch

Mako CPUE

41 140 164 63 40 187 97 66 67 73 90 112 40 100 13 61 115 257

1.43 1.13 1.32 0.66 0.26 1.09 0.53 0.33 0.34 0.33 0.45 0.52 0.19 0.45 0.06 0.28 0.56 1.08

18.25 77.90 78.91 59.51 86.48 100.08 102.44 98.20 102.42 106.22 96.34 107.88 90.97 106.35 114.72 108.08 110.54 111.65 1677

Mako Std. Error 0.30 0.14 0.26 0.19 0.09 0.26 0.14 0.05 0.05 0.10 0.07 0.15 0.07 0.08 0.02 0.05 0.10 0.22

Blue Catch 25 202 272 85 924 78 50 104 107 102 272 139 208 67 25 49 26 14

1726

Blue CPUE 0.82 1.66 2.24 0.90 7.19 0.48 0.27 0.53 0.55 0.47 1.41 0.61 1.05 0.31 0.11 0.22 0.13 0.06

Blue Std. Error 0.25 0.20 0.38 0.27 1.36 0.13 0.08 0.11 0.14 0.08 0.38 0.12 0.26 0.06 0.03 0.05 0.03 0.02

2749

Ray Catch 33 24 38 31 24 90 20 30 33 13 21 13 5 31 18 5 16 11

Ray CPUE 1.00 0.18 0.31 0.32 0.17 0.50 0.10 0.15 0.17 0.06 0.10 0.06 0.02 0.14 0.08 0.02 0.07 0.05

Ray Std. Error 0.46 0.04 0.07 0.05 0.05 0.15 0.03 0.07 0.04 0.02 0.04 0.02 0.01 0.03 0.03 0.01 0.02 0.02

456

Fig. 2. Boxplots showing the median and interquartile ranges of annual nominal CPUE by set from 1994 through 2013 (n = 460), and the standardized abundance indices based on the final general linear models (red solid line) for (A) shortfin mako shark (n = 450), and (B) blue sharks (n = 460) in the SCB. Red dashed lines represent the 95% confidence intervals for the standardized CPUEs based on 1000 bootstrap runs. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Table 3 Summary of number of sets, hooks, soak time and shortfin mako and blue shark CPUE by CDFG block. Total catch at each block and the CPUE standard error values are included. Letters show groupings of CPUEs found to not differ significantly from one another. Block

Number of Sets

Number of Hooks

Soak Time (HR)

Mako Catch

Mako CPUE

Mako Std. Error

Blue Catch

Blue CPUE

Blue Std. Error

707 723 742 805 828 846 848

59 60 66 70 71 66 68

11,390 11,612 12,689 13,382 13,498 12,456 13,114

218.52 230.43 241.78 256.07 256.48 234.24 239.42

117 193 196 387 284 224 325

0.28a 0.44abc 0.43ab 0.83c 0.60abc 0.55abc 0.72bc

0.04 0.10 0.06 0.11 0.09 0.09 0.13

133 92 139 507 577 634 667

0.35ab 0.22a 0.32a 1.24abc 1.62bc 1.68c 1.70c

0.06 0.04 0.08 0.25 0.46 0.35 0.40

put for the final model for blue sharks is shown in Appendix C of Supplementary material. GLM models without block as a factor as

well as including both survey and ancillary sets showed similar results with higher and more variable CPUE through 2000, lower

238

R. Runcie et al. / Fisheries Research 183 (2016) 233–243 Table 4A ANOVA results for the effects of block and year on size of shortfin mako caught during the survey sets. Source

df

Sum of Squares

Mean of Squares

F-ratio

p-value

Block Year Block × Year Residuals

6 17 91 1207

47,329 48,858 118,804 658,066

7888 2874 1306 545

14.468 5.271 2.395

<0.0001 <0.0001 <0.0001

Table 4B ANOVA results for the effects of block and year on size of blue sharks caught during the survey sets. Source

df

Sum of Squares

Mean of Squares

F-ratio

p-value

Block Year Block × Year Residuals

6 17 88 2281

614,714 312,888 219,243 973,516

102,452 18,405 2491 427

240.051 43.124 5.837

<0.0001 <0.0001 <0.0001

Makosharks : FL = 0.9173 × TL − 0.8078, R 2 = 0.986, n = 356 (range64–193 cmFL)

Bluesharks : FL = 0.8162 × TL + 0.0714, R 2 = 0.986, n = 1125 (range44–200 cmFL)

Fig. 3. CPUE in catch per 100 hook-hours with respect to sea surface temperature for all positive survey sets for (A) shortfin mako and (B) blue sharks.

but relatively consistent CPUE from 2001 through 2005, then a gradually declining trend through 2013 following relatively higher catch in 2006 (Appendix Fig. C.1 in Supplementary material). For blue sharks, CPUE varied across blocks (ANOVA, F = 5.18, p < 0.001) and was generally higher in the survey blocks to the southeast of Santa Catalina Island and east of San Clemente Island (Table 3, Appendix C in Supplementary material). Nominal CPUE for pelagic rays is shown in Table 2. Because fewer of this species were caught, and the survey was not conducted to track their relative abundance, no further analyses were conducted to standardize pelagic ray CPUE or examine the effects of various spatial, environmental and fishing factors on their catch over time. 3.3. Sea surface temperature and CPUE Survey and ancillary fishing occurred at sea surface temperatures ranging from 12.9 to 23.4 ◦ C. During all research effort, mako and blue sharks were caught at surface temperatures ranging from 15.6 to 23.4 ◦ C and 13.9 to 23.4 ◦ C, respectively. Survey nominal CPUE varied with temperature (Fig. 3), and as shown in the BRT analyses, temperature had a significant effect on nominal CPUE for mako sharks but not for blue sharks (Section 3.2; Appendix A in Supplementary material). The anomalously high nominal CPUEs for blue shark occurred during 2000 when the average set temperature was 19.97 ± 0.60 ◦ C (mean ± SD). 3.4. Shark size and sex composition There was no significant difference in the relationships between FL and TL by sex (Likelihood ratio test, ␹2 = 0.218, p = 0.64 for makos and ␹2 = 1.139, p = 0.29 for blues), thus the following sex-combined relationships were derived to convert TL to FL:

Length frequencies of mako sharks caught during the survey cruises were not found to differ between sexes (Two sample Kolmogorov-Smirnov test, D = 0.079, p = 0.999) and were thus combined. Makos caught averaged 115 ± 26.1 cm FL (mean ± SD). There were three distinct modes among the smaller sizes at 75–80, 100–105 and 125–130 cm FL (Fig. 4a). Female and male length frequencies of blue sharks caught were found to differ significantly (Two sample Kolmogorov-Smirnov test, D = 0.357, p = 0.009). The mean size of female blue sharks caught was 86 ± 20.6 cm FL (mean ± SD) and of male blue sharks was 99 ± 36.0 cm FL (mean ± SD). The length frequency distributions for female and male blue sharks each showed one mode at 75–80 and 80–85 cm FL, respectively (Fig. 4b). The majority of sharks caught were small; only 178 of 1896 mako sharks and 244 of 3802 blue sharks measured were greater than or equal to 150 cm FL. For mako sharks, the number of males caught exceeded the number of females caught for most size classes (Fig. 5a). The ratio of males to females for all mako sharks caught during the survey cruises was 1.38:1 (n = 1878, ␹2 = 48.56, p < 0.001). For age-0 mako sharks, the ratio of males to females was 1.15:1 which was not significantly different from 1:1 (n = 555, ␹2 = 2.7405, p = 0.098). For blue sharks the proportion of males caught increased with size (Fig. 5b), with only 3 females greater than or equal to 200 cm FL caught. Across all sizes, nearly equal numbers of males and females were caught with a male to female ratio of 0.99:1 (n = 3779, ␹2 = 0.077, p = 0.782). However, the male to female ratio of age0 blue sharks was 0.75:1 which differed from 1:1 (n = 2379, ␹2 = 47.173, p < 0.001). Interestingly, for pelagic rays of all sizes, females outnumbered males by a factor of 4.4. Year and block had significant effects on the size of mako and blue sharks caught (Tables 4A and 4B). Annual median size of makos ranged from 89 to 127 cm FL and of blue sharks ranged from 74 to 199 cm FL (Fig. 6). There was no clear trend in the size of mako or blue sharks caught over the course of the survey. The years with the highest median sizes of mako sharks caught were 2007 and 2012 whereas smaller makos were caught in 1996, 2005 and 2006.

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Fig. 4. Length frequency histograms by 5 cm length bins for sharks caught during the survey and ancillary sets: (A) shortfin makos (sex combined n = 1896) and (B) blue sharks (males n = 1881, females n = 1897).

Fig. 5. Proportion of males caught by 10 cm length bins during the survey and ancillary sets for (A) shortfin makos, and (B) blue sharks. Numbers above the bars are the numbers of sharks within each size bin.

For blue sharks, larger sharks were caught during the 2002, 2003, 2010, 2012 and 2013 surveys. The smallest blue sharks were caught during the 1997 survey. Median size for both species was greatest in the most northern block of the survey, block 707, southeast of Santa Cruz Island, and smaller sharks were caught in the four southern blocks of the survey (Fig. 7).

4. Discussion This study was initiated to learn more about the local abundance and biology of mako and blue sharks and represents the only fishery-independent survey for these species along the U.S. West Coast. Over the 20 years of sampling history, the time series

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Fig. 6. Size of (A) shortfin mako and (B) blue sharks caught by year in the survey sets. The horizontal line, box plots and error bars define the median, interquartile range and 1.5 times that range, respectively. The median size by year of shortfin makos caught ranged from 89 cm to 127 cm FL and of blue sharks ranged from 74 cm to 199 cm FL.

Fig. 7. Size of (A) shortfin mako and (B) blue sharks caught within each survey block. The horizontal line, box plots and error bars define the median, interquartile range and 1.5 times that range, respectively. Median fork length by survey block for shortfin mako ranged between 101 cm (block 828) to 128 cm (block 707). Median fork length by survey block for blue sharks ranged between 81 cm (block 805) and 166 cm (block 707).

of standardized CPUE demonstrates variability across years, and although the spatial coverage of the survey is limited, that relative abundance appears to have been higher before the early 2000s for both species. When compared to data from the experimental shark longline fishery that operated from 1988 through 1991, similar catch rates and interannual variability at the beginning of

this survey were observed. Mako shark CPUE in the experimental fishery differed significantly between years because of a drop in 1990; however, the average nominal CPUE by year was 1.475 mako sharks per 100 hook-hours (O’Brien and Sunada, 1994) and close to that observed during the early years of this survey. Based on the results of the analyses herein combined with the experimental fishery results, and the paucity of data on these species in California waters prior to the early 1990s, it is not certain what contributes to high interannual variability in catch rates and whether periodic fluctuations in local relative abundance were historically common. The results may signify temporal changes in local abundance of these vulnerable predators that should be more fully explored and continually monitored. Mako and blue sharks in the SCB belong to stocks that are believed to range throughout the entire North Pacific (ISC, 2014, 2015; Nakano, 1994; Kai et al., 2015; Block et al., 2011; Wells et al., 2013). While the SCB is an important area for these species, in that young-of-the-year and juveniles use the Bight as a nursery area, there are other apparent nursery areas in the North Pacific where young-of-the-year and juveniles are common (Nakano, 1994; Kai et al., 2015). While this survey points toward a generally declining trend within the SCB for juvenile blue sharks, and a relative decline followed by an increasing trend for juvenile mako sharks, it is important to know the context of the local trends relative to the entire stock. Recent population-wide analyses demonstrate discrepancies in relative abundance trends locally across the North Pacific for both species (ISC, 2014, 2015). While some regional analyses show increasing trends for mako sharks (Ohshimo et al., 2016; ISC, 2015; present study), others show declining trends (Chang and Liu, 2009; ISC, 2015) making it difficult to determine the stock-wide population status. Similarly, although the North Pacific blue shark population is believed to be healthy and increasing after declines in the 1980s (ISC, 2014), relative abundance estimates from regional fisheries show inconsistent trends (Ohshimo et al., 2016; Clarke et al., 2013; ISC, 2014; present study). Given the observed spatial and temporal segregation by size and sex for these species (Nakano, 1994; Semba et al., 2011; Nakano and Nagasawa, 1996), and because the SCB comprises a relatively small fraction of the

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total stock area, drawing population level conclusions should be done with caution. The survey demonstrates that there is a spatial pattern in the distribution of mako and blue sharks over a small area within the SCB, with a greater number and smaller sharks caught in the blocks to the south and southeast of Santa Catalina Island than in the more northern blocks. While spatial segregation has been shown over larger areas (Nakano, 1994; Semba et al., 2011; Nakano and Nagasawa, 1996; Ohshimo et al., 2016), this observation over the small area sampled is somewhat surprising. Historically, catch rates of mako sharks in the experimental longline fishery that operated in the SCB also showed high catch in the 7 blocks sampled during this survey. However, it is not clear whether fewer or larger sharks were caught in the more northern blocks (O’Brien and Sunada, 1994). For the pelagic drift gillnet fishery, catches of mako and blue sharks have consistently been high in the survey area, and adult makos are reportedly intermittently caught near the Channel Islands and outer banks of the SCB, although the published data do not show a persistent pattern in the distribution by size or relative number of sharks throughout the area (Hanan et al., 1993). Recreational shark fishers in southern California report that large mako sharks are more likely to be found to the north of Santa Catalina Island (K. Poe, personal communication). In addition, a recent increase in the incidence of shark bitten sea lions at San Miguel Island is presumed to be due to predation by large mako and white sharks (Carcharodon carcharias) in that area (J. Harris, personal communication). Juvenile pelagic sharks are likely to use nursery areas where prey abundance is high and the risk of predation is low (Heupel et al., 2007; Branstetter, 1990; Cartamil et al., 2010). The SCB is a highly productive area in the summer due to coastal upwelling and current patterns that serve to support a high abundance of the species common in mako and blue shark diets (Chelton et al., 1982; Bograd et al., 2009; Preti et al., 2012). Regarding predation risk, if the northern areas are favored by the larger sharks, the southern areas may provide better nursery habitat where young-of-the-year pups are less likely to fall prey to larger sharks. Detailed analysis of fisheries logbook and observer data may show spatial patterns consistent with those found in this survey. The majority of sharks caught were immature. For makos, considering a presumed late winter/spring pupping season (Mollet et al., 2000), the modes in the size frequency distribution observed in the survey correspond to ages 0, 1 and 2 sharks (Wells et al., 2013). In the North Pacific, male makos reach maturity at about 180–210 cm TL, 165–190 cm FL (Semba et al., 2011; Conde-Moreno ˜ 2006; Joung and Hsu, 2005) and females reach and Galván-Magana, maturity at about 275–295 cm TL, 250–270 cm FL (Semba et al., 2011; Joung and Hsu, 2005). No mature female and few mature male makos were caught throughout the survey period. Similarly, for blue sharks, the modal size of 885 cm FL corresponds to approximately age 1 (Cailliet and Bedford, 1983). Observer data for the pelagic drift gillnet fishery off southern California between 1990 and 2013 show that most blue sharks caught were also juveniles, with an average size of 115.5 cm FL (NOAA WCR drift gillnet fishery observer data). In the North Pacific, male blue sharks reach maturity at about 185–203 cm TL, 150–165 cm FL and females reach maturity at 186–212 cm TL, 151–172 cm FL (Nakano, 1994; Joung et al., 2011). During the survey period, only 43 mature female (>151 FL) blue sharks were captured and sharks greater than 220 cm FL were exclusively male. Although adult makos are occasionally taken in commercial and recreational fisheries in southern California (Hanan et al., 1993; Lyons et al., 2015), the relative scarcity of adult female mako and blue sharks in California fishery-dependent and -independent data is curious given the prevalence of youngof-the-year pups. In this study, the sex ratio for age-0 mako sharks is consistent with that found in other studies and did not differ significantly

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from 1:1 (O’Brien and Sunada, 1994; Mollet et al., 2000; NOAA West Coast Region (WCR) drift gillnet fishery observer data). In contrast, for age-0 blue sharks, females outnumbered males by about 1.33:1. We analyzed the sex ratio of age-0 blue sharks by year, and although sample sizes are low in some years, the annual sex ratio typically showed a greater number of females than males, significantly so in 4 of the 15 years during which at least 12 pups were caught. The same pattern is not found for blue sharks caught in the pelagic drift gillnet fishery for swordfish that also operates off the coast of southern California where sharks less than 90 cm FL are caught at a ratio of 0.98 males:1 female (NOAA WCR drift gillnet fishery observer data). Nakano and Seki (2003) summarized blue shark embryo sex ratio information from a number of global studies. With the exception of a study from New South Wales (Stevens, 1984), sex ratios of blue shark embryos were close to 1:1. They did conclude, however, that there is sex segregation in sub-arctic and temperate nursery areas where immature females predominate (Nakano and Seki, 2003). A departure from a 1:1 sex ratio in age-0 blue sharks (suggesting a skewed sex ratio at birth) was not expected, and given that the finding is not consistent with the fishery data from the same region, biological/ecological significance is questionable. Small changes in the size of fish caught over time can provide information on the relative condition of the population or the size of recruitment cohorts (Hilborn and Walters, 1992). The mean and median size of mako and blue sharks caught during the survey varied significantly by year, but with no consistent trend. Because this survey typically catches juveniles of a small size range, the average sizes are not reflective of the entire populations, and for some years, sample sizes were quite low. Inferences about whether high fishing mortality on larger fish is occurring can not be drawn. Nevertheless, the data may be valuable to demonstrate recruitment events. For example, the high catch rate of small sharks in 2000 may be indicative of a particularly strong recruitment event that year. Although there were declining trends in nominal and standardized CPUE during this survey, and a more recent positive trend for mako sharks, there was considerable interannual variation in catch rates, in particular for blue sharks. It is not clear if this is due to spatial availability, recruitment fluctuations, or sampling biases. Spatial availability and recruitment fluctuations may be environmentally linked. Previous studies have reported correlations between SST and catch rates of blue and mako sharks (Bigelow et al., 1999; Carvalho et al., 2011; Walsh and Kleiber, 2001; Casey and Kohler, 1992; Campana et al., 2005; Ohshimo et al., 2016). Other environmental factors have also been linked to the distribution of large pelagic fish including depth of the mixed layer, dissolved oxygen content, water clarity, and the presence of fronts (Zainuddin et al., 2006; Dewar et al., 2011; Humphries et al., 2010; Xu et al., 2015). While we report a positive relationship between SST and nominal CPUE for mako sharks in this study, it is possible that further work examining other factors will reveal a relationship between the abundance of blue or mako sharks in the SCB and longer term temperature anomalies or other environmental conditions. Inconsistencies in survey operations, weather conditions and data collection can affect CPUE. As conditions varied across the research platforms used, challenges in data analysis were encountered. We tried to account for all differences within the times and areas surveyed by analyzing only sets that were conducted using consistent methods, but the change from smaller vessels used in the experimental commercial longline fishery and during some of the early surveys to use of the NOAA R/V David Starr Jordan necessitated extending the hook leader length from 2 to 3 fm. Upon decommissioning of the R/V David Starr Jordan and returning to relatively smaller vessels, the survey continued with a leader length of 3 fm. Differences in vessel size can also affect vessel drift and thus fishing depth or area fished. Longline fishing depth is known to affect

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the species composition of the catch (Walsh et al., 2009; Boggs, 1992), and longline catenary shape and fishing depth is affected by currents and drift (Bigelow et al., 2006; Boggs, 1992), thus anything affecting the survey fishing depth may also affect the nominal CPUE estimates. Whether the leader length or vessel drift affected catchability is unknown and difficult to test with these data, given other potentially confounding factors, however “vessel” was not found to be an important factor in the BRT analyses. Finally, unlike surveys that are conducted for relatively constrained fish, for example those associated with specific benthic habitats, surveys for migratory fish in pelagic habitats may need to be more adaptive in nature as the pelagic habitat in which these animals live is spatially and temporally variable. An ideal fishery-independent survey for pelagic sharks in the SCB would use consistent gear aboard similar vessels, sample at the optimal spatial (including within and outside the core abundance areas to avoid potential hyper-stability) and temporal scales to track relative abundance, and collect additional measurements of environmental conditions and survey effort. This survey sampled a relatively small part of the SCB in the seven survey blocks, but the conclusion that the standardized CPUEs reflect local abundances of juvenile mako and blue sharks is supported by analyses that included data from ancillary sets throughout the larger SCB area and showed similar trends in abundance (Appendix Figs. B.1 and C.1 in Supplementary material). Despite the spatial scale of the data, it is possible to use these results combined with other data from nursery areas in the North Pacific Ocean in spatially-explicit population dynamics models. Future studies could aggregate data from nursery areas across the North Pacific Ocean and examine a broader suite of environmental information to use in ecosystem or single species dynamic models to best inform stock assessments and fisheries management. The observed CPUE trends may represent local changes in relative abundance that can affect prey abundances and other predators in the ecosystem, as well as commercial and recreational fishing, and diving operations in the area that depend on interactions with these sharks. Continued monitoring should help place these results in the context of the stock in the California Current and beyond.

Acknowledgements We thank the crews of the R/V David Starr Jordon, R/V Yellowfin, R/V Mako, F/V Ventura II, and F/V Southern Horizon. Thanks to Oscar Sosa-Nishizaki and his numerous students and colleagues from CICESE, as well as volunteers from Moss Landing Marine Labs, California State University Fullerton, California State University Long Beach, Monterey Bay Aquarium, Scripps Institution of Oceanography and other institutions. We also thank many field assistants and volunteers from the Southwest Fisheries Science Center. We thank Nancy Lo and Natalie Spear for contributing to early drafts of the manuscript, and Jeff Laake for assisting with some of the analyses. The survey was started in cooperation with CDFG; we thank Leeanne Laughlin and many other CDFG biologists for their participation during the earlier years. The original survey design and analysis of the commercial longline fishery data was conducted with assistance from Kevin Hill and Susan Smith. Partial funding for the survey was provided by NMFS, CDFG, and the NOAA National Cooperative Research Program. We dedicate this paper to two important collaborators in this research, Rand Rasmussen and Captain Pete Dupuy.

Appendices A–C. Supplementary Material Supplementary material associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.fishres. 2016.06.010. References Bigelow, K.A., Boggs, C.H., He, X., 1999. Environmental effects on swordfish and blue shark catch rates in the US North Pacific longline fishery. Fish. Oceanogr. 8 (3), 178–198. Bigelow, K.A., Musyl, M.K., Poisson, F., Kleiber, P., 2006. Pelagic longline gear depth and shoaling. Fish. Res. 77, 173–183. ˜ F., Marquez-Farías, F., 2008. Age and growth of Blanco-Parra, M.P., Galván-Magana, the blue shark, Prionace glauca Linnaeus, 1758, in the Northwest coast off Mexico. Rev. Biol. Mar. Oceanogr. 43 (3), 513–520. Block, B.A., Jonsen, I.D., Jorgensen, S.J., Winship, A.J., Shaffer, S.A., Bograd, S.J., Hazen, E.L., Foley, D.G., Breed, G.A., Harrison, A.L., Ganong, J.E., Swithenbank, A., Castleton, M., Dewar, H., Mate, B.R., Shillinger, G.L., Schaefer, K.M., Benson, S.R., Weise, M.J., Henry, R.W., Costa, D.P., 2011. Tracking apex marine predator movements in a dynamic ocean. Nature 475 (7354), 86–90. Boggs, C.H., 1992. Depth, capture time, and hooked longevity of longline-caught pelagic fish: timing bites of fish with chips. Fish. Bull. 90, 642–658. Bograd, S.J., Schroeder, I., Sarkar, N., Qiu, X., Sydeman, W.J., Schwing, F.B., 2009. Phenology of coastal upwelling in the California Current. Geophys. Res. Lett. 36, L01602. Branstetter, S., 1990. Early life-history implications of selected carcharhinoid and lamnoid sharks of the Northwest Atlantic. Elasmobranchs as Living Resources: Advances in the Biology, Ecology, Systematics and the Status of the Fisheries. NOAA Tech. Rep. NMFS. 90, 17–28. CDFG (Division of Fish and Game of California, Bureau of Commercial Fisheries), 1944. The commercial fish catch of California for the years 1930–1934, inclusive. Fish Bull. 44, 1–124. Cailliet, G.M., Bedford, D.W., 1983. The biology of three pelagic sharks from California waters, and their emerging fisheries: a review. CalCOFI Rep. 24, 57–69. Campana, S.E., Marks, L., Joyce, W., 2005. The biology and fishery of shortfin mako sharks (Isurus oxyrinchus) in Atlantic Canadian waters. Fish. Res. 73 (3), 341–352. Cartamil, D., Wegner, N.C., Kacev, D., Ben-Aderet, N., Kohin, S., Graham, J.B., 2010. Movement patterns and nursery habitat of the juvenile thresher shark Alopias vulpinus in the Southern California Bight. Mar. Ecol. Prog. Ser. 404, 249–258. Carvalho, F.C., Murie, D.J., Hazin, F.H., Hazin, H.G., Leite-Mourato, B., Burgess, G.H., 2011. Spatial predictions of blue shark (Prionace glauca) catch rate and catch probability of juveniles in the Southwest Atlantic. ICES J. Mar. Sci. 68 (5), 890–900. Casey, J.G., Kohler, N.E., 1992. Tagging studies on the shortfin mako shark (Isurus oxyrinchus) in the western North Atlantic. Mar. Freshw. Res. 43 (1), 45–60. Chang, J.H., Liu, K.M., 2009. Stock assessment of the shortfin mako shark (Isurus oxyrinchus) in the Northwest Pacific Ocean using per recruit and virtual population analyses. Fish. Res. 98 (1), 92–101. Chelton, D.B., Bernal, P.A., McGowan, J.A., 1982. Large-scale interannual physical and biological interaction in the California Current. J. Mar. Res. 40 (4), 1095–1125. Clarke, S.C., Harley, S.J., Hoyle, S.D., Rice, J.S., 2013. Population trends in Pacific Oceanic sharks and the utility of regulations on shark finning. Conserv. Biol. 27 (1), 197–209. ˜ F., 2006. Reproductive biology of the mako Conde-Moreno, M., Galván-Magana, shark Isurus oxyrinchus on the south-western coast of Baja California, Mexico. Cybium 30 (Suppl. 4), 75–83. Dewar, H., Prince, E.D., Musyl, M.K., Brill, R.W., Sepulveda, C., Luo, J., Foley, D., Orbesen, E.S., Domeier, M.J., Nasby-Lucas, N., Snodgrass, D., Laurs, R.M., Hoolihan, J.P., Block, B.A., McNaughton, L.M., 2011. Movements and behaviors of swordfish in the Atlantic and Pacific Oceans examined using pop-up satellite archival tags. Fish. Oceanogr. 20 (3), 219–241. Elith, J., Leathwick, J.R., Hastie, T., 2008. A working guide to boosted regression trees. J. Anim. Ecol. 77 (4), 802–813. Hanan, D.A., Holts, D.B., Coan Jr., A.L., 1993. The California drift gillnet fishery for sharks and swordfish, 1981–1982 through 1990–1991. Fish. Bull. 175, 1–95. Heupel, M.R., Carlson, J.K., Simpfendorfer, C.A., 2007. Shark nursery areas: concepts, definition, characterization and assumptions. Mar. Ecol. Progr. Ser. 337, 287–297. Hilborn, R., Walters, C.J., 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics and Uncertainty. Chapman and Hall, New York, N.Y, 570 pp. Hoenig, J.M., Gruber, S.H., 1990. Life-history patterns in the elasmobranchs: implications for fisheries management. NOAA Tech. Rep. NMFS 90, 1–16. Holts, D.B., Bedford, D.W., 1993. Horizontal and vertical movements of the shortfin mako shark Isurus oxyrinchus, in the Southern California Bight. Mar. Freshw. Res. 44, 901–909. Holts, D.B., Julian, A., Sosa-Nishizaki, O., Bartoo, N.W., 1998. Pelagic shark fisheries along the west coast of the United States and Baja California. Mexico Fish. Res. 39, 115–125. Humphries, N.E., Queiroz, N., Dyer, J.R., Pade, N.G., Musyl, M.K., Schaefer, K.M., Fuller, D.W., Brunnschweiler, J.M., Doyle, T.K., Houghton, J.D.R., Hays, G.C.,

R. Runcie et al. / Fisheries Research 183 (2016) 233–243 Jones, C.S., Noble, L.R., Wearmouth, V.J., Southall, E.J., Sims, D.W., 2010. Environmental context explains Lévy and Brownian movement patterns of marine predators. Nature 465 (7301), 1066–1069. ISC (International Scientific Committee), 2014. Stock assessment and future projections of blue shark in the North Pacific Ocean. In: International Scientific Committee for Tuna and Tuna-like species in the North Pacific Ocean, Taipei, Chinese-Taipei, 194 pp. ISC (International Scientific Committee), 2015. Indicator-based analysis of the status of shortfin mako shark in the North Pacific Ocean. In: International Scientific Committee for Tuna and Tuna-like species in the North Pacific Ocean, Kona, Hawaii, U.S.A, 33 pp. James, K.C., Lewison, R.L., Dillingham, P.W., Curtis, K.A., Moore, J.E., 2015. Drivers of retention and discards of elasmobranch non-target catch. Environ. Conserv., 1–10. Joung, S.-J., Hsu, H.-H., 2005. Reproduction and embryonic development of the shortfin mako, Isurus oxyrinchus Rafinesque, 1810, in the Northwestern Pacific. Zool. Stud. Taipei 44 (4), 487. Joung, S.-J., Hsu, H.-H., Liu, K.-M., Wu, T.Y., 2011. Reproductive biology of the blue shark, Prionace glauca, in the Northwestern Pacific. ISC Working Paper (ISC/11/SHARKWG-2/12). Kai, M., Shiozaki, K., Ohshimo, S., Yokawa, K., 2015. Growth and spatiotemporal distribution of juvenile shortfin mako (Isurus oxyrinchus) in the western and central North Pacific. Mar. Freshw. Res. 66 (12), 1176–1190. Kinney, M.J., Simpfendorfer, C.A., 2009. Reassessing the value of nursery areas to shark conservation and management. Conserv. Lett. 2 (2), 53–60. Lyons, K., Preti, A., Madigan, D.J., Wells, R.J.D., Blasius, M.E., Snodgrass, O.E., Kacev, D., Harris, J.D., Dewar, H., Kohin, S., MacKenzie, K., Lowe, C.G., 2015. Insights into the life history and ecology of a large shortfin mako shark Isurus oxyrinchus captured in southern California. J. Fish Biol. 87 (1), 200–211, http:// dx.doi.org/10.1111/jfb.12709. Maunder, M.N., Punt, A.E., 2004. Standardizing catch and effort data: a review of recent approaches. Fish. Res. 70 (2), 141–159. Mollet, H.F., Cliff, G., Pratt Jr., H.L., Stevens, J.D., 2000. Reproductive biology of the female shortfin mako, Isurus oxyrinchus Rafinesque, with comments on the embryonic development of lamnoids. Fish Bull. 98, 299–318. Mucientes, G.R., Queiroz, N., Sousa, L.L., Tarroso, P., Sims, D.W., 2009. Sexual segregation of pelagic sharks and the potential threat from fisheries. Biol. Lett., http://dx.doi.org/10.1098/rsbl.2008.0761. Musick, J.A., Burgess, G., Cailliet, G., Camhi, M., Fordham, S., 2000. Management of sharks and their relatives (Elasmobranchii). Fisheries 25, 9–13. NMFS (National Marine Fisheries Service), 2015. California/Oregon Drift Gillnet Observer Program Data Summaries and Reports. http://www.westcoast. fisheries.noaa.gov/fisheries/wc observer programs/sw observer program info/ data summ report sw observer fish.html. Nakano, H., 1994. Age, reproduction and migration of blue shark in the North Pacific Ocean. Bull. Nat. Res. Inst. Far Seas Fish. 31, 141–256. Nakano, H., Nagasawa, K., 1996. Distribution of pelagic elasmobranchs caught by salmon research gillnets in the north Pacific. Fish. Sci. 62 (6), 860–865. Nakano, H., Seki, M.P., 2003. Synopsis of biological data on the blue shark, Prionace glauca Linnaeus. Bull. Fish. Res. Agency Jpn. 6, 18–55. O’Brien, J.W., Sunada, J.S., 1994. A review of the southern California experimental drift longline fishery for sharks, 1988–1991. CalCOFI Rep. 35, 222–229.

243

Ohshimo, S., Fujinami, Y., Shiozaki, K., Kai, M., Semba, Y., Katsumata, N., Ochi, D., Matsunaga, H., Minami, H., Kiyota, M., Yokawa, K., 2016. Distribution, body length, and abundance of blue shark and shortfin mako offshore of northeastern Japan, as determined from observed pelagic longline data, 2000–2014. Fish. Oceanogr. 25 (3), 259–276. PFMC (Pacific Fishery Management Council), 2003. Fishery Management Plan and Environmental Impact Statement for U.S. West Coast Fisheries for Highly Migratory Species. NOAA Award No. NA03NMF4410067. Pacific Fishery Management Council, Portland Ore (August). PFMC (Pacific Fishery Management Council), 2016. Status of the U.S. West Coast Fisheries for Highly Migratory Species Through 2014. Pacific Fishery Management Council, Portland Ore (January). Porch, C.E., Scott, G.P., 1994. A numerical evaluation of GLM methods for estimating indices of abundance from West Atlantic bluefin tuna catch per trip data when a high proportion of the trips are unsuccessful. ICCAT Collect. Vol. Sci. Pap. 42, 240–245. Pratt Jr., H.L., Casey, J.G., 1983. Age and growth of the shortfin mako, Isurus oxyrinchus, using four methods. Can. J. Fish. Aquat. Sci. 40, 1944–1957. Preti, A., Soykan, C.U., Dewar, H., Wells, R.D., Spear, N., Kohin, S., 2012. Comparative feeding ecology of shortfin mako, blue and thresher sharks in the California Current. Environ. Biol. Fish. 95 (1), 127–146. Searle, S.R., Speed, F.M., Milliken, G.A., 1980. Population marginal means in the linear-model—an alternative to least-squares means. Am. Stat. 34, 216–221. Semba, Y., Aoki, I., Yokawa, K., 2011. Size at maturity and reproductive traits of shortfin mako, Isurus oxyrinchus, in the western and central North Pacific. Mar. Freshw. Res. 62 (1), 20–29. Smith, S.E., Au, D.W., Show, C., 1998. Intrinsic rebound potentials of 26 species of Pacific sharks. Mar. Freshw. Res. 49, 663–678. Stevens, J.D., 1975. Vertebral rings as a means of age determination in the blue shark (Prionace glauca L.). J. Mar. Biol. Assoc. U.K. 55 (3), 657–665. Stevens, J.D., 1984. Biological observations on sharks caught by sport fishermen off New South Wales. Aust. J. Mar. Fresh. Res. 35, 573–590. Stevens, J.D., 2008. The biology and ecology of the shortfin mako shark, Isurus oxyrinchus. In: Camhi, E.K. (Ed.), Sharks of the Open Ocean: Biology, Fisheries and Conservation. Blackwell Science Publications, Oxford, U.K, pp. 87–91. Walsh, W.A., Kleiber, P., 2001. Generalized additive model and regression tree analyses of blue shark (Prionace glauca) catch rates by the Hawaii-based commercial longline fishery. Fish. Res. 53 (2), 115–131. Walsh, W.A., Bigelow, K.A., Sender, K.L., 2009. Decreases in shark catches and mortality in the Hawaii-based longline fishery as documented by fishery observers. Mar. Coast. Fish. 1, 270–282. Wells, D.R.J., Smith, S.E., Kohin, S., Freund, E., Spear, N., Ramon, D.A., 2013. Age validation of juvenile shortfin mako (Isurus oxyrinchus) tagged and marked with oxytetracycline off southern California. Fish. Bull. 111, 147–160. Xu, Y., Nieto, K., Teo, S.L., McClatchie, S., Holmes, J., 2015. Influence of fronts on the spatial distribution of albacore tuna (Thunnus alalunga) in the Northeast Pacific over the past 30 years (1982–2011). Prog. Oceanogr., http://dx.doi.org/10. 1016/j.pocean.2015.04.013. Zainuddin, M., Kiyofuji, H., Saitoh, K., Saitoh, S.I., 2006. Using multi-sensor satellite remote sensing and catch data to detect ocean hot spots for albacore (Thunnus alalunga) in the northwestern North Pacific. Deep Sea Res. Part II 53 (3), 419–431.