Research Article - AstonJournalsastonjournals.com/manuscripts/Vol2013/FAJ-77_Vol2013.pdf · 4 Research Article the PDC program. Using POP and annual commercial shortfin mako shark

RESEARCH ARTICLE

Commercial Fishery Catch Characteristics and Population

Assessment of the Shortfin Mako Shark (Isurus oxyrinchus) in the Western

North Atlantic Ocean

Fisheries and

Aquaculture Journal,

Vol. 2013: FAJ-77

Co-Publisher: OMICS Group, www.omicsonline.org http://astonjournals.com/faj

1 Fisheries and Aquaculture Journal, Vol. 2013: FAJ-77

Commercial Fishery Catch Characteristics and Population Assessment of the Shortfin Mako Shark (Isurus oxyrinchus) in the Western North

Atlantic Ocean

Juan C Levesque* Geo-Marine, Inc., Environmental Resources Division, Marine Science Department,

2201 Avenue K, Suite A2, Plano, Texas 75074, USA. *Present Address: Cardno ENTRIX, Ecological Division, 3905 Crescent Park Drive,

Riverview, Florida 33578, USA.

Correspondence: [email protected], [email protected]

Accepted: Apr 25, 2013; Published: May 19, 2013 Abstract Pelagic sharks, an oceanic group of sharks, are an incidental bycatch in many global pelagic longline commercial fisheries, including the U.S commercial longline fishery that operates in the western North Atlantic Ocean. Shortfin mako shark (Isurus oxyrinchus) is one of the only pelagic sharks that have any economic value. Similar to other sharks, the shortfin mako shark is slow-growing, late-to-mature, and has a low fecundity, which makes this species vulnerable to overexploitation. In 2002, the International Union for Conservation of Nature (IUCN) classified the shortfin mako shark as Lower Risk (Near Threatened [NT]) on its annual Red List of Threatened and Endangered Species. Given the current conservation status and the general paucity of data on the status of the shortfin mako shark population, the objectives of this study were to characterize the commercial pelagic longline shortfin mako catch and assess its population in the western North Atlantic Ocean using a simple production model. Commercial data indicated that pelagic longline fishing effort has decreased with time, but most of the fishing effort continued to be in the Gulf of Mexico. Catches of shortfin mako shark have decreased over time, but observer data showed that larger animals were taken in the fishery. Overall, the Schaefer model was generally the least sensitive to varying K values, more sensitive to F values, and the most sensitive to r values. Keywords: Commercial fisheries; fishery management; pelagic sharks; shark bycatch; stock assessment; surplus-production model.

1. Introduction Sharks are classified as chondrichthyans (cartilaginous fishes), one of the most diverse and oldest taxa of vertebrates. Evidence from the fossil record suggests that chondrichthyans (sharks, skates, and rays) have existed for over 400 million years [1]. There are nearly 500 species of sharks [2]; sharks are found in every major ocean, including the deep sea, oceanic, neritic, and coastal environments [3]. Compagno [4] indicates that only 2.5% (26−31 species) of the 1,160 extant species of cartilaginous fish are considered oceanic or pelagic (open-ocean) species. Pelagic sharks are defined as open-ocean species that are usually found in offshore waters off the continental shelf. Although there are various species of sharks that are found in offshore waters (e.g., benthic and mesopelagic), only about 12 species are considered pelagic; pelagic sharks are generally distinguished from other species of sharks by their highly migratory behavior [1]. Many coastal sharks (e.g., dusky shark [Carcharhinus obscures] and great hammerhead shark [Sphyrna mokarran]) also undertake periodic localized migrations, but tagging studies illustrate that pelagic sharks often traverse greater distances on a regular basis [5]. For example, numerous blue sharks (Prionace glauca) tagged in the western North Atlantic Ocean have been recaptured in the Eastern Atlantic Ocean [5], and Casey and Kohler [6] reported that the shortfin mako shark (Isurus oxyrinchus) often migrates more than 500 kilometers (km).

Similar to many elasmobranchs, most pelagic sharks have little to no economic value. In fact, the only pelagic shark that does have some economic value in global commercial fisheries is the shortfin mako shark. In the United States, shortfin mako shark commercial landings in 2007 and 2008 were valued at $256,929 and $236,898, respectively [7]. Besides having commercial value, the shortfin mako shark is also a popular recreational species in the western North Atlantic Ocean [8]; shortfin mako sharks often make acrobatic leaps out of the water when they

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2 Research Article

are hooked on rod and reel [9]. There are no directed commercial fisheries for shortfin mako sharks; however, it is often captured incidentally in high seas commercial fisheries throughout the Atlantic Ocean; generally on pelagic longline gear [10, 11]. Despite the fact that there are no directed fisheries for shortfin mako shark, significant numbers are incidentally taken in commercial fisheries throughout the world. Using shark data from the Hong Kong market, Clark [12] estimated that between 200,000 and 300,000 (13,000-18,000 mt) shortfin mako sharks were taken each year in the Atlantic Ocean. In a report published in 2008, ICCAT [13] estimated that around 8,141 mt of shortfin mako sharks were taken in the Atlantic Ocean (North and South Management Units) in 2006. Because shortfin mako shark commercial catches continue to increase at a rate that appears to exceed recovery, many researchers today believe that the North Atlantic stock is at a critical level or may have even already collapsed [10, 11, 14, 15]. Analogous to other long-lived marine animals [16], the shortfin mako shark is slow-growing, late-to-mature, and has a low fecundity; thus, population growth is slow, which makes this species vulnerable to overfishing and overexploitation. Given the population status, the International Union for Conservation of Nature (IUCN) classified the shortfin mako shark in 2002 as Lower Risk (Near Threatened [NT]) on its annual Red List of Threatened and Endangered Species. Following the IUCN listing, the International Commission for the Conservation of Atlantic Tunas (ICCAT) conducted its first population assessment of shortfin mako shark on 14−18 June 2004 [11, 13]. Although the researchers indicated the findings should be considered preliminary, and viewed with caution, the assessment suggested that the shortfin mako shark may have suffered 50 percent depletion in the North Atlantic [11, 13]. In the South Atlantic, the working group pointed out that the shortfin mako shark had also suffered depletion, but the magnitude was less severe than that of the North Atlantic [11, 13]. According to the latest ICCAT stock assessment [13], population estimates for shortfin mako sharks were variable in the North Atlantic and assessment of the South Atlantic population was inconclusive.

Stock assessments are essential for the conservation and management of fisheries. These types of documents provide managers with biological information on a species and the status of the fishery, which helps them with their decision making [16]. Historically, population models have been used to assess shark stocks since the 1970s and 1980s with some reservation given their unique life-history dynamics. Today, researchers often use advanced analytical modeling techniques to estimate populations (e.g., Bayesian estimation; [16]); however, there are also several simple surplus-production models (SPM) that can be applied to assess shark populations, which are relatively easy to calculate and relatively accurate since they require fewer inputs [16-18]. In fact, SPMs may outperform more complex models because fewer parameters are required or estimated, which minimizes the uncertainty associated with each parameter [19, 20].

In the past 20 years, many aspects on the biology of the shortfin mako shark have been reported by researchers and recent reviews of the scientific literature have been summarized [21]; however, its population dynamics is still poorly known. Given the current conservation status and the general paucity of data on the shortfin mako shark population, the objectives of this study were to characterize the U.S. commercial pelagic longline catch of shortfin mako shark and assess its population in the western North Atlantic Ocean. Specifically, the shortfin mako shark population (Bt) was examined using a SPM with different values for intrinsic rates of increase (r), carrying capacity (K), and fishing mortality (Ft). 2. Methods 2.1. Study area The pelagic longline fishing grounds for the U.S. commercial fishing fleet extends from the Grand Banks off Newfoundland, Canada to the waters off South America; it also includes the Caribbean Sea and the Gulf of Mexico. For research and management purposes, the United States National Marine Fisheries Service (NMFS) divides the western North Atlantic Ocean (including the Gulf of Mexico and Caribbean) into 11 geographical statistical areas based on regions of similar types of fishing effort (Figure 1). The 11 NMFS geographical areas are defined as 1) Caribbean (CAR), 2) Gulf of Mexico (GOM), 3) Florida East coast (FEC), 4) South Atlantic Bight (SAB), 5) Mid-Atlantic Bight (MAB), 6) New England coastal (NEC), 7) Northeast distant waters (NED), 8) Sargasso Sea (SAR), 9) North Central Atlantic (NCA), 10) Tuna North (TUN), and 11) Tuna South (TUS).


3 Fisheries and Aquaculture Journal, Vol. 2013: FAJ-772.1. Study area

Figure 1: Map of the study area in the western North Atlantic Ocean illustrating the NMFS statistical areas [22]. The NMFS statistical areas are as follows: 1) Caribbean (CAR); 2) Gulf of Mexico (GOM); 3) Florida East Coast (FEC); 4) South Atlantic

Bight (SAB); 5) Mid-Atlantic Bight (MAB); 6) Northeast Coastal (NEC); 7) Northeast Distant (NED); 8) Sargasso (SAR); 9) North Central Atlantic (NCA); 10) Tuna North (TUN); and 11) Tuna South (TUS).

Longitude

2.2. Data Shortfin mako shark commercial fishery data (1985−2008) were accessed and compiled from three different U.S. commercial fishing sector programs within the Sustainable Fisheries Division of the NMFS Southeast Fisheries Science Center (SEFSC): Fisheries Log Book System (FLS; [1986−2008]), Pelagic Dealer Compliance (PDC; [1986−2008]), and Pelagic Observer Program (POP; [1992−2008]). The FLS is a record keeping system of fishing and non-fishing activity for commercial fishermen who are required to report their fishing activity via logbooks submitted for each fishing trip. The PDC is a program that requires commercial fish dealer permits for anyone who receives, purchases (from vessels), or imports many of the fish managed by NMFS Atlantic Highly Migratory Species (HMS) (i.e., Atlantic tunas, sharks, swordfish, or billfish). The POP is a program that was established to collect biological and fishing characteristic information from the U.S. pelagic longline commercial fishery. In the U.S., fishery observer coverage is mandatory for federal swordfish permit holders, and selection of a vessel for coverage is based on a random draw according to historical commercial fishing effort [22]. Fishery observer effort is based on the percentage of longline sets in given area and calendar quarter (quarter 1: January−March, quarter 2: April−June, quarter 3: July−September, quarter 4: October−December). On average, fishery observers spend 900 days at sea and observe 500 longline sets each year [22]. Historically, the POP’s goal was to observe about 5 percent of the pelagic longline fishing effort (number of sets per calendar quarter and area). Today the POP targets approximately 8 percent of the commercial fishing effort in the western North Atlantic Ocean under U.S. jurisdiction.

For these analyses, only U.S. pelagic longline commercial landings data from the western North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico were evaluated; data from the Pacific Ocean and other commercial fisheries were excluded. Commercial shortfin mako shark landings by weight (metric ton [mt]) were compiled from

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4 Research Article

the PDC program. Using POP and annual commercial shortfin mako shark catch data, the total number of sharks landed was estimated by dividing the total weight by the mean weight of individual animals measured in a given year (1992−2008). Total fishing effort information was obtained using the FLS and POP datasets. If any data was missing (e.g., hooks or weight), then an average value was applied, which was derived by using the average value for the year before and after. The annual catch-per-unit-effort (CPUE) was derived as the ratio between the total commercial shortfin mako shark landings (kilograms [kg]) and the number of hooks fished. Nominal catch rates (un-standardized) were defined in all cases as catch per 100 hooks. Graphs, descriptive statistics, and regression associations were created and derived using Microsoft Excel

®.

2.3. Population assessment Population estimates for shortfin mako shark were derived using the Schafer growth model [23]. This type of model assumes that the maximum sustainability yield (MSY) or maximum surplus production occurs at some population size below the carrying capacity. The Schaefer (logistic style) model assumes the population size (N) associated with MSY is half of the unfished population size [17]. The Schaefer model is expressed as:

dBt/Btdt = r (1- Bt/K), (1) where Bt is the biomass at time step t, r is the intrinsic rate of increase, K is the carrying capacity, and t represents time. In general, the Schaefer model is a logistic type equation that depicts a population as a sigmoid curve. Under fishing conditions, equation (1) can be written as:

dBt/Btdt = r (1- Bt/K) - Ft, (2) where Bt is the biomass at time step t, r is the intrinsic rate of increase, K is the carrying capacity, t represents time, and Ft is the fishing mortality at time t.

Sensitivity analyses were conducted to determine how the Schaefer model was driven by specific data sets or data points. For these analyses, the affects of different priors (r, K, and Ft) on the biomass (Bt) were tested. These sensitivity tests included: (1) specifying K as the 266.8 mt (maximum shortfin mako shark commercial landings (1985−2008), 400 mt (ICCAT 2008), and 500 mt [13]; (2) specifying r as 0.014 yr

-1, 0.053 yr

-1 , and 0.301 yr

-

1; all r values were based on available r estimates for several pelagic sharks (shortfin mako shark, porbeagle shark

[Lamna nasus], and blue shark [Prionace glauca], respectively [13]; (3) specifying t as 10, 20, 30, and 40 years; many pelagic sharks have a life-span expectancy between 15 and 32 years of age [13, 24]; and (4) specifying Ft as the linear association between CPUE and fishing effort for two different catch rate series: 1985−1995 and 1985−2008. Population projections (Bt) were generated using a computer program written in language C and compiled with Pelles C for Windows Version 6

®. The graphical output (time [t]) was reported as monthly

increments (0.08333) and the initial population size (No or NZERO) variable was set as 100.3 mt. The initial population size value (N1985−2008 = 100.3) was derived from the mean of commercial landings reported for shortfin mako shark during 1985 through 2008. 3. Results 3.1. Fishery characteristics The U.S. longline fishery targets both swordfish (Xiphias gladius) and tuna Thunnus spp.) with pelagic longline gear throughout the western North Atlantic Ocean (Figure 2). Pelagic longline gear consists of a heavy monofilament (700-900 lb test) mainline (7−65 kilometers long) that is suspended in the water column by a series of floats (dropline-float and monofilament line), high flyer buoys, and radio beacons. Between the floats, gangions (leaders [35−60 m long] with baited hooks are attached to the mainline using stainless steel longline clips at a regular interval (3−5 hooks between each float) determined by the fishing captain [22]. At one time, the industry could use any type of hook, but today the NMFS requires circle hooks to reduce sea turtle mortality (NMFS, 2004). In the NED NMFS statistical area, circle hooks must be 18/0 or larger and the offset must not exceed 10 degrees when using whole Atlantic mackerel (Scomber scombrus) or squid (Illex spp.) as bait. Outside of the NED, circle hooks must be18/0 or larger with an offset not to exceed 10 degrees; however, 16/0 or larger non-offset circle hook can



also be used when baiting with whole fish or squid. When vessels target swordfish, fishermen attach a chemical light stick to the leader around 2 meters (m) above the hook; light sticks are not used for targeting tuna [22].

Figure 2: Typical U.S. commercial pelagic longline configuration [21].

Buoy Float

U.S. Pelagic Longline (Mainline Section: (5-10 sections/Set))

Radio Beacon

Mainline

(1.8-5.0 nm)

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Surface

The total reported fishing effort by the U.S. pelagic longline fleet operating in the western North Atlantic Ocean, including the Gulf of Mexico and Caribbean Sea during 1986 through 2008 was 291,568 sets. The total


6 Research Article

number of reported pelagic longline sets ranged from 2,055 (~1,410,809 hooks) in 1986 to 19,409 (~13,324,762) in 1989 with a mean of 13,321 sets (~8,672,626 hooks) per year. Most longline sets (n = 100,530 or 34.5%) were reported in the GOM NMFS statistical area and the least (n = 1,607 or 0.6%) in the TUS NMFS statistical area (Figures 3, 4). The overall number of hooks per set ranged from 591.9 in 1992 to 776 in 2003 with a mean of 693.2. The corresponding polynomial association between fishing effort (the total number of hooks set) and time (year) was weakly described by the following formula: Fishing Effort = -25718(Time)

2 + 437249 (Time) + 8E+06; R² =

0.3689 (Figure 4). Figure 3: Fishing effort by the U.S pelagic longline fishery in the western North Atlantic during 1985 through 2008. The NMFS

statistical areas are as follows: 1) Caribbean (CAR); 2) Gulf of Mexico (GOM); 3) Florida East Coast (FEC); 4) South Atlantic Bight (SAB); 5) Mid-Atlantic Bight (MAB); 6) Northeast Coastal (NEC); 7) Northeast Distant (NED); 8) Sargasso (SAR); 9) North

Central Atlantic (NCA); 10) Tuna North (TUN); and 11) Tuna South (TUS).

Figure 4: Total fishing effort (Number of hooks and Hooks per set) by the U.S. pelagic longline fishery in the western North Atlantic during 1985 through 2008. The dotted line depicts the polynomial regression between fishing effort and year.

The number of sets observed by fishery observers aboard U.S pelagic longline vessels during 1992 through

2008 ranged from 329 (~2.1% of the fishing effort) in 1992 to 1,314 in 2008 with a mean of 575.4 (~14.9% of the fishing effort) (Figure 5). Based on POP observations, the number of hooks set per fishing day ranged from 591 in 1992 to 775 in 2003 with a mean of 686.5 hooks set per fishing day.

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Figure 5: The total fishing effort by the U.S. pelagic longline fishery and the number of sets observed by fishery observers in the western North Atlantic during 1992 through 2008.

3.2. Shortfin mako shark catch The U.S. pelagic longline commercial fishery has landed and sold a total of 2,406 mt (5,302,824 pounds [lbs]) of shortfin mako shark valued at US $4,562,402 during a 24 year period (1985−2008). Commercial landings of shortfin mako shark ranged from 17.6 mt (38,790 lbs) in 1985 to 266.8 mt (588,027 lbs) in 1993 with a mean of 100.24 mt (220,929 lbs) per year (Figure 6). Commercial landings in these years had an economic value of $57,143 and $314,567, respectively. The corresponding polynomial association between total commercial landings (mt) and time (year) was weakly described by the following formula: Total Landings (mt) = -0.8185 (Year)

2 + 22.333 (Year) -

11.793; R² = 0.4863 (Figure 6). The polynomial association between the shortfin mako shark economic value and time (year) was strongly described by the following formula: Economic Value = -1349.9 (Year)

2 + 36976 (Year) +

3501.6; R² = 0.6392 (Figure 7). The annual shortfin mako shark CPUE ranged from 0.23 kg per 100 hooks in 1987 to 2.66 kg per 100 hooks

in 1993 with a mean of 1.27 kg per 100 hooks. The corresponding exponential association between CPUE (kg/100 hooks) and time (year) was weakly described by the following formula: CPUE (kg/100 hooks) = 3E-31e

0.0353 (Year); R²

= 0.1939 (Figure 8). As expected, yield (total landings) and fishing effort (number of hooks) were positively correlated. The corresponding power association between yield and fishing effort was described by the following equation: Yield = 26183(Fishing Effort)

0.5691; R² = 0.4536 (Figure 9).

The polynomial association between CPUE (kg/100 hooks) and yield (kg) during 1985 through 1995, and 1985 through 2008 was described by the following equations: CPUE = 0.0485(Yield)

2 - 0.5036 (Yield) + 1.8196; R² =

0.6158 and CPUE = 0.0014 (Yield)2 + 0.0135 (Yield) + 0.8079; R² = 0.3634, respectively (Figure 10). However, the

association between CPUE and fishing effort (Number of hooks) was inversely proportional described by the following linear formula: CPUE = 1.3306 - 0.0599 (Fishing Effort); R² = 0.6864 (Figure 11). The number of sharks taken by the U.S. pelagic longline fishery ranged from 1,848 in 2006 to 17,409 in 1992 with a mean of 5,075 (1992−2008). The corresponding logarithmic association between the number of shortfin mako sharks taken and time was weakly described by the following formula: Number of mako sharks = -2915ln (Year) + 10820; R² = 0.357 (Figure 12).

Fishery observers reported a total of 2,813 shortfin mako sharks taken by the U.S. pelagic longline fleet during 1992 through 2005 (Levesque, 2007). Shortfin mako sharks were observed taken in every NMFS statistical area except in the SAR. The most number of the shortfin mako sharks were taken in the NED NMFS statistical area (n = 1,490 or 53%) and the least in the NEC NMFS statistical area (n = 281 or 10%).

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Figure 6: Shortfin mako total commercial landings (mt) in the western North Atlantic during 1985 through 2008. The dotted line depicts the polynomial regression between total landings and year.

Figure 7: Shortfin mako total commercial value (US$) in the western North Atlantic during 1985 through 2008. The dotted line depicts the polynomial regression between value and year.

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Figure 8: Catch per unit effort for shortfin mako in the western North Atlantic during 1985 through 2008. The dotted line depicts the exponential regression between CPUE and year.

Figure 9: Shortfin mako yield (commercial landings) in the western North Atlantic during 1985 through 2008. The dotted line

depicts the power regression association between landings and fishing effort (Number of hooks).

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Figure 10: Fishing mortality for shortfin mako in the western North Atlantic during 1985 through 1995 and 1985 through 2008. The dotted line depicts the regression association between CPUE and yield for each time-series.

Figure 11: Shortfin mako CPUE in the western North Atlantic during 1985 through 2008. The dotted line depicts the linear

regression association between CPUE and year.

y = 0.0014x2 + 0.0135x + 0.8079 R² = 0.3634

y = 0.0485x2 - 0.5036x + 1.8196 R² = 0.6158

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Figure 12: The number of shortfin mako sharks taken and the mean weight measured by fishery observers in the western North Atlantic during 1992 through 2008. The dotted line depicts the polynomial regression between the number of

shortfin mako sharks and year.

The total number of shortfin mako shark taken ranged from 33 in 1996 to 490 in 2004. Of these, fishery observers reported that most of the shortfin mako sharks were alive at gear retrieval (53% or n = 1,479). Overall, male shortfin mako sharks (55% or n = 1,259) outnumber females (45% or n = 1,041). In total, fishery observers measured 1,820 shortfin mako sharks ranging from 13 to 320 centimeters (cm) fork length (FL) with a mean of 145.3 cm FL (S.D. ± 46.1). Male shortfin mako sharks (n = 924; 67−256 cm FL; mean = 148.0 cm FL) were slightly longer in length than females (n = 813; 13−320 cm FL; mean = 138.5 cm FL). The smallest mean shortfin mako shark length was 128.3 cm FL (NEC NMFS statistical area) and the largest was 234 cm FL (SAR NMFS statistical area). The shortfin mako shark total length (TL)-fork length (FL) and TL-dressed weight (DW) associations were described by the following equations: (1) TL = 0.8757 (FL) +7.8052; n = 703; R² = 0.95 and (2) DW=0.0058 (TL)² + 62.643; n = 412; R² = 0.88. The mean weight of shortfin mako sharks measured by fishery observers ranged from 8.95 kg in 1992 to 49.24 kg in 1996 with a mean of 30.03 kg (Figures 13, 14). Based on fishery observer data (1992-2007), CPUE ranged from 0.0575 to 0.1858 shortfin mako sharks per 100 hooks with a mean of 0.1149 shortfin mako sharks per 100 hooks. 3.3. Shortfin mako shark population A total of 21 different sensitivity analyses were run using different combinations and values for r, K, t, and F (Figures 15−17). Overall, the t value showed a better representation of the data when it was increased incrementally (i.e., 10, 20, 30, and 40 years) for each run of the model. Therefore, the t estimate of 40 years was used for all other population projections (Figures 16, 17). The biomass was at its highest level (B = 160.9 mt) when K was set at the hypothetical value of 500 mt and its lowest level (B = 115.4 mt) when K was set at the historical maximum shortfin mako shark catch level (1993) of 266.8 mt; biomass was 39% higher when K was increased 53% (Figure 15). Although biomass increased in each run using K values of 266.8, 400, and 500 mt, the association between B and t was linear, which indicated that the overall B had not yet reached its theoretical maximum size; it was still increasing slightly (0.09%) by the end of the 40 year time step.

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Figure 13: The mean shortfin mako shark weight measured by fishery observers in the western North Atlantic during 1992 through 2008. The dotted line depicts the polynomial regression between mean weight and year.

Figure 14: Weight-frequency histogram of the number of shortfin mako sharks measured by fishery observers in the western

North Atlantic during 1992 through 2008.

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Figure 15: Sensitivity analysis for shortfin mako in the western North Atlantic using K = 266.8 (A), 400 (B), 500 (C), r = 0.014, t = 10, 20, 30, 40, and Ft = 0.0599. The solid lines depict the linear regression for each time-series.

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Using different r values based on available information for shortfin mako shark (0.014), porbeagle shark (0.053), and blue shark (0.301) demonstrated that the highest B was for the blue shark and the lowest B was for the shortfin mako shark (Figure 16). At the end of 40 years, the blue shark B was 67% (107.8 mt) greater than that of the shortfin mako shark B. Nonetheless, the model showed that the B for the blue shark had reached its theoretical maximum size at 40 years, while the B for porbeagle and shortfin mako shark was continuing to increase. Interestingly, application of the model demonstrated that when the derived F value was changed from the smaller value (-0.0599) to the larger (-0.123), the overall B for each of the species decreased (Figure 16).

Figure 16: Sensativity analysis for shortfin makos shark in the western North Atlantic using K = 266.8, r = 0.014, 0.053, 0.301, t = 40, Ft = 0.0599 (A), and Ft = 0.123 (B). The long dash red line depicts the blue shark, the shorter dash blue line depicts the

porbeagle, and the dotted black line depicts shortfin mako shark.

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The largest decrease in B was for the shortfin mako shark (13.2% or 24.4 mt) and the smallest was for the blue shark (0.76% or 2.1 mt), which supports the notion that species with lower r values are affected more by changes in fishing pressure than species with higher r values. As expected, the B was at its highest level (39% or 160.9 mt) when K was set at 266.8 mt and at its lowest level (97.7 mt) when K was set at 66.7 mt (Figure 17). Because the No (100.3 mt) was greater than K (66.7 mt), the B association with t was negatively correlated (Figure 17). Obviously, the model confirmed that K values of 133.4 and 266.8 mt displayed a positive correlation between B and t.

Figure 17: Sensitivity analysis for shortfin mako shark in the western North Atlantic using K = 266.8, 133.4, 66.7, r = 0.014, t =

40, and Ft = 0.0599.

4. Discussion One of the most important concepts in fisheries management is the affects of fishing (commercial or recreational) on populations. Among various responsibilities, fishery managers must balance conservation and sustainable exploitation. In the United States, this is a federal mandate of the Magnuson-Stevens Fishery Conservation and Management Act (MSFCMA); it is one of 10 national standards [25]. One component of a Fishery Management Plan (FMP) is a stock assessment. Stock assessment modelers rely on biological information for their model input values; however, unlike teleost, available information for sharks is limited and often unavailable.

Sharks are challenging to manage and researchers are often dependent upon commercial fisheries data to estimate populations. In general, pelagic sharks are among the most difficult to investigate since they display highly migratory behavior, which makes life-history and catch information difficult to obtain, especially since these species are also taken by numerous international fisheries. Nonetheless, understanding the dynamics of commercial fisheries can help with assessing shark catches and population status. Globally, the primary gear that takes pelagic sharks is pelagic longline gear.

In the western North Atlantic Ocean, this assessment showed that the U.S. pelagic longline fishery is complex and dynamic. In general, pelagic longline fishing effort (number of vessels in the fleet) in every area (NMFS statistical areas) has decreased since the early-1990s, but the number of hooks per set has increased since the late-1990s, which shows that the remaining vessels in the fishery are attempting to increase their success by setting more hooks. Interestingly, the number of sets has decreased, so fishermen are not extending their fishing trips, they are simply increasing the number of hooks they set each day. It is difficult to guess whether this will

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have a negative effect on the shortfin mako shark population in the future, but it appears that relative abundance (CPUE), in terms of weight, has remained relatively steady over time. This study did not evaluate fishing depth or any other fishing and environmental factor, but it is probable that these variables could have a greater affect on shortfin mako shark catches than the number of hooks set per day. Overall, shortfin mako shark landings and the corresponding economic value has decreased significantly since peaking in 1993, but with catches of lucrative fish (i.e., swordfish and tuna) continuing to decline, commercial fishermen may choose to target shortfin mako sharks in the future. Actually, anecdotal information indicates this is already taking place off the Carolinas (U.S. East Coast) during the winter. Disturbingly, it appears that although CPUE, in terms of weight, has remained steady over time, the numbers of sharks taken by the U.S. pelagic longline fishery has decreased, which is typically the first sign of trouble in a population. In general, the weight-frequency reported by fishery observers was skewed slightly toward larger animals. This phenomenon suggests that the fishery is taking larger animals, but in less numbers than in previous years. Because of their life-history traits (e.g., late to mature and low fecundity), it is probable that this is negatively affecting the population recovery, especially since the reproductive cycle for shortfin mako shark is every three years [13]. Despite this situation, the fishery observer data showed that the mean weight per animal has remained relatively stable over time. This suggests that the either the fishery has not yet “fished down” the population or the fishery is continuing to discover new fishing grounds or techniques that increases their odds at catching larger animals. At this time, the data does not show that the fishery is exploiting new fishing grounds given most of the fishing effort takes place in the GOM and the fact that most of the shortfin mako sharks are taken in the NED NMFS statistical area. Optimistically, the fishery observer data showed that slightly more shortfin mako sharks were alive upon gear retrieval, so if fishery managers ever wanted to prohibit the taking of shortfin mako sharks, many would be released alive. Based on the data, there are also many other available management options, such as prohibiting the taking of shortfin mako sharks in specific areas or size classes.

In addition to characterizing the shortfin mako shark catch in the U.S. pelagic longline fishery, an attempt was made to explore the effects of using different model variables to explore shortfin mako shark B under the logistic population growth style. Although advanced methods are available to researchers, Musick and Bonfil [16] suggested that SPM are ideal for assessing many shark populations given these types of models require only a few types of data. However, because these models require many assumptions, SPMs are being used less frequently in fishery management [17]. I believe SPMs have some utility under certain scenarios and species. In this study, I applied various K and F criteria using the Schaefer model; but the asymptote, or theoretical maximum population, was never reached. Overall, the Schaefer model was generally the least sensitive to varying K values, more sensitive to F values, and the most sensitive to r values. These analyses demonstrated that small changes in r had the largest consequences on the B. As evident by the specific model runs for three different pelagic sharks, the r value appeared to be more important, in terms of affect on the B, than F, which highlights the importance of having accurate and reliable biological data; it cannot be emphasized enough that models are only as good as the data. In these analyses, the outcome of the model suggested that current fishing rates have minimal impact on the population. If the population could be modeled according to the logistic equation, then this would be unreasonable given the current population status for the shortfin mako shark. To date, the scientific literature clearly demonstrates that sharks in general, and specifically the shortfin mako shark are at critical levels [11, 13]. Using the best available data should continue to be the most important factor when researchers apply models to assess a population stock. As evident from this study, F changes with time (10-yr time series vs 21-yr time series), so it is important to use the longest time series available. The findings of this study should only be viewed as preliminary given that these data were not statistically standardized or compared to other logistic style models, such as the Fox [26] model [17]. Hayes et al. [17] pointed out various factors that should be considered when utilizing SPM to assess shark populations. Agreeing with the authors, I echo many of the same concerns that Hayes et al. [17] emphasized in their study. They indicated that models should: (1) distinguish between mature and immature animals taken in the fishery; (2) account for fishing practices, considering catchability tends to increase with technological advances; abundance is assumed to be proportional to populations size; and (3) account for temporal and seasonal distribution; SPM assumes equal distribution throughout all geographical areas. 5. Conclusion Surplus-production models, such as the Schaefer model have the potential to model pelagic shark populations; however, input parameters must be derived from reasonable data. In this present examination, I only applied one No value (100.3 mt) in the model; therefore, it is recommended that future studies evaluate the effects of using



different virgin biomass values. This will be challenging considering the best available records only date back to the 1980s. However, there are some records for pelagic longline commercial fisheries for the 1950s [21]. Although these historical data are limited and problematic for various reasons, they can be applied in some instances for certain species, such as the blue shark [27]. In future studies, it is also recommended that more advanced methods incorporate the catchability coefficient (q), which is usually expressed as C = qEB, where B is the biomass, C is catch, and E is fishing effort [28].

In summary, Musick and Bonfil [16] stated that since data drive the analysis, there is no single “best” model; stock assessment is dynamic. Even with the use of models, I question if sustainable exploitation of long-lived species [29] is possible [30]. There is strong scientific evidence that suggests that sharks may not recover given the current fishing demands, limiting fishery resources, and their biology. Sharks populations do not appear to be recovering at the rate that we are exploiting them [10, 14-16]. There are many questions that remained unanswered, such as what is the optimal population size and what was the virgin biomass before commercial fisheries [31]? Will sharks be another example of “tragedy of the commons” [32]? Competing Interests The author declares there are no competing interests. Acknowledgement A great debt of gratitude is owed to J. Grover from the University of Texas at Arlington for providing valuable modeling and computer language C coding instruction throughout the 2009 fall semester. I would like to thank all the U.S. pelagic longline captains and crew for their assistance during my observer trips in the 1990s. I also thank L. Beerkircher from NMFS SEFSC for his assistance with the pelagic observer program data. References

[1] Pikitch EK, Camhi MD, Babcock, EA, 2008. Introduction to sharks of the open ocean. p. 1-10. In: MD Camhi, EK Pikitch, EA Babcock (ed.) Sharks of the Open Ocean: Biology, Fisheries and Conservation. Blackwell, Oxford, U.K.

[2] Compagno LJV, 2001. Sharks of the world. An annotated and illustrated catalogue of shark species known to date. Volume 2. Bullhead, mackerel and carpet sharks (Heterodontiformes, Lamniformes and Orectolobiformes). FAO Species Catalogue for Fishery Purposes 1, 2, p. 269.

[3] Simpfendorfer CA, Heupel MR, 2004. Assessing habitat use and movement. In: “Biology of Sharks and their Relatives”. J Carrier, JE Musick and M Heithaus (eds.), CRC Press, Boca Raton, p 553–572.

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[9] YouTube, 2009. Cartwheeling mako shark. [http://www.youtube.com/watch?v=K80NNKV4Mzo] [10] Baum JK, Myers RA, Kehler DG, Worm B, Harley SJ, Doherty PA, 2003. Collapse and conservation of shark populations.

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[20] Prager MH, 1994. A suite of extensions to a nonequilibrium surplus production model. Fishery Bulletin, 92: 374−389. [21] Levesque JC, 2007. A Comprehensive Review of the Biology and Preliminary Investigation of the Interactions with the U.S.

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[22] Lee DW, Brown CJ, 1998. SEFSC pelagic observer program data summary for 1992−1996. NOAA Technical Memorandum, National Marine Fisheries Service, Southeast Fisheries Science Center; 408, p. 25.

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[30] Camhi MD, Lauck E, Pikitch EK, Babcock EA, 2008. A global overview of commercial fisheries for open ocean sharks. In: MD Camhi, EK Pikitch, EA Babcock (ed.), “Sharks of the Open Ocean: Biology, Fisheries and Conservation”. Blackwell, Oxford, U.K.

[31] Cortes E, 2002. Incorporating uncertainty into demographic modeling: Application to shark populations and their conservation. Conservation Biology, 16: 1048−1062.

[32] Hardin G, 1968. Tragedy of the commons. Science, 162: 1243−1248. How to cite this article: Levesque JC, 2013. Commercial Fishery Catch Characteristics and Population Assessment of the Shortfin Mako Shark (Isurus oxyrinchus) in the Western North Atlantic Ocean. Fisheries and Aquaculture Journal, Vol. 2013: 18 pages, Article ID: FAJ-77.

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Research Article - AstonJournalsastonjournals.com/manuscripts/Vol2013/FAJ-77_Vol2013.pdf · 4 Research Article the PDC program. Using POP and annual commercial shortfin mako shark