Elasmobranch captures in the Fijian pelagic longline fishery

Abstract

Pelagic longline fisheries for relatively fecund tuna and tuna‐like species can have large adverse effects on incidentally caught species with low‐fecundity, including elasmobranchs.
Analyses of observer programme data from the Fiji longline fishery from 2011 to 2014 were conducted to characterize the shark and ray catch composition and identify factors that significantly explained standardized catch rates. Catch data were fitted to generalized linear models to identify potentially significant explanatory variables.
With a nominal catch rate of 0.610 elasmobranchs per 1000 hooks, a total of 27 species of elasmobranchs were captured, 48% of which are categorized as Threatened under the IUCN Red List. Sharks and rays made up 2.4% and 1.4%, respectively, of total fish catch. Blue sharks and pelagic stingrays accounted for 51% and 99% of caught sharks and rays, respectively.
There was near elimination of ‘shark lines’, branchlines set at or near the sea surface via attachment directly to floats, after 2011.
Of caught elasmobranchs, 35% were finned, 11% had the entire carcass retained, and the remainder was released alive or discarded dead. Finning of elasmobranchs listed in CITES Appendix II was not observed in 2014.
There were significantly higher standardized shark and ray catch rates on narrower J‐shaped hooks than on wider circle hooks. Based on findings from previous studies on single factor effects of hook width and shape, the smaller minimum width of the J‐shaped hooks may have caused the higher shark and ray catch rates. For sharks, the effect of hook width may have exceeded the effect of hook shape, where small increases in shark catch rates have been observed on circle vs J‐shaped hooks.
Shark and ray standardized catch rates were lowest in the latter half of the year. Focusing effort during the second half of the year could reduce elasmobranch catch rates.
Copyright © 2016 John Wiley & Sons, Ltd.

Full text

Elasmobranch captures in the Fijian pelagic longline fishery
SUSANNA PIOVANO
a,
*and ERIC GILMAN
b
a
The University of the South Pacific, Suva, Fiji
b
Hawaii Pacific University, Honolulu, USA
ABSTRACT
1. Pelagic longline fisheries for relatively fecund tuna and tuna-like species can have large adverse effects on
incidentally caught species with low-fecundity, including elasmobranchs.
2. Analyses of observer programme data from the Fiji longline fishery from 2011 to 2014 were conducted to
characterize the shark and ray catch composition and identify factors that significantly explained standardized
catch rates. Catch data were fitted to generalized linear models to identify potentially significant explanatory
variables.
3. With a nominal catch rate of 0.610 elasmobranchs per 1000 hooks, a total of 27 species of elasmobranchs were
captured, 48% of which are categorized as Threatened under the IUCN Red List. Sharks and rays made up 2.4%
and 1.4%, respectively, of total fish catch. Blue sharks and pelagic stingrays accounted for 51% and 99% of caught
sharks and rays, respectively.
4. There was near elimination of ‘shark lines’, branchlines set at or near the sea surface via attachment directly to
floats, after 2011.
5. Of caught elasmobranchs, 35% were finned, 11% had the entire carcass retained, and the remainder was
released alive or discarded dead. Finning of elasmobranchs listed in CITES Appendix II was not observed in 2014.
6. There were significantly higher standardized shark and ray catch rates on narrower J-shaped hooks than on
wider circle hooks. Based on findings from previous studies on single factor effects of hook width and shape, the
smaller minimum width of the J-shaped hooks may have caused the higher shark and ray catch rates. For sharks,
the effect of hook width may have exceeded the effect of hook shape, where small increases in shark catch rates
have been observed on circle vs J-shaped hooks.
7. Shark and ray standardized catch rates were lowest in the latter half of the year. Focusing effort during the
second half of the year could reduce elasmobranch catch rates.
Copyright #2016 John Wiley & Sons, Ltd.
Received 19 November 2015; Revised 04 March 2016; Accepted 25 March 2016
KEY WORDS: conservation evaluation; endangered species; fish; fishing; ocean; protected species
INTRODUCTION
Mortality in pelagic fisheries directly impacts both
market and non-market species, and can have
broad effects on community and ecosystem
structure, processes and stability (Goñi, 1998;
Stevens et al., 2000; Piovano et al., 2009, 2010;
*Correspondence to: Susanna Piovano, The University of the South Pacific, School of Biological and Chemical Sciences, Laucala campus, private mail
bag, Suva, Fiji. Email: susanna.piovano@usp.ac.fj
Copyright #2016 John Wiley & Sons, Ltd.
AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS
Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)
Published online in Wiley Online Library
(wileyonlinelibrary.com). DOI: 10.1002/aqc.2666

Gilman et al., 2013a, b; Polovina and
Woodworth-Jefcoats, 2013). Fisheries that target
species with r-selected life-history characteristics,
including high fecundity, fast growth, and high
natural mortality rates, such as tuna and tuna-like
species (Scombridae), can have strong effects on
incidentally caught species with k-selected
life-history strategies, including low fecundity and
slow growth, such as elasmobranchs (Dulvy et al.,
2008; Gilman, 2011; Croll et al., 2015). As a result
of their life-history characteristics and behaviours
such as forming aggregations for mating and
pupping and at nursery grounds, elasmobranchs
and other k-selected species have low resistance
and resilience to even low levels of anthropogenic
sources of mortality (Casey and Myers, 1998;
Musick, 1999; Hall et al., 2000; Stevens et al.,
2000; Dulvy et al., 2008). Longline fishing
mortality affects the abundance of pelagic sharks
much more strongly than most other pelagic apex
predator species, where even moderate fishing
mortality rates can trigger large population
declines for some species (Musick et al., 2000;
Kitchell et al., 2002).
Some species of elasmobranchs captured in
pelagic longline fisheries are at risk of global
extinction, and some populations are at risk of
extirpation (Dulvy et al., 2014; IUCN, 2015).
There has been increasing concern in recent
decades over the sustainability of elasmobranch
mortality rates in pelagic longline fisheries, over
the broad, community- and ecosystem-level effects
from declines in abundance of species and sizes of
elasmobranchs selectively caught by pelagic
longline fisheries, as well as over the adverse
socio-economic effects on longline fisheries from
shark interactions (Musick et al., 2000; Stevens
et al., 2000; Ward and Myers, 2005; Clarke et al.,
2006, 2011, 2013, 2014; Dulvy et al., 2008; Ferretti
et al., 2008, 2010; Gilman et al., 2008a, 2012;
Mandelman et al., 2008; Cortes et al., 2010; Worm
et al., 2013). Longline fishing mortality of some
elasmobranch species has the capacity to be
sustainably managed if robust harvest strategies
were adopted and there was high compliance with
harvest controls (Walker, 1998; Musick et al., 2000).
Mitigating fishing mortality of incidentally
caught species that are relatively vulnerable to
extinction owing to their life-history characteristics
and susceptibility to capture and mortality in
fisheries, which is one element of ecosystem-based
fisheries management, has received substantial
international attention since the late 1990s (Clarke
et al., 2014; Gilman et al., 2014). A range of
effective and commercially viable methods to
mitigate problematic pelagic longline bycatch has
been developed, although there has been mixed
progress in uptake of these best practices (Gilman,
2011; Piovano et al., 2012; Gilman et al., 2014).
With increasing pelagic fishing catch and effort
since the early 1950s, biomass and exploitation
rate limit reference points of some stocks of main
market species of tunas have been exceeded
(Williams and Terawasi, 2014; ISSF, 2015). While
the observed declines in abundance of highly
fecund, broadcast spawning, market species are
unlikely to result in irreparable harm or loss of
populations, longline fisheries may cause broader
protracted or permanent changes to the structure
and functioning of pelagic ecosystems (Myers
et al., 1999; Essington, 2010; Gilman et al.,
2013a). There is increasing understanding of
community- and ecosystem-level effects of the
selective removals of pelagic apex predators by
pelagic longline fisheries, largely from species- and
more recently size-based ecosystem trophic
interaction models and some empirical studies
(Cox et al., 2002; Kitchell et al., 2002; Hinke
et al., 2004; Polovina et al., 2009; Polovina and
Woodworth-Jefcoats, 2013). Collateral, indirect
effects of pelagic longline and other tuna fisheries
include, for example, altered pelagic trophic
structure and processes, where the selective
removal of older age classes of a subset of species
of a pelagic ecosystem apex predator guild has
cascading effects on the pelagic ecosystem food
web. For example, pelagic longline selective
removal of apex predators has resulted in a
top-down trophic effect by releasing pressure and
increasing abundance of mid-trophic level species,
altering the ecosystem size structure with a decline
in abundance of large-sized species of fish and
increase in abundance of smaller-sized species, and
possibly altering the length–frequency distribution
of populations subject to fishing mortality (Ward
and Myers, 2005; Gilman et al., 2012). The
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

selective removal of some species from the pelagic
ecosystem apex predators guild may alter the
relative abundance of species within this trophic
level, while the selective removal of large
individuals could be a driver favouring genotypes
for maturation at an earlier age, smaller-size and
slower-growth, potentially altering the
length–frequency distributions (size structure) and
evolutionary characteristics of affected populations
(Stevens et al., 2000; Ward and Myers, 2005; Zhou
et al., 2010; Gilman et al., 2012).
Previous studies that have assessed elasmobranch
catches in longline fisheries have largely been from
developed countries, with very few papers focusing
or including the Pacific Small Island Developing
States (Gilman et al., 2008b, 2015; Bromhead
et al., 2012; Godin et al., 2012; Favaro and Cote,
2015). Fiji, in the south-west Pacific Ocean, is
composed of about 300 islands and has an exclusive
economic zone (EEZ) of about 1 290 000 km
2
.Its
national commercial fishery focuses on tunas
captured by pelagic longline gear. The domestic
industrial tuna longline fleet developed in the 1990s
and in these last 20 years has targeted primarily
albacore tuna (Gillett, 2007; Fiji Offshore Fisheries
Division, 2015). In 2014, there were 60 longline
vessels licensed to fish in the Fiji EEZ, of which 50
were Fiji-flagged, and an additional 45 Fiji-flagged
vessels were authorized to fish exclusively on the
high seas and in EEZs of other PacificIsland
States (Fiji Offshore Fisheries Division, 2015). In
2014, the Fiji national fleet landed 6703t of
albacore tuna (50% of total retained catch), 3558t
of yellowfin tuna (26%), 1560t of bigeye tuna
(12%), and 1667t of other market species (billfishes
and tuna-like species, 12%) (Fiji Offshore Fisheries
Division, 2015). The Fiji albacore tuna longline
fishery was certified according to the Marine
Stewardship Council standards on 13 December
2012. Between 1999 and 2005, an estimated 78–
90% of caught sharks were finned and their
carcasses discarded (SPC unpublished data cited in
Thomson, 2007).
The goal of this study was to assess the impact of
the Fijian longline fishery on elasmobranchs by
analysing the Fiji Observer Programme 2011–2014
dataset (1) to identify the groups of sharks
(Selachii) and rays (Batoidea) most heavily caught,
and (2) to identify potentially significant variables
influencing catch rates of Selachii and Batoidea.
Findings will help to improve the understanding of
elasmobranch longline fishing mortality in Pacific
Small Island Developing States.
METHODS
Data
Fiji Observer Programme (FOP) data for the Fiji
longline tuna fishery were analysed. The Fiji
longline observer programme dataset is subject to
government confidentiality restrictions for the
protection of confidential fisheries statistics. Third
parties require authorization from Fiji Department
of Fisheries to obtain access to data.
FOP data provided for this study by the Fiji
Department of Fisheries, Offshore Division,
covered 2367 longline sets, 85.80% targeting tunas,
0.08% targeting both tunas and swordfish, and
1.27% targeting both tunas and sharks. No
information on target species was recorded for the
remaining 12.85% of the sets. The study period,
based on availability of FOP data for the Fiji
longline fishery, was from January 2011 to
December 2014. During this period, the observer
coverage rate increased from 3.0% to 16.7% (Fiji
Offshore Fisheries Division, 2015). FOP adheres
to the Secretariat of the Pacific Community data
collection protocols for tuna fishery observer
programmes (SPC, 2011) and Fiji’s observers are
certified under the SPC/FFA PIRFO standards
(Fiji Offshore Fisheries Division, 2013).
Statistical analysis
Generalized linear models (GLMs) were used to
identify potentially significant variables influencing
catch rates of Selachii and Batoidea in longline
sets targeting only tunas (2031 sets). Only sets with
information for all variables selected for inclusion
as GLM terms were included in the study sample
(1679 sets). Explanatory variables considered for
inclusion in the model were the continuous
variable ‘number of hooks’(centring was done
before the analysis) and factors ‘type of hook’
(J-shaped hooks, including J and Japanese tuna
hooks; circle hooks; and sets employing a mix of
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

J-shaped and circle hooks in various proportions);
‘bait size’(weight was used for this variable, which
included two categories of small and large baits,
determined using the median of weights used per
set); ‘branchline distance’(the distance between
two consecutive branchlines was used; the variable
was made up of two categories of short and long
distance determined using median branchline
distance in a set); ‘year’(2011, 2012, 2013 and
2014); and ‘quarter’(four 3-month periods
categories were used: 1st quarter: January–March,
2nd quarter: April–June, 3rd quarter
July–September, 4th quarter: October–December).
The best fitting model was selected based on
analysis of Akaike’s Information Criterion (AIC),
where the model with the lowest AIC value and
the smallest difference in AIC values (ΔAIC) had
the best fit to the dataset. GLMs were run with R
statistical software version 3.2.0 (R Core Team,
2015) with packages doBy (Højsgaard and
Halekoh, 2014), pscl (Jackman, 2015) and MASS
(Venables and Ripley, 2002).
RESULTS
In total, 3859 elasmobranch captures were
recorded, with an overall nominal catch per unit
effort (CPUE) of 0.610 elasmobranchs per 1000
hooks (Table 1). Of the 3815 elasmobranchs
observed captured for which information on the
fate was recorded, 34.6% had fins retained and the
remaining carcass discarded, 10.9% had the entire
carcass retained, 45.8% were released alive, and
8.7% were discarded dead.
Selachii
Selachii constituted 2.4% of the total number of fish
captured and composed 62.6% of the overall
number of elasmobranchs caught. In total, 27
Table 1. Elasmobranchs capture per unit of effort (CPUE number of shark captures per 1000 hooks), separated for subclass, family (in alphabetical
order) and species (in alphabetical order)
Common English name Scientific name CPUE per 1000 hooks IUCN category
Batoidea
Dasyatidae Pelagic stingray Pteroplatytrigon violacea 0.2252 LC
Mobulidae Giant oceanic manta ray Manta birostris 0.0021 VU
Selachii
Alopiidae Pelagic thresher Alopias pelagicus 0.0022 VU
Bigeye thresher Alopias superciliosus 0.0081 VU
Thresher shark Alopias vulpinus 0.0003 VU
Carcharhinidae Silvertip shark Carcharhinus albimarginatus 0.0022 NT
Grey reef shark Carcharhinus amblyrhynchos 0.0013 NT
Bronze whaler Carcharhinus brachyurus 0.0100 NT
Silky shark Carcharhinus falciformis 0.0430 NT
Galapagos shark Carcharhinus galapagensis 0.0003 NT
Blacktip shark Carcharhinus limbatus 0.0027 NT
Oceanic whitetip shark Carcharhinus longimanus 0.0174 VU
Blacktip reef shark Carcharhinus melanopterus 0.0003 NT
Sandbar shark Carcharhinus plumbeus 0.0016 VU
Tiger shark Galeocerdo cuvier 0.0014 NT
Blue shark Prionace glauca 0.1932 NT
Whitetip reef shark Triaenodon obesus 0.0005 NT
Dalatiidae Kitefin shark Dalatias licha 0.0002 NT
Cookiecutter shark Isistius brasiliensis 0.0014 LC
Lamnidae Great white shark Carcharodon carcharias 0.0002 VU
Shortfin mako Isurus oxyrhinchus 0.0670 VU
Longfin mako Isurus paucus 0.0144 VU
Somniosidae Velvet dogfish Zameus squamulosus 0.0003
Sphyrnidae Scalloped hammerhead Sphyrna lewini 0.0030 EN
Great hammerhead Sphyrna mokarran 0.0019 EN
Smooth hammerhead Sphyrna zygaena 0.0024 EN
Triakidae Whiskery shark Galeorhinus galeus 0.0005 VU
IUCN category (LC = Least Concern, NT = Near Threatened, VU = Vulnerable, EN = Endangered) is provided for those species with adequate data
(IUCN, 2015).
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

species of Selachii were observed captured
(Table 1). Blue shark Prionace glauca was the
predominant Selachii captured (50.6% of Selachii).
A number of distributions were initially
considered to model the count data in a GLM
framework (Zuur et al., 2009): Poisson,
zero-altered Poisson (ZAP), negative binomial
(NB) and zero-altered negative binomial (ZANB).
The Poisson distribution is commonly used to
model count data, but initial model explorations
indicated that the observed counts were
zero-inflated. A hurdle model using a ZAP
distribution was then used, which substantially
improved the fit. Hurdle models are designed to
account for two different processes being
responsible for captures (versus non-capture) and
for the number of fish captured (i.e. a different
process is responsible for influencing the number
of captures). Owing to overdispersion, a NB
model was fitted, which further improved the fit
compared with the Poisson models. Finally a
hurdle model using a ZANB distribution was
applied, which resulted in a small but significant
additional increase in model fit (Table 2).
All four models were clearly distinguishable
based on ΔAIC values (Table 2). The ZANB
model best explained shark captures (Table 2).
ZANB is a hurdle model that models the
probability that a zero value (no capture) is
observed based on zeros (no capture of sharks on
the set) versus non-zeros (at least one capture of
sharks in a set). Probability of capture was
significantly influenced by quarter and type of
hooks (Table 3). The odds ratio was 0.7220 (95%
Table 3. Significant variables modelled with ZANB (with coefficient estimate, standard error SE, and probability P). (A) Zeros component (binomial distribution). (B) Count component
(truncated negative binomial distribution)
Selachii Batoidea
Zeros component Counts component Zeros component Counts component
Coefficient
estimate SE P
Coefficient
estimate SE P
Coefficient
estimate SE P
Coefficient
estimate SE P
Year 2013 1.5309 0.4995 0.002
Quarter 2nd quarter 0.2746 0.1216 0.024
3rd quarter 0.3257 0.1480 0.028 0.5550 0.1622 <0.001 0.6988 0.1457 <0.001 0.6988 0.1457 <0.001
4th quarter 0.5379 0.1524 <0.001 0.3667 0.1720 0.033 0.9240 0.1652 <0.001 0.8074 0.1681 <0.001
Type of hooks J 0.4127 0.1356 0.002 1.3645 0.1455 <0.001 0.7393 0.1234 <0.001
Mix 0.6714 0.1890 <0.001 0.6334 0.1686 <0.001
Number of hooks 0.0003 <0.001 <0.001 0.0002 0.0001 0.018 0.0003 0.0001 0.011
Bait size Small bait 0.3246 0.1215 0.008 0.4778 0.1157 <0.001
Branchline
distance Short 0.4831 0.1162 <0.001 0.2511 0.1118 0.025
Table 2. Model comparison using Akaike’s Information Criterion
(AIC). Models compared used Poisson distribution (Poisson),
zero-altered Poisson distribution (ZAP), negative binomial
distribution (NB) and zero-altered negative binomial (ZANB).
AIC ΔAIC
Selachii
ZANB 4700.03 0.00
NB 4707.03 7.00
ZAP 4978.84 278.81
Poisson 5435.96 735.93
Batoidea
ZANB 3542.35 0.00
NB 3570.47 28.12
ZAP 3570.57 28.22
Poisson 3887.14 344.79
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

CI: 0.5402–0.9650) in the 3rd quarter of the year
and 0.5840 (95% CI: 0.4332–0.7872) in the 4th
quarter, compared with the 1st quarter of the year,
which was used as the reference category for this
factor. The odds ratio of a capture in sets using
only J-shaped hooks was 1.5109 (95% CI: 1.1584–
1.9708) relative to sets using only circle hooks,
and 1.9569 (95% CI: 1.3511–2.8344) for sets
using a mix of J-shaped and circle hooks, again
relative to sets with 100% circle hooks. The
second part of ZANB modelled the non-zero
observations by excluding the zero values with a
truncated negative binomial distribution. The
number of captures was significantly influenced
by factors year and quarter, and by the
covariate number of hooks (Table 3). In detail,
the odds ratio for the number of captures in
2013 was 4.6221 (95% CI: 1.7365–12.3028) that
in 2011. With respect to quarter, the odds ratio
for the number of sharks captured in the 3rd
quarter was 0.5741 (95% CI: 0.4177–0.7889)
that in the 1st quarter of the year, and in the
4th quarter the odds ratio was 0.6930 (95% CI:
0.4947–0.9709) that in the 1st quarter. The odds
ratio for the number of sharks captured also
increased with increasing number of hooks per
set (1.0003, 95% CI: 1.0001–1.0004).
Shark species in CITES appendix II
Captures of oceanic whitetip shark Carcharhinus
longimanus
When using the full dataset, which includes
longline sets targeting both tunas and sharks, for
the period 2011–2012, all 17 oceanic whitetips
captured were discarded after finning (a practice
in which fins are removed and retained, while
the rest of the body is discarded at sea). In 2013,
62 oceanic whitetips were captured, of which for
13% the entire fish was retained, 60% were
discarded after finning, 8% were discarded dead
and 19% were released alive. Of the 30 whitetip
sharks captured in 2014, for 7% the entire fish
was retained, 3% were discarded after finning,
27% were discarded dead and 63% released alive
(Figure 1).
Captures of hammerhead sharks Sphyrna lewini,
Sphyrna mokarran and Sphyrna zygaena
When using the full dataset, 46 hammerhead
sharks were captured in the period 2011–2014,
87% of which were caught during 2013. The
majority of hammerheads (80%) were discarded
after finning (Figure 2). In 2014 only two
hammerheads were observed captured, of which
one was retained and the other released alive.
Captures of great white shark Carcharodon
carcharias
A single specimen was captured in 2013, which was
finned.
Batoidea
Batoidea constituted 1.4% of the total number of
fish captured and 37.4% of the total number of
captured elasmobranchs. Pelagic stingrays
Pteroplatytrigon violacea made up 98.7% of the
rays (Table 1).
Figure 2. Fate of hammerhead sharks Sphyrna lewini,Sphyrna
mokarran and Sphyrna zygaena after capture in the longline gear
(cumulative data expressed as percentage per year, N = 46).
Figure 1. Fate of oceanic whitetip sharks Carcharhinus longimanus after
capture in the longline gear (expressed as percentage per year, N = 109).
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

As was done for the Selachii, a number of
distributions were initially considered to model the
Batoidea count data in a GLM framework:
Poisson, ZAP, NB and ZANB.
Models were clearly distinguishable based on
ΔAIC values except ZAP and NB (Table 2), for
which ΔAIC was 0.10. The best fitting model to
explain rays captures was ZANB, which scored
the lowest AIC. As explained previously in the
Selachii section, ZANB is a hurdle model that
allows the separation of variables influencing the
probability of a capture (using the category 0 for
no capture and the category 1 for at least one
capture recorded in a set) from those that
influence the number of captures (where only
observation of captures are used, and no capture
observations are excluded). Probability of capture
was significantly influenced by several factors
(quarter, type of hooks, bait size, and branchline
distance) and by the continuous variable number
of hooks (Table 3). The odds ratio of a capture in
the 3rd quarter was 0.2503 (95% CI: 0.1807–
0.3466), compared with the 1st quarter, while the
odds ratio of capture in the 4th quarter was 0.3969
(95% CI: 0.2872–0.5487) relative to the 1st
quarter. The odds ratio of capture on J-shaped
hooks was 3.9137 (95% CI: 2.9427–5.2053) relative
to sets using only circle hooks. The odds ratio for
small bait was 1.3834 (95% CI: 1.0903–1.7554),
and that of short branchlines distance (a proxy to
indicate shallower hook soak depth) was 0.6168
(95% CI: 0.4912–0.7746). The odds ratio of a
capture with an increasing number of hooks per
set was 1.0002 (95% CI: 1.00004–1.0004). The
same factors (quarter, type of hook, bait size, and
branchline distance) and the continuous variable
number of hooks per set also significantly
influenced the number of rays captured (Table 3).
The odds ratio of the number of rays captured was
0.7599 (95% CI: 0.5988–0.9644) in the 2nd quarter
of the year, 0.4972 (95% CI: 0.3737–0.6616) in the
3rd quarter, and 0.4460 (95% CI: 0.3208–0.6200)
in the 4th quarter, relative to the 1st quarter. For
the type of hook, the odds ratio of number of
captures on sets with 100% J-shaped hooks was
2.0945 (95% CI: 1.6447–2.6674) relative to sets
using only circle hooks, and was 1.8840 (95% CI:
1.3538–2.6218) for sets using a mix of circle and
J-shaped hooks relative to sets using only circle
hooks. The odds ratio for small bait size was
1.6122 (95% CI: 1.2805–2.0227), and 0.7780 (95%
CI: 0.6249–0.9686) for short branchline distance.
The odds ratio for the number of rays captured
also increased with increasing number of hooks
per set (1.0003, 95% CI: 1.0001–1.0005).
Ray species in CITES appendix II
Captures of manta ray Manta birostris
Using the full dataset, which includes longline sets
targeting both tunas and sharks, 13 manta rays
were captured in the period 2011–2014, of which
77% were captured during 2014. 39% of manta
rays were finned with the remaining carcass
discarded (Figure 3).
DISCUSSION
On-board observers recorded the use of ‘shark lines’
in more than half of observed sets in 2011 (59% of
sets monitored), while in the next 2 years it
dropped to about 1% (0.8% in 2012 and 1.1% in
2013). In 2014 there were no records of shark line
use. This rapid decline in shark line use was likely
a response to a national ban on shark lines that
came into effect in 2012 (Fiji Offshore Division,
2013). This preceded the adoption in 2014 of a
replacement conservation and management
measure (CMM) on sharks by the Western and
Central Pacific Fisheries Commission (WCPFC)
that allowed parties, including Fiji, to either ban
the use of wire leaders on branchlines or the use of
shark lines (WCPFC, 2014). Shark lines place
baited hooks near the surface by attaching
branchlines directly to floats instead of to the
Figure 3. Fate of manta ray Manta birostris after capture in the longline
gear (expressed as percentage, N = 13).
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

mainline, and large pieces of tuna or incidental
catch are often used for bait. Catch rates of some
shark species on shark lines have been found to be
significantly higher and haulback survival rates
significantly lower than on hooks between floats
(Bromhead et al., 2012; Caneco et al., 2014;
Gilman and Hall, 2015). Banning shark lines
effectively reduces shark catch rates and does not
pose a conflict with by-catch mitigation of other
taxonomic groups of conservation concern
(Gilman et al., 2016).
Hook type had a significant effect on capture
probability for both shark and ray standardized
catch rate models. The odds of shark capture
on sets that used only J-shaped hooks were
about 1.5 times greater than on sets that used
only circle hooks. Sets using only J-shaped
hooks had even greater odds of capturing rays,
estimated to be about 4 times higher than sets
using only circle hooks. There are potential
confounding factors in this variable, because
several sizes of hooks with different minimum
widths were deployed, even within the same set,
and because the J-shaped hook category
included both Japanese tuna hooks and J hooks,
whichbothhaveapointdirectedawayfromthe
shank, but have differences in other design
elements (e.g. Japanese tuna hooks have a bend
in the upper portion of the shank, J hooks have
a straight shank). Hook shape and minimum
widthhavebeendocumentedtosignificantly
affect shark and ray catch rates (reviewed in
Gilman and Hall, 2015; Gilman et al., 2016).
Most previous studies have found higher shark
catch rates on circle hooks than on J-shaped
hooks, and lower ray catch rates the wider the
hook (Vega and Licandeo, 2009; Ward et al.,
2009; Piovano et al., 2010; Curran and Beverly,
2012; Serafy et al., 2012; Andraka et al., 2013).
However, as in the current study, most of these
past studies had simultaneous variability in
hook shape and width, leader material and
other potentially significant explanatory
variables. Circle hooks tend to result in lower
rates of foul hooking and tend to catch in the
corner of the mouth, while J-shaped hooks tend
to result in deep hooking. Owing to the
prevalent hooking location, when non-wire
leaders are used, J-shaped hooks are expected to
result in lower shark catch rates than circle
hooks, as deeply-hooked sharks are able to bite
through the non-wire leader, while mouth-
hooked sharks cannot escape by biting through
the leader. For species that tend to be caught
by ingesting a baited hook, hook size affects
susceptibility to capture, as the larger the hook,
the lower the probability that an organism can
fititinitsmouth(Yokotaet al., 2012).
Type of hooks, bait size and branchline distance
influenced the number of rays captured but not
that of sharks. In sets using J-shaped hooks (either
all hooks were J-shaped or a portion of the hooks
were J-shaped), the use of small bait resulted in an
increased capture rate of rays, while short
branchline distance (<17 m) (an indicator that the
gear soaked at a relatively shallow soak depth),
decreased the odds of ray capture. While no
significant interaction among these factors was
observed in the current study, J-shaped hooks and
small-sized bait were found to be associated with a
higher capture rate of pelagic stingrays in a
longline fishery in the Mediterranean Sea (Piovano
et al., 2010). In accordance with a WCPFC CMM
designed to reduce sea turtle bycatch (WCPFC,
2008), Fiji Fisheries Offshore Division has
required the use of dehookers for turtles hooked in
the mouth or foul hooked in the body, and line-
cutters when hooks are ingested deeply (Fiji
Offshore Division, 2013). The measure also
prescribes sea turtle bycatch mitigation measures
by shallow-set longline fisheries targeting
swordfish (either use ‘large’circle hooks, fish bait,
or other measure approved by the Commission).
Even though this requirement was not prescribed
for use by longline fisheries targeting tunas, the
Fiji Fisheries Offshore Division has encouraged
the use of circle hooks by the Fiji longline fishery
in order to contribute to reducing sea turtle
bycatch (Fiji Offshore Division, 2013, 2015).
The variable number of hooks per set was a
significant term in the standardized shark and ray
catch rate models. The number of hooks deployed
per set is a measure of relative longline fishing
effort routinely included in catch rate
standardization models. Based on the observed
effect of this variable, a reduction in the number
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

of vessels and/or a reduction in the number of
larger vessels, which are capable of deploying a
larger number of hooks per set and to fish in less
favourable weather conditions than smaller
vessels, would reduce shark and ray catch levels.
The number of Fiji-licensed longline vessels
decreased from 121 in 2011 to 105 in 2014, and
during this same period the number of longline
vessels longer than 31 m decreased from 59% to
45% (Fiji Offshore Fisheries Division, 2015).
The variable season also significantly influenced
both shark and ray standardized catch rates. In
the 3rd and 4th quarters there were lower
standardized catch rates, which was a larger effect
for sharks than rays. Changes in El Niño Southern
Oscillation (ENSO) phases and other large-scale
climate variability such as Pacific Decadal
Oscillation phases which occurred during the study
period may have resulted in inter-annual and
longer-scale changes in the relative abundance of
shark species within the fisherys fishing grounds,
influencing catch rates (Lehodey, 2001; Lehodey
et al., 2015). For example, the onset of an El Niño
phase in 2013, and the observed 2.5 times higher
nominal shark catch rate in the Fiji fishery in 2013
relative to 2012, suggests that ENSO phase affects
shark relative abundance and catch rates.
Unfortunately, any correlation between capture
rates and relative abundance of sharks due to
responses to ENSO or other cyclical climate
variability is difficult to test owing to a lack of
information on shark relative abundance.
Global levels of reported landings of sharks and
rays has increased steadily from 1950, peaking in
2003, followed by a small (15%) decline (Davidson
et al., 2015). The majority of elasmobranchs are
long-lived, with late age-at-maturity and low
fecundity. This slow life-history strategy makes
sharks less able to cope with direct or indirect
mortality due to fishing activities (Dulvy et al.,
2008). As a result, several shark species have been
classified as Near Threatened or Threatened
according to IUCN categories (IUCN, 2015). Of
the 27 species of sharks observed captured in the
Fiji fishery, 41% are Near Threatened under the
IUCN Red List, and 48% are categorized as
Threatened (either Vulnerable or Endangered)
(Table 1).
The oceanic whitetip shark (Carcharhinus
longimanus), scalloped hammerhead shark
(Sphyrna lewini), great hammerhead shark
(Sphyrna mokarran), smooth hammerhead shark
(Sphyrna zygaena), and manta rays (Manta spp.)
were included in CITES Appendix II in 2014.
1
Fiji
is a member of the Western and Central Pacific
Fisheries Commission, which has adopted a
binding measure that bans the retention of oceanic
whitetip sharks (WCPFC, 2011). Data collected by
on-board observers show that even though the
fishery has not fully complied with the measure, a
clear improvement was detected from 2011 to
2014: the percentage of oceanic whitetips released
alive increased from 0% in 2011 to 63% in 2014
(Figure 1). Also, while 100% of oceanic whitetips
were finned in 2011 and 2012, and 60% were
finned in 2013, only 3% were finned in 2014. Large
reductions in fishing mortality rates may be
needed to address the poor conservation status of
some shark populations (Casey and Myers, 1998).
For example, a reduction in fishing mortality rate
of about 40% and 60% was proposed by Myers
and Worm (2005) as needed to ensure the survival
of oceanic whitetip and scalloped hammerhead
sharks in the Atlantic Ocean.
Capture rates of hammerhead sharks were highly
variable by year during the 4 year time series. Most
were captured in 2013. Most caught hammerheads
were finned (80%). In 2014 only two hammerheads
were captured, one was retained, and none were
finned (Figure 2). Manta rays also exhibited a
significant difference in captures by year, with the
highest nominal catch rate occurring in 2014.
Altogether, more than half the manta rays
captured were either finned (39%) or retained
(30%) (Figure 3). Even though the total mortality
rate of manta rays recorded for the Fiji longline
fishery was high, the number caught was low. In
2014 33% of caught manta rays were released alive
and 10% discarded dead (and thus not retained
nor finned). In Fiji, the authority for marine
species listed in Appendix II of CITES is the
Department of Fisheries. Compliance with the
CITES Appendix II listing of hammerheads and
1
Decision of 12/06/2013, to come into effect on 14/09/2014 (see
checklist.cites.org)
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

manta rays (Mobula spp.) will likely result in further
reductions in finning of these species.
The two elasmobranch species with the highest
capture rate in the Fiji longline fishery were
pelagic stingray and blue shark. Neither species is
categorized as Threatened by IUCN (the former is
listed as LC, the latter as NT; IUCN, 2015). Their
capture is common in pelagic longline fisheries
throughout the Pacific, Atlantic and Indian
Oceans, as well as in the Mediterranean Sea
(Domingo et al., 2005; Gilman et al., 2008b;
Piovano et al., 2009, 2010). They are considered
less sensitive to fishing mortality due to their
relatively high fecundity rate and resilience
(Cortes, 2002), but an increase in their capture
rates in the last decade has raised concern
(Davidson et al., 2015). In Fiji, blue shark was
already the most common elasmobranch captured
by the domestic longline fleet more than 15 years
ago, while at that time pelagic stingray was not
even in the top five elasmobranch species by
number of captures (Swamy, 1999). The increase
in pelagic stingray captures might be the result of
a higher observer coverage rate and improvements
in observer data recording as bycatch became an
increasingly prominent issue. Or there may have
been an increase in pelagic stingray local
abundance, which in the tropical Pacific Ocean
may have resulted from a decline in predation
caused by reductions in local abundance of apex
predator species that prey on pelagic stingrays,
and a decline in competition from reduced local
abundance of sympatric competitors (Ward and
Myers, 2005; Baum and Worm, 2009).
Proper data collection and stock assessment are
the most useful tools to identify the pressure that
shark populations can sustain. Increased on-
board observer coverage rates and improvements
in data collection protocols for pelagic longline
fleets is necessary to support more robust
statistical analyses, including to improve the
accuracy and precision of elasmobranch catch
and survival rate estimates. This in turn would
enable improved accuracy of assessments of the
population-level effects of fishing mortality on
pelagic sharks and rays. A key improvement
needed in longline observer data collection is to
accurately identify all caught elasmobranchs to
species level. As our knowledge of basic
biological information for most elasmobranch
stocks is severely deficient (Dulvy et al., 2014;
Croll et al., 2015), increased on-board observer
coverage rates would also contribute to filling
these critical information gaps, for example, by
documenting sex, maturity, and reproductive
stage of both rare and common elasmobranch
species captured in longline fisheries.
It has been argued that management of activities
to protect sharks should focus on identifying levels
of sustainable catch, rather than prohibiting shark
fishing (Clarke et al., 2013). Longline fishing
mortality of some elasmobranch stocks has the
capacity to be sustainably managed if robust
harvest strategies are adopted and high
compliance with harvest control rules, one element
of a harvest strategy, occurs (Walker, 1998;
Musick et al., 2000). However, there are deficits in
fundamental biological information for most
elasmobranch stocks (Walker, 1998; Shotton,
1999; Musick et al., 2000). There is also high
uncertainty in estimates of fishing mortality levels,
in particular of rare, but also of common
elasmobranch stocks caught in pelagic longline
fisheries (Worm et al., 2013; Clarke et al., 2006,
2014; Gilman et al., 2016). These information gaps
need to be filled in order for management systems
to develop harvest strategies with high certainty of
achieving sustainable exploitation.
ACKNOWLEDGEMENTS
We are greatful Fiji Fisheries Department Director
Aisake Batibasaga and Offshore Fisheries Division
Principal Fisheries Officer Anare Raiwalui for
supporting this project and giving access to the
Fiji Observer Programme dataset, and Offshore
Fisheries Division Senior Fisheries Officer Netani
Tavaga for providing the dataset. We
acknowledge and thank Fiji longline observers for
their data collection. Conversations with Yonat
Swimmer were instrumental in drafting this
research project. This project was endorsed by Fiji
Fisheries Department and funded by US NOAA
NMFS Pacific Islands Fisheries Science Center
(WE-133F-14-SE-3230). Insightful comments
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

provided by two anonymous peer reviewers and by
the editor John Baxter greatly improved the
manuscript.
REFERENCES
Andraka S, Mug M, Hall M, Pons M, Pacheco L, Parrales M,
Rendon L, Parga M, Mituhasi T, Segura A, et al. 2013.
Circle hooks: developing better fishing practices in the
artisanal longline fisheries of the Eastern Pacific Ocean.
Biological Conservation 160: 214–223.
Baum JK, Worm B. 2009. Cascading top-down effects of
changing oceanic predator abundances. Journal of Animal
Ecology 78: 699–714.
Bromhead D, Clarke S, Hoyle S, Muller B, Sharples P,
Harley S. 2012. Identification of factors influencing shark
catch and mortality in the Marshall Islands tuna longline
fishery and management implications. Journal of Fish
Biology 80: 1870–1894.
Caneco B, Donovan C, Harley S. 2014. Analysis of WCPO
Longline Observer Data to Determine Factors Impacting
Catchability and Condition on Retrieval of Oceanic White-
Tip, Silky, Blue, and Thresher Sharks. In WCPFC-SC10–
2014/EB-WP-01, Federated States of Micronesia: Western
and Central Pacific Fisheries Commission, Kolonia.
Casey J, Myers R. 1998. Near extinction of a large, widely
distributed fish. Science 281: 690–691.
Clarke S, McAllister M, Milner-Gulland E, Kirkwood G,
Michielsens C, Agnew D, Pikitch E, Nakano H, Shivji M.
2006. Global estimates of shark catches using trade records
from commercial markets. Ecology Letters 9: 1115–1126.
Clarke S, Harley S, Hoyle S, Rice J. 2011. An Indicator-based
Analysis of Key Shark Species based on Data Held by SPC-
OFP. In WCPFC-SC7–2011/EB-WP-01, Federated States
of Micronesia: Western and Central Pacific Fisheries
Commission, Kolonia.
Clarke S, Harley S, Hoyle S, Rice J. 2013. Population trends in
Pacific oceanic sharks and the utility of regulations on shark
finning. Conservation Biology 27: 197–209.
Clarke S, Sato M, Small C, Sullivan B, Inoue Y, Ochi D. 2014.
Bycatch in Longline Fisheries for Tuna and Tuna-like
Species: A Global Review of Status and Mitigation
Measures. In FAO Fisheries and Aquaculture Technical
Paper 588, United Nations, Rome: Food and Agriculture
Organization of the.
Cortes E. 2002. Incorporating uncertainty into demographic
modeling: application to shark populations and their
conservation. Conservation Biology 16: 1048–1062.
Cortes E, Arocha F, Beerkircher L, Carvalho F, Domingo A,
Heupel M, Holtzhausen H, Santos M, Ribera M,
Simpfendorfer C. 2010. Ecological risk assessment of
pelagic sharks caught in Atlantic pelagic longline fisheries.
Aquatic Living Resources 23:25–34.
Cox S, Essington T, Kitchell J, Martell S, Walters C, Boggs C,
Kaplan I. 2002. Reconstructing ecosystem dynamics in the
central Pacific Ocean, 1952–1998 II. A preliminary
assessment of the trophic impacts of fishing and effects on
tuna dynamics. Canadian Journal of Fisheries and Aquatic
Sciences 59: 1736–1747.
Croll DA, Dewar H, Dulvy NK, Fernando D, Francis MP,
Galván-Magaña F, Hall M, Heinrichs S, Marshall A,
Mccauley D, et al. 2015. Vulnerabilities and fisheries
impacts: the uncertain future of manta and devil rays.
Aquatic Conservation: Marine and Freshwater Ecosystems.
DOI: 10.1002/aqc.2591
Curran D, Beverly S. 2012. Effects of 16/0 circle hooks on
pelagic fish catches in three South Pacific albacore longline
fisheries. Bulletin of Marine Science 88: 485–497.
Davidson LNK, Krawchuk MA, Dulvy NK. 2015. Why have
global shark and ray landings declined: improved
management or overfishing? Fish and Fisheries.
DOI:10.1111/faf.12119.
Domingo A, Menni RC, Forselledo R. 2005. Bycatch of the
pelagic ray Dasyatis violacea in Uruguayan longline
fisheries and aspects of distribution in the southwestern
Atlantic. Scientia Marina 69: 161–166.
Dulvy N, Baum J, Clarke S, Compagno L, Cortes E,
Domingo A, Fordham S, Fowler S, Malcom F, Gibson
C, et al. 2008. You can swim but you cant hide: the
global status and conservation of oceanic pelagic sharks
and rays. Aquatic Conservation: Marine and Freshwater
Ecosystems 482: 459–482.
Dulvy N, Fowler S, Musick J, Cavanagh RD, Kyne PM,
Harrison LR, Carlson JK, Davisdson LNK, Fordham
S, Francis MP, et al. 2014. Extinction risk and
conservation of the world’ssharksandrays.eLife 3:
e0059.
Essington T. 2010. Trophic cascades in open ocean ecosystems.
In Trophic Cascades. Predators, Prey and the Changing
Dynamics of Nature, Terborgh J, Estes J (eds). Island Press:
Washington DC; 91–106.
Favaro B, Cote I. 2015. Do by-catch reduction devices in
longline fisheries reduce capture of sharks and rays? A
global meta-analysis. Fish and Fisheries 16: 300–309.
Ferretti F, Myers RA, Serena F, Lotze H. 2008. Loss of large
predatory sharks from the Mediterranean Sea. Conservation
Biology 22: 952–964.
Ferretti F, Worm B, Britten G, Heithaus M, Lotze H. 2010.
Patterns and ecosystem consequences of shark declines in
the ocean. Ecology Letters 13: 1055–1071.
Fiji Offshore Fisheries Division, 2013. Annual scientific report
to the Western and Central Pacific Fisheries Commission.
Part 1: information on fisheries, research and statistics for
2012. Fiji. Offshore Fisheries Division, Fisheries
Department, Ministry of Fisheries and Forest. WCPFC-
SC9-AR/CCM-07.
Fiji Offshore Fisheries Division, 2015. Annual scientific report
to the Western and Central Pacific Fisheries Commission.
Part 1: information on fisheries, research and statistics for
2014. Fiji. Offshore Fisheries Division, Fisheries
Department, Ministry of Fisheries and Forest. WCPFC-
SC11-AR/CCM-07.
Gillett R. 2007. A short history of industrial fishing in the
Pacific Islands. FAO RAP Publication 2007/22.
Gilman E. 2011. Bycatch governance and best practice
mitigation technology in global tuna fisheries. Marine
Policy 35: 590–609.
Gilman E, Hall M. 2015. Potentially Significant Variables
Explaining Bycatch and Survival Rates and Alternative
Data Collection Protocols to Harmonize Tuna RFMOs’
Pelagic Longline Observer Programmes. In Appendix 1 to
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

WCPFC-SC11–2015/EB-IP-05, Federated States of
Micronesia: Western and Central Pacific Fisheries
Commission, Kolonia, Pohnpei.
Gilman E, Kobayashi D, Chaloupka M. 2008b. Reducing
seabird bycatch in the Hawaii longline tuna fishery.
Endangered Species Research 5: 309–323.
Gilman E, Clarke S, Brothers N, Alfaro-Shigueto J,
Mandelman J, Mangel J, Peterson S, Piovano S, Thomson
N, Dalzell P, et al. 2008a. Shark interactions in pelagic
longline fisheries. Marine Policy 32:1–18.
Gilman E, Chaloupka M, Read A, Dalzell P, Holetschek J,
Curtice C. 2012. Hawaii longline tuna fishery temporal
trends in standardized catch rates and length
distributions and effects on pelagic and seamount
ecosystems. Aquatic Conservation: Marine and
Freshwater Ecosystems 22: 446–488.
Gilman E, Owens T, Kraft T. 2013a. Ecological risk assessment
of the Marshall Islands longline tuna fishery. Marine Policy
44: 239–255.
Gilman E, Suuronen P, Hall M, Kennelly S. 2013b. Causes and
methods to estimate cryptic sources of fishing mortality.
Journal of Fish Biology 83: 766–803.
Gilman E, Passfield K, Nakamura K. 2014. Performance of
regional fisheries management organizations: ecosystem-
based governance of bycatch and discards. Fish and
Fisheries 15: 327–351.
Gilman E, Chaloupka M, Merrifield M, Malsol N, Cook C.
2015. Standardized catch and survival rates, and effect of a
ban on shark retention Palau pelagic longline fishery,
Aquatic Conservation: Marine and Freshwater Ecosystems .
DOI:10.1002/aqc.2599.
Gilman E, Chaloupka M, Swimmer Y, Piovano S. 2016. A
cross-taxa assessment of pelagic longline by-catch
mitigation measures: conflicts and mutual benefits to
elasmobranchs. Fish and Fisheries. DOI:10.1111/faf.
12143.
Godin A, Carlson J, Burgener V. 2012. The effect of circle
hooks on shark catchability and at-vessel mortality rates
in longlines fisheries. Bulletin of Marine Science 88:
469–483.
Goñi R. 1998. Ecosystem effects of marine fisheries: an
overview. Ocean and Coastal Management 40:37–64.
Hall M, Alverson D, Metuzal K. 2000. By-catch: problems and
solutions. Marine Pollution Bulletin 41: 204–219.
Hinke J, Kaplan I, Avdin K, Watters G, Olson R, Kitchell J.
2004. Visualizing the food-web effects of fishing for tunas in
the Pacific Ocean. Ecology and Society 9: 10.
Højsgaard S, Halekoh U. 2014. doBy: Groupwise statistics,
LSmeans, linear contrasts, utilities. R package version 4:
5–13.
ISSF. 2015. ISSF Tuna Stock Status Update, 2015: Status of
the World Fisheries for Tuna. In ISSF Technical Report
2015–03, International Seafood Sustainability Foundation:
Washington, D.C., USA.
IUCN. 2015. The IUCN Red List of Threatened Species.
Version 2015–3. http://www.iucnredlist.org [23 September
2015].
Jackman S. 2015. pscl: Classes and Methods for R Developed
in the Political Science Computational Laboratory,
Stanford University. Department of Political Science,
Stanford University: Stanford, California. R package
version 1.4.9.
Kitchell J, Essington T, Boggs C, Schindler D, Walters C. 2002.
The role of sharks and longline fisheries in a pelagic
ecosystem of the central Pacific. Ecosystems 5: 202–216.
Lehodey P. 2001. The pelagic ecosystem of the tropical
Pacific Ocean: dynamic spatial modelling and biological
consequences of ENSO. Progress in Oceanography 49:
439–468.
Lehodey P, Senina I, Nicol S, Hampton J. 2015. Modelling the
impact of climate change on South Pacific albacore tuna.
Deep Sea Research, Part II 113: 246–259.
Mandelman J, Cooper P, Werner T, Lagueux K. 2008. Shark
bycatch and depredation in the U.S. Atlantic pelagic
longline fishery. Reviews in Fish Biology and Fisheries 18:
427–442.
Musick J. 1999. Criteria to define extinction risk in marine
fishes. Fisheries 24:6–14.
Musick J, Burgess G, Camhi M, Cailliet G, Fordham S. 2000.
Management of sharks and their relatives (Elasmobranchii).
Fisheries 25:9–13.
Myers R, Bowen K, Barrowman N. 1999. Maximum
reproductive rate of fish at low population sizes.
Canadian Journal of Fisheries and Aquatic Sciences 56:
2404–2419.
Myers RA, Worm B. 2005. Extinction, survival or recovery of
large predatory fishes. Philosophical Transactions of the
Royal Society B 360:13–20.
Piovano S, Swimmer Y, Giacoma C. 2009. Are circle hooks
effective in reducing incidental capture of loggerhead sea
turtles in a Mediterranean longline fishery? Aquatic
Conservation: Marine and Freshwater Ecosystems 19:
779–785.
Piovano S, Clò S, Giacoma C. 2010. Reducing longline
bycatch: the larger the hook, the fewer the stingrays.
Biological Conservation 143: 261–264.
Piovano S, Basciano G, Swimmer Y, Giacoma C. 2012.
Evaluation of a bycatch reduction technology by
fishermen: a case study from Sicily. Marine Policy 36:
272–277.
Polovina J, Woodworth-Jefcoats P. 2013. Fishery-induced
changes in the subtropical Pacific pelagic ecosystem size
structure: observations and theory. PLOsOne 8:e62341
Polovina J, Abecassis M, Howell E, Woodworth P. 2009.
Increases in the relative abundance of mid-trophic level
fishes concurrent with declines in apex predators in the
subtropical North Pacific, 1996-2006. Fisheries Bulletin 107:
523–531.
R Core Team. 2015. R: A language and environment for
statistical computing. R Foundation for Statistical
Computing, Vienna, Austria. www.R-project.org.
Serafy J, Orbesen E, Snodgrass D, Beerkircher L, Walter J.
2012. Hooking survival of fishes captured by the United
States Atlantic pelagic longline fishery: Impact of the
2004 circle hook rule. Bulletin of Marine Science 88:
605–621.
Shotton R (Ed). 1999. Case Studies of the Management of
Elasmobranch Fisheries. FAO Fisheries Technical Paper no.
378, Part 2, Food and Agriculture Organization of the
United Nations: Rome.
SPC. 2011. Report of the eight Meeting of the Tuna Fishery
Data Collection Committee: 16–19 November 2009,
Noumea, New Caledonia. Secretariat of the Pacific
Community (SPC), Forum Fisheries Agency (FFA) series.
S. PIOVANO AND E. GILMAN
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)

Stevens J, Bonfil R, Dulvy N, Walker P. 2000. The effects of
fishing on sharks, rays and chimaeras (Chondrichthyans)
and implications for marine ecosystems. ICES Journal of
Marine Science 57: 476–494.
Swamy K. 1999. Shark fisheries in Fiji: their management and
issues of future concern. In FAO. Case Studies of the
Management of Elasmobranch Fisheries. FAO Fisheries
Technical Paper, No. 378, part 1, Food and Agriculture
Organization of the United Nations: Rome, Italy.
Thomson N. 2007. Fiji pelagic longline tuna fishery:
industry practice and attitudes towards shark depredation
and unwanted bycatch. In Shark Depredation and
Unwanted Bycatch in Pelagic Longline Fisheries: Industry
Practices and Attitudes, and Shark Avoidance Strategies,
Gilman E, Clarke S, Brothers N, Alfaro-Shigueto J,
Mandelman J, Mangel J, Petersen S, Piovano S,
Thomson N, Dalzell P, et al.(eds).WesternPacific
Regional Fishery Management Council: Honolulu, USA;
88–99.
Vega R, Licandeo R. 2009. The effect of American and Spanish
longline systems on target and non-target species in the
eastern South Pacific swordfish fishery. Fisheries Research
98:22–32.
Venables WN, Ripley BD. 2002. Modern Applied Statistics with
S, 4th edn.New York: Springer.
Walker T. 1998. Can shark resources be harvested sustainably?
A question revisited with a review of shark fisheries. Marine
and Freshwater Research 49: 553–572.
Ward P, Myers R. 2005. Shifts in open-ocean fish communities
coinciding with the commencement of commercial fishing.
Ecology 86: 835–847.
Ward P, Epe S, Kreutz D, Lawrence E, Robins C, Sands A.
2009. The effects of circle hooks on bycatch and target
catches in Australia’s pelagic longline fishery. Fisheries
Research 97: 253–262.
Williams P, Terawasi P. 2014. Overview of tuna fisheries in the
western and central Pacific Ocean, including economic
conditions. In Document WCPFC-SC10–2014/GN WP-1,
Western and Central Pacific Fisheries Commission: Palikir,
Federated States of Micronesia.
WCPFC. 2008. Conservation and Management of Sea Turtles.
In CMM 2008–03, Federated States of Micronesia: Western
and Central Pacific Fisheries Commission, Kolonia, Pohnpei.
WCPFC. 2011. Conservation and Management Measure for
Oceanic Whitetip Shark. In CMM 2011–04, Federated
States of Micronesia: Western and Central Pacific Fisheries
Commission, Kolonia, Pohnpei.
WCPFC. 2014. Conservation and Management for Sharks. In
CMM 2014–05, Federated States of Micronesia: Western
and Central Pacific Fisheries Commission, Kolonia, Pohnpei.
Worm B, Davis B, Kettermer L, Ward-Paige C, Chapman D,
Heithaus M, Kessel S, Gruber S. 2013. Global catches,
exploitation rates, and rebuilding options for sharks.
Marine Policy 40: 194–204.
Yokota K, Mituhasi T, Minami H, Kiyota M. 2012.
Perspectives on the morphological elements of circle hooks
and their performance in pelagic longline fisheries. Bulletin
of Marine Science 88: 623–629.
Zhou S, Smith A, Punt A, Richardson A, Gibbs M, Fulton E,
Pascoe S, Bulman C, Bayliss P, Sainsbury K. 2010.
Ecosystem-based fisheries management requires a change to
the selective fishing philosophy. Proceedings of the National
Academy of Sciences 107: 9485–9489.
Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith G. 2009.
Mixed Effects Models and Extensions in Ecology with R,
Springer: New York.
ELASMOBRANCH CAPTURES IN THE FIJIAN PELAGIC LONGLINE FISHERY
Copyright #2016 John Wiley & Sons, Ltd. Aquatic Conserv: Mar. Freshw. Ecosyst. (2016)