Scholarly article on topic 'Vulnerability of oceanic sharks as pelagic longline bycatch'

Vulnerability of oceanic sharks as pelagic longline bycatch Academic research paper on "Biological sciences"

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Abstract of research paper on Biological sciences, author of scientific article — A.J. Gallagher, E.S. Orbesen, N. Hammerschlag, J.E. Serafy

Abstract Bycatch (the unintentional catch of non-target species or sizes) is consistently ranked as one of the greatest threats to marine fish populations; yet species-specific rates of bycatch survival are rarely considered in risk assessments. Regulations often require that bycatch of threatened species be released; but, if animals are already dead, their release serves no conservation purpose. We examined the survival of 12 shark species caught as bycatch in the US Atlantic pelagic longline fishery. Shark survival was evaluated in relation to fishery target (swordfish versus tuna) and four operational, environmental, and biological variables to evaluate the underlying mechanisms affecting mortality. Survival estimates ranged from 33% (night shark) to 97% (tiger shark) with seven of the 12 species being significantly affected by at least one variable. We placed our survival results within a framework that assessed each species’ relative vulnerability by integrating survival estimates with reproductive potential and found that the bigeye thresher, dusky, night, and scalloped hammerhead shark exhibited the highest vulnerabilities to bycatch. We suggest that considering ecological and biological traits of species shows promise for designing effective conservation measures, whereas techniques that reduce fisheries interactions in the first place may be the best strategy for highly vulnerable species.

Academic research paper on topic "Vulnerability of oceanic sharks as pelagic longline bycatch"

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Contents lists available at ScienceDirect

Global Ecology and Conservation

journal homepage: www.elsevier.com/locate/gecco

Original research article

Vulnerability of oceanic sharks as pelagic longline bycatch

qi A.J. Gallaghera,b>*, E.S. Orbesenc, N. Hammerschlaga,b,d, J.E. Serafyc,d

a Leonard and Jayne Abess Center for Ecosystem Science and Policy, University of Miami, Coral Gables, FL, USA b RJ Dunlap Marine Conservation Program, University of Miami, Miami, FL, USA

c National Marine Fisheries Service, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL, USA d Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL, USA

article info

Article history: Received 19 June 2014 Accepted 20 June 2014 Available online xxxx

Keywords:

Vulnerability

Human-impacts

Stress

Fishing

Bycatch

abstract

Bycatch (the unintentional catch of non-target species or sizes) is consistently ranked as one of the greatest threats to marine fish populations; yet species-specific rates of bycatch survival are rarely considered in risk assessments. Regulations often require that bycatch of threatened species be released; but, if animals are already dead, their release serves no conservation purpose. We examined the survival of 12 shark species caught as bycatch in the US Atlantic pelagic longline fishery. Shark survival was evaluated in relation to fishery target (swordfish versus tuna) and four operational, environmental, and biological variables to evaluate the underlying mechanisms affecting mortality. Survival estimates ranged from 33% (night shark) to 97% (tiger shark) with seven of the 12 species being significantly affected by at least one variable. We placed our survival results within a framework that assessed each species' relative vulnerability by integrating survival estimates with reproductive potential and found that the bigeye thresher, dusky, night, and scalloped hammerhead shark exhibited the highest vulnerabilities to bycatch. We suggest that considering ecological and biological traits of species shows promise for designing effective conservation measures, whereas techniques that reduce fisheries interactions in the first place may be the best strategy for highly vulnerable species. © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

1. Introduction 1

Overfishing represents the greatest threat to marine fish stocks globally (Hutchings and Reynolds, 2004; Jackson et al., Q2 2

2001; Pauly et al., 2002) and substantial research has focused on better understanding the vulnerabilities and resilience of 3

marine species to sustained fishing (Dulvy et al., 2008; Worm and Branch, 2012). Modeling and ranking the vulnerabilities of 4

dissimilar species to fisheries capture can provide insight into how fishery-related stressors affect ecologically/biologically 5

similar (or different) species as well as provide a mechanism for prioritizing species for conservation actions (Astles et al., 6

2006; Gallagher et al., 2012). 7

Elasmobranchs are particularly vulnerable to overfishing due to their relatively low reproductive output and low 8

potential for population recovery compared to most teleosts (Myers and Worm, 2005; Stevens et al., 2000). Several 9 elasmobranchs are experiencing drastic population declines across their range (e.g., Baum et al., 2003; Dulvy et al., 2008;

* Correspondence to: University of Miami, RJ Dunlap Marine Conservation Program, 4600 Rickenbacker Causeway, Miami, FL, 33149, USA. Tel.: +1 305 421 4356; fax: +1 305 421 4675.

E-mail addresses: gallagher.austin@gmail.com, agallagher@rsmas.miami.edu (A.J. Gallagher).

http://dx.doi.org/10.1016/j.gecco.2014.06.003

2351-9894/© 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by- nc- nd/3.0/).

2 A.J. Gallagher et al. / Global Ecology and Conservation xx (xxxx) xxx-xxx

Ferretti et al., 2010). While many shark species are targeted for the global shark fin trade or otherwise retained for consumption (Clarke et al., 2006; Worm et al., 2013), elasmobranchs are also unintentionally caught as bycatch in many fisheries, and this catch can often exceed that of the actual targeted species (Bonfil, 1994; Molina and Cooke, 2012). Bycatch is often (but not always) discarded regardless of their at-vessel status (live, injured or dead), and is poorly reported in some fishery records making it difficult to assess impacts (Barker and Schluessel, 2005; Bonfil, 1994). Additionally, management regulations often require that bycatch of threatened species be released to promote their conservation (Molina and Cooke, 2012); however, if fishes are dead upon gear retrieval then such practices can be futile for conservation efforts. However, understanding the at-vessel status of individuals caught as bycatch and modeling their survival in light of biological, environmental, and operational variables can provide insights into the underlying mechanisms driving mortality, thus informing which aspects of a fishery might be modified to mitigate lethal effects of capture on a species-specific basis (Serafy etal., 2012).

Longline fishing provides one of the largest sources of fisheries interactions with sharks, and it is well known that species with limited biological productivity are among the most vulnerable to all forms of fishing mortality, including bycatch (Cortés et al., 2010). Previous studies describing the observational at-vessel survival rates of certain shark species in both pelagic and bottom longline fisheries have documented a wide range of estimated survival rates among species (e.g. Beerkircher et al., 2002; Diaz and Serafy, 2005; Morgan and Burgess, 2007; Morgan and Carlson, 2010). This work has provided a strong foundation to begin asking additional questions about how bycatch affects the survival of shark species; specifically, assessing the potential influences of operational, environmental and biological variables of the fishery under investigation. For example, pelagic longline fisheries often switch between fishery targets (i.e., tuna versus swordfish), thereby altering environmental (time of day) and operational (fishing depth) aspects of the fishery. However, it is unclear if and how these operational differences affect the survival of sharks captured as bycatch. Thus, there is a need to model species-specific survival in light of fishery targets and other potentially significant variables which may affect survival.

To address these gaps, the present study provides an assessment of at-vessel hooking survival for 12 shark species encountered as bycatch in the US Atlantic pelagic tuna and swordfish longline fishery from 1995 to 2012. Study objectives were to: (1) determine the influence of fishery target (tuna or swordfish) as well as various operational (soak time and hook depth), environmental (sea surface temperature) and biological (animal length) variables on shark bycatch survival to evaluate the potential underlying mechanisms driving at-vessel mortality and; (2) determine and rank species-specific hooking survival rates (i.e., proportion alive upon gear retrieval) for the 12 focal shark species after adjusting for these variables. To generate an overall index of relative vulnerability to bycatch, we integrated our results into a framework that incorporated species-specific reproductive potential (age at maturity and fecundity). The novelty in our study resides in the ability to assess the influence of fishery-related variables on survival, as well as by controlling for these variables when generating new survival estimates from nearly two decades of bycatch data. Our findings are discussed in terms of each species' phylogeny, conservation status, reproductive output, physiology, and degree of specialization in selected functional and behavioral traits (Gallagher et al., 2014a).

2. Methods

2.1. Study and data location

The US pelagic longline fishery operates year-round throughout the western Atlantic Ocean and primarily targets swordfish (Xiphius gladius), yellowfin tuna (Thunnus albacares), and bigeye tuna (Thunnus obesus). In the present study, we used shark bycatch data derived from the tuna- and swordfish-directed pelagic longline fishery in the western Atlantic Ocean and Gulf of Mexico from 1995 to 2012. Set-specific data were provided by the US National Marine Fisheries Service (NMFS) Pelagic Observer Program (POP). The POP gathers detailed information on each longline set including: target species, time and location of deployment, hook type, number of hooks, number of light sticks, bait, soak duration, sea surface temperature, and estimated hook depth. Information is also collected on the details of catch, such as the identity (species and/or genus) of captured taxa, their numbers, their size (fork length, FL; visually estimated) and their status (live/dead/damaged) at boat-side when the longline gear is retrieved. Sharks are classified as ''dead'' if they show no visible movement. If a shark is either dead or alive, but exhibits extensive injuries, the fish is classified as ''damaged''. Further details of observer protocols are available at http://www.sefsc.noaa.gov/fisheries/observers/forms.htm.

2.2. Species assessed

We focused our analyses on 12 shark species that are readily identifiable (with training) at the species level and commonly captured as bycatch with both tuna- and swordfish-directed pelagic longline gear in the Atlantic Ocean and/or Gulf of Mexico. These shark species included: bigeye thresher (Alopias superciliosus), blue (Prionaceglauca), dusky (Carcharhinus obscurus), longfin mako (Isuruspaucus), night (Carcharhinus signatus), oceanic whitetip (Carcharhinus longimanus), porbeagle (Lamna nasus), sandbar (Carcharhinusplumbeus), scalloped hammerhead (Sphyrna lewini), shortfin mako (Isurus oxyrinchus), silky (Carcharhinus falciformis), and tiger (Galeocerdo cuvier).

A.J. Gallagher etal./ Global Ecology and Conservation xx (xxxx) xxx-xxx 3

2.3. Analyses and survival estimates 1

To test the hypothesis of no influence of operational (target, soak time and hook depth), environmental (sea surface 2

temperature), or biological variables (animal length) on the at-vessel hooking survival of sharks (binomial variable; 3

dead/alive) caught as bycatch upon gear retrieval, we followed the methodology in Serafy et al. (2012) and used logistic 4

regression to generate a model which was inclusive of all recorded variables which would likely affect catch/survival for each 5

species. We applied the same model for each species without following a stepwise factor addition/removal methodology. 6

The following model was applied separately for each species: 7

logit(S) = Target + Depth + Soak + Temp + Length 8

where S = Survival (0, 1 = dead, alive); Target = species targeted (tuna or swordfish); Temp = sea surface temperature 9

(° C); Depth = maximum hook depth (in water column; m); Soak = soak duration (h); and Length = straight upper jaw/snout 10

fork length (FL; cm). 11

Tunas are primarily targeted during the day and swordfish at night. We assigned the fishing target (tuna or swordfish) 12

based on the proportion of light sticks to hooks used (swordfish, >0.7; tuna, <0.4; all data <0.7 and >0.4 were considered 13

a ''mixed target'' and omitted from analysis). Fishes that were missing survival status, exhibited excessive soak times 14

(i.e., >24 h) and/or unrealistic temperatures (e.g., <1°C) were eliminated from analysis. All data used were recorded from 15

1995 to 2012. In 2004, the US National Marine Fisheries Service (NMFS) banned the use of J hooks in the US pelagic longline 16

fishery, requiring all fishers to use circle hooks. To eliminate the influence of hook type in our analysis, we omitted any sets 17

made prior to 2005 which used J hooks. Two variables which we were not able to incorporate directly into our models were 18

hook size and degree offset. This is largely due to the lack of consistent measurement of these factors in the POP database; 19

however, there is little variation in size for circle hooks across sets in the fishery (Serafy et al., 2012). 20

Species-specific least square mean survival estimates were used to determine shark survival rates. Mean survival rates 21

were estimated for both swordfish- and tuna-directed sets. Species were also categorized according to their International 22

Union for Conservation of Nature (IUCN) Red List status (The International Union for the Conservation of Natue, 2013) and 23

the US National Marine Fisheries prohibited fishing target status (according to the POP database). Life history information 24

on the reproductive traits of each species (female age at maturity and fecundity) were obtained from the reference tables 25

within Cortés (2000, 2002) and Dulvy et al. (2008), as well as Hazin et al. (2000) using data from the Atlantic or Gulf of 26

Mexico stocks of each species (in the rare case when these data were not available, other regions from the above papers 27

were used as surrogates; parameters were averaged if a range was provided for a given species). Using these estimates, we 28

ranked species according to their reproductive potential (lower fecundity and higher age at maturity = higher sensitivity), 29

with higher rankings conferring higher risk, as the low-fecundity/low-natural mortality strategies of many elasmobranch 30

fishes appear to render them less capable of population change than many teleost fishes (Myers and Worm, 2005; Stevens 31

et al., 2000). We also scored each species' overall relative vulnerability to longline fishery bycatch by averaging ranks of age- 32

at-maturity, fecundity, and mean survival between both tuna and swordfish sets (with higher survival = lower rank; each 33

metric weighted similarly). Statistical analyses were performed using SAS (SAS Institute 1990) and statistical significance 34

was declared at p < 0.05. 35

3. Results 36

3.1. Effects of fishery-related variables on survival 37

A total of 3431 swordfish and 1596 tuna sets were analyzed, with the number of observations per taxon ranging from 139 38

(longfin mako) to 17,780 (blue shark) for combined targeted sets. Estimated lengths ranged from 30 cm FL (shortfin mako 39

and silky shark) to 480 cm FL (tiger shark, Table 1). Less than 1% of all captured sharks were classified as ''damaged'', and 40

we removed these observations from our analyses to avoid confounding factors (i.e., the response variable would no longer 41

be binomial). At-vessel survival was significantly affected by one or more independent variables in seven of the 12 species 42

assessed (60%, Table 1). Statistically significant effects for fishing target (tuna/swordfish) were detected for four of the taxa 43

assessed: blue (decrease), silky (increase), longfin mako (decrease), and night shark (decrease; Table 1). Furthermore, three 44

species were significantly affected by soak time, with survival decreasing with increasing soak time for blue, porbeagle, and 45

silky sharks (Table 1). Hook depth was a significant variable for four of the species analyzed, whereby positive relationships 46

with survival were found for blue, night, and scalloped hammerhead sharks, and a negative relationship with survival for 47

porbeagle shark (Table 1). Survival of four species was significantly affected by temperature, with inverse relationships 48

detected for silky, blue, dusky, and night sharks (Table 1). Lastly, length was a significant factor affecting survival of 5 of 12 49

species: survival of silky, blue, dusky, and night shark significantly increased with body length, whereas it decreased with 50

length for longfin mako (Table 1). Although it is not recommended to report R2 values from fitted logistic regression models 51

due to their routinely low values (Hosmer and Lemeshow, 2000), pseudo-R2 value were generated following Shtatland et al. 52 (2002) and presented in Table 1. Q3 53

A.J. Gallagher et al. / Global Ecology and Conservation xx (xxxx) xxx-xxx

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TIG BSH OCS POR SSB DUS SMA LMA FAL BTH SPL SNI Species

Fig. 1. Least-square mean survival estimates for 12 species encountered as bycatch in pelagic longline sets targeting swordfish. US National Marine Fisheries Service shark species identification codes are as follows: 'TIG' = tiger; 'BSH' = blue; 'OCS' = oceanic whitetip; 'POR' = porbeagle; 'SSB' = sandbar; 'DUS' = dusky; 'SMA' = shortfin mako; 'LMA' = longfin mako; 'FAL' = silky; 'BTH' = bigeye thresher; 'SPL' = scalloped hammerhead; 'SNI' = night. Gray dots indicate species prohibited from retention by pelagic longline gear as designated by the US National Marine Fisheries Service. Error bars represent the 95% confidence intervals. Fish classified as ''damaged'' were not included in the analyses and are thus not represented here.

TIG BSH POR SSB OCS DUS SMA FAL BTH SPL SNI LMA Species

Fig. 2. Least-square mean survival estimates for 12 species encountered as bycatch in pelagic longline sets targeting tuna. US National Marine Fisheries Service shark species identification codes are as follows: 'TIG' = tiger; 'BSH' = blue; 'OCS' = oceanic whitetip; 'POR' = porbeagle; 'SSB' = sandbar; 'DUS' = dusky; 'SMA' = shortfin mako; 'LMA' = longfin mako; 'FAL' = silky; 'BTH' = bigeye thresher; 'SPL' = scalloped hammerhead; 'SNI' = night. Gray dots indicate species prohibited from retention by pelagic longline gear as designated by the US National Marine Fisheries Service. Error bars represent the 95% confidence intervals. Fish classified as ''damaged'' were not included in the analyses and are thus not represented here.

3.2. Survival estimates and reproductive capabilities

Least squares mean hooking survival rates varied between fishery targets and among species. In swordfish sets, survival 2

was high for tiger (97.1%), blue (82.7%), and oceanic whitetip sharks (77.3%; Fig. 1), and lower for night shark (22.2%), 3

scalloped hammerhead (42.3%), bigeye thresher (44.9%), and silky shark (49.4%; Fig. 1). Tuna-directed sets exhibited a similar 4

pattern of higher survival for tiger (96.5%), blue (87.0%), and porbeagle sharks (82.7%, despite low sample size), and lower 5

survival for night (43.8%) and longfin mako sharks (37.4%; Fig. 2). 6

Ranking species according to their reproductive capabilities (based on data from Cortés, 2000, 2002; Hazin et al., 2000; 7

Dulvy et al., 2008) showed that the blue and oceanic whitetip shark had the youngest age at maturity, 5 and 5.5 years, 8

respectively; (Table 2), whereas tiger, silky, night, and bigeye thresher sharks all were associated with moderate age at Q4 9

maturity rankings (8-12.7 years, Table 2). Conversely, four species were associated with older ages at maturity and thus 10

rankings: porbeagle (13 years), scalloped hammerhead (15 years), sandbar (15.5 years), and the dusky shark (19 years). 11

High fecundity (number of pups per litter per year) translated into low rankings for tiger (55 pups, ranked lowest), blue (37 12

pups, 2nd lowest), and scalloped hammerhead sharks (35 pups, 3rd lowest). Higher sensitivity was evident for species with 13

few pups per litter such as the dusky (9 pups, 7th), the sandbar (8 pups, 8th), porbeagle (4 pups, 9th), and bigeye thresher 14

(3 pups, 10th). A continuum of overall relative vulnerability (average of mean survival, age at maturity, and fecundity 15

rankings) among species emerged which appeared to cluster certain groups of species: tiger, blue, and oceanic whitetip 16

sharks exhibited low vulnerability, whereas the night, scalloped hammerhead, shortfin mako, dusky, bigeye thresher, and 17

longfin mako emerged the most vulnerable to longline bycatch mortality (although the latter species should be treated with Q5 18

caution due to lack of life-history data; Figs. 3 and 4). Q7 19

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Table 2

Species attributes and their respective overall relative vulnerability rankings (lower ranking = lower vulnerability).

Species Age at Maturity Fecundity Fecundity No. No. Mean Mean Vulnerability

maturity ranking (offspring/year) ranking observed observed survival survival ranking

(years) alive dead rate rank

Longfin mako 18.5a 10 3 10 73 66 48.9 9 9.7

Bigeye thresher 12.7b 6 3b 10 178 189 48.3 10 8.7

Dusky 19 11 9 7 193 81 72.1 6 8.0

Sandbar 15.5 9 8 8 138 51 73.3 5 7.3

Scalloped 15b 8 35b 3 336 391 45.9 11 7.3

hammerhead

Shoftfin mako 18.5 10 12.5 5 1503 623 71.4 7 7.3

Night shark 10b 5 15 4 292 849 33.0 12 7.0

Porbeagle 13 7 4 9 193 62 78.6 3 6.3

Silky 9.5b 4 10 6 1004 86 57.8 8 6.0

Oceanic whitetip 5.5b 2 12.5 5 162 51 74.3 4 3.7

Tiger 9 3 55 1 1305 43 96.8 1 1.7

Blue 5 1 37 2 14788 2992 84.9 2 1.7

Age at maturity and fecundity estimates were derived from the appendices used in Cortés (2000, 2002) and Dulvy et al. (2008) corresponding to stocks from the Northwest Atlantic unless otherwise noted (with a 'b'). a Due to a lack of data on longfin mako age at maturity, we used the same data as the shortfin mako.

b Symbols refer to regions used for that particular measure: BTH = Northwest Pacific; SNI = Southwest Atlantic from Hazin et al. (2001); OCS = Central Pacific; SPL = Northwest Gulf of Mexico; FAL = Northwest Gulf of Mexico.

Fig. 3. Interaction plot showing mean survival rate (%, swordfish and tuna combined), age at maturity (in years), and fecundity (# of pups per litter per year) for each species. US National Marine Fisheries Service shark species identification codes are as follows: 'TIG' = tiger; 'BSH' = blue; 'OCS' = oceanic whitetip; 'POR' = porbeagle; 'SSB' = sandbar; 'DUS' = dusky; 'SMA' = shortfin mako; 'LMA' = longfin mako; 'FAL' = silky; 'BTH' = bigeye thresher; 'SPL' = scalloped hammerhead; 'SNI' = night.

1 4. Discussion

2 4.1. The impacts of bycatch

3 It is estimated that bycatch represents a major threat to over 70% of elasmobranch species (Molina and Cooke, 2012)

4 and there is mounting evidence that populations of elasmobranchs subjected to bycatch can decline over short time scales

5 (decades; Casey and Myers, 1998; Baum and Myers, 2004). The responses of individuals to the process of hook-and-line

6 capture can vary highly among species (Mandelman and Skomal, 2009; Gallagher et al., 2014b), leading to differences

7 in acute (maintenance of physiological equilibrium, Frick et al., 2010) and long-term (survival and reproductive fitness)

8 consequences.

9 This study is one of the first attempts to investigate the effect of fishery target on shark bycatch survival in pelagic

10 longline fisheries, and we found it to be significant for one-third of the species assessed. For 7 of the 12 (58%) species, we

11 rejected the null hypothesis of no influence of fishery-related variables on shark survival (Table 1). Survival was significantly

12 lower for blue, night and silky sharks in swordfish sets. Swordfish directed sets are often made at sunset to take advantage

13 of the fact that swordfish feed near the surface at night. Blue and night sharks, and to a lesser extent, silky sharks, are

14 medium-bodied, ram-feeding species that also forage on prey species that ascend to the surface at night (Bonfil, 2008;

15 Nakano and Stevens, 2008). Due to individuals already expending energy during food acquisition, as well as the social stress

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c (B 8

• •

o • • •

BSH TIG OCS FAL POR SNI SMA SSB SPL DUS BTH LMA Species

Fig. 4. Overall relative vulnerability scores for all of the shark species assessed. Each score was obtained by averaging the sensitivity rankings of species survival rate (swordfish and tuna combined), age at maturity, and fecundity (see Table 3). Increasing vulnerability confers a higher overall relative risk to bycatch. Colors signify species-specific IUCN Red List category [47]: orange = "Near Threatened;'' red = "Vulnerable;'' maroon = "Endangered". US National Marine Fisheries Service shark species identification codes are as follows: 'TIG' = tiger; 'BSH' = blue; 'OCS' = oceanic whitetip; 'POR' = porbeagle; 'SSB' = sandbar; 'DUS' = dusky; 'SMA' = shortfin mako; 'LMA' = longfin mako; 'FAL' = silky; 'BTH' = bigeye thresher; 'SPL' = scalloped hammerhead; 'SNI' = night. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

resulting from competition, we hypothesize that the process of being captured and subsequently fighting on a longline may synergistically result in additive metabolic and physiological burdens resulting in higher rates of mortality for these species.

4.2. Physiological effects 3

Temperature is a major controlling factor in the behavior, growth, and life history of most fish species. However, the 4

interaction among water temperatures, fishery capture stress and survival is poorly understood, particularly in bycatch 5

scenarios for marine fishes (Davis, 2002; Gale et al., 2013). Warmer water temperatures typically contain lower amounts of 6

dissolved oxygen and can increase the metabolic rate and magnitude of capture stress in sharks (Skomal and Bernal, 2010). 7

Our data indicated that the survival of blue, dusky, night, and silky sharks - all ectothermic species - significantly decreased 8

with increasing temperature. Survival showed a significant increase at deeper hook depths for blue, scalloped hammerhead 9

and night sharks supporting the notion that access to deeper, cooler waters may limit oxygen deficits when captured 10

(Table 1). An additional factor which could influence survival due to asphyxiation is soak times of the gear, which may 11

be prolonged when captured on short gangions (which limit ram-ventilation) during commercial longline fisheries. Blue, 12

porbeagle, and silky sharks exhibited decreasing survival with increased soak time in our study (Table 1). Collectively, these 13

results suggest that elevations in water temperature and soak time could significantly decrease the survival of some sharks 14

captured as bycatch in pelagic longlines, and that avoiding fishing during times/seasons with warmer water temperatures, 15

and/or setting hooks in cooler, deeper water may be tactics for mitigating shark stress and mortality associated with 16

fishing (Hoffmayer et al., 2012). This would presume that captured individuals would not suffer barotrauma as seen in 17

teleosts, whereas the feasibility of a change in fishing tactics would depend on the effect it would have on fish catches of 18

targeted species. Furthermore, while temperature here is treated as a linear factor, future work might explore the possibility 19

of species-specific temperature thresholds that dictate survivability. 20

Temperature changes can also result in other sublethal effects on fishes (e.g., physiological disturbance, behavioral 21

changes, reproductive loss; Cooke et al., 2002). These fitness losses may be of special concern for large and/or fecund 22

individuals, as previous work has shown that temperature and other stresses of capture function to interrupt endocrine 23

systems and processes associated with reproduction (Barton and Iwama, 1991; Pankhurst and Dedual, 1994). Furthermore, 24

while there is considerable uncertainty as to the effects of anthropogenic climate change on marine systems (Hoegh- 25

Guldberg and Bruno, 2010), the potential of warming sea temperatures may exacerbate the above relationships between 26

elevated temperatures and shark survival as bycatch. 27

4.3. Stress and exhaustion 28

Fish metabolic processes often scale with body size (Clarke and Johnston, 1999; Dowd et al., 2006). Recent evidence suggests that as sharks increase in size, they may become more resistant to the physiological consequences of fisheries capture (Gallagher et al., 2014b). Our results are in agreement with these studies for blue, dusky, silky, sandbar and night shark (Tables 1 and 2). Interestingly, these five species share body plans that lack unique morphological structures (as seen in other species, such as the hammerhead's cephalofoil) and they generally attain smaller maximum sizes than some of the other species in our study (i.e., tiger, thresher). Moreover, the survival of this complex of species (blue, dusky, silky, sandbar, night) was affected similarly by the suite of factors examined. The diversification of body plans is one of the most important factors leading to evolutionary divergence, and how specialization of key traits (morphological and functional) in captured fishes affects their subsequent survival is an area deserving of future study (Gallagher et al., 2014a).

8 A.J. Gallagher et al. / Global Ecology and Conservation xx (xxxx) xxx-xxx

1 Tiger sharks were ranked the most robust species to bycatch mortality in our study, exhibiting ~97% at-vessel survival in

2 both swordfish and tuna sets (Figs. 1 and 2), and, when considering their high fecundity and relatively low age at maturity,

3 this species received one of the lowest overall relative vulnerability rankings (Table 2). Their apparent tolerance to capture

4 stress is consistent with other work documenting minimal physiological disruption on fishing lines (Mandelman and Skomal,

5 2009; Gallagher et al., 2014b) and very low (2%-8%) mortality in pelagic and bottom longlines (Beerkircher et al., 2002;

6 Morgan and Burgess, 2007; Morgan and Carlson, 2010). Blue sharks and sandbar sharks were also ranked as relatively robust

7 against bycatch mortality, and are both known to resist physiological disturbance (metabolic and respiratory acidoses; Brill

8 et al., 2008; Campana et al., 2009). However, the differences in reproductive rates between these species alter their relative

9 vulnerability to bycatch (Figs. 2 and 3): blue sharks reach maturity nearly three-times faster and produce about four-times

10 as many pups per litter than sandbar sharks, resulting in a higher vulnerability to bycatch for the sandbar shark.

11 4.4. Vulnerability

12 Species in the present study are clustered in groups according to their vulnerability (Fig. 3). Silky sharks, which were

13 found to have the highest degree of vulnerability in a 2010 International Commission for the Conservation of Atlantic

14 Tunas (ICCAT) ecological risk assessment for Atlantic sharks (ICCAT, 2011), displayed moderate survival in tuna sets, but low

15 survival in swordfish sets, which resulted in moderate-to-low survival rankings and a moderate vulnerability ranking. Mean

16 survival rates of bigeye thresher, scalloped hammerhead and night sharks were the lowest of the 12 species assessed (Fig. 3).

17 Despite the relatively high fecundity of the scalloped hammerhead (Cortés, 2000,2002), its slow attainment of maturity and

18 low survival render it more vulnerable to bycatch (Table 2, Fig. 4), a pattern also evident in the bigeye thresher. Both of these

19 species are phylogenetically divergent and morphologically specialized: thresher sharks have evolved an elongated upper-

20 lobe of the caudal fin used in prey capture (Oliver et al., 2013); whereas hammerhead species possess a distinctive cephalofoil

21 which is thought to afford enhanced sensory capabilities (McComb et al., 2009). The shape of an animal has a direct effect on

22 how they exchange energy and materials with their surroundings, and functional specialization is often tied to the concept

23 of'trade-offs' (Irschick et al., 2005; Gallagher et al., 2014a). As mentioned earlier, species with basic body plans were actually

24 afforded higher survival as they attained larger sizes. However, whether these structures may have resulted in trade-offs that

25 reduce survival upon capture (i.e., smaller mouths resulting in limited oxygen update during fighting) remains unknown.

26 4.5. Risk assessment

27 Survival assessments, such as the one employed here, may help predict the susceptibility of sharks to exploitation over

28 long time scales. For example, a fishery-independent shark survey conducted off Florida's coast in the early 1980s found

29 that scalloped hammerheads were among the top three most common species (Berkeley and Campos, 1988), but have

30 been subject to an estimated annual rate of change of -20% since 1992 (Baum et al., 2003). In the Northwest Atlantic,

31 scalloped hammerheads suffered a nearly 90% decline between 1986 and 2000 (Baum et al., 2003). In our study, we found

32 that scalloped hammerheads exhibited among the lowest survival rates as bycatch (Table 2). When considering the findings

33 from the above time-series, we suggest bycatch capture likely played an important role in the decline of this species. This

34 point is supported by that fact that populations of species that exhibited high tolerance to bycatch in our study (i.e., tiger)

35 may be stabilizing or increasing in recent years in the Northwest Atlantic (Baum and Blanchard, 2010; Carlson et al., 2012),

36 suggesting that life-history parameters in isolation do not explain overharvest. That said, the rankings of overall relative

37 vulnerability used in the present study may not reflect the susceptibility of shark stocks to exploitation throughout the

38 Atlantic Ocean if a small proportion of the stock is present where the majority fishing occurs, or if the abundance of the

39 species in question is very high. While performing an Atlantic-wide stock assessment to vulnerability from bycatch is

40 beyond the scope of this study, future work could employ spatial analyses using data from the many national fishing fleets

41 operating in the Atlantic and examine vulnerability based on catch, effort and susceptibility (e.g., probability of encounter).

42 Furthermore, we recognize that other measures such as maximum body size, maximum age, and growth rates are valuable

43 measures of resilience of fishes to exploitation; we used age at maturity and fecundity because they are both recognized

44 among the most important biological predictors of extinction risk and these standardized metrics are comparable among

45 species (Reynolds et al., 2005).

46 Our results also suggest that, broadly, the IUCN Red List (The International Union for the Conservation of Natue, 2013)

47 categories accurately reflect the overall relative vulnerabilities of the 12 species examined in this study (Fig. 4). For example,

48 the two least vulnerable species (blue and tiger sharks) were listed as ''Near Threatened'' by the IUCN, and three of the most

49 vulnerable species (bigeye thresher, dusky, and night shark, excluding longfin mako due to data limitations) were all listed

50 as ''Vulnerable''. Silky sharks exhibit moderate overall vulnerability to pelagic longline bycatch and appear to be properly

51 listed as ''Near Threatened'', whereas the oceanic whitetip displayed low overall vulnerability yet are listed as ''Vulnerable''

52 globally and ''Critically Endangered'' in our study area. These differences suggest that the existing risk categorization of

53 species may be augmented by survival assessments and that interactions with other fisheries (e.g., incidental captures in

54 trawls or direct harvest) or combinations of other extrinsic factors (gear changes, species misidentification) may better

55 explain the reported extreme declines than bycatch in pelagic longline fisheries for certain species (i.e., oceanic whitetip).

A.J. Gallagher etal./ Global Ecology and Conservation xx (xxxx) xxx-xxx 9

5. Conclusions i

While bycatch has been cited as a major driver of extinction risk for pelagic shark species, it clearly does not affect 2

all species similarly. Moreover, longline bycatch mortality has differential explanatory power in framing the population 3

declines (and risks) of certain species, as evidenced by the large gradient in vulnerability that we documented. For those 4

species which are most affected, however, our study agrees with the notion that the best conservation strategy may be 5

to reduce shark interactions with fishing gear (e.g., time-area closures) because solely restricting harvest or discarding 6

captured individuals will not eliminate mortality if sharks are already dead upon gear retrieval (Gilman, 2011; Jordan et al., 7

2013). In addition to restricting longline fishing where species susceptible to bycatch mortality occur, other strategies that 8

show some promise for altering species-specific vulnerabilities to capture may include setting lines in deeper water, altering 9

the bait used, and employing sensory based deterrents (Gilman, 2011; Jordan et al., 2013). For example, Rigg et al. (2009) 10

found that scalloped hammerhead sharks (a species we found to exhibit among the lowest at-vessel survival) avoided the 11

magnetic fields of magnets placed on fishing gear, while Hutchinson et al. (2012) found the use of lanthanide metals on 12

longline hooks reduced the catch of scalloped hammerhead sharks. 13

Studies on fish species have been traditionally slower to link ecology and evolution to risk of extinction when compared to 14

their terrestrial counterparts (Reynolds et al., 2005). However, the need to consider the phenotypic and adaptive responses 15

when predicting survival outcomes, especially marine fishes threatened with extinction, is gaining recognition (Young et al., 16

2006; Gallagher et al., 2014a). Our study adds to the growing body of literature that provide suggestions for reducing 17

bycatch mortality to threatened species (e.g., setting in deeper water, time-area closures, using species-specific deterrents). 18

Moreover, our work suggests that the historical selection of biological and ecological traits may have disparate consequences 19

when species are exposed to fishery stressors. Accordingly, consideration of species' ecological and evolutionary variables 20

in addition to survival rates and life-history parameters may be useful in determining which management strategies offer 21

the most effective conservation benefits in the future. 22

Acknowledgments 23

We greatly appreciate the thoughtful insights on this manuscript provided by P. Kyne, S. Cooke, D. Shiffman, as well 24

L. Natanson and L. Beerkircher. We also thank all of the observers who collected these data. We appreciate the oversight 25

from K. Broad and G. Maranto at the Abess Center for Ecosystem Science and Policy, University of Miami. This work was 26

made possible by funding from the Florida Sea Grant, Disney Worldwide Conservation Fund, RJ Dunlap Marine Conservation 27 Program and the Batchelor Foundation. The US National Marine Fisheries Service also contributed to this work. We also thank Q8 28

the anonymous reviewers who strengthened this manuscript. 29

References 30

Astles, K.L., Holloway, M.G., Steffe, A., Green, M., Ganassin, C., Gibbs, P.J., 2006. An ecological method for qualitative risk assessment and its use in the 31

management of fisheries in New South Wales. Aust. Fish. Res. 82, 290-303.

Barker, M.J., Schluessel, V., 2005. Managing global shark fisheries: suggestions for prioritizing management strategies. Aquat. Conserv. Mar. Freshw. Ecosyst. 32 15,325-347.

Barton, B.A., Iwama, G.K., 1991. Physiological changes in fish from stress in aquaculture with emphasis on the response and effects of corticosteroids. Ann. 33 Rev. Fish Dis. 1,3-26.

Baum, J.K., Blanchard, W., 2010. Inferring shark population trends from generalized linear mixed models of pelagic longline catch and effort data. Fish. Res. 34 102,229-239.

Baum, J.K., Myers, R.A., 2004. Shifting baselines and the decline of pelagic sharks in the Gulf of Mexico. Ecol. Lett. 7,135-145. 35

Baum, J.K., Myers, R.A., Kehler, D.G., Worm, B., Harley, S.J., Doherty, P.A., 2003. Collapse and conservation of shark populations in the Northwest Atlantic. 36 Science 299, 389-392.

Beerkircher, L.R., Cortés, E., Shivji, M., 2002. Characteristics of shark sycatch observed on pelagic longlines off the southeastern United States, 1992-2000. 37 Mar. Fish. Rev. 64, 40-49.

Berkeley, S.A., Campos, W.L., 1988. Relative abundance and fishery potential of pelagic sharks along Florida's east coast. Mar. Fish. Rev. 50,9-16. 38

Bonfil, R., 1994. Overview of world elasmobranch fisheries. FAO Tech Report. p. 119. 39

Bonfil, R., 2008. The biology and ecology of the silky shark, Carcharhinus falciformis. In: Camhi, M., Pikitch, E.K., Babcock, E. (Eds.), Sharks of the Open 40

Ocean: Biology, Fisheries and Conservation. Blackwell Publishing Ltd., pp. 114-127.

Brill, R., Bushnell, P., Schroff, S., Seifert, R., Galvin, M., 2008. Effects of anaerobic exercise accompanying catch-and-release fishing on blood-oxygen affinity 41

of the sandbar shark (Carcharhinus plumbeus, Nardo). J. Exp. Mar. Biol. Ecol. 354,132-143.

Campana, S., Joyce, W., Manning, M., 2009. Bycatch and discard mortality in commercially caught blue sharks Prionace glauca assessed using archival 42

satellite pop-up tags. Mar. Ecol. Prog. Ser. 387, 241-253.

Carlson, J.K., Hale, L.F., Morgan, A., Burgess, G., 2012. Relative abundance and size of coastal sharks derived from commercial shark longline catch and effort 43 data. J. Fish Biol. 80,1749-1764.

Casey, J.M., Myers, R.A., 1998. Near extinction of a large, widely distributed fish. Science 281,690-692. 44

Clarke, A., Johnston, N.M., 1999. Scaling of metabolic rate with body mass and temperature in teleost fish. J. Anim. Ecol. 893-905. 45

Clarke, S.C., McAllister, M.K., Milner-Gulland, E.J., Kirkwood, G.P., Michielsens, C.G.J., Agnew, D.J., Pikitch, E.K., Nakano, H., Shivji, M.S., 2006. Global estimates 46

of shark catches using trade records from commercial markets. Ecol. Lett. 9,1115-1126.

Cooke, S.J., Schreer, J., Wahl, D., Philipp, D., 2002. Physiological impacts of catch-and-release angling practices on largemouth bass and smallmouth bass. 47 Amer. Fish. Soc. Symp. 31,489-512.

Cortés, E., 2000. Life history patterns and correlations in charks. Rev. Fish Biol. Fish. 8, 299-344. 48

Cortés, E., 2002. Incorporating uncertainty into demographic modeling: application to shark populations and their conservation. Conserv. Biol. 16, 49 1048-1062.

Cortés, E., Arocha, F., Beerkircher, L., Carvalho, F., Domingo, A., Heupel, M., Holtzhausen, H., Santos, M.N., Ribera, M., Simpfendorfer, C., 2010. Ecological risk 50 assessment of pelagic sharks caught in Atlantic pelagic longline fisheries. Aquatic Living Res. 23, 25-34.

10 A.J. Gallagher et al. / Global Ecology and Conservation xx (xxxx) xxx-xxx

1 Davis, M.W., 2002. Key principles for understanding fish bycatch discard mortality. Can. J. Fish. Aquat. Sci. 59,1834-1843.

2 Diaz, G.A., Serafy, J.E., 2005. Longline-caught blue shark (Prionace glauca): factors affecting the numbers available for live release. Fish. Bull. 103,720-724.

3 Dowd, W.W., Brill, R., Bushnell, P., Musick, J., 2006. Standard and routine metabolic rates of juvenile sandbar sharks (Carcharhinus plumbeus), including

the effects of body mass and acute temperature change. Fish. Bull. 104,323-331.

4 Dulvy, N., et al., 2008. You can swim but you can't hide: the global status and conservation of oceanic pelagic sharks and rays. Aquat. Conserv. Mar. Freshw.

Ecosyst. 482, 459-482.

5 Ferretti, F., Worm, B., Britten, G.L., Heithaus, M.R., Lotze, H.K., 2010. Patterns and ecosystem consequences of shark declines in the ocean. Ecol. Lett. 13,

1055-1071.

6 Frick, L.H., Reina, R.D., Walker, T.I., 2010. Stress related physiological changes and post-release survival of Port Jackson sharks Heterodontus portusjacksoni

and gummy sharks Mustelusantarcticus following gill-net and longline capture in captivity. J. Exp. Mar. Biol. Ecol. 385, 29-37.

7 Gale, M.K., Hinch, S.G., Donaldson, M.R., 2013. The role of temperature in the capture and release of fish. Fish Fish. 14,1-33.

8 Gallagher, A.J., Hammerschlag, N., Shiffman, D.S., Giery, S.T., 2014a. Evolved for extinction? The cost and conservation implications of extreme specialization

9 in hammerhead sharks. BioScience. http://dx.doi.org/10.1093/biosci/biu071.

10 Gallagher, A.J, Kyne, P.M., Hammerschlag, N., 2012. Ecological risk assessment and its application to elasmobranch conservation and management. J. Fish

Biol. 80,1727-1748.

11 Gallagher, A.J., Serafy, J.E., Cooke, S.J., Hammerschlag, N., 2014b. Physiological stress response, reflex impairment, and survival of five sympatric shark

species following experimental capture and release. Mar. Ecol. Prog. Ser. 496, 207-218.

12 Gilman, E.L., 2011. Bycatch governance and best practice mitigation technology in global tuna fisheries. Mar. Policy 35,590-609.

13 Hazin, F., Lucena, F.M., Souza, T.S.A.L., Boeckman, C.E., Broadhurst, M.K., Menni, R.C., 2000. Maturation of the night shark, Carcharhinus signatus, in the

southwestern equatorial Atlantic Ocean. Bull. Mar. Sci. 66,173-185.

14 Hoegh-Guldberg, O., Bruno, J.F., 2010. The impact of climate change on the world's marine ecosystems. Science 328,1523-1528.

15 Hoffmayer, E.R., Hendon, J.M., Parsons, G.R., 2012. Seasonal modulation in the secondary stress response of a carcharhinid shark, Rhizoprionodon

terraenovae. Comp. Biochem. Physiol., A: Mol. Integ. Physiol. 162,81-87.

16 Hosmer, D.W., Lemeshow, S., 2000. Applied Logistic Regression, second ed.. John Wiley & Sons, Inc, New York.

17 Hutchings, J.A., Reynolds, J.D., 2004. Marine fish population collapses: consequences for recovery and extinction risk. BioScience 54, 297-309.

18 Hutchinson, M., Wang, J.H., Swimmer, Y., Holland, K., Kohin, S., Dewar, H., Wraith, J., Vetter, R., Heberer, C., Martinez, J., 2012. The effects of a lanthanide

metal alloy on shark catch rates. Fish. Res. 131-133,45-51.

19 ICCAT, 2011, Recommendtaion by ICCAT on the conservation of silky sharks caught in association with ICCAT fisheries.

20 file: http://C:/Users/eorbesen/Downloads/2011-08-e.pdf (accessed 6.11.14).

21 Irschick, D., Dyer, L., Sherry, T.W., 2005. Phylogenetic methodologies for studying specialization. Oikos 110,404-408.

22 Jackson, J.B., et al., 2001. Historical overfishing and the recent collapse of coastal ecosystems. Science 293,629-637.

23 Jordan, L.K., Mandelman, K.W., McComb, D.M., Fordham, S.V., Carlson, J.K., Werner, T.B., 2013. Linking sensory biology and fisheries bycatch reduction in

elasmobranch fishes: a review with new directions for research. Conserv. Physiol. 1,1-20.

24 Mandelman, J.W., Skomal, G.B., 2009. Differential sensitivity to capture stress assessed by blood acid-base status in five carcharhinid sharks. J. Comp.

Physiol.. B, Biochem. Syst. Environ. Physiol. 179, 267-277.

25 McComb, D.M., Tricas, T.C., Kajiura, S.M., 2009. Enhanced visual fields in hammerhead sharks. J. Exp. Biol. 212,4010-4018.

26 Molina, J.M., Cooke, S.J., 2012. Trends in shark bycatch research: current status and research needs. Rev. Fish Biol. Fish. 22, 719-737.

27 Morgan, A., Burgess, G.H., 2007. At-vessel fishing mortality for six species of sharks caught in the Nrothwest Atlantic and Gulf of Mexico. Gulf Caribbean

Res. 19,123-129.

28 Morgan, A., Carlson, J.K., 2010. Capture time, size and hooking mortality of bottom longline-caught sharks. Fish. Res. 101,32-37.

29 Myers, R.A., Worm, B., 2005. Extinction, survival, or recovery of large predatory fishes. Phil. Trans. R. Soc. B 360,13-20.

30 Nakano, H., Stevens, J., 2008. The biology and ecology of the blue shark, Prionace glauca. In: Camhi, M., Pikitch, E.K., Babcock, E. (Eds.), Sharks of the Open

Ocean: Biology, Fisheries and Conservation. Blackwell Publishing Ltd., pp. 140-148.

31 Oliver, S.P., Turner, J.R., Gann, K., Silvosa, M., D'Urban Jackson, T., 2013. Thresher sharks use tail-slaps as a hunting strategy. PLoS One 8, e67380.

32 http://dx.doi.org/10.1371/journal.pone.0067380.

33 Pankhurst, N., Dedual, M., 1994. Effects of capture and recovery on plasma levels of cortisol, lactate and gonadal steroids in a natural population of rainbow

trout. J. Fish Biol. 45,1013-1025.

34 Pauly, D., Christensen, V., Guenette, S., Pitcher, T.J., Sumaila, U.R., Walters, C.J., Watson, R., Zeller, D., 2002. Towards sustainability in world fisheries. Nature

418,689-695.

35 Reynolds, J.D., Dulvy, N.K., Goodwin, N.B., Hutchings, J.A., 2005. Biology of extinction risk in marine fishes. Proc. R. Soc. B 272, 2337-2344.

36 Rigg, D.P., Peverell, S.C., Hearndon, M., Seymour, J.E., 2009. Do elasmobranch reactions to magnetic fields in water show promise for bycatch mitigation?

Mar. Freshwater Res. 60, 942-948.

37 Serafy, J.E., Orbesen, E.O., Snodgrass, D.J.G., Beerkircher, L.R., Walter, J.F., 2012. Hooking survival of fishes captured by the United States Atlantic pelagic

longline fishery: impact of the 2004 circle hook rule. Bull. Mar. Sci. 88,605-621.

38 Shtatland, E.S., Kleinman, K., Cain, E.M., 2002, One more time about R2 measures of fit in logistic regression. In: SAS Conference Proceedings: NESUG 2002

39 September 29-October 2,2002, Buffalo, New York, available at http://www.nesug.org/Proceedings/nesug02/st/st004.pdf.

40 Skomal, G.B., Bernal, D., 2010. Physiological responses to stress in sharks. In: Carrier, J., Musick, J.A., Heithaus, M. (Eds.), Sharks and Their Relatives II:

Biodiversity, Adaptive Physiology, and Conservation. CRC Press, Boca Raton, pp. 459-490.

41 Stevens, J.D., Bonfil, R., Dulvy, N.K., Walker, P.A., 2000. The effects of fishing on sharks, rays, and chimaeras (chondrichthyans), and the implications for

marine ecosystems. ICES J. Mar. Sci. 57, 476-494.

42 The International Union for the Conservation of Natue, 2013, IUCN Red List of Threatened Species. Retrieved from http://www.iucnredlist.org (accessed

43 10.03.14).

44 Worm, B., Branch, T.A., 2012. The future of fish. Trends Ecol. Evol. 27,594-599.

45 Worm, B., Davis, B., Kettemer, L., Ward-Paige, C.A., Chapman, D., Heithaus, M.R., Kessel, S.T., Gruber, S.H., 2013. Global catches, exploitation rates, and

rebuilding options for sharks. Mar. Policy 40,194-204.

46 Young, J.L., Bornik, Z.B., Marcotte, M.L., Charlie, K.N., Wagner, G.N., Hinch, S.G., Cooke, S.J., 2006. Integrating physiology and life history to improve fisheries

management and conservation. Fish Fish. 7, 262-283.