The blue shark (Prionace glauca) is an oceanic species that occurs in temperate and tropical waters around the globe (Robins and Ray, 1986). This species is a major bycatch of

pelagic longline fleets that operate to supply the world’s growing demand for tunas and swordfish (Xiphias gladius)

(Stevens, 1992; Bailey et al., 1996; Francis, 1998; Francis et al., 2001; Macias and de la Serna, 2002); numerically, the blue shark is the top nontarget species captured by the

U.S. longline pelagic Atlantic fleet (Beerkircher et al

Diaz, Guillermo A.

Serafy, Joseph E.

English

Aquatic Commons

720
ART & EQUATIONS ARE LINKED PREFLIGHT GOOD
The blue shark (Prionace glauca) is 
an oceanic species that occurs in tem-
perate and tropical waters around 
the globe (Robins and Ray, 1986). 
This species is a major bycatch of 
pelagic longline fleets that operate to 
supply the world’s growing demand 
for tunas and swordfish (Xiphias gla-
dius) (Stevens, 1992; Bailey et al., 
1996; Francis, 1998; Francis et al., 
2001; Macias and de la Serna, 2002); 
numerically, the blue shark is the top 
nontarget species captured by the 
U.S. longline pelagic Atlantic fleet 
(Beerkircher et al.1). 
Ward et al. (2004) examined the 
effect of longline soak time (set du-
ration) on the catch rate of several 
target and bycatch species, including 
the blue shark. However, they did not 
investigate the effects of fish size, 
set duration, and water tempera-
ture on shark survival, and, there-
fore, numbers potentially available 
for live release (Francis et al., 2001; 
Campana et al.2). Knowledge of such 
relationships may be of value: 1) for 
minimizing bycatch mortality on this 
and other highly vulnerable pelagic 
species through modification of fish-
ing strategy; and 2) for blue shark 
stock assessments that are based on 
commercial longline catch data.
Materials and methods
Data analyses were conducted on a 
portion of the U.S. Atlantic Pelagic 
Observers Program (POP) database. 
The POP places trained observers 
aboard commercial fishing vessels 
Longline-caught blue shark (Prionace glauca): 
factors affecting the numbers available  
for live release*
Guillermo A. Diaz
Joseph E. Serafy
National Marine Fisheries Service
Southeast Fisheries Science Center
75 Virginia Beach Drive
Miami, Florida 33149
E-mail address (for G. A. Diaz): Guillermo.diaz@noaa.gov
to record detailed information about 
each fishing set, the catch and the 
bycatch that would not otherwise 
be collected. Recorded information 
includes individual fish size (mea-
sured or estimated) and disposition 
(alive or dead), surface water tem-
perature (°C) at gear deployment and 
at haulback, and set location (lati-
tude and longitude). The duration of 
each set (soak time, in hours) can 
be obtained because time at start of 
gear deployment and at end of gear 
retrieval is also recorded. In the pres-
ent study, we restricted our analy-
ses to observed sets made from 1992 
to 2002 by U.S. f lag vessels north 
of 35°N latitude (Fig. 1). This area 
includes much of the U.S. exclusive 
economic zone north of Chesapeake 
Bay but also includes waters overly-
ing the Grand Banks. Data resulting 
from experimental fishing conducted 
from 2001 to 2004 over the Grand 
Banks area (i.e., north of 35°N lat-
itude and west of 60°W longitude) 
were not included because they did 
not reflect typical fishing operations.
For analysis purposes, blue shark 
were placed in 25-cm fork length (FL) 
size classes and water temperatures 
(means) and set durations into 2°C 
and 2-hour intervals, respectively. 
Size intervals were set at 25 cm 
FL to increase the number of obser-
vations in each size category and to 
reduce the bias that results from 
estimating lengths versus actually 
measuring them (e.g., observed in-
crease in the frequency of the esti-
mated lengths in 5- or 10-cm inter-
vals). For each combination of size, 
* Contribution number SFD-2005-030 
from the Sustainable Fisheries Divi-
sion, Southeast Fisheries Science Cen-
ter, NMFS, 75 Virginia Beach Drive, 
Miami,  FL 33149.
Manuscript submitted 19 July 2004  
to the Scientific Editor’s Office.
Manuscript approved for publication  
5 April 2005 by the Scientific Editor.
Fish. Bull. 103:720–724 (2005).
1 Beerkircher, L. R., C. J. Brown, and D. 
W. Lee. 2002. SEFSC pelagic obser- 
ver program data summary for 1992− 
2000. NOAA Tech. Memo. NMFS-
SEFSC-486, 23 p. Southeast Fisheries 
Science Center, Miami, FL 33149.
2 Campana S., P. Gonzalez, W. Joyce, and 
L. Marks. 2002. Catch, bycatch and 
landings of blue shark (Prionace glauca) 
in the Canadian Atlantic. Canadian 
Science Advisory Secretariat, Research 
Document 2002/101, 41 p. Marine Fish 
Division, Bedford Institute of Ocean-
ography. Dartmouth, Nova Scotia, B2Y 
4A2, Canada.
temperature, set duration, season, 
and area (i.e., Grand Banks and U.S. 
Atlantic east coast), the proportion of 
blue shark released alive (PDA) was 
calculated. 
Only sharks explicitly recorded as 
“discarded alive” or “discarded dead” 
were used and only proportions de-
rived from at least 20 observations 
(i.e., captured sharks) were analyzed. 
The influence of the fish size, water 
temperature, set duration, area, and 
season (and all possible interactions) 
on PDA was assessed by using the lin-
ear model
Pi = β0 + β1 Ti + β2 Di + β3 Si  
+ β4 Li + β5 Ai + Ci,
where Pi = to the proportion of blue 
shark discarded alive; 
 T = the temperature; 
 D = set duration; 
 S = season;
 L = length;
 A = set area, 
 C = the residual term of the 
ith observation; and
 β0 – β5 are model parameters. 
Prior to regression, proportions were 
arcsine-transformed according to the 
methods of Sokal and Rohlf (1981). In 
721NOTE Diaz and Serafy: Factors affecting the number of Prionace glauca available for live release in fisheries 
ART & EQUATIONS ARE LINKED PREFLIGHT GOOD
50°N
40°N
30°N
20°N
80°W 70°W 60°W 50°W 40°W
80°W 70°W 60°W 50°W 40°W
50°N
40°N
30°N
Atlantic Ocean
Grand
Banks
N
Figure 1
Locations of observed longline sets (1992−2002) recorded in the U.S. Pelagic 
Observers Program database and analyzed in the present study. 
the event that a factor was found to be nonsignificant 
(P>0.05), it was removed and a regression was rerun 
until all highest order model terms were significant 
(Hocking, 1976; Draper and Smith, 1981). We assumed 
maturity (both sexes) occurred at 185 cm FL (Pratt, 
1979). The average PDA and the ratio of immature-to-
mature individuals discarded in each 0.5-degree cell 
were estimated and plotted in order to visually examine 
the spatial distribution of these two variables.
Results
Data from 702 longline sets were used in analyses and 
resulted in size and condition (i.e., live or dead) informa-
tion on 4290 individual blue shark. From these data, a 
total of 37 proportions (i.e., PDA values) were calculated 
and used in regression analyses.
Most of the sets targeted swordfish (39%) or sword-
fish and tuna (36%), or unspecified tuna species (14%). 
Bigeye tuna and yellowfin tuna were the target of 8% 
and 3% of the sets, respectively. About 88% of the sets 
included in the analysis were characterized as “night 
sets” and the remaining were “day sets.”
Overall, more blue shark were released alive (69%) 
than dead. Shark sizes, water temperatures, and set 
durations used in the multiple linear regression ranged 
from 75 to 300 cm FL (median=175 cm), 8 to 29°C 
(median=19°C), and 6 to 14 hours (median=12), respec-
tively. About 68% of all released animals measured less 
than the size of sexual maturity (i.e., <185 cm FL).
Multiple linear regression indicated that no interac-
tion terms were statistically significant and that only 
shark size and set duration had significant effects on 
PDA (r
2=0.86, n=37, P<0.00001; Table 1). Plots of the 
observed proportions and the predicted response surface 
illustrate how the proportion of live releases increases 
with shark size and decreases with duration of set (Fig. 
2, A and B). Whereas set duration has a moderate im-
pact on the largest size classes, the proportion of live 
sharks <185 FL (i.e., immature stages) is consider-
ably reduced even at relatively short set durations. For 
example, predicted PDA for the smallest sharks (i.e., 
FL=75 cm) was 0.67 and 0.47 for set durations of 6 and 
14 hours, respectively; for those animals measuring 250 
cm FL, it was 0.94 and 0.80 for the same set durations. 
Maps of mean PDA values and of the proportion of imma-
ture sharks caught indicated conspicuous differences off 
the U.S. east coast versus over the Grand Banks (Fig. 
3, A and B). Specifically, the proportion of live releases 
Table 1
Regression coefficients and associated standard error 
values (SE) for the estimation of proportion of blue shark 
released alive (PDA) (n=37), where β0 corresponds to the 
intercept, and β1 and β2 are coefficients associated with 
blue shark fork length and set duration, respectively.
Parameters Estimate SE P > |t|
β0 0.967 0.0500 <0.0001
β1 0.0021 0.0002 <0.0001
β2 −0.0269 0.0037 <0.0001
722 Fishery Bulletin 103(4)
Figure 2
(A) Observed proportions of blue shark discarded alive 
(n=37) for each fork-length set duration combination; 
and (B) predicted response surface.
1.0
0.8
0.6
0.4
0.2
0.0
P
ro
po
rt
io
n 
re
le
as
ed
 a
liv
e
14
12
10
8
6
4
Set duration (h) 50
100
150
200
250
300
350
Fo
rk 
len
gth
 (c
m)
1.0
0.8
0.6
0.4
0.2
0.0
P
ro
po
rt
io
n 
re
le
as
ed
 a
liv
e
14
12
10
8
6
Set duration (h)
100
150
200
250
300
Fo
rk
 le
ng
th
 (c
m
)
4
A
B
tended to be lower over the Grand Banks than off the 
U.S. east coast and the mean ratio of immature blue 
shark tended to be higher.
Discussion
Our results indicate that blue shark tolerance to the 
stresses associated with longline capture decreases with 
animal size at levels that vary with set duration. These 
results are consistent with the findings of Neilson et al. 
(1989) and Milliken et al. (1999) who observed greater 
discard mortality among the smallest sizes classes of 
longline-caught Atlantic halibut (Hippoglossus hippo-
glossus) and cod (Gadus morhua), respectively. In our 
study, set duration represented the maximum possible 
time a given fish was “on-hook,” and thus was only the 
coarsest of measures of the magnitude and duration of 
stress experienced by hooked fishes. Nevertheless, this 
crude measure appears to have captured enough of the 
cumulative stress effects on fish survival to emerge as 
a significant factor. In contrast, water temperature did 
not emerge as important in our analysis. However, we 
suspect this resulted because surface water tempera-
tures (the only temperature measurements available) are 
poor indicators of the levels and changes in temperature 
actually experienced by captured sharks. Presumably, 
better predictions of condition at boat-side (and thus 
live discard quantities) could be made with knowledge 
of time-on-hook, depth, and temperature of capture, 
rate of gear retrieval, sea conditions, etc. Unfortunately, 
many of the measurements that are likely most relevant 
to recording shark condition at boat-side can only be 
made by distributing and retrieving large quantities of 
electronic instruments (i.e., temperature-depth recorders 
and hook-timers, see Boggs, 1992) near the hooks, and 
for each set. Such an approach is not only costly, but also 
difficult to implement without a research team dedicated 
for this purpose. Similarly, only by directed research 
can questions of postrelease mortality be addressed. 
Clearly, the proportions of living blue shark considered 
in our study are minimum estimates of fishing impacts 
because they do not account for delayed mortality of 
individuals released injured or otherwise impaired. For 
gauging postrelease mortality of longline-caught blue 
shark, tagging studies are warranted (Neilson et al., 
1989; Kohler et al., 2002).
Evident in the maps is that the proportion of blue 
sharks available for live release was not homogeneous 
throughout the spatial range examined. Overall the 
proportion of blue shark released alive was higher (0.78) 
along the U.S. Atlantic east coast and decreased over the 
Grand Banks (0.67) (Fig. 3A). The maps also indicated 
that overall the proportion of immature blue sharks was 
highest over the Grand Banks (0.93) compared to the 
U.S. Atlantic east coast (0.63) (Fig. 3B). In their exami-
nation of U.S. Atlantic east coast longline catches south 
of the present study (i.e., between 35° and 22°N latitude), 
Beerkircher et al. (2004) found that 0.87 of blue shark 
caught were alive at boat-side. It seems likely, therefore, 
that contributing to the relatively higher survival ob-
served by Beerkircher et al. (2004) was that only about 
half of the blue shark in their analysis were immature 
(as inferred from size). Blue shark interactions over the 
Grand Banks deserve special attention because most in-
dividuals discarded by the U.S. pelagic longline fleet are 
captured in that area. In 2002, for example, two thirds 
of the estimated 4335 blue shark mortalities attributed 
to U.S. Atlantic pelagic longline fleet were captured in 
this area (Diaz, unpubl. data3).
3 Diaz, G. A. 2005. NMFS Pelagic longline logbook pro-
gram. NMFS/SEFSC Miami, FL 33149.
723NOTE Diaz and Serafy: Factors affecting the number of Prionace glauca available for live release in fisheries 
Figure 3
(A) Average proportion of blue shark released alive and (B) average proportion 
of immature blue shark released in pelagic longline sets.  Proportions were 
estimated for 0.5-degree cells where at least one longline set was deployed in 
the period 1992−2002.
50°N
40°N
50°N
40°N
50°N
40°N
50°N
40°N
70°W 60°W 50°W 40°W
70°W 60°W 50°W 40°W
70°W 60°W 50°W 40°W
70°W 60°W 50°W 40°W
0.0–0.2
0.2–0.4
0.6–0.8
0.4–0.6
0.8–1.0
Atlantic
Ocean
0.0–0.2
0.0
0.2–0.4
0.6–0.8
0.4–0.6
0.8–1.0
A
B
Ward et al. (2004) modeled the effect of set duration 
on pelagic longline catches and found that blue shark 
catch rates increased with set duration. According to 
our results, the increase in set durations also leads to 
increases in the number retrieved dead. In concept, a 
possible management measure to achieve reductions 
in blue shark mortality may include shortening long-
line set durations. However, a regulation of this nature 
would be difficult to implement (let alone enforce) be-
cause swordfish catch rates are also lowered when set 
durations are shortened (Ward et al., 2004) and there-
fore result in negative economic impacts that would 
likely be unacceptable to the industry.
Results of this analysis also have implications for 
blue shark stock assessment. Stock assessments based 
on longline fisheries data often use a hook selectivity 
function of a logistic form, whereby hook retention is 
100% for fish larger than a certain size. In the particu-
724 Fishery Bulletin 103(4)
lar case of blue shark, where most individuals caught 
are released (dead or alive), fishing mortality is best 
estimated from the number of animals released dead, 
rather than from all animals caught. Because larger 
animals have a higher probability of being released 
alive, a logistic selectivity function without size or age 
survival adjustment, could lead to overestimation of 
impacts on the stock. Thus, a dome-shaped selectivity 
function that incorporates the size-based survival infor-
mation presented in the present study may represent an 
improvement over current techniques. 
Acknowledgments
We thank L. Brooks, E. Cortes, S. Turner, and two 
anonymous reviewers for invaluable comments on the 
manuscript. 
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Longline-caught blue shark (Prionace glauca): factors affecting the numbers available for live release*

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Longline-caught blue shark (Prionace glauca): factors affecting the numbers available for live release*

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