CMS
CONVENTION ON
MIGRATORY
SPECIES
Distribution: General
UNEP/CMS/Inf.10.30
5 October 2011
Original: English
TENTH MEETING OF THE
CONFERENCE OF THE PARTIES
Bergen, 20-25 November 2011
Agenda Item 19
ASSESSMENT OF BYCATCH IN GILL NET FISHERIES
(Prepared by Sextant Technology Ltd. for CMS)
Pursuant to the recommendation of the 16th Meeting of the Scientific Council, the CMS
Secretariat commissioned Sextant Technology Ltd. to undertake an assessment of bycatch of
CMS-listed species in gill net fisheries, as well as of available mitigation measures and their
effectiveness. Their report is presented in this Information document in the original form in
which it was delivered to the Secretariat. An executive summary is also provided as document
UNEP/CMS/Conf.10.33.
For reasons of economy, documents are printed in a limited number, and will not be distributed at the meeting.
Delegates are kindly requested to bring their copy to the meeting and not to request additional copies.
2
Report to the Convention on Migratory Species
Assessment of Bycatch in Gill Net Fisheries
30 September 2011
S. M.Waugh 1,2 D.P. Filippi 2 and R. Blyth 2, P.F. Filippi 2
1 Present add ress: Museum of New Zeala nd Te Papa Tonga rewa, PO Box 467,
We llington, New Zeala nd. susa n.wa ugh@te papa.govt. nz
2Sexta nt Techno logy Ltd, 116 Wilton Road, We llington, New Zeala nd
1
2
Acknowledgements
The report was funded by t he United Nat ions Environment Progra mme under cont ract.
We a re grateful to Heid run Fris h a nd Ba rry Baker for t heir guida nce in t he prepa rat ion of
t he report. Tha nks a lso to BirdLife Internat iona l for supply of data for t he a na lyses. The
Minist ry of Fis heries in New Zea la nd supplied deta iled fis hery data. Tha nks to Cleo Sma ll
a nd David Kirby for tec hnica l d iscussions in t he prepa rat ion of t he resea rc h. We a re
grateful to Sea A round Us Proj ect for provision of fis hing effort data. Tha nks to Proj ect
G lo ba l for provision of fis hing effort a nd bycatc h informat ion. Tha nks to Minist ry of
Agricult ure a nd Livestoc k (T urkey), Swed is h Boa rd of Fis heries, Minist ry of Fis heries &
Rod rigues (Ma urit ius), Minist ry of Agricult ure & Fis heries (Belgium), Inst it ut Fra nça is de
Rec herc he pour l'Exploitat ion de la Mer, Fis heries Attac he Government of Ma lta,
Va nuat u Fis heries Depa rt ment, Government of St Helena, Minist ry for Agricult ure,
Forest ry a nd Food (Slovenia), Ba ha mas Depa rt ment of Fis heries for t heir replies to our
request for informat ion.
3
I
ti
." Summary Exec u ve ................................................................................................................................. 7"
II Int rod ctio n
."
................................................................................................................................................ 9"
u
1
11
n
n
i itio of g illnet f ishing
." Def
............................................................................................................ "
13
2
i
int
ti n w it h g illnet f isheries
.......................................... "
." Spec es gro ups – modes of erac o
15
III
t
." Me hod................................................................................................................................................... "
1
15
t
t
." Da a search me hods ....................................................................................................................... "
2
16
illn t
t
i ti n
." G e me hod descr p o ............................................................................................................ "
a)" A na lys is met hod ............................................................................................................................. 16"
b)
verla p a na lys is ............................................................................................................................. 16"
" O
c)" Spec ies inc luded in t he st udy ................................................................................................... 17"
d)" Spec ies d ist ributio n ma ps .......................................................................................................... 17"
e)" A reas of high s pec ies d ivers ity ................................................................................................. 19"
f)" Overla p betwee n s pec ies a nd g illnet f isheries ..................................................................22"
3
22
ti n
t
t
." Ass ump o s of he s udy............................................................................................................... "
nking a nd ote ntia l for g illnet f ishing to
4
i i
t b illn t i in
." Spec es mpac ed y g e f sh g – ra
p
2
i act o latio ns
............................................................................................................................... 7"
mp p pu
lt
31
IV
." Res u s .................................................................................................................................................... "
1
31
i
i ti n
." F shery descr p o ............................................................................................................................ "
a)" G lo ba l overv iew of t he g illnet f isheries ................................................................................ 31"
b)
36
illnet f isheries in o t h s ia a nd o t h East s ia
" G
S u A
S u
A .......................................................... "
c)" G illnet f isheries in Nort hwest Pac if ic ..................................................................................... 37"
d)" G illnet f isheries in East As ia ....................................................................................................... 37"
e)" G illnet f isheries in Nort hern Euro pe....................................................................................... 38"
f)" G illnet f isheries in So ut h America ........................................................................................... 39"
g)" G illnet f isheries in t he Med iterra nea n Sea ..........................................................................40"
h)" G illnet f isheries in Africa .............................................................................................................41"
4
i)
ill
i
i i
i
2
G net f sher es n Ocean a ........................................................................................................4 "
2. Overlap ana lys is outputs.................................................................................................................4 5
"
"
d
ll
i
i
)
5
a " Exposure n ex for a spec es...................................................................................................4 "
"
b)
xposure index by spec ies group............................................................................................49"
" E
it igat ion methods and the ir applicat ion in g illnet f isheries..........................................66
3.
" M
"
l
Al
i
)
a " V sua erts .....................................................................................................................................66"
b) Acoust ic Alerts: ...............................................................................................................................67
"
"
c)" Operat iona l measures:.................................................................................................................68"
d)
it igat ion conc lus ions ................................................................................................................70
"
" M
i
i
V." D scuss on .................................................................................................................................................71"
1." Spec ies ...................................................................................................................................................71"
2. A rea .........................................................................................................................................................71
"
"
it igat ion effects...............................................................................................................................72
3.
" M
"
4." Limitat ions of the study...................................................................................................................7 3"
d i
I
V ." Recommen at ons:............................................................................................................................76"
ibli
9
II
V ." B ography.........................................................................................................................................7 "
III A nnexes..................................................................................................................................................89
"
V ."
1." Marine spec ies listed under the C MS part of the study.....................................................89"
2.
Z stat ist ics.........................................................................................................................................93
" EE
"
3.
esults
" R
4." Results
by overlap index .............................................................................................................. 100
"
by unÃwe ighted exposure............................................................................................ 10 3
"
a)" UnÃwe ighted exposure of a ll spec ies ................................................................................. 10 3"
b)
nÃwe ighted exposure of sea birds ..................................................................................... 106"
" U
c)" UnÃwe ighted exposure of sea turt les ................................................................................. 108"
d)
nÃwe ighted exposure of sharks ......................................................................................... 109"
" U
e)" UnÃwe ighted exposure of pinnipeds and otters;........................................................... 110"
5.
esults by EEZ and High Seas FAO areas.............................................................................. 111"
" R
5
a)" High Seas FAO areas and EEZ sorted by t he ir cont ribut ion in t he unâwe ighted
exposure for all spec ies .................................................................................................................... 111"
b)
gh Seas FAO areas and EEZ sorted by t he ir cont ribut ion in t he IUCN we ighted
" Hi
exposure for all spec ies .................................................................................................................... 115"
c)" High Seas FAO areas EEZ sorted by t he ir cont ribut ion in t he exposures for all
spec ies groups...................................................................................................................................... 119"
6. Survey .................................................................................................................................................. 139
"
"
6
A study was cond ucted to assess the impacts of g illnet f is hing on s pec ies listed by the
Conve nt ion of Mig rato ry Spec ies (C MS s pec ies) Conce rns a bo ut the impact of inc ide nta l
.
b
d
o
r
n
g
n
f
s
n
g
s
n
r
ss
f
o
r ma rine ma mma ls, turt les, sea birds a nd
t
li
t
i
ill
et
i
h
i
h
ee
e
x
e
e
m
a y
a
p
s ha rks Suc h long lived a nd/o r to ppredato r po pulat ions have life histo ry t ra its that
.
ma ke the m inhe re nt ly v ulne ra ble to add it ive ad ult mo rta lity, w ith po pulat ion dec reases
poss ible w ith add it iona l f is he ries mo rta lity
.
he rev iew of f is he ry info rmat ion conc luded that g illnet f is he ries a re too poo rly
doc ume nted to e na ble a na lyses of f is he ry act iv ity o r c ha racte risat ion of the f is hing f leets
us ing g illnet methods into d isc reet f is he ry units athe r the resea rc h used s umma ry
. R
g illnet data at a unive rsa l leve l T his a pproac h may lead biases in the a na lys is of impacts
.
of g illnet f is hing on nonta rget C MS s pec ies, s ha rks, turt les, ma rine ma mma ls a nd
sea birds
T
.
s n n o rmat ion a bo ut s pec ies a nd g illnet f is hing d ist ribut ion, the a na lys is exa mined
the re lat ive ex pos ure of s pec ies to g illnet act iv ity T he info rmat ion was the n we ig hted by
.
a facto r to ta ke into acco unt the v ulne ra bility of po pulat ions to ext inct ion (I UC N
we ig hted ex pos ure). Spec ies most ex posed to g illnet f is hing ca me f ro m a ll s pec ies
g ro ups listed unde r the C MS
U i g i f
.
A reas of hig h d ive rs ity (C MS s pec ies) we re west coast of So uth A me rica, west coast of
Af rica f ro m the Ca pe of Good Ho pe to A lge ria, T he ed Sea / Pe rs ia n G ulf to A ra bia n
R
G ulf, New Zea la nd / Tas ma n Sea, a nd the Aegea n Sea
.
he twe nty Exc lus ive Econo mic Zones of 2 37 a reas, in w hic h the g reatest ex pos ure to
f is hing ris k occ urs fo r C MS listed s pec ies (we ig hted by I UC N ra nk) we re: Mya nma r,
V iet na m, Pe ru, I nd ia,
uss ia (Pac if ic), C hile, So uth Af rica, C hina, Na mibia, G reece,
R
Ga la pagos, Ba ng lades h, Ja pa n (Ma in Is la nds), Weste rn I ndones ia, Easte rn I ndones ia,
No rway, Ma urita nia, United Kingdo m, A lge ria, a nd Mo rocco
T
.
he fo rty s pec ies most ex posed to ris k f ro m
ra nk, by taxon g ro up we re:
T
‚
net f is hing, w he n we ig hted by
g ill
I UC N
ea birds – Af rica n Pe ng uin, Pe ruv ia n Div ing pet re l, Ja pa nese Murre let, Da rk
rumped Pet re l, Waved A lbat ross, Socot ra Co rmo ra nt, Humbo ldt Pe ng uin,
S
7
Ba lea ric
A
‚
Shea rwate r
,
do in’s
Au
u
Shea rwate r
,
G
ll
u ,
Sho rt 8ta iled
o rpo ise
o rt h
etacea ns & Sire nia ns – Finless
rrawaddy Do lphins D go ng
P
, I
,
u
, N
C
Rig ht W ha le
Bott le nose
H
um
Sea ls
Rive r
Sea
, O mu
a nd
, A
o
D lphin
,
p8bac ked
W ha le
‚
ink8footed
lbat ross
.
ac if ic
P
‚
P
O
H
um
Heav is ide’s
o
D lphin
,
ra W ha le
Sea
t la nt ic
Bl
e
u
p8bac ked
o
D lphin
,
W ha le
,
B
o
D lphin
,
Fin W ha le
,
o rt he rn Rig ht W ha le
N
,
Se i W ha le
o rpo ise
P
,
r
e iste r
u m
, I
ndo 8 ac if ic
P
Ba ird’s
Bea ked
.
tte rs
–
Med ite rra nea n
Mo nk
Sea l
,
Ma rine
tte r
O
,
So
t he rn
u
tte r
O
.
T
rt les
u
–
Haws kbill
T
rt le
u
,
e
p’s
K m
Rid ley
T
u
rt le
,
eat he rbac k
L
T
u
rt le
,
ogge rhead T rt le G ree n T rt le
live Rid ley T rt le
L
u
,
u
, O
u
.
‚
o ngf in Ma ko Sha rk
o rbeag le Sha rk W ha le
Sha rks – Bas king Sha rk
, L
, P
,
Sha rk
,
G reat W hite Sha rk
.
T he
a in reco
e ndat io n of t he resea rc h in re lat io n to
it igat io n was t hat f is he ry 8 a nd
m
mm
m
s pec ies 8s pec if ic so l
g
t io ns need to be exa
ined a nd prio rit ised T he st dy prov ides so
e
u
m
u
m
.
ida nce as to w hic h a reas a nd w hic h s pec ies inte ract io n a re
u
f
rt he r
u
o nito ring a nd
m
effect ive at red
c los
res
u
a nage
e nt
m
m
.
o s ing le
N
m
it igat io n
ost like ly to be nef it f ro
m
m
et hod was fo nd to
m
u
c ing bycatc h of
MS s pec ies ac ross taxo n g ro ps
u
u
.
C
A
be
rea a nd seaso na l
ay co
e nea r to reso lv ing a ll s pec ies iss es b t a re
nlike ly to be a feas ible
m
m
u
,
u
u
o pt io n to i
ple
e nt g ive n t he hig h re lia nce of co
nit ies o n f is h f ro
g illnet f is hing
m
m
,
mmu
m
as a food so
a nd pa rt ic
u
rce
.
Resea rc h to def ine s pec if ic po ints of inte ract io n betwee n
MS s pec ies
la r f is he ries is
rge nt ly needed
u
u
.
T he re is a st ro ng need fo r i
w it h a pa rt ic
la r foc
u
m
proved o bse rve r data
,
bette r reco rds of byca
g ht s pec ies
u
s in t he a reas of hig h ove rla p of at 8ris k s pec ies a nd a hig h de ns ity
u
of f is hing effo rt T he
.
iss
C
next ste p is fo r f
u
rt he r f ine r8sca led
,
resea rc h to add ress
bycatc h
es in t hose a reas a nd fo r data to assess po p lat io n a nd be hav io ra l facto rs fo r t he
u
,
u
u
s pec ies ide nt if ied as hig hest ris k in t his a na lys is is wa rra nted
.
8
T he
Co nve nt io n
Mig rato ry
on
Spec ies
was
esta blis hed
to
co nse rve
w hic h
s pec ies
t rave rse nat io na l bo unda ries Spec ies listed unde r t he Co nve nt io n (C MS s pec ies) inc lude
.
ma ny to ptpredato r s pec ies w hic h a re inhe re nt ly ‘ ra re’ in eco log ica l te rms (Co nve nt io n
,
on
Mig rato ry
20 11)
Spec ies
.
T hese
s pec ies
have
ty pica lly
lo ng
lifes pa ns
a nd
low
re prod uct ive o ut put T hese life thisto ry t ra its ma ke s uc h s pec ies pa rt ic ula rly se ns it ive to
.
f
po pulat io n c ha nges as a res ult o add it ive mo rta lity (Stea rns 1992 Sibly a nd Ho ne 200 3)
,
,
s uc h as t hat imposed by f is he ries bycatc h
mpe rat ives ex ist w it hin inte rnat io na l f is he ries
. I
ma nage me nt f ra mewo rks to add ress no ntta rget effects of f is hing
,
inc lud ing minimiz ing
waste a nd red uc ing catc h of no ntta rget s pec ies a nd a pply ing preca ut io na ry a pproac hes
,
to t he ma nage me nt f is hing act iv it ies w he n info rmat io n is unce rta in (FAO 199 5)
G illnet f is hing a nd its
muc h
resea rc h
f
f
pote nt ia l impacts o n no ntta rget s pec ies have bee n t he oc us o
Me lv in
(e g
. .
.
et
al
.
1999
,
G ilma n
2009
,
o kke bo rg
L
20 11)
.
I
t
is
we ll
doc ume nted t hat g illnet f is hing catc hes a w ide ra nge of no ntta rget s pec ies a nd co nce rn
has
bee n
A mo ng
ra ised
t hese
f is hing
,
o n t he
C MS s pec ies
mo rta lity T his
.
j urisd ict io ns
,
impacts
is
may
of
be
t his
bycatc h o n v ulne ra ble
pa rt ic ula rly
to
v ulne ra ble
w ild life
po pulat io ns
.
ff
po pulat io n e ects
beca use t he ir nat ura l ra nges exte nd ove r wate rs of
w it h c umulat ive
effects f ro m ma ny d iffe re nt
f is he ries
act iv it ies
of
mult iple
affect ing
t he m a nd t he ir life thisto ries place g ive t he s pec ies po pulat io ns a n inhe re nt v ulne ra bility
,
to added ad ult mo rta lity Coo rd inated effo rts ac ross secto rs of t he resea rc h co mmunity
,
.
f is hing
o pe rato rs
a nd
reg ulat ing
age nc ies
a re
needed
to
add ress
t he
inc ide nta l ca pt ure of C MS s pec ies in g illnet f is hing (Me lv in a nd Pa ris h 1999)
Des pite
ma ny
yea rs
of
co nce rn ove r t he
impacts
of
g illnet
f is hing
pro ble ms
of
.
o n to ptpredato r
s pec ies it re ma ins a n e nig mat ic f is he ry: litt le is know n of t he state of t he ta rget stoc ks
,
,
f is hing
f
ff
pract ices catc h bycatc h a nd d isca rd ing act iv it ies a nd is hing e ic ie ncy T his lac k
,
,
,
.
of know ledge may be t he res ult of d ive rse d rive rs: g illnet f is he ries a re ofte n ‘ low va lue’
f is he ries
(W ilso n et a l 20 10 Minist ry of
,
.
Fis he ries 20 11) fo r w hic h deta iled
mo nito ring
reg imes a re uneco no mic to imple me nt; t hey a re ofte n c lassed as a s ing le f is he ry
,
w he n
in rea lity t hey reg ro up a d ive rs ity of f is hing o pe rat io ns bot h in te rms of ta rget stoc ks
a nd f is hing met hods; bot h a rt isa na l a nd ind ust ria l f is he ries a re desc ribed as o ne f is he ry
catego ry yet c lea rly o pe rate o n a d iffe re nt bas is; g illnet f is hing in deve lo ping co unt ries
a re a poo rly doc ume nted yet impo rta nt s ubs iste nce act iv ity
,
.
9
W hile t he inc ide nta l catc h of ma ny C MS s pec ies is doc ume nted, prio rit isat io n of effo rts
is
needed
as
to
how
to
add ress
t he
pote nt ia l
impacts
of
mo rta lity
its
on
w ild life
po pulat io n
his is bot h in te rms of t he zo nes to ta rget fo r mit igat io n a nd in re lat io n to
. T
t he s pec ies pote nt ia lly impacted
mit igate t he f is he ry
o llow ing s uc h data gat he ring a nd a na lys is, effo rts to
. F
inte ract io ns ca n be ta rgeted, a nd t he f is he ries co nce rned ca n be
mo nito red a nd f is he rme n me nto red to
red uce
pote nt ia l ris ks to s pec ies
ppro priate
. A
mit igat io n tec hno log ies ca n be ta rgeted at t he a reas a nd f is he ries w hic h a re
prod uce
t he
g reatest
be nef it
in
te rms
of
ris k
red uct io n
.
W it ho ut
mo re
like ly to
deta iled
info rmat io n o n s pec ies inte ract io ns w it h g illnet f is hing act iv ity, a nd data o n t he nat ure
a nd exte nt of t he f is he ries, t he exte nt of mo rta lity of C MS s pec ies, a nd res ult ing ris k to
po pulat io n v ia bility is pro ble mat ic to ex plo re in mea ningf ul ways
.
T
he a pproac hes we a pplied to a na lys ing t he ris k posed by g illnet f is hing to C MS s pec ies
co me f ro m a n Eco log ica l Ris k
T
hese
a pproac hes
have
A
ssess me nt
bee n
a pplied
f ra mewo rk (e g
(ER
A)
. .
w ide ly
to
f is he ries
0 11
o bday et a l
H
. 2
).
ma nag ing
iss ues
of
s usta ina bility a nd e nv iro nme nta l effects, in pa rt ic ula r in info rmat io n poo r e nv iro nme nts
.
We used a q ua litat ive assess me nt of t he ex pos ure of s pec ies to g illnet f is hing act iv ity by
co mpa ring t he s pat ia l d ist ribut io ns a nd de ns ity of act iv ity (w he re ava ila ble
)
fo r bot h t he
he o utco mes prov ide a re lat ive ra nking of s pec ies in
C MS s pec ies a nd g illnet f is he ries
. T
te rms of t he ir ex pos ure to f is hing effo rt, a nd t he co nt ribut io n of f is hing effo rt in eac h
Exc lus ive
Eco no mic Zo ne inte rnat io na lly, to t he ex pos ure
index
.
We we re t hus a ble to
ra nk s pec ies a nd a reas in te rms of t he like lihood of adve rse effects of g illnet f is hing
.
Beca use of t he limited info rmat io n a bo ut t he nat ure of t he f is hing o pe rat io ns fo und in
o ur
a nd
rev iew,
of
be hav io ura l
t he
inte ract io ns
of
s pec ies
w it h t hose
f is he ries,
o ur
a na lys is sto ps s ho rt of exa mining s pec ies o r po pulat io n leve l impacts of mo rta lity f ro m
t he f is he ries
.
Rat he r it ide nt if ies t he g ro ups of s pec ies, a nd t he a reas w hic h req uire most
d ilige nt a nd deta iled exa minat io n fo r t he f ut ure, to add ress a ny
ris k of
mo rta lity
no n
C MS s pec ies po pulat io ns
.
T
he need to mit igate adve rse effects of f is hing o n C MS s pec ies req uires f is he ry ºs pec if ic
ta rget ing
t he
.
C urre nt ly, t he o bsc urity of g illnet f is he ries, in te rms of t he info rmat io n a bo ut
o pe rat io ns,
reco mme ndat io ns
leve l
of
be ing
effo rt,
catc h,
deve lo ped
to
a nd
bycatc h
ta rget
t hese
occ urring
prec ludes
s pec if ic
mit igat io n
act iv it ies
.
F
urt he r,
deta iled resea rc h into t he pro ble ms t hat a ppea r to be of g reatest mo me nt is needed
.
10
T he stated
req uire me nt to
f ra mewo rk
fo r
impe rat ives
g lo ba lly
s urro und ing
meet t he
f is he ries
g illnet
princ iples set o ut
to
needs
f is hing.
be
in t he ecosyste m ma nage me nt
ba la nced
G illnet
f is hing
aga inst
is
a
t he
v ita l
soc io Óeco no mic
met hod
of
food
gat he ring fo r a la rge po pulat io n g lo ba lly bot h in deve lo ping a nd ind ust ria lised nat io ns.
,
Fis h
,
inc lud ing
aq uac ult ure
prod ucts
acco unted
fo r
16%
of
prote in
po pulat io ns g lo ba lly in 2008 (FAO 20 10). T his is a n inc reas ing food so urce
,
inta ke
fo r
w it h leve ls of
t rade in f is h prod ucts s how ing a n ave rage a nnua l inc rease of 6% pe r yea r in t rade fo r
t he last seve ra l yea rs (FAO 20 10). T he pro po rt io n of t he wo rld’s food inta ke t hat de rives
f ro m g illnet f is hing is not c lea rl
y re po rted
,
but of 142 millio n to nnes of f is h prod uct io n
in 2008 (FAO 20 10) it was est imated t hat 20% of g lo ba l f is h prod uct io n is la nded f ro m
g illnet f is hing a nnua lly (SA UP 20 11; ave rage rat io fo r 2004 – 2006). It acco unts fo r a hig h
pro po rt io n of t he
prote in de live red to ta ble
,
pa rt ic ula rly
so me nat io ns re ly a lmost exc lus ive ly o n g illnet f is hing.
in deve lo ping
nat io ns w he re
,
"
Fo r t he purposes of t his st udy g illnet f is hing inc ludes a ll f is he ries w hic h use pass ive net
,
met hods to ta rget f is h a nd inc ludes set net g illnet d rift net t ra mme l net f is hing. Set nets
,
,
,
,
a re nets of a ny mes h s ize t hat a re de ployed by f loat ing t he net in t he wate r co lumn in
,
pe lag ic (nea r s urface)
,
midd le Óde pt hs o r e piÓbe nt hic wate r leve ls. G illnets a re made of a
,
f mate ria ls w it h rece nt inc rease in use of mo nof ila me nt prod ucts fo r nets d ue
va riety o
,
,
to its d ura bility a nd low cost. T he FAO (FAO 1990) def ines s ix maj o r g ro ups of g illnet
f is he ries a nd eac h of w hic h has a FAO sta nda rd a bbrev iat io ns code (he re in brac kets): a)
Set nets (G NS); b) e nc irc ling nets (G NC); c) co mbined g illnets – t ra mme l nets (GT N); d)
d rift nets (G ND); e) t ra mme l nets (T NR); f) f ixed g illnets (G NF) (f ig ure 1).
G illnets a re des ig ned to t ra p f is h by t he g ills. T hey ca n be of va ria ble d ime ns io n f ro m a
,
few mete rs to seve ra l kilo met res lo ng.
put toget he r to fo rm a f leet.
I n ind ust ria l f is he ries
,
bloc ks of g illnets (ta ns) a re
La rge vesse ls ca n ca rry seve ra l f leets of
kilo met res of net.
11
nets de ploy ing
,
a)
b)
c)
d)
e)
f
ure 1Gi llnet types as defi ned by the FAO (FAO 200 1). a) Set gi llnets, b) Enci rc li ng gi llnet, c) Combi ned
gi llnet – tra mme l net, d) Drift net, e) T ra mme l nets, f) Fixed gi llnet
Fig
12
Because of the need to work with data about f is hing effort for this st udy we have been
,
limited to researc hing reported (and therefore ‘ lega l’) gillnet f is hing only. T here are
many separate problems associated with illega l gillnet f is hing and g host f is hing w hic h
are not addressed here. T he work is only concerned with gillnet f is hing in the marine
enviro nment. Gillnet bycatc h is a lso an issue for CMS species occupying est uarine
environments suc h as the otters, manatees and some cetaceans but these issues are not
addressed in this report.
Gillnets are designed to be t ransparent and have the same density as water,
them diff icult to detect in the water co lumn (Rowe 2007 ein 1980) and it is
, L
reason that many species become entang led. Interact ions between nonOtarget
making
for t his
species
and gillnets can be est imated only by t he proport ion of anima ls that are caug ht and
drown in gillnets. It is not possible to est imate t he proport ion of species that become
entang led and f ree the mse lves and/or break f ree wit h part of the f is hing gear attac hed
to the m (T homas and Kaste lien 1990).
Entang lement of cetaceans has occ urred in every region w here substant ia l gillnett ing
operat ions and the presence of marine mamma ls overlap (Jefferson and Curry 1994).
Here we inc lude sea cows as part of the group ‘cetaceans’ due to gross ly similar feeding
be haviours to sma ll cetaceans. It is thoug ht that the ability for cetaceans to detect
gillnets is primarily thro ug h acoust ic means (T homas and Kaste lein 1990). Cetaceans are
able to detect gillnets by the so und the net makes as water passes throug h it and
possibly by the acoust ic propert ies that f is h create w hen ent rapped in the net
and Kaste lein 1990). Sma ller cetaceans (mainly do lphins and porpoises)
entang led and may drown in the gillnet because they are not st rong enoug h
(T homas
become
to break
f ree and come to the surface to breathe w he reas larger cetaceans are more able to
,
th
h
t
h
t
t
th
ft
swim roug
e ne s, bu
is o en results in towing gear w hic h can cause inj ury and
death (Cetacean Bycatc h Resource Center 20 11).
Pinnipeds and other sma ll marine mamma ls (e.g. sea otters) interact with gillnets in a
similar way to sma ll cetaceans, becoming entang led by their flippers/ limbs w hen they
interact with the net. For sea ls, there have been reports that some become att racted to
13
gillnets through the use of acoustic pingers a nd associate gillnets with a n easy food
source (referred to as the ‘d inner be ll effect’) causing a n increased risk of e nta ng leme nt
as we ll as damage to the target catch (Beeso n a nd Ha na n 1996, Mate 1993).
T he seabird species most susceptible to capt ure in gillnets are d iving species;
e ncountering a nd becoming e nta ng led in the net whe n d iving to forage for food a nd
d row ning before t he net is retrieved ( e lvin et a l. 1999 T rippe l et a l. 2003 re nc h 2011).
M
,
,F
Seabird bycatch has bee n wide ly docume nted in coasta l highƒseas d rift a nd demersa l
,
,
gillnet fisheries. Seabirds may be a lso be caught in gillnets set deeper tha n their
max imum d iving depth as seabirds may e nco unter nets as they are set or hauled
(Lokkeborg 2010).
Seabirds might a lso be e nta ng led in lost gillnets or d iscarded piece of gillnets at this
materia l is opportunistica lly co llected by seabirds for the co nstructio n of their nest. T his
ca n a lso prese nt a risk for the chicks being caught in the nest by pieces of gillnet
gathered by its pare nts d uring nestƒbuild ing (Mo ntevecchi 1991).
Like marine mamma ls sea turt les become e nta ng led in gillnets a nd d row n if they ca nnot
,
break free from the gillnet a nd reach the surface for air. Serious inj ury ca n a lso be
sustained to f lippers from lines a nd ropes which support the gillnet in the water co lumn
(G illma n 2010).
Sharks become e nta ng led in gillnets whe n they swim into the net a nd become caught
,
by fins/gills whe n trying free themse lves. Once wrapped in the gillnet, the shark the n
suffocates. G illnets are a lso used to harvest sharks as a target spec ies. Shark damage to
nets is unique as they leave behind s limy materia l a nd rough skin which they deposit o n
the net. Aside from fish harvest, gillnets are a lso used to protect swimmers from shark
attacks whic h results in shark morta lity.
14
All objectives of the work were addressed with a common methodology set out below.
,
The first approach used to evaluate the impact of gillnet fisheries o n CMS species was to
get detailed information about gillnet fisheries species distribution bycatch and
,
,
mitigation. T he informat io n was sought directly from the national departments in charge
of the fisheries and thus for each j urisdictio n hav ing an Exc lusive Economic Zone (EEZ).
Agencies were contacted by email and by fax covering the 262 EEZ and 18 high seas
,
FAO areas. Agencies we re inv ited to fill a form established for the purpose of this
studies (see annex) or to indicate any relevant documents where the information
requested could be found.
The information solic ited was a technical desc ription about the gillnets used in EEZs and
in the high seas area the number of vessels vessel size period of the year recent
,
,
,
,
landed catc h estimation effort estimation spatial information mitigat ion and bycatc h
,
,
,
,
summary data.
Despite these efforts and nume ro us contact attempts less than 15 replies were received.
,
The information published found online were usually not detailed enough or too old
,
,
for the requirements of t he research. In particular information to distinguish one fishery
from another and to define fineºscaled information relevant to different target fisheries
,
,
fleets or areas was lacking.
,
At the same time we rev iewed online and published literature. Most of t he documents
,
found were too old too general or could not be generalised to fishery specific to inform
,
the analysis of fishery characterisation.
It was therefore not possible to establish a gillnet fishery classification and to produce
accurate global maps of the fishing effort for eac h type of gillnet for the last 3 years (this
met hod is detailed in the next chapter)
15
An alternative approach was ado pted which co ns isted of produc ing a mo re ge neral
,
v iew of t he g illnet f ishing activ ities at a g lobal scale. Fo r t his purpose, effo rt maps were
based o n t he g illnet f isheries land catch estimatio n published o nline (SA UP 2011).
Simultaneo usly to t he off ic ial req uests numero us local and g lobal No nàGovernme ntal
,
O rganisatio ns were co ntacted and info rmatio n was req uested rega rd ing animal bycatch
and effective ness of mitigatio n. T hose req uests were f ruitf ul and de livered deta iled
info rmat io n rega rd ing cetacean and sea bird bycatch and mo re ge neral info rmatio n fo r
t he ot he r spec ies.
An approach was ado pted to use t he ava ila ble info rmatio n based o n a s ing le g illnet
,
class reg ro uping all t he d iffere nt g illnet gea rs. T he se ns itiv ity of a spec ies to be caug ht
in a g illnet has also bee n s implif ied based o nly o n be hav io ural info rmatio n. T his met hod
is prese nted in t he next chapter.
T he process of t he overlap analys is was staged in several phases:
‚
t he a rea of hig h spec ies d ivers ity was ex plo red based o n t he
,
d istributio ns of 123 ma rine spec ies listed under CMS.
‚
Seco ndly a reas of hig h de ns ity of g illnet f ishing fo r 262 EEZ and 18 hig h seas
,
FAO a reas were ide ntif ied.
‚
T hirdly t he ex posure of each CMS spec ies to g illnet f ishe ries at a g lobal scale
,
was calculated. T he results a re ranked a) by spec ies t he most ex posed and b)
First
by t he EEZ f ishery (all g illnet f ishing w it hin t he EEZ co mbined) hav ing t he
most pote ntial impact in terms of bycatch. T hese ranks were t he n weig hted
by t he t hreat ranking ide ntif ied by t he I nternat io nal Unio n fo r t he
Co nservatio n of Nat ure (I UC N) fo r each spec ies in t he analys is to g ive a
16
weighted score by spec ies, ref lect ing t he like ly populat io n leve l of impact of
fisheries ex pos ure
‚
F
weighted ex pos ure).
(I UC N
ina lly, t he res ults were categorized in t hree leve ls of ex pos ure: highly
ex posed,
oderate ly ex posed, least ex posed.
m
he species inc luded in t he st udy
T
o nve nt io n o n
C
he
T
C MS
M
a
re t he 12 3
ma
rine species
l
isted
der t he
un
igratory Species.
spec ies were split in
gro ups: cetacea ns
5
sea birds, sha rks, t urt les, ot her sea
co nta ins respect ive ly
&
sire nia ns (hereafter cetacea ns),
s (pinnipeds
ma mma l
d sea otters).
an
ch gro up
Ea
species, 59 spec ies, a nd 6 species each for t he re ma ining
gro ups. T he categorisat io n of t he species is set o ut in t he a nnex of t his doc ume nt (Ta ble
18 Ta ble 19 Ta ble 20 Ta ble 2 1 a nd Ta ble 22).
,
,
,
or each spec ies
F
o ngit ude
a
46
dist ribut io n
ma
p was esta blished wit h a reso lut io n 0. 1°
x 0.
1° degrees
t it ude derived fro m published dist ribut io n ma ps. Depe nding how we ll
,
know n was t he species t he dist ribut io n ma p co nta ins differe nt layers of a nima l de nsity.
,
l
d
an
la
Sing le lay er distribution map s
ost of t he species (exc luding t he birds), t he ma ps co nsisted of a sing le layer
dist ribut io n ra nge. T hose ma ps have bee n published by t he I UC N (I UC N 20 11) a nd have
or
F
m
bee n re edited for t he purpose of t he st udy.
Dual lay er distribution map s
e n species have t heir
T
t he species ra nges:
a
hose species were:
S
T
h r ,
T urt le
S a k
H
um
d
an
pbac k
a
H
W
ma
kn
hortfin
Ma k
Tu
o
S
ha rk,
oggerhead
L
rt le.
la
yers of ce rta inty based o n
ow n dist ribut io n,
reas of
ha le,
w ksbill
ps based o n two
T
he
ma
Tu
s king
a
B
rt le,
G
d
an
a
ha rk,
S
ree n
reas of
G
reat
rt le,
Tu
certa in dist ribut io n.
un
W
hite
ha rk,
S
eat herbac k
L
ow ledge of
kn
Tu
orbeag le
P
rt le,
id ley
R
ps for t hose species were esta blished fro m t he
17
o nline publis hed ma ps of t he Fis he ries a nd Aq uac ult ure De pa rt me nt of t he
20 11)
.
W
FAO (FAO
e have affected a de ns ity of 1 fo r t he data fo r a reas of know n d ist ribut io n a nd
0 1 to t he a reas of unce rta in d ist ribut io n
.
.
Bird distribution map s
T he bird d ist ribut io n ma ps we re prov ided by Bird Life I nte rnat io na l (Bird Life I nte rnat io na l
a nd
Nat ure Se rve
20 11)
.
T he
A rme nia n G ull
is
not
recog nised
as
a
d ist inct
taxo n
by
Bird Life I nte rnat io na l t he refo re t he d ist ribut io n ma p f ro m publis hed so urces was used
(De l Hoyo et a l 1996) A ll ma ps had a s ing le laye r s ha pef ile desc ribing t he ra nge of t he
.
.
s pec ies Howeve r w he n t he s ize a nd t he locat io n of most of t he breed ing s ites was we llw
.
know n
fo r
s pec ies
a
A lbat rosses
a nd
d ist ribut io n
ma ps
a pproac h was
(e g
. .
Pet re ls
,
t hose
s hags
,
by add ing
used
fo r
32
listed
by
t he
e nde mic
Ag ree me nt
s pec ies
,
pe ng uins)
hots pots of d ist ribut io n a ro und
s pec ies
fo r w hic h we
too k
into
t he
on
,
we
Co nse rvat io n
improved
of
t he
breed ing co lo nies T his
.
acco unt
mo re
t ha n
500
breed ing s ites (A nnex Ta ble 2 3)
.
Bird distribution with forag ing radius app roach
To improve t he d ist ribut io n ma ps we ass umed t hat t he s pec ies we re c luste red a ro und
,
breed ing s ites d uring t he breed ing seaso n To imple me nt t his a pproac h it was ass umed
,
.
t hat
no nwbreede r birds occ upied t he f ull s pec ies
ra nge
,
w hile t he
breed ing ad ults
in
breed ing seaso n we re s pread a ro und t he ir breed ing co lo nies fo llow ing a n ex po ne nt ia l
decay f unct io n w hic h exte nds up to t he ir max imum fo rag ing ra nge rad ius de noted r
max .
T he de ns ity of t he
breede rs at a d ista nce
r f ro m t he ir co lo ny fo llows a n ex po ne nt ia l
decay def ined by:
経長追勅勅鳥勅追 岫堅岻 噺 欠 抜 結
r is t he d ista nce f ro m t he co lo ny a nd
欠噺
認
欠
嶋投"岫轍 轍迭岻抜認
認尿尼猫
""""""""岫'ł"な岻"
def ined by t he eq uat io n be low:
牒迩任如
完轍 尿尼猫 勅
嶋投"岫轍 轍迭岻抜認
認尿尼猫
18
""""""""岫'ł"に岻
b rds at t he co lo ny
.
i
ra nge, breede r de ns ty was ass umed to be ze ro
.
i
鶏頂墜鎮
s
i
t he
numbe r of
breed ng
i
eyo nd
B
t he
max mum fo rag ng
i
i
O uts de of t he
i
breed ng seaso n, we co ns de red t hat ad ults occ up ed t he f ull s pec es
i
i
i
i
ra nge a lo ng w t h no n£breede rs
he hot £s pots we re we g hted w t h t he rat o of t me
. T
i
i
i
i
i
s pe nt o n t he breed ng s tes pe r yea r
.
i
i
Figu re 2 ¬ Exa mple of a n i mproved sea bi rd dist ri butio n fo r t he G rey Pet re l
he squa re root of t he de nsity has
. T
bee n used i nstead of t he de nsity to hig hlig ht low de nsity a rea fo r t he pu rposes of t his ma p i llust ratio n o nly
.
exa m ned
.
i
d st r but o n, t was poss ble to s how a reas of h g h s pec es d ve rs ty
.
i
i
i
i
i
i
i
i
i
T
he
d st r but o n of
i
i
i
t he
C MS s pec es
i
d st r but o n
i
i
i
no rma l zat o n was def ned as fo llow:
i
i
i
Fo r
th s
i
purpose,
t he
c umulat ve ly
i
of
eac h
19
was
s pec es
i
was
y
B
s umm ng
i
no rma l zed
.
i
T
he
t he r
i
s pat a l
i
D
sp
完栂墜追鎮鳥 経鎚椎 噺 な""""""""岫'ł"ぬ岻"
e p ese nts t he s pat ia lly no
a lized a ni
a l de ns ity of t he s pec ies sp.
r
r
rm
m
had t he sa
e we ig ht,
m
unknow n o
T he
r
a king t he
m
es ults
r
Eac h s pec ies
inde pe nde nt f o
po pulat io n s ize w hic h is
r m
poo ly know n fo
a ny s pec ies, es pec ia lly cetacea ns.
r
r m
s pat ia lly
no
a lized
rm
d ist ibut io ns
r
we e
r
su
ed
mm
fo
r
a ll
s pec ies.
T he
es ult
r
is
eq uiva le nt to a de ns ity of s pec ies, he e ca lled t he s pec ies d ive s ity index a nd de noted
r
r
SDI.
Hig h va lues
be
m
r
nu
of
of
SDI
s pec ies
鯨経荊 噺 デ鎚椎勅頂沈勅鎚 経鎚椎 """"""""岫'ł"ね岻"
e p ese nt
r
r
p ese nt
r
a eas
r
a nd/o
r
of
hig h s pec ies
a eas
r
co nce nt ated (Fig u e 3).
r
r
20
w he e
r
d ive s ity,
r
o ne
o
r
w hic h
o e
m r
ind icate
s pec ies
a e
r
a
hig h
hig hly
Figu re 3ÿ
De nsity of species a no rmalised SDI. Hig h values re prese nt a reas of hig h species dive rsity.
21
Five important a reas of s pec ies d ivers ity a re a ppa re nt:
outh A merica, es pec ially the western coast
‚ S
‚ T
‚ T
he Western coast of Africa from the Ca pe of Good Hope to Algeria
he Red ea/ Pers ian Gulf and A rabian Gulf
S
ew Zealand/Tas man Sea
‚ N
‚
Aegean ea
S
s s all hots pots a ppea r in the v ic inity of maj or seabird co lo nies, s uc h as those
Numerou , m
a reas show n in the mid ocean a reas of the southern Ind ian and Atlant ic Oceans,
Hawa iian c ha in and south of ew Zealand.
N
An overla p index was noted
uant ify ing the overla p betwee n a s pec ies
頚鎚椎 帳帳跳 q
d ist ribut io n and the g illnet f isheries of an EEZ. he overla p index is def ined by the
T
fo llow ing e uat io n.
q
填
頚鎚椎 帳帳跳 噺 謬完栂墜追鎮鳥 経鎚椎 抜 系帳帳跳 """"""""岫'ł"の岻"
i
i i
Dsp is the s pat ially normalized de ns ity of the co ns idered s pec ies
. 系帳帳跳 s the f sh ng effort
de ns ity in the co ns idered EEZ or hig h seas a rea.
i s/EEZ were sorted by order of importance and d iv ided
h
la ind
a hs
T e over p ex of e c pec e
by the s um of the overla p index.
Due to the lack of informat io n rega rd ing g illnet f ishing effort and the d iscrepancy of
the units used to describe the effort by d iffere nt f ishery ad minist rat io ns, it was not
poss ible to establish a g lo bal homoge nous effort de ns ity ma p for the g illnet f ishing.
22
Therefore t he estimation of t he gillnet catc h by EEZ and by hig h seas FAO areas by Sea
A round Us Proj ect for t he years 2004 2005 and 2006 was used ore recent catc h
,
,
. M
estimation was not availa ble at t he time of t he study. Vectoria l maritime boundaries
publis hed in t he Maritime Boundaries Geodata base availa ble from t he Flanders Marine
I nstitute ( IZ Be lgium) were used to represent t he 262 EEZ in t he study ( IZ 2011)
VL ,
VL
.
Figure 4 Maritime boundaries of the 262 EEZ and the 18 High Seas FAO areas.
The catc h estimated by Sea A round Us Proj ect refers to 'reported land ings' as t he ot her
catc h components are usua lly unknow n (e.g. unreported land ings, d iscards, and g host
kills). The estimations were made from t he fo llow ing data sources: FAO Fis hstat, IC ES,
GFC M, CCA MLR, RECO FI, C ECA F and adj usted among ot her t hings, to retain only marine
finfis h species (e.g. fres hwater fis h, mo lluscs and crustacean) (SAUP 2011). The catc h
estimation may be s lig ht ly greater t han t he officia l j urisd iction statistics, however, t hey
constitute a homogenous set of data whic h ref lect t he importance of t he gillnet activity
in eac hj urisd iction.
23
The estimation of catc h by Sea Around Us Proj ect applies to a w hole EEZ owever t he
. H
ex haustive rev iew of g illnet f is heries presented in t his report revealed t hat g illnets were
used most ly w it hin 20 nautical miles (nm) from s hore. I nd ust rialized nations were more
likely to extend g illnet f is heries across t he ir w hole EEZs and beyond, but coastal
deployment of t he g illnet was still dominant
.
To ta ke into account t hese d ifferences in t he d ist ribution of t he effort, t he analys is was
run w it h 3 d ifferent scenarios:
oastal scenario: The effort was spread only w it hin 20 nm from t he coast.
‚ C
0: 0 scenario: The effort was spread equally between t he 20 nm coastal band
and t he rema ining EEZ, w it h 50% of effort in eac h area.
il consumption equivalent per capita: This is t he standard scenario used and
‚ O
present in results. This intermed iate scenario was based on t he o il
consumption equivalent per capita for eac h EEZ. The rev iew of g illnet
f is heries hig hlig hted t hat ind ust rialized count ries were more likely to deploy
ind ust rial f is hing activ ities across t he w hole EEZ, includ ing g illnet f is heries.
Poorly ind ust rialized count ries have t he ir g illnets most ly deployed along t he
coast w it hin 20 nm of t he coast. O il consumption equivalent per capita was
c hosen to represent t he level of ind ust rialization of nations and as an index to
spread g illnet effort in t he EEZs. If t he o il consumption equivalent per capita
was less t han 1000 kg, t he g illnet effort was spread in t he coastal 20 nm st rip
only. If t he o il consumption per capita is greater t han 1000 kg, t he effort is
spread equally in t he 20 nm coastal st rip and t he rema ining area of t he EEZ.
The o il consumption per capita per EEZ are presented in t he annexes (Ta ble
24, Figure )
5.
‚ 5 5
The estimation of catc h for hig h seas areas were spread uniformly in t he entire hig h seas
areas w hatever t he scenario.
24
Figure 5 Ò Oil consumption equiva le nt per capita sce nario. Light gree n areas represe nt t he EEZs having a n oil
consumption equiva le nt per capita less t ha n 1000 kg. Dark gree n areas represe nt EEZs having a n oil
consumption equiva le nt per capita greater t ha n 1000 kg. High seas zones are not represe nted.
The hig hest g illnet effort de ns it ies were found in 6 ma ins areas:
e ntra l As ia/I nd ia
‚ C
est Africa
‚
W
‚
N
‚
W
‚
N
‚
Sout h As ia
ort hern Euro pe
est Sout h America
ort h As ia (Ja pa n, C hina, Russ ia, Korea)
25
Figu re 6 Gillnet effo rt de nsity dist ri buted fo llowing t he oil co nsu mptio n equiva le nt per ca pita sce na rio ex pressed i n catc h de nsity [tonnes . km.2]1/ 2
26
T he a nalys is was run fo llow ing t he t hree effort d ist ribut io n sce na rios desc ribed a bove.
To eva luate t he se ns it iv ity of t he o utco mes to t he d ist ribut io n of t he effo rt, fo r eac h
s pec ies t he ex pos ure co mputed w it h t he coasta l sce nario and w it h t he ex pos ures
co mputed w it h t he 50: 50 sce na rio was co mpa red.
T he test of se ns it iv ity s howed t hat t he ra nk of t he s pec ies was bare ly affected by t he
va riat io n of t he effo rt d ist ribut io n betwee n t he two sce narios, o ne w it h a ll t he effort
w it hin t he coastal st rip, t he ot he r w it h it s pread 50: 50 betwee n coast a nd w ide r EEZ. T he
o ut puts of t hese two extre me sce narios s howed ve ry litt le d iffe re nce in s pec ies ex pos ure
(Fig ure 7), w it h t he s pec ies most affected by t his c ha nge was t he Sho rt Xta iled A lbat ross
(PHA) w hic h was a bit mo re ex posed unde r t he 50: 50 sce nario. G ive n t his s lig ht
move me nt in s pec ies ex pos ure ind ices, we proceeded to apply t he ‘o il eq uiva le nt’
sce nario to t he re maining as pects of t he analys is, co nf ide nt t hat t his c hange had litt le
leve rage o n t he s pec ies list ings, but cons ide ring t hat it mo re realist ically re prese nted t he
s pread of effo rt by EEZ t ha n eit he r of t he mo re s implist ic sce na rios.
27
0 .020
NPH
ORB
STB
0 .015
DUG
STM
SYW LSA
SOC
o
ir
a
en
sc
50
0 .010
50/
re ,
osu
E xp
0 .005
0 .000 BMU
CAC
BAM
BAO
BOB
BAE
BAB
BEB
BAP
0 .000
TUAPOT
PHG
STI
HGR
SPD
STV
ST POP
G ST
E
LAU
CEH
LIC
PHV
SDG
LPV
STR
PEG
EBJ
SPH
BAM
STS
EBG
LGE
LOF
ST
F
BAO
ST
MMN
BEB
CEE
POS
PUM
LML N
LGA
SBG
LGB
LHM
EIM
LPK
CT MCAT
GRG
LAA
CAC
DCC
DEL
PUC
HYA
ST H
DDE
LGH
RHT
CHM
LLE
PHA SNA
IPA
OFL
SNL
IOX
MMO
TSNR
UTCCC
BAE
BAP
MNV
BOB
PCC
OOR
PYM
PIR
POB
BMULGS
PT G
SNC
LGO
PCR
LOP
LAT
CEC
PHIGLM
DIM
PCW
DNB
PRK
PHN
LRL
TORH
HC
THH
DIP
PXP
DICSTP
PCO
BAB
EBA
CAM
PCI
PRO
MA I
MAH
DIPOD
X
PHE
PHF
PTT
POW
DAM
0 .005
0 .0 10
0 .0 15
0 .020
Exposure, Coast al scenario
Figu re 7 ¦ Co mpa riso n of t he ex posu re of a s pecies to gi llnet fis hi ng co mputed wit h t he coasta l scena rio a nd
t he ex posu re co mputed wit h t he 50: 50 scena rio
The s pec ies t hat were most ex posed to g illnet f is he ries we re coasta l s pec ies ove rla pping
w it h t he reg io ns of hig h de nsity g illnet f is hing. Spec ies w it h s mall d ist ribut io ns in reg io n
of hig h f is hing effo rt de ns ity (e.g. Te rns a nd G ulls) we re part ic ula rly ex posed. Howeve r
some of t he m we re se ldo m o bse rved ca ug ht in g illnets.
Conve rse ly s pec ies t hat we re less exposed we re so ut he rn pe lag ic s pec ies ove rla pping
,
litt le w it h g illnet f is he ries o r s pec ies w it h w ides pread ra nges ove rla pping moderate ly
,
h
h
w it g illnet f is e ries.
Idea lly t he ex pos ure index s ho uld be we ig hted w it h a be hav io ura l index of ind iv id ua ls of
t hat s pec ies to be ca ug ht in g illnets to est imate t he ris k of adve rse effects fo r t he w ho le
,
h
po pulat io n. An est imat io n of t e t rue s usce pt ibility fo r eac h s pec ies to eac h g illnet
f is he ry was not poss ible to do d ue to t he lac k of info rmat io n.
28
Howeve r o have a a pprox ima e es ima io n of he ex pos ure E f ro m he ove rla p O a
sp
sp ,
, t
t
t
t
t
t
d
b
d
d
s implif ie
e havio ura l in ex Bsp was es ima e
t
t .
継鎚椎 帳帳跳 噺 稽鎚椎 抜 頚鎚椎 帳帳跳 """"""""岫'ł"は岻"
T he s implif ied be hav ioura l index was def ined as fo llows:
T he s pec ies was acco rded a be hav io ura l index of 1 if:
.0
‚
‚
T he re was a leas o ne o bse rva io n of byca c h in a g illne f is he ry
t
t
t
t
t
.
T he animal had a leas one be haviour prese n ing a ris k o be ca ug h by
t
t
t
t
t
g illne s
t .
Be havio urs w hic h may
A ll
t
pu he anima l a ris k of be ing ca ug h we re:
tt
t
t
‚
follow ing f is hing vesse ls
,
‚
feed ing f ro m f is he ries offa l
,
‚
d iving o ca c h prey
t
t
,
‚
s ea ling ba i s f ro m f is hing lines
t
t
,
‚
feed ing o n f is he ries a rge s pec ies (ad ul s ize)
t
t
t
.
he o he r s pec ies a re acco rded a s implif ied be hav io ura l index of
1
t
0.0
T he nex s e p was o foc us o n hrea e ned s pec ies and ide n ify w hic h of he m we re he
t t
t
t
t
t
t
t
mos ex posed o he g illne f is he ries
t
t t
t
.
Fo r
his purpose he ex pos ure index Esp was we ig h ed w i h he hrea e ned s pec ies rank
t
, t
t
t t
t
t
b
se o u y he I n e rna iona l Unio n fo r he Co nse rva io n of Na ure (IUCN 2 11) T he IUCN
t
t
t
t
t
t
t
t
0
.
coeff ic ien of he s pec ies was de no ed Tsp T he IUCN we ig h ed expos ure is no ed Wsp
t
t
t
t
t
.
.
激鎚椎 帳帳跳 噺 劇鎚椎 抜 継鎚椎 帳帳跳 """"""""岫'ł"ば岻"
T he coeff ic ie n T we re def ined as fo llows:
t sp
29
Table 1 Weight Tsp functio n of IUCN ra nk
IUCN Rank
NT
LC
VU
EN
CR
Not defined
Tsp
.4
.2
.6
.8
1.0
.5
30
The results of t he IUCN weig hted exposure ana lysis are out lined be low. The
intermediate results, overlap and unFweig hted exposure, are presented in t he annexes
of t his document (page 100 and page 103)
In 2006, t he tota l from gillnet fis hing landed catc h was est imated about 16 million
tonnes (SA UP 2011). This represented 20% of t he world tota l landed catc h. The catc h
remained t he same during t he decade 1996 F 2006 however when examined in detail,
great variat ions in t he cont ribut ion of t he gillnet fis heries varied in t ime and in space.
The EEZs were sorted by order of importance of t heir gillnet catc h in 2006 (Table 2 data
,
source: SA UP 2011). The percentage of gillnet catc h of t he tota l fis h catc h for eac h
j urisdict ion is noted.
The regions present ing t he hig hest gillnet catc h in 2006 were :
‚
Nort heast & nort hwest Pacific: Russia Pacific nort hwest hig h seas FAO area.
,
‚
Sout h Asia: India and Bang lades h, eastern Indian Ocean hig h seas FAO area
‚
Sout heast Asia: Viet nam, Myanmar, Philippines, Indonesia, Ma laysia, Thailand
and Pacific western cent ra l hig h seas FAO area.
‚
East Asia: China, Japan.
‚
Nort hern Europe: Norway Ice land.
,
The c haracterist ics of gillnet fis heries are presented be low by region. Details about
gillnet fis heries by j urisdict ion are presented when t hey make a significant cont ribut ion
eit her in terms of gillnet effort on in bycatc h. A full descript ion of t he gillnet fis heries
31
are presented in the annex of this document based on the replies of our survey and
public ly availa ble informat ion (Ta ble 38)
Table 2 Gi llnet catch by EEZ i n 2006 (SAUP 2011). T he perce ntage of total fish catch f rom gi llnet catch and
the gi llnet catch de nsity a re set out by EEZ sorted by gi llnet catch i n 2006
EEZ
Russia Pacific
Myanmar
India
Vietnam
Pacific Western Central - High seas Areas
Indian Ocean Eastern - High seas Areas
Indonesia (Eastern)
China
Pacific Northwest - High seas Areas
Indonesia (Western)
Bangladesh
Norway
Japan Main Isl.
Iceland
Philippines
Pacific Southeast - High seas Areas
Morocco
Malaysia Sarawak
Indian Ocean Western - High seas Areas
Malaysia East
Japan Outer Isl.
Thailand
Russia Barrents Sea
Korea South
Korea North
Peru
Alaska
Malaysia West
Western Sahara (Morocco)
Pacific Eastern Central - High seas Areas
Mauritania
United Kingdom
Chile
Mexico
Malaysia Sabah
Nigeria
Svalbard Isl. (Norway)
Madagascar
Sierra Leone
Canada
Guinea
Greenland
Pakistan
Brazil
Iran
Denmark
Greece
Cameroon
Atlantic Eastern Central - High seas Areas
Namibia
Spain
Taiwan
Papua New Guinea
Atlantic Western Central - High seas Areas
Atlantic Southwest - High seas Areas
Senegal
South Africa
Gillnet catch year
2006 [tonnes]
1597186
1462590
1446008
1443049
789796
711725
639530
634024
566316
464922
436808
355914
272443
244520
225021
181062
155914
152563
146348
136132
132840
127672
118336
117830
117423
113138
106897
103973
103422
103354
100007
96557
95415
92509
83896
83033
82922
79545
73260
71751
67199
62073
59522
58648
58463
54471
51617
51171
49839
49115
48679
47546
45652
44471
42820
39315
38101
32
Gillnet
catch/ Total
catch %
32
86
41
79
32
69
31
9
50
27
91
18
17
21
13
10
20
32
17
27
14
26
53
21
59
2
5
24
18
16
44
6
3
10
27
29
57
60
60
7
71
15
23
13
29
9
18
56
20
12
11
16
16
42
6
10
7
Gillnet catch
Density
[tonnes. km -2]
0.467
2.811
0.887
1.033
0.124
0.032
0.177
0.277
0.055
0.189
5.562
0.255
0.148
0.317
0.099
0.007
0.573
0.978
0.009
1.024
0.051
0.417
0.090
0.248
1.015
0.125
0.003
1.512
0.344
0.003
0.643
0.125
0.047
0.028
0.936
0.383
0.195
0.066
0.459
0.012
0.614
0.026
0.269
0.018
0.356
0.506
0.104
3.483
0.006
0.088
0.088
0.041
0.019
0.006
0.003
0.250
0.036
Cambodia
Angola
Pacific Southwest - High seas Areas
Sweden
Oman
Guyana
Somalia
Yemen
Saudi Arabia Persian Gulf
Faeroe Isl.(Denmark)
USA East Coast
United Arab Emirates
France
Ecuador
Australia
Suriname
Ireland
Gabon
Maldives
Tunisia
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Turkey Black Sea
Turkey Mediterranean Sea
Gambia
Atlantic SouthEast - High seas Areas
New Zealand
Desventuradas Isl.(Chile)
Algeria
Poland
Italy
Ghana
Venezuela
Atlantic Northeast - High seas Areas
Atlantic Northwest - High seas Areas
Canary Isl.(Spain)
Bahrain
Croatia
Andaman & Nicobar Isl. (India)
Solomon Isl.
Pacific Northeast - High seas Areas
Fiji
Tanzania
Sudan
Colombia
Jan Mayen Isl. (Norway)
Saudi Arabia Red Sea
Germany
Argentina
Jamaica
Kuwait
Libya
Sri Lanka
Finland
USA West Coast
Egypt
Haiti
Netherlands
Cote d'Ivoire
USA Golf Of Mexico
Portugal
Latvia
Galapagos Isl.(Ecuador)
Dominican Rep.
Russia Baltic Sea Kaliningrad
Mauritius
Cuba
Congo Republic
Uruguay
Ukraine
Kiribati
37400
36712
36354
32956
31791
31375
28805
28370
25789
25504
25412
25198
24526
23154
21886
19061
18776
18454
18353
17745
17658
16993
15979
15771
15361
15334
14906
14712
13889
12944
12915
12711
11117
11107
10801
10057
9723
9719
9646
9281
9063
8343
8264
7741
7641
7620
7566
7322
7100
6522
6456
6445
6444
6317
6139
5833
5599
5557
5352
4839
4798
4636
4587
4190
4178
4075
3973
3794
3609
3527
33
63
18
16
11
21
59
88
20
26
4
2
29
7
14
13
63
3
43
10
16
14
7
5
49
10
4
13
10
19
10
5
4
2
6
16
33
10
24
48
13
51
35
46
17
25
19
11
1
56
43
47
27
8
1
32
72
5
23
1
4
6
8
42
10
12
20
16
4
16
15
0.782
0.073
0.002
0.194
0.059
0.231
0.035
0.052
0.758
0.095
0.028
0.441
0.073
0.098
0.003
0.149
0.046
0.095
0.020
0.173
0.035
0.099
0.191
0.697
0.001
0.004
0.033
0.114
0.440
0.024
0.057
0.027
0.002
0.004
0.024
1.132
0.172
0.015
0.006
0.002
0.007
0.035
0.094
0.009
0.026
0.041
0.132
0.007
0.027
0.533
0.018
0.012
0.071
0.008
0.023
0.052
0.088
0.032
0.008
0.015
0.150
0.006
0.017
0.360
0.003
0.011
0.098
0.029
0.025
0.001
Qatar
Russia Siberia
Easter Isl.(Chile)
Hong Kong
Panama
Singapore
French Guyana
Mozambique
Mayotte (FR)
Lebanon
French Polynesia
Brunei
Cape Verde
Estonia
Malta
Lithuania
Congo
Cyprus
Israel
Eritrea
Navassa Isl. (Haiti)
Albania
Honduras
Martinique
Lord Howe Isl. (Australia)
Montenegro
Liberia
Trinidad & Matin Isl (BR)
Sao Tome & Principe
Benin
Micronesia
Togo
Trinidad & Tobago
Channel Isl.(UK)
Costa Rica
Madeira Isl.(Portugal)
Brit. Virgin Isl.(UK)
Azores Isl.(Portugal)
Guadeloupe (FR)
Kenya
Christmas Isl.(Australia)
Syria
Macau (China)
El Salvador
Cocos Isl.(Australia)
St Lucia
Puerto Rico (US)
Dominica
Russia Black Sea
Equatorial Guinea
Vanuatu
Gaza Strip
New Caledonia
Marshall Isl.
Seychelles
Timor Leste
Guinea-Bissau
Wallis & Futuna (FR)
Tuvalu
Russia Baltic Sea St Petersburg
Nicaragua
Antigua & Barbuda
Palau
Comoros Isl.
Haiwaii NorthWest Isl.
Anguila (UK)
Falkland Isl.(UK)
St Paul & Amsterdam (FR)
Belgium
St Pierre & Miquelon (FR)
3014
2891
2864
2686
2680
2514
2256
2047
2022
1866
1863
1750
1738
1727
1670
1568
1533
1506
1387
1329
1267
1251
1251
1175
1133
1062
1045
1018
902
895
895
855
843
837
826
804
803
778
654
619
617
603
594
592
560
556
500
494
488
466
427
421
417
396
377
343
331
323
279
275
241
215
213
207
206
180
165
161
159
152
34
18
35
7
5
3
8
44
8
33
22
18
73
25
3
15
7
33
18
24
15
78
38
34
31
35
15
10
22
18
11
4
5
20
3
18
10
62
5
6
23
43
18
3
3
39
37
11
16
5
22
3
21
13
4
1
94
3
50
14
2
1
7
5
4
7
72
0
11
3
42
0.095
0.001
0.004
1.281
0.008
3.055
0.017
0.004
0.032
0.097
0.000
0.069
0.002
0.043
0.030
0.257
1.430
0.015
0.051
0.017
0.110
0.112
0.005
0.025
0.002
0.143
0.004
0.002
0.005
0.030
0.000
0.056
0.011
0.072
0.001
0.002
0.010
0.001
0.007
0.006
0.002
0.059
14.488
0.006
0.001
0.036
0.003
0.017
0.007
0.002
0.001
0.163
0.000
0.000
0.000
0.004
0.003
0.001
0.000
0.022
0.002
0.002
0.000
0.001
0.000
0.002
0.000
0.000
0.046
0.012
Mozambique Channel Isl. (FR)
Haiwaii Main Isl.
Grenada
Ascencion Isl.
Iraq
Tonga
St Vincent & The Grenadines
Monaco
American Samoa
Norfolk Isl. (Australia)
Windward Netherlands Antilles
Arctic Sea - High seas Areas
Cook Isl.(NZ)
St Kitts & Nevis
Indian Ocean Antarctic - High seas Areas
Bahamas
Brit. Indian Oce (UK)
Guam (US)
Montserrat (UK)
Djibouti
Barbados
Bosnia
Tromelin Isl.(FR)
Crozet Isl.(FR)
Leeward Netherland Antilles
Palmyra Atoll & Kingman Reef (US)
Cayman Isl.(UK)
Reunion (FR)
Jordan
Johnston Atoll (US)
Northern Marianas (US)
Kerguelen Isl. (FR)
Nauru
Jarvis Isl.(US)
Slovenia
Bermuda (UK)
Bulgaria
Romania
Tokelau (NZ)
Guatemala
Belize
Georgia
Prince Edward Isl. (SA)
Clipperton Isl.(FR)
Pitcairn (UK)
Samoa
Niue (NZ)
St Helena (UK)
Howland & Baker Isl.(US)
Atlantic Antarctic - High seas Areas
South Georgia & Sandwich Isl. (UK)
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Turks & Caicos Isl. (UK)
Wake Isl.(US)
Pacific Antarctic - High seas Areas
149
145
128
122
107
103
91
86
75
69
69
69
69
67
64
58
56
54
50
50
46
45
42
41
40
37
35
24
22
21
16
16
15
14
14
13
12
10
8
7
5
4
4
4
3
3
1
1
1
1
0
0
0
0
0
0
0
0
35
2
3
12
12
26
15
59
11
6
33
93
88
15
15
4
1
5
2
100
19
17
8
1
5
28
4
100
1
14
3
0
0
1
2
2
8
5
17
31
1
0
5
3
0
100
1
33
2
0
0
0
0
0
0
0
0
0
0
0.000
0.000
0.005
0.000
0.179
0.000
0.003
0.302
0.000
0.000
0.006
0.000
0.000
0.007
0.000
0.000
0.000
0.000
0.007
0.007
0.000
3.214
0.000
0.000
0.001
0.000
0.000
0.000
0.232
0.000
0.000
0.000
0.000
0.000
0.075
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
EEZs in South Asia and South East Asia were c haracterized by a great variety of small
scale/art isanal g illnet f is heries operat ing essent ially in coastal ins hore areas and
,
est uaries, target ing a w ide range of s pec ies. During the last decade, the smallÁscale
f is heries beca me more and more mec hanized as many boats were equipped out board
motors he coastal f is hing co mmunit ies of these reg ions have been severely impacted
. T
by the s una mi of ece mber 2004
T
D
.
yanmar. Drift nets and g illnets are co mmonly used in Myanmar to f is h
pelag ic s pec ies (f inf is h) and de mersal f is h s uc h as marine catf is h and j ewf is h
and s hrimps (Proj ect G lo bal 2011). T he g illnet landed catc h was one the
hig hest of the world in 2006 (1.46 million tonnes). T he g illnet catc h has
almost t ripled in the last decade (0.48 million tonnes in 1996, 1.46 million
tonnes in 2006, SAUP 2011).
‚ M
angladesh. T he Banglades hi g illnet f is heries consisted most ly of art isanal
g illnet d rift nets and set nets target ing de mersal f is h, I ndian salmon and
s hrimps hese g illnets are operated between 8 m and 30 m depth in ins hore
.T
areas all year round excepted d uring the monsoon period (Hossa in 2004).
d d
i
sd b di
s( 8
s i 996 and
T he g llnet lan e catc h ha ou le n 10 year 25 ,000 tonne n 1
437 000 tonnes in 2006) (SAUP 2011) and many of the targeted s pec ies have
,
been overÁexplo ited (Khan et al 200 3) Banglades h is one of the j urisdict ions
.
.
w ith the hig hest density of g illnet catc h per km2.
‚ B
ndia. I ndia f is heries relied heav ily on coastal art isanal g illnet f is heries (4 1% of
the total catc h in 2006) (SAUP 2011). So me rev iews of f is hing cent res in I ndia
indicated the use of motorized boats up to 15 m long deploy ing g illnets
a bout 0. 5Á6 km long up to 70 km fro m the coast (Yous uf 2008). T he g illnet
landed catc h has doubled in the last 10 years (0.68 million tonnes in 1996,
1.44 million tonnes in 2006) (SAUP 2011).
‚ I
ietnam. he g illnet landed catc h in 2006 consisted of more than 86% of the
T
total landed catc h in 2006. It has increased by 4 5% d uring the years 1996 Á
2006 (SAUP 2011). T he g illnet f is hing density was a mong the hig hest in the
world. T he number of g illnet boats and d rift net boats (non mec hanized and
mec hanized) were est imated to be greater than 28000 in 2005 ( ung 2006)
D
.
‚ V
36
o
a. Indo nesia is o ne the to p 5 j urisd ict io ns fo r g illnet catch w ith mo re
‚ Ind nesi
tha n 1. 1 millio n to nnes fo r the yea r 2006 (Table 2). Indo nesia n f is he ries a re
ext re me ly d ive rse. Fis he ries a re most ly s ma ll sca le invo lv ing nume ro us
unpowe red a nd powe red s ma ll sized vesse l (334202 boats in 1998) ost of
. M
the unpowe red boats we re o pe rated in the v ic inity of coasta l v illages by 3 5
f is he rmen a nd a w ide va riety of gea r inc lud ing g illnets. T he f is hing secto r
re presented 2 millio n f is he rmen in 1998 ( AO 20 11)
ll
r pr
d
F
. G i net catch e esente
~30% of the tota l catch fo r both Weste rn a nd Easte rn Indo nesia. G illnet catch
inc reased stead ily by abo ut 4% d uring the last 5 yea rs in both Easte rn a nd
Weste rn Indo nesia (SAUP 20 11).
ll
d d rift nets a re abunda nt ly used in the No rthwest Pac if ic to catch Sockeye,
G i nets a n
Pink a nd C hum sa lmo n a nd sq uids 566 000 to nnes of f is h a nd sq uids we re ca ug ht w ith
.
g illnets a nd d rift net in 2006, re present ing ha lf of the tota l catch Since 1997, the tota l
.
catch a nd the g illnet catch has dec reased pro po rt io na lly by 50% (SAUP 20 11).
acific Russia EEZ. G illnet act iv ity in the Pac if ic Russia EEZ is essent ia lly
do minated by Russia n a nd Ja pa nese la rge sca le d rift net f is he ries ta rget ing
Sockeye, Pink a nd C hum sa lmo ns a nd sq uids (Artukhin et al 20 10) Russia was
.
.
o ne of the few j urisd ict io ns st ill a llow ing lo ng d rift net f is hing in its EEZ T hose
.
la rge sca le f is he ries co mpeted st ro ngly w ith a rt isa na l/s ma ll sca le f is he ries d ue
to the de plet io n of the f is hing stock
‚ P
.
a. (so urce FAO 20 11) W ith 6 34000 to nnes of g illnet catch, C hina is o ne
‚ Chin
of the most impo rta nt playe rs in g illnet f is he ries (SAUP 20 11) In 2004, the
.
r
g
l
o
C
o
d
o
2
o
o
r
d
9
9
37
7
ma ine f is hin f eet f hina c nsiste f
m t ize vesse ls, s how ing
litt le cha nge f ro m 1999 T he a reas in which the vesse ls o pe rated inc luded the
.
o
l
j
ur
d
o
o
nat i na
is ict i n f C hina a nd othe r a reas unde r agree ments between
C hina a nd the East Asia n j urisd ict io ns (inc lud ing Ja pa n, Re public of Ko rea a nd
V iet nam), as we ll as o n the hig h seas Tota l f leet powe r was 13 74 millio n kW
.
.
.
In 2004, the most co mmo n f is hing gea r used was the t raw l net. In te rms of
37
production, t rawlers accounted for 47.6% of catch, g illnets accounted for
around 17%, set nets 15%, lines and hooks 6%, purse se ines 5. 3%, and ot her
f ishing gears 9%. Compared w it h 1999, t he t rawl catch was s imilar, but t he
proportion of g illnet, lines and hooks and purse se ines increased, while t he
proportion of set nets and ot her f ishing gear decreased. T he catch in 2004
i
t
t
i i
i t
ti
i i ti
bas cally reflec ed he ma n f shery resources n he na onal j ur sd c on of
Z
i
t i t
i
i
it i
t
C h na. O u s de he C h nese EE area, squ d, ha r a l, Jack mackerel and unas
were t he ma in target stocks. I n 2004, t here were 4060 marine f ishery v illages,
82 more t han in 1999 and t here were 3 32 million t rad itional f ishermen in
,
.
’
i
i
i
i
i
i
i
t t
i
C h na s mar ne f sher es. F shery v llages were ma nly concen ra ed n
Shandon 946) uan on 896) Z hej ian 6 54) uj ian 522) iaonin 410)
g (
,G
g g (
,
g (
, F
(
, L
g (
0)
i
i
i
t
t
t
i
t
and Ha nan (29 . Fuj an prov nce had he g rea es number n erms of
t rad itional f ishermen 900 000) followed y uan don 660 000) Shandon
(
,
b G
g
g (
,
g
80
000)
380
000)
80
000)
80
000)
Z
i
i
i
i
and L aon ng (1
(5
, hej ang (
, Ha nan (2
.
apan: T he FAO prof ilme was not ava ila ble for t his j urid iction at t he time of
‚ J
writing.
rway (source FAO 20 11) T he fleet was comprised of 9,9 31 vessels in 2003.
‚ No
3 6
i
t
t
t
i
T h s was 25 per cen less han 1999 when here were 1 , 19 vessels. T he ma n
spec ies targeted by t hese vessels were cod and herring. T he fleet is d iv ided
into coastal and offshore administ rative cate ories
i
i
g
. Offshore f sher es are
purse se iners, long liners and t rawlers. T he coastal fleet cons ists of relatively
small vessels, most ly between e ig ht and 13 met res long. T he coastal fleet
t
t
i
it
i t
i i
i
i
generally arge s demersal spec es w h a var e y of f sh ng gear, nclud ng
i t
i
i
i
i
t
i
i
g llne s, handŠl nes, long Šl nes and Dan sh se nes. Cod were he ma n spec es
t i t
i
bo h n erms of volume and value, followed by haddock, ang lerf sh and
sa it he. T hese vessels were operated by 1Š2 f ishermen and were on average
10. 5 g ross tonnage.
land source celand ic isheries 20 11) illnets were ma inly used y small
G
b
. (
I
F
‚ Ice
to intermed iate s ized oats s imilar in s ize to lon liners Each net is a out 50
b
,
g
b
.
0
)
t
t
t
ti
t
t
m long, bu a few (of en around 1 m ne s are ed oge her and a number of
such units placed by each ship. T he nets are left to soak for one nig ht,
38
preferably not longer to maintain the quality of the catch. G illnets are used
extensively during the late winter season when the cod is migrating to the
spawning grounds. T hese fisheries begin in January, reach a peak in March
and end in May. G illnets are used all around Iceland but by far the most
important grounds are south Iceland and south west Iceland where the main
spawning grounds are found (Figure 8). Cod is the primary target for gillnets
as with so many other fishing gears, but large amounts of saithe are also
fished, as well as lesser amounts of haddock, monkfish, ling. Besides cod
gillnets, many specialized versions of bottom gillnets are also used, mainly
differing in mesh size. For example, there are nets optimized for haddock
(140½150 mm mesh size), lumpsuckers (180½270 mm), flatfish (165½200 mm)
and Atlantic halibut (460 mm). Except for the lumpsucker nets, none of these
are in large scale use. Common gillnets used in cod fisheries have a 140 to
204 mm mesh size the former being the minimum allowed in most grounds
,
.
All of these nets are bottom gillnets. Driftnets have only been used in Herring
fisheries (63 mm mesh size) and only prior to 1987 (G unnarsson et al. 1998,
Kristjá nsson 198 3 ó r 2002 ó r 2003 ó r 2005)
,Þ
,Þ
,Þ
Figure 8 Ò Location of effort with gillnets i n 2008 (sets), dark areas i ndicate hig hest effort (source Ice landic
Fis heries 2011).
mall scale fisheries in Peru are widespread and numerous (>100 ports,
‚ Peru. S
>9500 vessels, >37000 fishermen) and operate industrial along the Peruvian
39
coastline (A lfaroþShigueto et al. 20 11). T he s mall scale fis heries have ra pid ly
expanded in recent decades (i. e. 34% and 54% increase in t he number of
fis hermen and vessels (A lfaroþShigueto et al 0 10)
he ma in fis hing gear
.2
. T
cons ists of a variety of met hod includ ing g illnets, d riftnets, tra mmel nets and
botto m setnets (A lfaroþShigueto et al. 20 11). T he s mall scale fis heries are
primarily export oriented and all s pec ies are used ind iscriminately in fis hmeal
prod uct ion, adversely affect ing marine biod ivers ity, conf lict ing also w it h
art isanal s ubs istence fis heries occ urring w it hin 5 miles f ro m t he coast (Sue iro
00 5) he est imated g illnet landed catc h was 11 000 tonnes for 006
. T
3
2 ,
h
i
i
i
i
0
rank ng Peru a mong t e to p 2 most mportant g llnet contr butors g lo bally
(SA UP 0 11)
2
2
.
ile. G illnett ing is a co mmonly used art isanal and large scale fis hing met hod
‚ Ch
in t he EEZ of Chile he g illnet fis heries cons ist of art isanal/ large scale d riftnet
.T
fis heries and art isanal coastal g illnets arge scale d riftnets target ma inly
. L
swordfis h. T he d riftnets mig ht range between 2.4 km and 4.3 km long, 60 m
dee p des pite t he offic ial limitat ion of 47 km (We id ner and Serrano 1997)
,
2.
.
I nd ustrial d riftnet fis heries o perate w it h boats between 18 m and 7 m long
3
.
he number of vessels in t he ind ustrial f leet has red uced by one order of
T
mag nit ude between 1991 and 200 3 (IFO P 2006). A rt isanal d riftnets fis heries
use s horter d riftnets up to 1.8 km long and 4 5 m dee p w it h a mes h s ize a bo ut
5 c m ident ical to ind ustrial d riftnet (We id ner and Serrano 1997) o perated by
,
3 ,
f
h
d
if
9
18
I
s maller boats o
þ
m. n bot cases, r tnets are set between 9 m and 60
m de pt h. T he coastal art isanal g illnets are o perated by s maller boats w it h
s maller mes h (20 c m) set at 1 to 2 miles f ro m t he s hore. T he art isanal g illnet
ma inly targets are j ac k mac kerel, sard ines and anc hov ies. T he re ported landed
catc h of t he SUBPESCA ind icated t hat t hese art isanal g illnet fis heries were t he
ma in contributor of all Chilean g illnet fis heries (4 37,000 tonnes of fis h ca ug ht
in 00 5 þ 006 co mpared to ~ 000 tonnes of fis h ca ug ht by d riftnets in 1995)
2
2
3
(SUBPESCA 2006).
fi h i
f
h
di
dB
i
i
i
T e Me terranean an lac k Sea g llnet s er es cons st mostly o s mall scale art sanal
fis heries o perat ing w it hin 1 miles of t he s hore 80% of t he Euro pean fis hing vessels are
2
.
40
<12m long (~33000 boats). The fis hing met hods are diverse traw ls, driftnets, gillnets,
purse seines and long lines and many boats use multiple gear types (A nc ha 2008).
G illnets are most ly used for ins hore fis heries but a lso in hig h seas area targeting hig h
va lue species (e.g merlin, bluefin tuna, Black Sea turbot). The European Union banned
pe lagic driftnet in 2002 however nonY European Union countries increasing ly use t he m
in t he Mediterranean (OC EANA 2006). Illega l large sca le swordfis h driftnets fis heries are
still operating a ll year long in severa l Mediterranean areas suc h as t he Alboran Sea.
Genera l Fis heries Co mmission for t he Mediterranean adopted a binding reso lution
w here driftnets of any lengt h were pro hibited for capturing large migratory species.
However co mpliance wit h t hese agree ment is far to be co mplete and illega l fis h is still
reported to occur according to OC EANA, (OC EANA 2009, EJF 2007, Secretary of
Co mmerce of t he United State 2008).
I n terms of gillnet fis heries in t he Mediterranean G reece has t he largest f leet wit h 21000
,
boats and is a lso t he main European gillnet catc h contributor (Gerosa and Casa le 1999 ).
France has 742 boats of an average lengt h of 7mY9m using gillnet driftnet encirc ling
,
,
nets to target brea ms, so le hake, red mullets and crustacean in t he Mediterranean
invo lving ~1000 fis hermen (IFREMER 2011).
T urkey is a lso an important gillnet player wit h t he lack Sea turbot fis hery invo lving 185
B
boats operating 19000 botto m gillnets fro m six ports in western T urkey (Oztürk 2001)
Morocco Mediterranean fis heries was t he bulk of large sca le driftnet fis hing nations wit h
a f leet invo lving 117 vesse ls using driftnets up to 14 km long (T ude la et a l. 2005).
However t he Moroccan Government is phasing out of Morocco’s driftnet f leet under t he
EUYMorocco Fis heries Partners hip Agree ment and initiatives wit h t he United State
(Secretary of Co mmerce of t he United States 2008)
orocco. I n its At lantic fis heries, Morocco wit h 259,000 tonnes of gillnet
catc h in 2006 is one of t he 10 biggest contributors of gillnet catc h g lo ba lly.
Morocco's gillnet fis heries are represented by an artisana l fis hery sector
operating in coasta l areas and large sca le driftnet swordfis h fis hery operating
in t he Mediterranean described previous ly. The artisana l fis hery consists of
around 18000 s ma ll wooden boats (<6m long) wit h out board engines. The
‚ M
41
main fishing gear used are gillnets to catch sma ll species. Most of the catch
supplies loca l markets (Franquesa et a l. 2001).
auritania. (source FAO 2011) W ith 100000 tonnes of fish caught with
gillnets in 2006, Mauritania is an important player in gillnet bycatch.
ll
l
ll
l
l
Mauritanian gi net fisheries are most y sma sca e/artisana fisheries
supplying loca l markets. T he artisana l fishing sector consisted in 3000 dugout
boats and 10000 fishermen.
‚ M
uth Africa. Gillnets used in South Africa consist only of the shark gillnet
fishery. T hey are used to protect the swimmers from shark attacks. T he overa ll
length of shark nets is 27 km deployed in 38 loca lities hey are usua lly set
.5
. T
at 400 m from the coast in sha llow water, in 2 or 3 rows. T he dimension of the
net ranged between 200 m and 300 m in length with wide stretched mesh
(50cm) (Kwazulu®Nata l Sharks Board 2011).
‚ So
w Zealand. (source: New Zea land Ministry of Fishery 2011). Gillnet fisheries
in New Zea land were most ly represented by setnet fisheries (6278 tonnes in
2006) and inshore driftnet fisheries (44 tonnes in 2006) he number of vesse ls
.T
ll
l
4
7
participating in gi netting in New Zea and was 5 in 2006 but decreased to
304 vesse ls in 2009. 87% of those vesse ls were less than 12 m long. T he top 5
targets species by tota l net length in order were: f latfish, rig, schoo l shark,
grey mullet and tarakihi. T he number of fishing events by net length, mesh
size and net height are presented in the Table 3. T he distribution of the gillnet
catch for the period 2006 ®2010 is presented in Figure 9.
‚ Ne
42
Table 3 Ã The size of gi llnets used i n New Zealand by count of fis hi ng event (source New Zealand Mi nist ry of
Fis hery 2011).
Measure
Total net length (m)
Net height (m)
Mesh Size (mm)
Category
<400
400 to <600
600 to <800
800 to <1000
1000 to <1200
Over 1200
Unknown
<2
2 to <2.6
2.6 to <3
3 to <4
4 & over
Unknown
<120
120 to <125
125 to <130
130 to <175
175 & over
Unknown
2006/2007
4,151
4,642
5,007
3,674
4,468
4,716
3
1,628
1,611
1,358
2,369
1,782
17,913
5,114
4,196
7,858
6,143
2,833
517
2007/2008
3,630
3,794
4,688
3,180
3,540
4,111
2008/2009
3,017
4,317
4,163
3,455
3,588
3,916
1,561
1,377
1,744
1,923
1,903
14,435
4,645
3,343
6,881
4,868
2,726
480
1,538
1,121
1,553
1,606
2,107
14,531
5,129
2,598
6,919
4,523
2,476
811
2009/2010
3,028
4,302
4,283
4,064
3,986
4,144
4
1,637
1,234
1,730
1,642
2,064
15,504
5,237
2,465
8,119
4,427
2,854
709
Table 4 Ã The number of gi llnet captures reported by fis hermenwithi n New Zealand EEZ for species listed by
the Conventionon Migratory Species (source New Zealand Mi nist ry of Fis hery 2011).
Species Name
Common dolphin
Dusky dolphin
Green Turtle
Humpback Whale
Dolphins and Toothed Whales
White Pointer Shark
Southern Giant Petrel
White -chinned Petrel
2008/2009
1
0
1
1
3
3
1
0
2009/2010
3
1
0
0
0
5
0
1
43
Figure 9 ì Total estimated catch for all gi llnetti ng events for t he period 2006 ì2010 i n t he New Zealand EEZ
(source New Zealand Mi nistry of Fis hery 2011).
The total number of captures for t he CMS species reported by fis hermen since
t he introduction of t he nonfis h protected species catc h return are detailed in
Table 4.
44
The analysis outputs were presented in tabular form and ma pped to s how relat ive
ex posure levels wit hin eac h EEZ. For all s pecies summed, Figure 10 s hows t he areas
w here most ex posure occurs (red colours).
Figure 10 J EEZs and High Seas FAO areas s howi ng with the IUCN weighted exposures summed across species.
A reas with colours furthest up the scale bar (red colours) had higher species exposures.
The 30 EEZs having t he hig hest ex posure, for t he sum of all s pecies was ex plored (Table
5).
45
Table 5 p EEZ and high seas FAO areas prese nting t he highest ex posu re fo r all species (to p 30 ranked
j u risdictio ns in desce nding o rde r of impo rtance).
Sum of all species IUCN
weighted exposures in the
EEZ
Rank
1
EEZ or high seas FAO area
Myanmar
1.54
2
Vietnam
1.52
3
Peru
1.49
4
India
1.43
5
Russia Pacific
1.29
6
Chile
1.28
7
South Africa
1.27
8
China
1.27
9
Namibia
1.25
10
Greece
1.20
Galapagos Isl.(Ecuador)
1.16
Bangladesh
1.13
11
12
13
14
Japan Main Isl.
1.12
Indonesia (Western)
1.11
1.07
15
Indonesia (Eastern)
16
Norway
1.06
17
Mauritania
1.01
18
United Kingdom
0.99
19
Algeria
0.98
20
Morocco
0.95
21
Western Sahara (Morocco)
0.95
22
Pacific Western Central - High seas Areas
0.92
23
Iceland
0.91
24
Tunisia
0.87
Japan Outer Isl.
0.86
26
Turkey Mediterranean Sea
0.85
27
Pacific Northwest - High seas Areas
0.85
28
Philippines
0.84
29
Bahrain
0.83
30
Korea South
0.81
25
The most exposed species, using t he IUCN weig hted o utcomes were sorted into 3
categories; most exposed (pink), moderately exposed (green) and least exposed (blue).
A ll five species gro ups in t he st udy were represented wit hin t he top 40 most exposed
species to gillnet fis hing (Ta ble 6).
46
Table 6 ¹Species ranked by IUCN¹weighted exposure. All species. T hose marked wit h pink shading are t he
most exposed 40 species, t hose shaded green were t he moderately exposed 40 species, and t hose shaded blue
t he least exposed species
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Species
code
NPH
ORB
MMN
SPD
DUG
EIM
LPK
PEG
DCC
LOF
EBJ
POT
EBG
SYW
PTG
PIR
PHG
CAC
CHM
SPH
TUA
LPV
CEH
BOB
BAP
BMU
PUM
SOC
CTM
IPA
POS
PHA
PUC
RHT
LOP
BEB
CCC
BAO
LMN
LAU
IOX
PYM
DIM
PCR
POB
PHN
HYA
Family
cetacean
cetacean
marine mammals other
seabirds
cetacean
turtle
turtle
seabirds
turtle
marine mammals other
cetacean
cetacean
cetacean
seabirds
seabirds
seabirds
seabirds
turtle
turtle
seabirds
cetacean
turtle
cetacean
cetacean
cetacean
cetacean
seabirds
cetacean
shark
shark
cetacean
seabirds
seabirds
shark
marine mammals other
cetacean
shark
cetacean
shark
seabirds
shark
cetacean
seabirds
seabirds
cetacean
seabirds
cetacean
species
Neophocaena phocaenoides
Orcaella brevirostris
Monachus monachus
Spheniscus demersus
Dugong dugon
Eretmochelys imbricata
Lepidochelys kempii
Pelecanoides garnotii
Dermochelys coriacea
Lontra felina
Eubalaena japonica
Sousa teuszii
Eubalaena glacialis
Synthliboramphus wumizusume
Pterodroma phaeopygia
Phoebastria_irrorata
Phalacrocorax nigrogularis
Caretta caretta
Chelonia mydas
Spheniscus humboldti
Tursiops aduncus
Lepidochelys olivacea
Cephalorhynchus heavisidii
Balaenoptera borealis
Balaenoptera physalus
Balaenoptera musculus
Puffinus mauretanicus
Sousa chinensis
Cetorhinus maximus
Isurus paucus
Phocoena spinipinnis
Phoebastria_albatrus
Puffinus creatopus
Rhincodon typus
Lontra provocax
Berardius bairdii
Carcharodon carcharias
Balaenoptera omurai
Lamna nasus
Larus audouinii
Isurus oxyrinchus
Physeter macrocephalus
Thalassarche_melanophrys
Pelecanus crispus
Pontoporia blainvillei
Phoebastria_nigripes
Hyperoodon ampullatus
47
Common name
Finless Porpoise
Irrawaddy Dolphin
Mediterranean Monk Seal
African Penguin
Dugong Sea Cow Dugong
Hawksbill Turtle
Kemp's Ridley Turtle
Peruvian diving petrel
Leatherback Turtle
Marine Otter
North Pacific Right Whale
Atlantic Hump-backed Dolphin
Northern Right Whale
Japanese Murrelet
Dark-rumped Petrel
Waved Albatross
Socotra Cormorant
Loggerhead Turtle
Green Turtle
Humboldt Penguin
Indian or Bottlenose Dolphin
Ridley Turtle
Heaviside's Dolphin
Sei Whale
Fin Whale
Blue Whale
Balearic shearwater
Indo-Pacific Humpbacked Dolphin
Basking shark
Longfin Mako shark
Burmeister Porpoise
Short-tailed Albatross
Pink-footed Shearwater
Whale Shark
Southern River Otter
Baird's Beaked Whale
Great White Shark
Omura' Whale
Porbeagle shark
Audouin's Gull
Shortfin Mako shark
Sperm Whale
Black-browed Albatross
Dalmatian Pelican
La Plata Dolphin
Black-footed Albatross
Northern Bottlenose Whale
IUCN
weighted
exposure
2.466
2.421
2.204
2.201
2.164
2.073
2.009
1.972
1.965
1.852
1.842
1.795
1.779
1.762
1.743
1.642
1.592
1.572
1.484
1.466
1.433
1.386
1.383
1.369
1.366
1.324
1.269
1.267
1.234
1.140
1.131
1.131
1.116
1.113
1.102
1.097
1.094
1.094
1.090
1.085
1.075
1.019
1.004
0.972
0.971
0.941
0.915
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
SNL
CEE
OOR
PHF
THH
LAT
LGO
DEL
LGS
SNC
LLE
STM
PCW
GLM
MMO
PRK
CEC
PRO
DIC
POW
DIP
DIX
PHI
PCO
BAB
POD
HGR
LIC
PTT
POP
LGE
DNB
PHV
LML
BAM
SBG
LHM
DAL
LGA
LGB
THC
PCI
ORH
GRG
LAA
PCC
DDE
LGH
OFL
PHE
SNA
SNR
TUT
MNV
EBA
MAI
MAH
cetacean
cetacean
cetacean
seabirds
seabirds
seabirds
cetacean
cetacean
cetacean
cetacean
seabirds
seabirds
seabirds
cetacean
cetacean
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
cetacean
marine mammals other
seabirds
seabirds
cetacean
seabirds
seabirds
marine mammals other
seabirds
cetacean
seabirds
seabirds
cetacean
cetacean
cetacean
seabirds
seabirds
cetacean
cetacean
seabirds
seabirds
cetacean
cetacean
marine mammals other
seabirds
cetacean
cetacean
cetacean
cetacean
cetacean
seabirds
seabirds
Stenella longirostris
Cephalorhynchus eutropia
Orcinus orca
Phoebetria fusca
Thalassarche_chlororhynchos
Larus atlanticus
Lagenorhynchus obscurus
Delphinapterus leucas
Lagenorhynchus australis
Stenella clymene
Larus leucophthalmus
Sterna maxima
Procellaria westlandica
Globicephala melas
Monodon monoceros
Procellaria parkinsoni
Cephalorhynchus commersonii
Procellaria aequinoctialis
Thalassarche_chrysostoma
Pterodroma cahow
Diomedea epomophora
Diomedea exulans
Phoebastria_immutabilis
Procellaria conspicillata
Balaenoptera bonaerensis
Phocoena dioptrica
Halichoerus grypus
Larus ichthyaetus
Pterodroma atrata
Phocoena phocoena
Larus genei
Thalassarche_bulleri
Phoca vitulina
Larus melanocephalus
Balaena mysticetus
Sterna bergii
Larus hemprichii
Phocoenoides dalli
Lagenorhynchus acutus
Lagenorhynchus albirostris
Thalassarche_cauta
Procellaria cinerea
Orcaella heinsohni
Grampus griseus
Larus armenicus
Pelecanus onocrotalus
Delphinus delphis
Lagenodelphis hosei
Arctocephalus australis
Phoebetria palpebrata
Stenella attenuata
Stenella coeruleoalba
Tursiops truncatus
Megaptera novaeangliae
Eubalaena australis
Macronectes giganteus
Macronectes halli
48
Spinner Dolphin
Chilean Dolphin
Killer whale
Sooty Albatross
Yellow-nosed Albatross
Olrog's Gull
Dusky Dolphin
White Whale
Peale's Dolphin
Clymene dolphin
White-eyed Gull
Royal Tern
Westland Petrel
Long-finned Pilot Whale
Narwhal
Black Petrel
Commerson's Dolphin
White-chinned Petrel
Grey-headed Albatross
Cahow Bermuda Petrel
Royal Albatross
Wandering Albatross
Laysan Albatross
Spectacled Petrel
Antarctic Minke whale
Spectacled Porpoise
Grey Seal
Great Black-headed Gull
Henderson Petrel
Common Porpoise
Slender-billed Gull
Buller's Albatross
Common Seal
Mediterranean Gull
Bowhead Whale
Great Crested Tern
Sooty Gull
Dall's Porpoise
Atlantic White-sided Dolphin
White-beaked Dolphin
Shy Albatross
Grey Petrel
Australian Snubfin dolphin
Risso's Dolphin
Armenian Gull
White Pelican
Common Dolphin
Fraser's Dolphin
South American Seal
Light-mantled Sooty Albatross
Pantropical Spotted Dolphin
Striped Dolphin
Bottlenosed Dolphin
Humpback Whale
Southern Right Whale
Southern Giant Petrel
Northern Giant Petrel
0.906
0.852
0.849
0.830
0.829
0.816
0.764
0.764
0.754
0.752
0.748
0.720
0.718
0.678
0.675
0.658
0.636
0.621
0.592
0.591
0.584
0.575
0.571
0.564
0.549
0.530
0.522
0.518
0.511
0.504
0.485
0.471
0.470
0.462
0.448
0.429
0.428
0.428
0.419
0.417
0.408
0.405
0.402
0.399
0.390
0.384
0.373
0.372
0.369
0.364
0.361
0.355
0.351
0.341
0.235
0.195
0.191
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
PXP
STB
STI
LSA
DAM
STE
BAE
LRL
CAM
STV
STR
STS
STG
STN
STF
SDG
CAT
STH
STP
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Phalacrocorax pygmeus
Sterna bernsteini
Sterna lorata
Larus saundersi
Diomedea amsterdamensis
Sterna balaenarum
Balaenoptera edeni
Larus relictus
Caperea marginata
Sterna sandvicensis
Sterna repressa
Sterna saundersi
Sterna bengalensis
Sterna nilotica
Sterna albifrons
Sterna dougallii
Sterna caspia
Sterna hirundo
Sterna paradisaea
Pygmy Cormorant
Chinese Crested Tern
Peruvian tern
Saunder's Gull
Amsterdam Albatross
Damara Tern
Bryde's whale
Relict Gull
Pygmy Right whale
Sandwich Tern
White-cheeked Tern
Saunder's Tern
Lesser Crested Tern
Gull-billed Tern
Little Tern
Roseate Tern
Caspian Tern
Common Tern
Arctic Tern
0.184
0.024
0.024
0.020
0.012
0.011
0.009
0.006
0.006
0.006
0.005
0.005
0.005
0.005
0.005
0.005
0.005
0.004
0.002
The res ults in t his sect ion a re prese nted wit h a table of s pecies leve l rat ings fo r s ix
s pecies g roups (cetaceans, seabirds, pinnipeds & otters, t urt les and s ha rks). The res ults
in t he first table s ums t he expos ure fo r CMS s pecies ac ross all fis hery a reas; second t he
info rmat ion is prese nted in map fo rm, dis playing t he s pat ial dist ribut ion of s ummed
s pecies in t he g roup and plotted by EEZ; t hirdly, t he cont ribut ion of expos ure f rom eac h
EEZ is tabulated, and t hose wit h t he g reatest cont ribut ion included.
Cetaceans & Sirenians
This s pecies g roup was most affected in Sout heast As ia, Sout h As ia, East As ia, No rt heast
Pacific, No rt hern Europe and Sout h A merica (Figure 11). G illnet expos ure affects s maller
coastal dwe lling s pecies as we ll la rge w hales (Table 7). Cetaceans a re s pread eve nly
betwee n t he hig hest, medium and lowest ris k g roupings in Table 7. The EEZs w here t he
expos ure occurred a re set out in Table 8.
49
Figure 11 : EEZs and High Seas FAO areas s howi ng wit h t he IUCN weighted exposures summed across
cetaceans. A reas wit h colours furt hest up t he scale bar (red colours) had higher cetaceanexposures.
50
Table 7 _ Cetaceans ranked by thei r IUCN_weig hted exposure. Those ma rked with pink s hading a re the most
exposed 40 species, those s haded gree n were the moderate ly exposed 40 species, and those s haded blue the
least exposed species
Rank
1
2
5
11
12
13
21
23
24
25
26
28
31
36
38
42
45
47
48
49
50
54
55
56
57
61
62
64
72
73
77
82
85
86
87
90
91
94
95
98
99
100
101
102
111
113
Species
code
NPH
ORB
DUG
EBJ
POT
EBG
TUA
CEH
BOB
BAP
BMU
SOC
POS
BEB
BAO
PYM
POB
HYA
SNL
CEE
OOR
LGO
DEL
LGS
SNC
GLM
MMO
CEC
BAB
POD
POP
BAM
DAL
LGA
LGB
ORH
GRG
DDE
LGH
SNA
SNR
TUT
MNV
EBA
BAE
CAM
Family
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
species
Neophocaena phocaenoides
Orcaella brevirostris
Dugong dugon
Eubalaena japonica
Sousa teuszii
Eubalaena glacialis
Tursiops aduncus
Cephalorhynchus heavisidii
Balaenoptera borealis
Balaenoptera physalus
Balaenoptera musculus
Sousa chinensis
Phocoena spinipinnis
Berardius bairdii
Balaenoptera omurai
Physeter macrocephalus
Pontoporia blainvillei
Hyperoodon ampullatus
Stenella longirostris
Cephalorhynchus eutropia
Orcinus orca
Lagenorhynchus obscurus
Delphinapterus leucas
Lagenorhynchus australis
Stenella clymene
Globicephala melas
Monodon monoceros
Cephalorhynchus commersonii
Balaenoptera bonaerensis
Phocoena dioptrica
Phocoena phocoena
Balaena mysticetus
Phocoenoides dalli
Lagenorhynchus acutus
Lagenorhynchus albirostris
Orcaella heinsohni
Grampus griseus
Delphinus delphis
Lagenodelphis hosei
Stenella attenuate
Stenella coeruleoalba
Tursiops truncatus
Megaptera novaeangliae
Eubalaena australis
Balaenoptera edeni
Caperea marginata
Common name
Finless Porpoise
Irrawaddy Dolphin
Dugong Sea Cow Dugong
North Pacific Right Whale
Atlantic Hump-backed Dolphin
Northern Right Whale
Indian or Bottlenose Dolphin
Heaviside's Dolphin
Sei Whale
Fin Whale
Blue Whale
Indo-Pacific Humpbacked Dolphin
Burmeister Porpoise
Baird's Beaked Whale
Omura' Whale
Sperm Whale
La Plata Dolphin
Northern Bottlenose Whale
Spinner Dolphin
Chilean Dolphin
Killer whale
Dusky Dolphin
White Whale
Peale's Dolphin
Clymene dolphin
Long-finned Pilot Whale
Narwhal
Commerson's Dolphin
Antarctic Minke whale
Spectacled Porpoise
Common Porpoise
Bowhead Whale
Dall's Porpoise
Atlantic White-sided Dolphin
White-beaked Dolphin
Australian Snubfin dolphin
Risso's Dolphin
Common Dolphin
Fraser's Dolphin
Pantropical Spotted Dolphin
Striped Dolphin
Bottlenosed Dolphin
Humpback Whale
Southern Right Whale
Bryde's whale
Pygmy Right whale
51
IUCN
weighted
exposure
2.466
2.421
2.164
1.842
1.795
1.779
1.433
1.383
1.369
1.366
1.324
1.267
1.131
1.097
1.094
1.019
0.971
0.915
0.906
0.852
0.849
0.764
0.764
0.754
0.752
0.678
0.675
0.636
0.549
0.530
0.504
0.448
0.428
0.419
0.417
0.402
0.399
0.373
0.372
0.361
0.355
0.351
0.341
0.235
0.009
0.006
Table 8 … EEZ and high seas FAO areas prese nting t he highest ex posure fo r all t he cetacean & sire nians listed in
desce nding o rde r of impo rtance.
EEZ or high seas FAO area
Vietnam
Myanmar
India
China
Indonesia (Western)
Russia Pacific
Indonesia (Eastern)
Japan Main Isl.
Norway
Bangladesh
Chile
Philippines
Pacific Northwest - High Seas Areas
Indian Ocean Eastern - High Seas Areas
Iceland
Malaysia Sarawak
Korea South
Malaysia East
Malaysia Sabah
Thailand
Malaysia West
Japan Outer Isl.
Korea North
Canada
United Kingdom
Angola
Pacific Western Central - High Seas Areas
South Africa
Brazil
Mauritania
Cambodia
Taiwan
Peru
Western Sahara (Morocco)
Namibia
Alaska
Madagascar
Argentina
Australia
Pacific Southeast - High Seas Areas
Morocco
Nigeria
Pakistan
Guinea
Papua New Guinea
Sierra Leone
Mexico
USA East Coast
Greenland
Indian Ocean Western - High Seas Areas
Senegal
Svalbard Isl. (Norway)
Atlantic Southwest - High Seas Areas
Cameroon
Pacific Eastern Central - High Seas Areas
Ireland
Pacific Southwest - High Seas Areas
Iran
Russia Barrents Sea
Faeroe Isl.(Denmark)
France
Sum of all cetacean and
sirenian IUCN weighted
exposures in the EEZ
1.000
0.953
0.903
0.801
0.751
0.743
0.733
0.655
0.642
0.635
0.571
0.570
0.549
0.536
0.521
0.518
0.516
0.507
0.502
0.502
0.497
0.486
0.468
0.419
0.416
0.405
0.403
0.394
0.388
0.386
0.384
0.383
0.378
0.374
0.373
0.373
0.354
0.348
0.340
0.333
0.328
0.324
0.322
0.317
0.317
0.317
0.309
0.309
0.308
0.306
0.297
0.296
0.291
0.289
0.288
0.283
0.278
0.276
0.273
0.265
0.265
52
Seabirds
Seabirds are most affected by gillnet f ishing in Sout h A merica Sout h Af rica & Namibia
,
,
New Zea land and nort heast Pacif ic (Figure 12). They are a lso hig hly exposed in most of
t he sout hern and cent ra l hig h seas areas. The mode of interact ions wit h gillnets was
apparent for t his s pecies group wit h many of t he d iving seabirds more exposed to
gillnet f ishing t han s urface feeders (Table 9). Seabirds were represented in t he hig hest,
med ium and least exposed groups. The expos ure in EEZs most cont ribut ing for seabirds
is set out in Table 10.
Figure 12 Õ EEZs and High Seas FAO areas s howi ng wit h t he IUCN weighted exposures summed across
seabi rds. A reas wit h colours furt hest up t he scale bar (red colours) had higher seabi rd exposures.
53
Table 9 ú Seabird I UCNúweighted exposu re
Rank
4
8
14
15
16
17
20
27
32
33
40
43
44
46
51
52
53
58
59
60
63
65
66
67
68
69
70
71
75
76
78
79
81
83
84
88
89
92
93
97
103
104
105
106
107
108
109
110
112
114
115
116
Species
code
PEG
SYW
PTG
PIR
PHG
SPH
PUM
PHA
PUC
LAU
DIM
PCR
PHN
PHF
THH
LAT
LLE
STM
PCW
PRK
PRO
DIC
POW
DIP
DIX
PHI
PCO
LIC
PTT
LGE
DNB
LML
SBG
LHM
THC
PCI
LAA
PCC
PHE
MAI
MAH
PXP
STB
STI
LSA
DAM
STE
LRL
STV
STR
STS
STG
Family
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
species
Pelecanoides garnotii
Synthliboramphus wumizusume
Pterodroma phaeopygia
Phoebastria_irrorata
Phalacrocorax nigrogularis
Spheniscus humboldti
Puffinus mauretanicus
Phoebastria_albatrus
Puffinus creatopus
Larus audouinii
Thalassarche_melanophrys
Pelecanus crispus
Phoebastria_nigripes
Phoebetria fusca
Thalassarche_chlororhynchos
Larus atlanticus
Larus leucophthalmus
Sterna maxima
Procellaria westlandica
Procellaria parkinsoni
Procellaria aequinoctialis
Thalassarche_chrysostoma
Pterodroma cahow
Diomedea epomophora
Diomedea exulans
Phoebastria_immutabilis
Procellaria conspicillata
Larus ichthyaetus
Pterodroma atrata
Larus genei
Thalassarche_bulleri
Larus melanocephalus
Sterna bergii
Larus hemprichii
Thalassarche_cauta
Procellaria cinerea
Larus armenicus
Pelecanus onocrotalus
Phoebetria palpebrata
Macronectes giganteus
Macronectes halli
Phalacrocorax pygmeus
Sterna bernsteini
Sterna lorata
Larus saundersi
Diomedea amsterdamensis
Sterna balaenarum
Larus relictus
Sterna sandvicensis
Sterna repressa
Sterna saundersi
Sterna bengalensis
Common name
Peruvian diving petrel
Japanese Murrelet
Dark-rumped Petrel
Waved Albatross
Socotra Cormorant
Humboldt Penguin
Balearic shearwater
Short-tailed Albatross
Pink-footed Shearwater
Audouin's Gull
Black-browed Albatross
Dalmatian Pelican
Black-footed Albatross
Sooty Albatross
Yellow-nosed Albatross
Olrog's Gull
White-eyed Gull
Royal Tern
Westland Petrel
Black Petrel
White-chinned Petrel
Grey-headed Albatross
Cahow Bermuda Petrel
Royal Albatross
Wandering Albatross
Laysan Albatross
Spectacled Petrel
Great Black-headed Gull
Henderson Petrel
Slender-billed Gull
Buller's Albatross
Mediterranean Gull
Great Crested Tern
Sooty Gull
Shy Albatross
Grey Petrel
Armenian Gull
White Pelican
Light-mantled Sooty Albatross
Southern Giant Petrel
Northern Giant Petrel
Pygmy Cormorant
Chinese Crested Tern
Peruvian tern
Saunder's Gull
Amsterdam Albatross
Damara Tern
Relict Gull
Sandwich Tern
White-cheeked Tern
Saunder's Tern
Lesser Crested Tern
54
IUCN
weighted
exposure
1.972
1.762
1.743
1.642
1.592
1.466
1.269
1.131
1.116
1.085
1.004
0.972
0.941
0.830
0.829
0.816
0.748
0.720
0.718
0.658
0.621
0.592
0.591
0.584
0.575
0.571
0.564
0.518
0.511
0.485
0.471
0.462
0.429
0.428
0.408
0.405
0.390
0.384
0.364
0.195
0.191
0.184
0.024
0.024
0.020
0.012
0.011
0.006
0.006
0.005
0.005
0.005
117
118
119
120
121
122
123
STN
STF
SDG
CAT
STH
STP
PEG
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Sterna nilotica
Sterna albifrons
Sterna dougallii
Sterna caspia
Sterna hirundo
Sterna paradisaea
Pelecanoides garnotii
Gull-billed Tern
Little Tern
Roseate Tern
Caspian Tern
Common Tern
Arctic Tern
Peruvian diving petrel
55
0.005
0.005
0.005
0.005
0.004
0.002
1.972
Table 10 EEZ and high seas FAO areas presenti ng t he highest ex posure for all t he seabi rds i n descendi ng
order of importance
EEZ or high seas FAO area
Peru
Chile
South Africa
Pacific Southeast - High Seas Areas
Namibia
Indian Ocean Eastern - High Seas Areas
New Zealand
Galapagos Isl.(Ecuador)
Atlantic Southwest - High Seas Areas
Japan Main Isl.
Pacific Southwest - High Seas Areas
Russia Pacific
Pacific Eastern Central - High Seas Areas
Argentina
Morocco
Japan Outer Isl.
Indian Ocean Western - High Seas Areas
Iran
Atlantic SouthEast - High Seas Areas
Yemen
Australia
India
Angola
Brazil
Greece
Turkey Mediterranean Sea
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Pacific Northwest - High Seas Areas
Mexico
Egypt
Alaska
Mauritania
Spain
United Arab Emirates
Ecuador
Somalia
Uruguay
China
Pacific Western Central - High Seas Areas
Pakistan
Western Sahara (Morocco)
Bahrain
Oman
Korea South
Saudi Arabia Persian Gulf
Italy
Tunisia
Saudi Arabia Red Sea
Algeria
France
Senegal
Croatia
Sudan
Kuwait
Qatar
Pacific Northeast - High Seas Areas
Canada
Falkland Isl.(UK)
Lebanon
Gambia
Mozambique
Sum of all seabird IUCN
weighted exposures in the EEZ
0.576
0.566
0.436
0.384
0.366
0.321
0.314
0.279
0.275
0.264
0.257
0.242
0.226
0.222
0.222
0.221
0.201
0.188
0.185
0.180
0.176
0.175
0.172
0.172
0.161
0.160
0.159
0.156
0.155
0.152
0.149
0.146
0.142
0.142
0.141
0.141
0.140
0.135
0.134
0.131
0.129
0.125
0.125
0.123
0.123
0.120
0.117
0.112
0.108
0.106
0.099
0.097
0.092
0.091
0.089
0.088
0.086
0.085
0.083
0.081
0.080
56
Seals and otters IUCN?weighted exp osure
Seals and otters are most exposed to gillnet fishing in Sout h America ast of
, E
o rt h Af rica and o rt hern uro pe (Figure 13) he most exposed
Mediterranean Sea
, N
N
E
.T
spec ies included Mediterranean Mo nk Seal, fo llowed by t he two otter spec ies, all in t he
most exposed g roup of spec ies (Ta ble 11). T he EEZs co nt ributing most to t he expos ure
are set out in Ta ble 12.
Figure 13 t EEZs and High Seas FAO areas s howi ng wit h t he IUCN weighted exposures summed across
i
p nni peds and otters. A reas wit h colours furt hest up t he scale bar (red colours) had higher pi nni ped and otter
exposures.
57
Table 11 ™ Seals and otters ranked by thei r IUCN™weighted exposure. Those marked with pi nk s hadi ng are the
most exposed 40 species those s haded g reen were the moderately exposed 40 species, and those s haded blue
the least exposed specie ,
Rank
3
10
35
74
80
96
Species
code
MMN
LOF
LOP
HGR
PHV
OFL
Family
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
species
Monachus monachus
Lontra feline
Lontra provocax
Halichoerus grypus
Phoca vitulina
Arctocephalus australis
Common name
Mediterranean Monk Seal
Marine Otter
Southern River Otter
Grey Seal
Common Seal
South American Seal
IUCN weighted
exposure
2.204
1.852
1.102
0.522
0.470
0.369
Table 12 ™ EEZ and high seas FAO areas presenti ng the highest exposure fo r all the seals and otters i n
descendi ng o rder of i mpo rtance.
Sum of all seal and otter
IUCN weighted exposures
in the EEZ
0.242
0.152
0.149
0.122
0.114
0.107
0.106
0.099
0.063
0.062
0.052
0.043
0.037
0.035
0.034
0.033
0.032
0.031
0.028
0.028
0.028
0.026
0.025
0.023
0.023
0.022
0.022
0.022
0.021
0.021
0.018
EEZ or high seas FAO area
Chile
Peru
Greece
Algeria
Argentina
Tunisia
Turkey Mediterranean Sea
Croatia
Norway
Montenegro
Iceland
United Kingdom
Sweden
Russia Barrents Sea
Denmark
Madeira Isl.(Portugal)
Canada
Faeroe Isl.(Denmark)
Bosnia
Poland
Ireland
Russia Pacific
Finland
France
Albania
Germany
Netherlands
Latvia
USA East Coast
Russia Baltic Sea Kaliningrad
Cyprus
58
Turtle IUCNËweighted exposure
Turtles we re most affected by gillnet f ishing in so ut h Asia, so ut heast Asia, east Asia,
no rt hwest Af rica, weste rn Europe, Mexico a nd Ja pa n (Fig ure 14).
T his species g ro up may be highly affected by gillnet f ishing wit h all t urtle species
represented wit hin t he top 40 species most exposed to gillnet f ishing (Ta ble 13) T he
EEZs cont ribut ing t he g reatest components of t he risk to t urtles a re set o ut in Ta ble 14.
Figure 14 EEZs and Hig h Seas FAO a reas s howi ng with t he IUCN weig hted exposures su mmed ac ross turtles.
A reas wit h co lours furthest u p the scale ba r (red co lours) had hig her turt le exposures.
"
59
Table 13 ( Turt les ra nked by their IUCN(weig hted ex posure. Those ma rked wit h pi nk s hadi ng a re t he most
exposed 40 species, those s haded green we re t he mode rately exposed 40 species, a nd t hose s haded blue t he
least exposed species
Rank
6
7
9
18
19
22
Species
code
EIM
LPK
DCC
CAC
CHM
LPV
Family
turtle
turtle
turtle
turtle
turtle
turtle
species
Eretmochelys imbricata
Lepidochelys kempii
Dermochelys coriacea
Caretta caretta
Chelonia mydas
Lepidochelys olivacea
Common name
Hawksbill Turtle
Kemp's Ridley Turtle
Leatherback Turtle
Loggerhead Turtle
Green Turtle
Ridley Turtle
60
IUCN
weighted
exposure
2.073
2.009
1.965
1.572
1.484
1.386
Table 14 O EEZ and hig h seas FAO areas prese nting t he hig hest ex posure fo r a ll t he turt les in desce nding o rde r
of impo rta nce.
EEZ or high seas FAO area
India
Vietnam
Myanmar
China
Indonesia (Eastern)
Mauritania
Pacific Western Central - High seas Areas
Bangladesh
Indonesia (Western)
Morocco
Western Sahara (Morocco)
Mexico
Philippines
United Kingdom
Malaysia Sarawak
Senegal
Malaysia East
Thailand
Japan Main Isl.
Japan Outer Isl.
Korea South
Malaysia West
Spain
Pacific Northwest - High seas Areas
Korea North
Malaysia Sabah
Madagascar
Indian Ocean Eastern - High seas Areas
Nigeria
USA East Coast
France
Sierra Leone
Guinea
Pakistan
Taiwan
Venezuela
Atlantic Eastern Central - High Seas Areas
Namibia
Brazil
Angola
Cameroon
South Africa
Denmark
Papua New Guinea
Cambodia
Canary Isl.(Spain)
Tunisia
Atlantic Western Central - High Seas Areas
Peru
Guyana
Sum of all turtle IUCN
weighted exposures in
the EEZ
0.422
0.420
0.415
0.347
0.340
0.323
0.319
0.316
0.313
0.295
0.277
0.269
0.264
0.254
0.243
0.241
0.235
0.230
0.224
0.224
0.219
0.218
0.217
0.212
0.211
0.209
0.208
0.208
0.200
0.200
0.196
0.196
0.195
0.193
0.191
0.187
0.185
0.184
0.182
0.178
0.178
0.178
0.170
0.170
0.168
0.167
0.166
0.166
0.165
0.162
61
Shark I UCNpweig hted exp osure
Sha rks were most ex posed to g illnet f is hing in East Asia, Ja pan, Sout hEast As ia, Sout h
As ia, Morocco but a lso widely spread in many EEZs a nd hig h seas areas (Figure 15) his
.T
h
h
h
h
h
h
ff
t
t
f
t
f
f
t
species group may be ig ly a ec ed by gillne is ing w i
ive o
e six s ark species
represented wit hin t he top 40 spec ies most ex posed to gillnet f is hing (Ta ble 15). T he
EEZs cont ribut ing most to t he expos ure of s ha rks to g illnet f is hing are set out in Table
16.
Figure 15 « EEZs and High Seas FAO a reas showing wit h t he IUC N weighted ex posures summed across sha rks.
A reas wit h colours furt hest u p t he sca le ba r (red co lours) had hig he r sha rk ex posures.
62
Table 15 Ò Sha rk ra nked by thei r IUC NÒweig hted exposure. T hose marked with pi nk shadi ng are t he most
exposed 40 species, those shaded g reen were t he mode rately exposed 40 species, a nd t hose shaded blue t he
least exposed species
Ra nk
29
30
34
37
39
41
Species
code
CTM
IPA
RHT
CCC
LMN
IOX
Family
shark
shark
shark
shark
shark
shark
species
Cetorhinus maximus
Isurus paucus
Rhincodon typus
Carcharodon carcharias
Lamna nasus
Isurus oxyrinchus
Common name
Basking shark
Longfin Mako shark
Whale Shark
Great White Shark
Porbeagle shark
Shortfin Mako shark
63
IUCN
weighted
exposure
1.234
1.140
1.113
1.094
1.090
1.075
Table 16 ú EEZ and hig h seas
of i mpo rta nce.
FAO
EEZ or high seas FAO area
China
Japan Main Isl.
Vietnam
India
Pacific Western Central - High Seas Areas
Myanmar
Morocco
Indian Ocean Eastern - High Seas Areas
Pacific Northwest - High Seas Areas
Russia Pacific
Pacific Southeast - High Seas Areas
Mauritania
Indonesia (Eastern)
Western Sahara (Morocco)
Chile
Korea South
Peru
South Africa
Bangladesh
Indonesia (Western)
Guinea
Japan Outer Isl.
USA East Coast
Taiwan
Korea North
Spain
United Kingdom
Mexico
Greece
Philippines
Namibia
Indian Ocean Western - High Seas Areas
Norway
Senegal
Brazil
Pacific Eastern Central - High Seas Areas
Madagascar
France
Italy
Tunisia
Malaysia Sarawak
Australia
Iceland
Atlantic Eastern Central - High Seas Areas
Atlantic Southwest - High Seas Areas
Malaysia East
Thailand
Canada
Canary Isl.(Spain)
Atlantic Western Central - High Seas Areas
Malaysia West
Algeria
Gambia
Turkey Mediterranean Sea
Croatia
Malaysia Sabah
Sierra Leone
Ecuador
Angola
Libya
Nigeria
a reas
e e nti ng t he hig hest ex posu re fo r all t he s ha rks i n desce ndi ng o rde r
pr s
Sum of all shark IUCN weighted
exposures in the EEZ
0.241
0.213
0.202
0.199
0.198
0.192
0.192
0.190
0.183
0.171
0.164
0.158
0.156
0.156
0.153
0.153
0.152
0.149
0.146
0.145
0.144
0.144
0.144
0.141
0.141
0.140
0.138
0.136
0.135
0.135
0.133
0.133
0.132
0.130
0.129
0.128
0.127
0.118
0.117
0.117
0.112
0.111
0.110
0.110
0.110
0.109
0.106
0.105
0.104
0.102
0.101
0.100
0.100
0.100
0.098
0.096
0.096
0.095
0.094
0.092
0.092
64
S
p ecies level analy sis conclusion:
T he
d
d
res ults of t he st u y s how t hat a ll taxo n g ro ups a re affecte
eac h g ro up
b
y g illnet f is hing w it h
b
d
d t
e ing re prese nte
w it hin t he to p 40 s pec ies most hig hly ex pose
o g illnet
d d
f is hing of t he C MS s pec ies inc lu e
d
d
d
in t he st u y T urt les a n
s ha rks a re hig hly affecte
.
d
d
d
w it h 5/6 s ha rk s pec ies re prese nte
w it hin t he to p 40, a n
a ll t urt le s pec ies ra nke
w it hin
t he to p 2 5 T hese two g ro ups of C MS s pec ies a re
.
f is hing
.
65
b
d b
like ly to
e most impacte
y g illnet
T he
mit igat io n tec hniq ues
a im of
d
l
inc i e nta
ca pt ure
c irc umsta nces
t hat
ld
s ho u
no nWta rget
of
l
d
ea
to
t he
b
e
no nWta rget
b
ll
o r s u sta nt ia y
200 3).
(Bac hce
s pec ies
d
eat h of
l
e iminate
to
s pec ies
re
d
uce
Unde rsta nd ing
ll
in g i nets
is
t he
t he
esse nt ia
l t
o
d t
l
b
d
d
e e rmining how f ut ure mo rta it ies ca n
e preve nte
(Rowe 2007), a n
as s uc h, c ha nges
to pract ices a nd imple me nt ing mit igat io n is esse nt ia l.
Ma ny mit igat io n met hods to red uce bycatc h have bee n pro posed a lt ho ug h ve ry few of
t hese
have
Exte ns ive
ll
g i net
b
l
d
ee n a pp ie
rev iews
f is hing
ll
(Fre nc h 20 11) o r a re o pe rat io na y
l
fo r s ing e
mit igat io n tec hniq ues
of
ge ne ra
ll
y
have
b
d
d
ee n co n ucte
bl
uns uita
e
s pec ies Wg ro ups
Me lv in
(e.g.
&
(Dawso n 199 1).
or
Pa rris h
l
re at io n to
in
1999,
ll
Bu
2006,
ll
l
l
l
b
Rowe 2007. G i ma n et a . 2009, G i ma n et a . 20 10, ACA P 20 11, Lo kke o rg 20 11). T hese
rev iews
d
an
o rig ina
l
resea rc h
pa pe rs
l
re at ing
to
mit igat io n
resea rc h a re
d
s umma rise
b l
d
ll
l
d
d.
e ow. Mit igat io n met ho s w hic h a re s pec if ic to g i net f is he ries o n y a re
isc usse
T his met hod invo lves a le rt ing no nWta rget s pec ies to g illnets w it h v is ua l c ues in o rde r to
d t
d
l
e e r no nWta rget s pec ies, w it h t he a im of
ec reas ing e nta ng e me nt
l d
l
inc u e c ha ng ing net co o ur, net
ll
i uminat io n, us ing
l
l
rates. V is ua
a e rts
l
bl ) t
a rge r (mo re v is i
e
w ine s izes fo r
b
l
d
d
l
nets, inc reas ing t he num e r of f i a me nts use
in t he nets a n
v is ua
ma rke rs (i.e.: co rks)
l
d
l
l
b
d
b
w hic h a re p ace
a o ng t he net. V is ua c ues have
ee n effect ive at re
uc ing
ycatc h fo r
sea
b
d
ir s
ll
(Bu
2007),
l
l.
(G i ma n et a
20 10).
re
d
uce
d
d
an
nets.
t he
pinnipe
d
s
l
(Ba r ow
d
an
200 3)
Ca me ro n
d
an
t urt les
O ne iss ue w it h t his met hod is t hat ta rget catc h rates a re ofte n a lso
l
l
l
as a res u t of v is ua a e rts.
Me lv in et a l.
20
cetacea ns,
50
d th t
(1999) fo un
a
mes hes
of
t he
l
Rhinoce ros a uk et
net
b
d
d
ec rease
w he n t he
ycatc h of co mmo n murres
we re
ma
d
e
b
l
ycatc h was a so
mo re
re
d
uce
bl ,
v is i
e
d
b
d
co mpa re
l
ut o n y
in t he
w it h
uppe r
l
l
nets. T he catc h of t he ta rget soc keye sa mo n howeve r was a so
re
d
uppe r
l
mo nof i a me nt
50
uce
mes hes of
d
b
y
mo re
t ha n ha lf w he n t he uppe r 50 mes hes we re made mo re v is ible.
Wa ng et a l. (20 10) invest igated t he use of v is ua l a le rts to red uce t he bycatc h of t urt les in
ll
d
lh
l
d
l
ll
d
ll
g i nets. Sha rk s ha pe
si
o uettes we re p ace
a o ng t he g i net a n
i uminat io n of nets
66
b
ch
ca l l
h
d as p t nt a l d t
h l
e mi
ig ts we re use
o e
i
e e rre nts fo r g ree n sea t urt les. W
ie
y LED a nd
s ha rk s ha ped
s ilho uettes
ta rget s pec ies catc h rate.
re
d
c d
u e
sea
b catc h
y
,
t urt le
Bot h ty pes of
t hey
a lso
c hn
illuminat io n te
iq ues
s ubsta nt ia lly
re
d
c d
u e
re
d
c d
u e
b catc h w h l
ie
y
ha
c
c
catc h at s.
r
e
v ing no effe t o n ta rget s pe ies
Ping ers
Pinge rs we re f irst deve lo ped to dete r ma rine
ma mma ls f ro m g illnets.
Pinge rs a re s ma ll
c wa n n
d
c
hat
h
h¢f
d s
hat w h n
unde rwate r aco ust i
r i g
ev i es t
e mit
ig
req ue ncy pulse
ig na ls t
e
,
attac hed a lo ng a
A lt ho ug h
net
,
d t
c
h n
h
e e r no n¢ta rget s pe ies f ro m a pproac
i g t e
ha
ve
pinge rs
c
effe t ive ness a ppea rs to
b
cc ssf
ee n s u
e
ul
in
re
d
c
u ing
b catc h
y
b
h
c
c
c
e ve ry f is e ry a nd s pe ies s pe if i
leve ls
(Rowe 2007).
net
fo r so me
(Zo llet 2009).
b
c
d c n
b catc h
c
d
h
ee n effe t ive at re
u i g
of
o mmo n
o lp ins (Eva ns et a l. 1977)
y
d
h
o lp ins
(Bo rd ino et a l. 2002)
,
,
Jo hnsto n 2002)
h
2002) a nd s o rt
bac
d
um p
ke
a rbo ur po rpo ises
H
d
h
o lp ins
H
Pinge rs
ha
,
ve
ca na
ra nc is
, F
(C ulik et a l. 200 1
ea rin et a l. 2000
, G
,
(Pedde mo rs
b a
d c
d
h
e ke
o mmo n
o lp ins
s pec ies
pinniped
2000)
s pec ies
(Jo hnsto n
(Ba rlow a nd Ca me ro n 200 3). Ca rretta et a l.
(2008) o bse rved t he co mplete e liminat io n of bea ked w ha le
b catc h w h n p n
e
i ge rs we re
y
d c d t
h
d ft
h
int ro
u e
o t e Ca lifo rnia
ri
g illnet f is e ry.
I nfo rmat io n o n t he use of pinge rs at dete rring sea bird bycatc h is ve ry limited. Me lv in et
a l.
(1999)
d t
e e rre nts
fo und
we re
t hat
c
o mmo n
d
inco rpo rate
murre
w it h
b catc h
y
was
mo nof ila me nt
re
d
nets.
c d
u e
In
b
y
t he
w he n
50%
sa me
st udy
aco ust ic
h w
o
eve r
,
pinge rs had no effect at dete rring Rhinoce ros a uklets f ro m e nta ng le me nt.
Ba rlow
a nd
Ca me ro n
(200 3)
o
bs
d
e rve
a
re
d
c d
u e
b catc h
y
rate
of
sea ls
a nd
s ea
lio ns
w he n aco ust ic dete rre nts we re used yet in ot he r st ud ies pinnipeds have assoc iated t he
,
,
so und
of
pinge rs
w it h
food
(Bo rd ino
et
a l.
2002)
,
t hus
inc reas ing
acc ide nta l
h
c
e nta ng le me nt of t ese s pe ies.
Pro ble ms assoc iated w it h aco ust ic dete rre nts
c asta l a
c
c
o
reas fo r ing so me s pe ies
Rowe
2007).
a bit uat io n
H
may
a lso
d
inc lu e
ha b tat
c
c
i
ex lus io n es pe ia lly f ro m
,
b¢ pt
into s u
o
ima l fo rag ing
b
e
an
iss ue
putt ing
into
ha b tat
i
(C ulik et a l. 200 1
,
h
q uest io n t e
lo ng
te rm
c
c st l
c
h
effe t ive ness of pinge rs (Cox et a l. 200 3). Pinge rs a re a lso
o
o mpa riso n to ot e r
y (in
67
i i
i
m t gat o n
met hods),
t hey
need
i i
se rv c ng,
reg ula r
t hey
a nd
ca n
f
i t
n e r e re
i
w th
net
i
i
i
o pe rat o ns s uc h as sett ng a nd ha ul ng
.
fl
Passi
ve Re
ectors
T his
i
met hod
(ma inly
nvo lves
cetacea ns)
if i
y ng
mod
a re
mo re
f
i
pro pe rt es o
t he aco ust ic
ik
l
e ly
to
detect
t he
t he g illnet so t hat a nima ls
prese nce
o
f
i
g llnets
.
od
M
if i
i
cat o ns
f ib
f
f ib
i
i
i
i
i
i
i
nc lude c he m ca lly e nha nc ng net
res, nc reas ng t he de ns ty o
net
res, a nd add ng
f
ex t ra
b
ased
loat
or
on
t he
i
g llnets
i
c ha ns
(Goodso n
.
T ria ls
et
t he
a lo ng
i
ass umpt o n t hat
(Read 2000)
i
do lph ns
o
b
ead
i
do lph ns
i
us ng
a nd
.
o r cetacea ns,
F
i
po rpo ses
ha rbo ur
a nd
2007)
f
re lecto rs
i
pass ve
994)
1
al
..
(Rowe
net
have
i
ec ho locate
red uced
i
po rpo ses
t his
n
t he
f
b
ycatc h o
(T rippe l
et
al
..
meas ure
i
s
f
i i i
v c n ty
o
b tt
o
le nose
200 3)
.
A
n
b
bi
b
b
i
i
i
se rved red uct o n n sea
rd
ycatc h occ urred w he n
a r um s ulphate was added to t he
f
ny lo n o
as t hey
200 3)
f
bi
i
i
ib t
i
i ibi it
g llnets, yet t h s was att r
u ed to t he nc reased v s
l y o t he nets to sea
rds
had
b
ee n dyed
b
lue to
mas
f th
k th
i
i i
i
e co lo ur o
e c he m ca l add t o n (T r ppe l et a l
.
.
Iss ues
i
i
w th th s
i
nc lude
met hod
net
ha nd ling
pro
b
le ms,
t he
hig h cost
f
o
i
c he m ca lly
f
f
i
i
i
if i
e nha nc ng nets a nd t he leve l o va r at o n o r cetacea ns to detect t he mod
ed net (Rowe
2007)
.
l
Time/ A rea
c osures
T ime/a rea
c los ures
have
t he
i
pote nt a l
to
b
e
f
s uccess ul
f
or
a ll
i
s pec es
g ro ups
if
f i hi
f
i
i
i
i
i
if i
mple me nted a ppro pr ate ly T h s met hod nvo lves c los ng a n a rea to
s
ng o r a s pec
c
.
t ime
i
pe r od
w he n
i
co ns de red to
leve ls
b
e too
f
o
i
i
nc de nta l e nta ng le me nt
hig h (Rowe 2007)
f th
f
k
now ledge o
e te mpo ra l patte rns o
.
i
or th s
F
f
or
i
pote nt a l
met hod to
b
i
ycatc h s pec es
a re
ff
b
i
i
e e ect ve, a n ex te ns ve
fi h
b th
b
i
i
o
pote nt a l
ycatc h s pec es a nd ta rget
s
i
i
i
s pec es s req u red
.
i
i
i
i
i
urray et a l (2000) noted t hat t he s pat a l a nd te mpo ra l va r at o n n occ ure nce
n so me
M
.
f
i
s pec es
ro m yea r to yea r may
a rea
f
b
i
o r s u ta
le c los ure
fi h
i
g llnet
s e ry
i
. A
ma
k
e
it
iff i
i
i
i
d
c ult to dete rm ne t he a ppro pr ate t me a nd
n exa mple o
f
f
n t he G ul o
f t hi
s was
f
i
a ne
o r t he
M
hig hlig hted
f
mo nt h o
68
f th
b
i k
y t he c los ure o
e s n
N
b
ove m e r,
994
1
i
n a n atte mpt to
a rbo ur po rpoise bycatc h. Hig hest bycatc h rates we re obse rved in Se pte mbe r;
we ll befo re t he c los ure dates and t his, co upled wit h t he small a rea w hic h t he meas ure
1999) howeve r s howed t hat
cove red
, proved t he c los ure ineffective. Me lvin et al. (
,
,
red uce
h
ope ning fis he ries only
ing peak salmon abundance
s uppo rting t he time/a rea mitigation tec hniq ue.
d ur
red uced
seabird bycatc h,
Subsurface net setting
T his met hod involves
anging t he
pt h at w hic h t he net is set to red uce bycatc h. It is
pa rtic ula rly applicable fo r seabirds as most seabird bycatc h is obse rved at de pt hs of less
t han 20m be low t he s urface (Zyde lis et al. 2009) and by setting t he net be low t he
maximum d iving de pt h, it g reatly red uces bycatc h of d iving seabirds (Lokke bo rg 20 11).
A red uction in seabird bycatc h was obse rved in t he Japanese gillnet fis he ry w he n nets
ch
de
we re set 2 m be low t he s urface, howeve r fis hing effic ie ncy was also
9 5%
199 3 c ited by e lvin et al 1999)
,
(Hayase & Yats u
M
.
.
red uced
by
u
p to
Net modifications
Fis hing eq uipme nt mod ifications have bee n effective at red uc ing bycatc h in seabirds
11)
3)
F
( re nc h 20 , pinnipeds, cetaceans (No rt hridge and Sande rson 200 and t urtles
R
)
( ome ro 2008 . It is ofte n d iffic ult, howeve r, to alte r fis hing eq uipme nt att ributes
wit ho ut red uc ing fis hing effective ness (Bull 2007).
Eq uipme nt
size,
anges inc lude mod ifying t he
ch
d
iamete r of monofilame nt twine and mes h
ing net pane l he ig ht and red uc ing t he numbe r and le ngt h of tie downs used.
3)
No rt hridge and Sande rson (200 obse rved significantly red uced bycatc h leve ls in seal
and ha rbo ur po rpoise bycatc h w he n t hinne r twine d iamete r was used, possibly beca use
red uc
t he t hinne r twine meant it was easie r fo r t hese spec ies to break f ree. Nets t hat we re
smalle r in profile (half pane l he ig ht) had less t urtle bycatc h and re leasing t urtles was
9)
1 )
E
easie r in smalle r nets
( c ke rt et al. 2008 and Gea rha rt et al. 200 . Cambie (20 0
s uggested t hat setting eq uipme nt in s hallowe r wate r and adj usting t he we ig hting
de
sign of t he nets, wo uld allow e ntangled t urtles to
69
re
ac h t he s urface to breat he.
Time of day fishing restrictions
The time of day t hat fis hing nets are set can potentially impact bycatc h rates elvin et
. M
al (1999) s howed t hat by avoiding fis hing at dawn, bycatc h rates of bot h t he auklet and
t he common murre were reduced significantly w hile target catc h rates were only
reduced by around 5%.
Ot her operational measures t hat may potentially reduce bycatc h include:
‚
reduced net soak time,
‚
provisional equipment carried on board to release incidental bycatc h,
‚
regular patrolling of nets to release incidental bycatc h,
‚
avoiding congregations of bycatc h species w here possible,
‚
attac hing suspender lines to t he gillnet w hic h hold t he net below t he float
line.
This review demonstrates t hat t here is no one universal solution to t he problem of
gillnet bycatc h. Many mitigation tec hniques are species{ and area{specific and w hile one
measure may work for one species or species group, it may be ineffective or detrimental
to anot her. Additionally, some tec hniques t hat are very effective at reducing bycatc h are
also linked to reductions in fis hing efficiency. Bycatc h reduction t hroug h mitigation has
been demonstrated to some degree in all species groups, yet t he effectiveness t hese
met hods wit hin eac h species group in not universal.
T ime/area closures have t he potential to be useful at reducing bycatc h across multiple
species groups yet t he effectiveness of t his met hod is closely linked to spatial and
temporal patterns of t he non{target species (Lokkeborg 20 11). For many species, more
in{dept h biological information is needed to apply t his met hod effectively.
70
The results of t his st udy s how t hat g illnet bycatc h is a ubiquitous pro blem w it h all taxon
,
g roups in t his st udy (s harks cetaceans sea birds t urt les pinnipeds otters) be ing
,
,
,
,
,
represented w it hin t he top 40 hig hest ranked spec ies for likely adverse effects of g illnet
f is hing. The s hark and t urt le g roups were bot h hig hly ranked w it h all t urt le spec ies
ranked w it hin t he top 25 spec ies most exposed spec ies, and 5 out of t he 6 s hark spec ies
ranked w it hin t he top 40. W it hin t he CMS listed spec ies, t hese are t he two spec ies
g roups w hic h are most likely affected by adverse effects of g illnet f is hing.
The impact t hat g illnet f is hing is hav ing on spec ies populat ions was not eluc idated from
t his analys is; all populat ions could to some deg ree be affected by g illnet f is hing but t he
,
,
hig hest ranking spec ies are likely to be affected more st rong ly.
The results from t his analys is hig hlig ht f ive important areas w here t here was a hig h
overlap between spec ies and g illnet f is hing and t hat require furt her examinat ion. These
areas were:
‚
Sout h A merica (bot h At lant ic and Pac if ic coast lines)
‚
West coast of Africa (from Cape of Good Hope to A lgeria)
‚
The Red Sea/Pers ian Gulf to A ra bian Gulf
ew Zealand/Tasman Sea
‚ N
‚
The Aegean Sea
If spec if ic populat ions are affected by bycatc h mortality from g illnets t hese areas are t he
,
ones in w hic h adverse effects are most likely to be o bserved. These are also t he areas
w here more monitoring and deta iled f is hing stat ist ics are required to assess impacts at a
populat ion level in more deta iled analys is.
71
Table 17 ¾ Top 10% of EEZs most like ly to be affecting each species group.
Species Group
Top 10% EEZ most affected
Cetaceans
China, Russ ia Pac ific, India, Myanmar
Seabirds
and Vietnam
.
Chile, Pe ru, So ut h Af rica and Mo rocco
Sharks
Russ ia Pac ific, Myanmar, Mo rrocco,
India, Vietnam, Ja pan (Ma in Is l ) and
.
China
T
urt les
ang lades h,
Indo nes ia
B
aste rn),
(E
China, Myanmar, Vietnam and India
.
Sea ls and Otte rs
Chile and
r ay
No w
C urre nt ly, t he re is no s ing le so lut io n t hat can be a pplied g lo ba lly to so lve g illnet bycatc h
issues fo r t he C MS s pec ies T he st udy of how gear tec hno logy a lo ne, o r in co mbinat io n
.
i
h
h
t
t
r
m
a
r
an
b
o
e
e su es c
e used as an effect ive so lut io n is st ill in its infancy (G ilman et
w
a l 20 10) So lut io ns to g illnet bycatc h pro ble ms are extre me ly co mplex and need to be
.
.
add ressed o n a case by case bas is T he re are many facto rs t hat co ntribute to t he efficacy
.
of a part icular measure inc luding t he g illnet fis he ry ty pe, catc h pe r unit effo rt, t he area
fis hed, and t he s ize and be hav io ur of t he no ntarget s pec ies (G ilman et a l 20 10, Wa llace
.
et a l. 20 10). So me tec hniq ues t hat are ve ry effect ive at red uc ing bycatc h are a lso linked
to red uct io ns in fis hing effic ie ncy
.
he leve l of effect ive ness fo r so me mit igat io n met hods varies bot h betwee n and w it hin
s pec ies g ro ups. T his was o bse rved by Me lv in et a l. (1999) w ho fo und t hat Co mmo n
Murre bycatc h was red uced by 50% w he n aco ust ic pinge rs we re inco rpo rated w it h
mo nofilame nt nets In t he same st udy howeve r, pinge rs had no effect at dete rring
.
Rhinoce ros A uklets f ro m e ntang le me nt
.
T
mo ngst t he most effect ive mit igat io n so lut io ns rev iewed in t his st udy we re t ime/area
c losures. T his met hod has proved to be ve ry effect ive in a numbe r of diffe re nt areas, and
A
72
ca n pote nt ia lly
f
be s uccess ul at
met hod
pro ble m w it h t his
o pe rat io na lly
a nd
s pec ies
v ia ble
ta rget
howeve r is t hat to
exte ns ive
,
red uc ing bycatc h ac ross mult iple s pec ies g ro ups
ne
. O
s pec ies
te mpo ra l a nd
req uired
is
be
imple me nted a ppro priate ly a nd
,
(Murray
et
of
know ledge
s pat ia l
000)
2
.
al
.
G
pote nt ia l
at he ring
t his
be
bycatc h
ty pe
of
info rmat io n ca n be ve ry t ime co ns uming to s uff ic ie nt ly ta ke into acco unt t he leve ls of
seaso na l va riat io n needed to def ine t he s ize of t he a rea
a rea w ill be c losed
,
a nd t he t ime pe riod t hat t he
.
It is a lso c rit ica l t hat t he soc ioeco no mic s it uat io n is assessed w he n ta king into acco unt
0 10) I n ma ny deve lo ping co unt ries g illnet f is hing
v ia ble mit igat io n meas ures ( ilma n
,
G
2
.
is
ma in too l fo r food
t he
fo r s ubs iste nce
gat he ring
co mmunit ies
ma king
t ime/a rea
mit igat io n
meas ures
c los ures s imply not a po lit ica lly v ia ble ma nage me nt o pt io n
.
ea r
G
tec hno logy
used
a pproac hes
in
co nj unct io n
w it h
ot he r
s pec if ic to ind iv id ua l f is he ries a nd no nDta rget s pec ies is like ly to be t he most v ia ble way
fo rwa rd in ma ny a reas
he effect ive use of aco ust ic dete rre nts (cetacea ns pinnipeds)
,
,
. T
pass ive ref lecto rs (cetacea ns sea birds pinnipeds) a nd t he a lte rat io n of f is hing met hods
,
,
(a ll s pec ies
f urt he r
g ro ups)
have
deve lo pme nt
req uire me nt
fo r
a ll s how n
a nd
eve ry
pro mise
imple me ntat io n
s pec ies
g ro up
at
be ing
of
effect ive
mit igat io n
rev iewed
in
t his
mit igat io n too ls
.
meas ures
st udy
.
is
oweve r
,
H
an
t he
T
he
urge nt
lac k
of
info rmat io n o n bot h mit igat io n meas ures a nd ind iv id ua l s pec ies be hav io urs has made it
d iff ic ult
to
reco mme nd
t he
s pec ies/ s pec ies g ro up
e
. W
most
effect ive
ty pes
of
mit igat io n
meas ures
fo r
eac h
reco mme nd t he f urt he r mo re deta iled a na lys is of s pec if ic
,
f is he ry/ s pec ies g ro up co uplings to deve lo p t hese so lut io ns f urt he r
.
a llace et a l ( 0 10) ac know ledges t hat w he n exa mining t he impacts of f is hing bycatc h
W
. 2
o n t urt le po pulat io ns
,
ff
f
f
bycatc h mit igat io n e o rts s ho uld oc us o n a reas o hig h bycatc h /
hig h effo rt a reas
reas t hat have low o bse rved effo rt but pote nt ia lly hig h impacts o n
,
. A
t he
po pulat io n mea ns t he re
is
less co nf ide nce
in bycatc h rates a nd o bse rve r effo rts
,
s ho uld be inc reased to q ua nt ify t hese iss ues
.
T
his st udy
most
prov ides a g lo ba l a na lys is of t he g illnet
impo rta nt
reg io ns fo r f urt he r invest igat io n
.
bycatc h pro ble m a nd o ut lines t he
ac k of
L
info rmat io n has
like ly t hat s ma ll but impo rta nt effects a re c urre nt ly unde rDre prese nted
73
mea nt
it
is
ine sca le effects
. F
(to
co uld
)
km
0
.1
info r
at io n
m
has
li
be
m
ex plo red
ited
by
t he
a na lyt ica l
a pplicat io ns
t he
add ress g illnet bycatc h pro ble
of
t he
ode l
m
used
a nd
a na lys is
,
he re
but
ea nt
m
poo r q ua lity
t hat
we
ca nnot
s at a loca l leve l
m
.
It is i
po rta nt to note t hat t he ove rla p betwee n s pec ies d ist ribut io ns a nd g illnet f is hing
m
effo rt
is
lin ed
k
not
to
hig h
req uire be hav io ura l info r
info r
at io n t hat
m
is
rates
of
bycatc h
o rta lity
m
.
T
leve l of
his
wo uld
a na lys is
odes of inte ract io ns w it h g illnets;
at io n fo r eac h s pec ies o n
m
m
no nnex iste nt o r d iff ic ult to o bta in fo r
a ny s pec ies to a s uff ic ie nt
m
leve l fo r t his st udy
o r exa
ple
a ny of t he coasta l s pec ies have hig h ra n s d ue to
, m
. F
m
k ,
hig h ex pos ure
dete r
m
to
g illnet
act iv ity
(co nocc urre nce
in t he
sa
a reas)
e
m
it
re
a ins
m
to
be
ined w het he r ex pos ure eq uates to inte ract io ns betwee n t he s pec ies a nd g illnets
a nd t he
o rta lity occ urs in pro po rt io n to t he leve l of ex pos ure
n atte
pt to acco unt
m
. A
m
in t he a na lys is was do ne by inco rpo rat ing t he be hav io ur of eac h s pec ies into t he a na lys is
to o ut line a ny pote nt ia l inte ract io ns t hat a s pec ies
ay have w it h g illnets
ve n ta ing
m
. E
k
be hav io ur into co ns ide rat io n it
is st ill
ay be li e ly t hat t he
ag nit ude of t he pro ble
,
m
k
m
m
be ing unde rnre prese nted fo r so
T
he a na lys is
has
bee n do ne
ide nt if ied as hav ing a
fo r t he
low ex pos ure
ot he r s pec ies had bee n ta
Ove rnest i
e s pec ies
m
.
C MS s pec ies o nly
.
in o ur st ud ies co uld
So
e
m
be a reas of
he re
hig h ex pos ure
if
e n into acco unt
k
.
at io n of t he ex pos ure
ay occ ur w he n t he re is no te
po ra l ove rla p betwee n
m
m
m
t he f is hing seaso n a nd s pec ies d ist ribut io ns in t he a rea d ue to
T
bee n
Zs w hic h have
EE
ay
m
be
a
co ns ide ra ble
unde rest i
at io n of
m
t he
hig hly co nce nt rated
his
. T
d ist ribut io n
into
do n't
ta
e
k
acco unt
loca l
ig rat io n
.
ex pos ure
g illnet f is hing a nd s pec ies a re
a ps
m
m
ay
m
hots pots
in a reas
w he re
bot h
be so w he n t he s pec ies
s uc h
as
feed ing
zo nes
,
ig rat io n co rrido rs re prod uct io n s ites
his
ay affect pa rt ic ula rly t urt les a nd sea birds
,
m
. T
m
w hic h breed o n t he coast line a nd so co uld
g illnet act iv it ies
be
pote nt ia lly
hig hly ex posed to
ins ho re
.
Mis re prese ntat io n of t he ex pos ure
re prese ntat io n of t he
ay occ ur d ue to bot h unifo r
m
m
ot h d ist ribut io ns
s pec ies d ist ribut io n a nd t he g illnet catc h d ist ribut io n
ay not ove rla p
. B
m
in rea lity at s
T
he re
was
wate rs of
a ll te
po ra l a nd s pat ia l sca les
m
m
.
a
hig he r
leve l of
re po rt ing
a nd
o bse rvat io n of
bycatc h
inc ide nce
in t he
o re ind ust ria lised nat io ns It is poss ible t hat bycatc h
o rta lity of s pec ies t hat
m
.
m
74
a re
d ist ributed
f req
ue nt ly
.
o uts ide
ind ust ria lised
a reas
is
occ urring
,
but
not
be ing
re po rted
as
G ilma n (20 10) o ut lines t hat t he re a re fo ur catego ries of info rmat io n t hat a re needed to
catego rise t he ris k t hat coasta l nets a re pos ing to sea t urt les
. T
hese catego ries ca n be
a pplied broad ly to cove r a ll s pec ies g ro ups in t his st udy
.
T
hese a re:
wledge o n t he
Kno
‚
mag nit ude of t he
pro ble m in te rms of
bot h no n¤ta rget
s pec ies a nd t he f is he ry
f t e f
f
aracterisati
is ery ; gea r ty pes used c ha racte rist ics o eac h gea r
,
Ch
on o
h
h
‚
ty pe a nd f is hing o pe rat io ns a nd catc h c ha racte rist ics
.
f
ramew
a ageme t
M n
n
‚
o
rk;
w hic h
inc ludes
mo nito ring
a nd
mit igat io n
prog ra mmes
f
ci ec
mic c
siderati
w hat a re t he implicat io ns o how mit igat io n
So
o
ono
on
on –
‚
meas ures w ill effect soc ia l a nd eco no mic s it uat io ns ?
T
he st udy
impacts
prese nted
on
he re
no n¤ta rget
re prese nts a
s pec ies
.
I
t
nove l e le me nt
uses
t he
in unde rsta nd ing g illnet f is hing
ext re me ly
poo r
info rmat io n
a bo ut
t he
f is he ries to ex plo re
ff
w hic h a reas a nd s pec ies t hat may be to have adve rse ly a ected by
mo rta lity
s pec ies
in g illnets
or
.
T
he
po pulat io ns
info rmat io n
we re
not
req uire me nts
met
.
to
eve rt he less
,
N
exa mine
ta rget ing
info rmat io n gat he ring ca n be prio rit ised as a res ult of t he st udy
.
75
f is he ries
of
impacts
mit igat io n
on
a nd
T he st udy fo und:
‚
T he
info rmat io n
a bo ut
ava ila ble
f is he ries
g illnet
ext re me ly
is
poo rly
doc ume nted, ha mpe ring deta iled a na lys is of t he pro ble m of inc ide nta l catc h
in t hese w ide ly used f is hing met hods
.
‚
ycatc h
B
linked
w it h g illnet
f is he ries
is
reco rded,
s pa rse ly
c reat ing
poss ible
biases in a ny a na lyses
.
‚
ist ribut io n fo r
D
ma ny
po pulat io n data
s pec ies,
cetacea ns,
s uc h as
is
know n,
poo rly
as
a re
a nges may be desc ribed, but a reas of inte nse use a re not
. R
desc ribed fo r ma ny g ro ups of a nima ls listed o n C MS a ppe nd ices
.
‚
ffo rt
E
was
co nce nt rated
so ut h
in
east
As ia,
no rt he rn
E
uro pe,
Pac if ic, west Af rica n Coast a nd t he west coast of So ut h A me rica
‚
no rt h
west
.
A reas of hig h s pec ies d ive rs ity fo r C MS s pec ies we re t he west coast of So ut h
A me rica, west coast of Af rica f ro m t he Ca pe of Good Ho pe to A lge ria, t he
Sea
/
Pe rs ia n G ulf
Aegea n Sea
‚
T he
twe nty
to
A ra bia n G ulf,
New
Zea la nd
/
Tas ma n
Sea,
a nd
ed
R
t he
.
xc lus ive
E
co no mic
E
Zo nes
2 37
of
a reas
a na lysed,
in w hic h t he
g reatest ex pos ure to f is hing ris k occ urs fo r C MS listed s pec ies (we ig hted by
I UC N ra nk) we re: Mya nma r, V iet na m, Pe ru, I nd ia,
Af rica, C hina, Na mibia, G reece, Ga la pagos,
Weste rn I ndo nes ia,
aste rn I ndo nes ia,
E
A lge ria, a nd Mo rocco
‚
R
uss ia (Pac if ic), C hile, So ut h
a ng lades h, Ja pa n (Ma in Is la nds),
B
No rway,
Ma urita nia,
United
Kingdo m,
.
T he fo rty s pec ies most ex posed to ris k f ro m g illnet f is hing, w he n we ig hted by
I UC N ra nk, by taxo n g ro up we re:
‚
eabirds
S
Murre let,
Humbo ldt
–
Af rica n
a rkørumped
D
Pe ng uin,
Pe ng uin,
Pet re l,
a lea ric
B
Waved
.
iv ing øpet re l,
D
A lbat ross,
Shea rwate r,
A udo uin’s G ull, Sho rt øta iled A lbat ross
76
Pe ruv ia n
Socot ra
Pinkøfooted
Ja pa nese
Co rmo ra nt,
Shea rwate r,
‚
ns & Sir ni ns – Finless Porpoise, Irrawaddy Dolphins,
Dugong, Nort h Pacif ic Rig ht W hale, At lant ic Hump$backed Dolphin,
Nort hern Rig ht W hale, Bott lenose Dolphin, Heaviside’s Dolphin, Fin
W hale, Sei W hale, Indo $Pacif ic Hump$backed Dolphin, Blue W hale,
Burmeister Porpoise, Baird’s Beaked W hale, Omura W hale
tac a
Ce
e
a
e
‚
S ls nd S O
Sout hern River Otter.
‚
S Tur l s – Hawskbill Turt le, Kemp’s Rid ley Turt le , Leat herback
Turt le, Loggerhead Turt le, Green Turt le, Olive Rid ley Turt le.
‚
Sh rks – Basking Shark, Longf in Mako Shark, Porbeagle Shark,
W hale Shark, Great W hite Shark.
a
a
a
e
e
a
e
tt
e
rs – Med iterranean Monk Seal, Marine Otter,
t
e
a
Bycatc h t hroug h entanglement was known to occur for sea t urt les, cetaceans,
pinnipeds, sirenians and s harks. Diving sea birds were documented entangled
w hen d iving for food, but some species may become entangled d uring
hauling or sett ing of nets
.
Among most likely to be affected, CMS listed s harks and t urt les have hig h
‚
rankings compared to ot her taxa: All six t urt le species are listed among t he
top 23 ranked species ident if ied in t he analysis, and all 6 s hark species are in
t he top 41 ranked species.
‚
‚
Mit igat ion met hods ident if ied included visual alerts, acoust ic alerts, seasonal
or area closures or c hanges to net conf igurat ions.
‚
However, mit igat ion met hods were found to eit her red uce f is hing eff iciency
considera bly, or had litt le documented of bycatc h red uct ion effect.
‚
Seasonal or area closure t herefore appears to be t he most effect ive way of
avoid ing bycatc h of non$target species in gillnet f is heries.
‚
Target ing closures to cover periods of most intensive interact ion between
affected non$target species is necessary, and f urt her researc h is needed to
examine t he interact ions in areas ident if ied in t his st udy, specif ically to
examine be havioural data and seasonal occurrence of affected species and
f is heries
.
77
‚
Next steps: There are strong requirements for improved observer data, better
records of bycaught species with a particular focus in the areas of high
overlap of at^risk species and strong fishing effort. Further, finer^scaled
research to address bycatch issues in the areas, and for the species identified
as highest risk in this analysis is warranted.
78
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80
D'Argrosa
a
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or a o a a Phocoena sinus g
s r s r g
or
or
raoa a g o
a
D'Argrosa
r o
a
a a a
o's ar sa a g
s r s Dr g a s a o a o
o
o o s r a o o og
Da so
a a o or s o
s or g s ar a a
D oo
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s
a oo o
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or o
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D ar
o s r s aa sa
s r o Agr r Agro as
sr aa sa A a s r s a s s
o go
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or
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81
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(
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Bh b
in
h k
n,
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ct
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3 Po ulation growth rate and its determinants an overview n Sibly ,
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Silvani ,
S anish driftnet fishing and incidental catches in the western
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1999
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L.
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Simeone , A , Bernal ,
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ncidental mortality of Humboldt Penguins
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3
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<http ://fishstat .seafdec .org > . Consulted FebruaryÿAugust 20 11.
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Alam , M.F.,
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Tregen a ,
N. J . C ., Berrow , S .D., Hammond , P.S . and Leaper , R. ( 1997) . Harbour porpoise (
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Trippel ,
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Tripathy ,
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Trippel ,
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Van Waerebeek , K. R., Julio
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Peru ,
Danish
Wider
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Observations on incidental catch of cetaceans in three landing centres along the Indian coast.
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88
Ta ble 18 u T he 46 s pecies of t he C MS pa rt of t he cetacea n a nd si re nia n g rou p
.
CMS list
I
II
I/II
II
I
II
I/II
II
II
II
II
II
II
II
II
I
I
I
II
II
II
II
II
II
II
II
I
II
II
I/II
II
II
II
II
II
II
I/II
I/II
II
II
II
II
II
II
II
II
Species
code
BAM
BAB
BOB
BAE
BMU
BAO
BAP
BEB
CAM
CEC
CEE
CEH
DEL
DDE
DUG
EBA
EBG
EBJ
GLM
GRG
HYA
LGH
LGA
LGB
LGS
LGO
MNV
MMO
NPH
ORB
ORH
OOR
POD
POP
POS
DAL
PYM
POB
SOC
POT
SNA
SNC
SNR
SNL
TUA
TUT
Group
Species
Cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
Balaena mysticetus
Balaenoptera bonaerensis
Balaenoptera borealis
Balaenoptera edeni
Balaenoptera musculus
Balaenoptera omurai
Balaenoptera physalus
Berardius bairdii
Caperea marginata
Cephalorhynchus commersonii
Cephalorhynchus eutropia
Cephalorhynchus heavisidii
Delphinapterus leucas
Delphinus delphis
Dugong dugon
Eubalaena australis
Eubalaena glacialis
Eubalaena japonica
Globicephala melas
Grampus griseus
Hyperoodon ampullatus
Lagenodelphis hosei
Lagenorhynchus acutus
Lagenorhynchus albirostris
Lagenorhynchus australis
Lagenorhynchus obscurus
Megaptera novaeangliae
Monodon monoceros
Neophocaena phocaenoides
Orcaella brevirostris
Orcaella heinsohni
Orcinus orca
Phocoena dioptrica
Phocoena phocoena
Phocoena spinipinnis
Phocoenoides dalli
Physeter macrocephalus
Pontoporia blainvillei
Sousa chinensis
Sousa teuszii
Stenella attenuate
Stenella clymene
Stenella coeruleoalba
Stenella longirostris
Tursiops aduncus
Tursiops truncates
Alternative species name
Common name
Bowhead Whale
Antarctic Minke whale
Sei Whale
Bryde's whale
Blue Whale
Omura' Whale
Fin Whale
Baird's Beaked Whale
Pygmy Right whale
Commerson's Dolphin
Chilean Dolphin
Heaviside's Dolphin
White Whale
Common Dolphin
Dugong Sea Cow Dugong
Southern Right Whale
Northern Right Whale
North Pacific Right Whale
Long-finned Pilot Whale
Risso's Dolphin
Northern Bottlenose Whale
Fraser's Dolphin
Atlantic White-sided Dolphin
White-beaked Dolphin
Peale's Dolphin
Dusky Dolphin
Humpback Whale
Narwhal
Finless Porpoise
Irrawaddy Dolphin
Australian Snubfin dolphin
Killer whale
Spectacled Porpoise
Common Porpoise
Burmeister Porpoise
Dall's Porpoise
Sperm Whale
La Plata Dolphin
Indo-Pacific Humpbacked Dolphin
Atlantic Hump-backed Dolphin
Pantropical Spotted Dolphin
Clymene dolphin
Striped Dolphin
Spinner Dolphin
Indian or Bottlenose Dolphin
Bottlenosed Dolphin
89
Ta ble 19 ’ T he 59 s pecies of t he C MS i n t he sea bi rd g rou p
.
CMS list
I
II
II
II
I
I/II
II
II
II
I/II
II
I
I
II
II
I
I/II
I/II
II
II
I
II
II
II
II
II
II
II
II
II
II
I
I
I
I
I
II
I
II
II
II
II
I
II
II
II
I
II
II
II
II
II
II
I
II
II
Species
code
DAM
DIP
DIX
LAA
LAT
LAU
LGE
LHM
LIC
LLE
LML
LRL
LSA
MAI
MAH
PEG
PCR
PCC
PHG
PXP
PHA
PHI
PIR
PHN
PHF
PHE
PRO
PCI
PCO
PRK
PCW
PTT
POW
PTG
PUC
PUM
SPD
SPH
STF
STE
STG
SBG
STB
CAT
SDG
STH
STI
STM
STN
STP
STR
STV
STS
SYW
DNB
THC
Group
Species
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
Seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Diomedea amsterdamensis
Diomedea epomophora
Diomedea exulans
Larus armenicus
Larus atlanticus
Larus audouinii
Larus genei
Larus hemprichii
Larus ichthyaetus
Larus leucophthalmus
Larus melanocephalus
Larus relictus
Larus saundersi
Macronectes giganteus
Macronectes halli
Pelecanoides garnotii
Pelecanus crispus
Pelecanus onocrotalus
Phalacrocorax nigrogularis
Phalacrocorax pygmeus
Phoebastria_albatrus
Phoebastria_immutabilis
Phoebastria_irrorata
Phoebastria_nigripes
Phoebetria fusca
Phoebetria palpebrata
Procellaria aequinoctialis
Procellaria cinerea
Procellaria conspicillata
Procellaria parkinsoni
Procellaria westlandica
Pterodroma atrata
Pterodroma cahow
Pterodroma phaeopygia
Puffinus creatopus
Puffinus mauretanicus
Spheniscus demersus
Spheniscus humboldti
Sterna albifrons
Sterna balaenarum
Sterna bengalensis
Sterna bergii
Sterna bernsteini
Sterna caspia
Sterna dougallii
Sterna hirundo
Sterna lorata
Sterna maxima
Sterna nilotica
Sterna paradisaea
Sterna repressa
Sterna sandvicensis
Sterna saundersi
Synthliboramphus wumizusume
Thalassarche_bulleri
Thalassarche_cauta
Alternative species name
Larus michahellis
Diomedea albatrus
Diomedea immutabilis
Diomedea irrorata
Diomedea nigripes
Diomedea bulleri
Diomedea cauta
90
Common name
Amsterdam Albatross
Royal Albatross
Wandering Albatross
Armenian Gull
Olrog's Gull
Audouin's Gull
Slender-billed Gull
Sooty Gull
Great Black-headed Gull
White-eyed Gull
Mediterranean Gull
Relict Gull
Saunder's Gull
Southern Giant Petrel
Northern Giant Petrel
Peruvian diving petrel
Dalmatian Pelican
White Pelican
Socotra Cormorant
Pygmy Cormorant
Short-tailed Albatross
Laysan Albatross
Waved Albatross
Black-footed Albatross
Sooty Albatross
Light-mantled Sooty Albatross
White-chinned Petrel
Grey Petrel
Spectacled Petrel
Black Petrel
Westland Petrel
Henderson Petrel
Cahow Bermuda Petrel
Dark-rumped Petrel
Pink-footed Shearwater
Balearic shearwater
African Penguin
Humboldt Penguin
Little Tern
Damara Tern
Lesser Crested Tern
Great Crested Tern
Chinese Crested Tern
Caspian Tern
Roseate Tern
Common Tern
Peruvian tern
Royal Tern
Gull-billed Tern
Arctic Tern
White-cheeked Tern
Sandwich Tern
Saunder's Tern
Japanese Murrelet
Buller's Albatross
Shy Albatross
II
II
II
THH
DIC
DIM
seabirds
seabirds
seabirds
Thalassarche_chlororhynchos
Thalassarche_chrysostoma
Thalassarche_melanophrys
Diomedea chlororhynchos
Diomedea chrysostoma
Diomedea melanophris
Yellow-nosed Albatross
Grey-headed Albatross
Black-browed Albatross
Ta ble 20 ® T he 6 s pecies of t he C MS i n t he s ha rk g roup
CMS list
I/II
I/II
II
II
II
II
Species
code
CCC
CTM
IOX
IPA
LMN
RHT
Group
Species
Shark
Shark
Shark
Shark
Shark
Shark
Carcharodon carcharias
Cetorhinus maximus
Isurus oxyrinchus
Isurus paucus
Lamna nasus
Rhincodon typus
Alternative species name
Common name
Great White Shark
Basking shark
Shortfin Mako shark
Longfin Mako shark
Porbeagle shark
Whale Shark
Ta ble 2 1 ® T he 6 s pecies of t he C MS i n t he tu rt le g rou p
CMS list
I/II
I/II
I/II
I/II
I/II
I/II
Species
code
CAC
CHM
DCC
EIM
LPK
LPV
Group
Species
Alternative species name
Turtle
Turtle
Turtle
Turtle
Turtle
Turtle
Caretta caretta
Chelonia mydas
Dermochelys coriacea
Eretmochelys imbricata
Lepidochelys kempii
Lepidochelys olivacea
Common name
Loggerhead Turtle
Green Turtle
Leatherback Turtle
Hawksbill Turtle
Kemp's Ridley Turtle
Ridley Turtle
Ta ble 22 ® T he 6 s pecies of t he C MS i n t he ot he r sea ma mma ls g rou p
CMS list
II
I
I
I/II
II
II
Species
code
HGR
LOF
LOP
MMN
OFL
PHV
Group
Species
Marine mammals other
Marine mammals other
Marine mammals other
Marine mammals other
Marine mammals other
Marine mammals other
Halichoerus grypus
Lontra feline
Lontra provocax
Monachus monachus
Arctocephalus australis
Phoca vitulina
Alternative species
name
Common name
Grey Seal
Marine Otter
Southern River Otter
Mediterranean Monk Seal
South American Seal
Common Seal
91
Ta ble 2 3 Ë T hi rty two sea bi rd s pecies fo r w hic h a fo ragi ng Ëradius a pproac h was a pplied
Species
code
Species
Common name
World
population
DAM
DIP
DIX
LAT
LAU
MAI
MAH
PHG
PHA
PHI
PIR
PHN
PHF
PHE
PRO
PCI
PCO
PRK
PCW
PTT
POW
PTG
PUC
SPD
SPH
STB
STI
DNB
THC
THH
DIC
DIM
Diomedea amsterdamensis
Diomedea epomophora
Diomedea exulans
Larus atlanticus
Larus audouinii
Macronectes giganteus
Macronectes halli
Phalacrocorax nigrogularis
Phoebastria albatrus
Phoebastria immutabilis
Phoebastria irrorata
Phoebastria nigripes
Phoebetria fusca
Phoebetria palpebrata
Procellaria aequinoctialis
Procellaria cinerea
Procellaria conspicillata
Procellaria parkinsoni
Procellaria westlandica
Pterodroma atrata
Pterodroma cahow
Pterodroma phaeopygia
Puffinus creatopus
Spheniscus demersus
Spheniscus humboldti
Sterna bernsteini
Sterna lorata
Thalassarche bulleri
Thalassarche cauta
Thalassarche chlororhynchos
Thalassarche chrysostoma
Thalassarche melanophrys
Amsterdam Albatross
Royal Albatross
Wandering Albatross
Olrog's Gull
Audouin's Gull
Southern Giant Petrel
Northern Giant Petrel
Socotra Cormorant
Short-tailed Albatross
Laysan Albatross
Waved Albatross
Black-footed Albatross
Sooty Albatross
Light-mantled Sooty Albatross
White-chinned Petrel
Grey Petrel
Spectacled Petrel
Black Petrel
Westland Petrel
Henderson Petrel
Cahow Bermuda Petrel
Dark-rumped Petrel
Pink-footed Shearwater
African Penguin
Humboldt Penguin
Chinese Crested Tern
Peruvian tern
Buller's Albatross
Shy Albatross
Yellow-nosed Albatross
Grey-headed Albatross
Black-browed Albatross
26
7900
8050
3500
19200
50170
11800
110000
470
591356
9620
61307
13890
22611
1241000
111684
10000
3333
4000
74999.5
71
14999.5
24000
28500
15000
25
1750
30460
12585
69100
95748
601686
92
Pop type (0
whole; 1
breeding pairs)
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
0
1
1
1
1
1
1
1
1
1
1
Foragi
ng
radius
(km)
1200
1000
1800
7
160
189
550
0
1500
1000
165
250
350
1516
1868
600
600
522
400
195
200
200
200
400
170
100
100
413
200
1800
800
1100
Start of the
Breeding
season
month
2
10
1
7
2
6
8
1
10
9
3
10
7
9
10
2
9
10
2
1
10
4
11
11
5
1
10
12
7
8
9
9
Endt of the
Breeding
season
month
2
10
1
11
7
6
5
1
6
7
12
6
5
5
5
12
3
6
12
1
6
9
5
11
5
1
1
9
7
4
5
5
Table 24 ä Ene rgy use (kg of oi l equiva le nt pe r ca pita) by EEZ Ene rgy use refe rs to use of pri ma ry e ne rgy
.
befo re t ra nsfo rmatio n to ot he r e nd äuse fue ls hic h is equa l to i ndige nous productio n plus i mpo rts a nd stoc k
,w
c ha nges, mi nus ex po rts a nd fue ls su pplied to s hi ps a nd ai rc raft e ngaged i n i nte rnatio na l t ra ns po rt. Esti matio n
f ro m t he Wo rld Ba nk: ave rage va lue fo r pe rio2002ä200 a nd United Natio n Statistics Divisio n yea r 2004 2005
,
o r 2006. Listed i n a lpha betica l o rde r by EEZ na me.
Country
Albania
Algeria
Sovereign
Albania
Algeria
ISO
ALB
DZA
Energy use
(kg of oil eq per
capita) average
2000-2005
615
901
American Samoa
Angola
Antigua and
Barbuda
Argentina
Australia
United States
Angola
Antigua and
Barbuda
Argentina
Australia
ASM
AGO
7827
536
ATG
ARG
AUS
1695
1652
5647
Macquarie Island
Australia
Australia
Australia
AUS
AUS
5647
5647
Bahamas Exclusive Economic Zone
Bahraini Exclusive Economic Zone
Bangladeshi Exclusive Economic Zone
Bahamas
Bahrain
Bangladesh
Bahamas
Bahrain
Bangladesh
BHS
BHR
BGD
2144
9407
142
Barbados Exclusive Economic Zone
Belgian Exclusive Economic Zone
Barbados
Belgium
Barbados
Belgium
BRB
BEL
1451
5594
Bermudian Exclusive Economic Zone
Bosnian and Herzegovinian Exclusive
Economic Zone
Bouvet Island Exclusive Economic Zone
Brazilian Exclusive Economic Zone
Trindade Exclusive Economic Zone
Bermuda
Bosnia and
Herzegovina
Bouvet Island
Brazil
Trindade
United Kingdom
Bosnia and
Herzegovina
Norway
Brazil
Brazil
BMU
2717
BIH
BVT
BRA
BRA
1167
5772
1091
1091
Belizean Exclusive Economic Zone
British Indian Ocean Territory Exclusive
Economic Zone
Solomon Islands Exclusive Economic
Zone
British Virgin Islands Exclusive Economic
Zone
Belize
British Indian
Ocean Territory
Belize
BLZ
1021
United Kingdom
IOT
3729
EEZ name
Albanian Exclusive Economic Zone
Algerian Exclusive Economic Zone
American Samoa Exclusive Economic
Zone
Angolan Exclusive Economic Zone
Antigua and Barbuda Exclusive Economic
Zone
Argentinean Exclusive Economic Zone
Australian Exclusive Economic Zone
Macquarie Island Exclusive Economic
Zone
Lord Howe Isl Australia
Solomon Islands
SLB
123
United Kingdom
Brunei
Darussalam
Bulgaria
Myanmar
Eritrea
Cambodia
Cameroon
Canada
VGB
1464
Brunei Darussalam
Bulgarian Exclusive Economic Zone
Myanmar Exclusive Economic Zone
Eritrean Exclusive Economic Zone
Cambodian Exclusive Economic Zone
Cameroonian Exclusive Economic Zone
Canadian Exclusive Economic Zone
Solomon Islands
British Virgin
Islands
Brunei
Darussalam
Bulgaria
Myanmar
Eritrea
Cambodia
Cameroon
Canada
BRN
BGR
MMR
ERI
KHM
CMR
CAN
7472
2500
270
194
323
392
8012
Cape Verdean Exclusive Economic Zone
Cape Verde
Cape Verde
CPV
209
Cayman Islands Exclusive Economic Zone
Sri Lankan Exclusive Economic Zone
Cayman Islands
Sri Lanka
United Kingdom
Sri Lanka
CYM
LKA
3387
438
Chilean Exclusive Economic Zone
Chile
Chile
CHL
1475
93
Source
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
Chile
CHL
1475
Chile
CHL
1475
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
Chile
China
Taiwan
CHL
CHN
TWN
1475
906
906
2006 (United Nation
Statistics Division)
World Bank
World Bank
Christmas Island
Cocos Islands
Colombia
Australia
Australia
Colombia
CXR
CCK
COL
5647
5647
676
Comoro Islands
France
Democratic
Republic of the
Congo
République du
Congo
COM
MYT
60
1108
COD
330
World Bank
Congolese Exclusive Economic Zone
Comoro Islands
Mayotte
Democratic
Republic of the
Congo
République du
Congo
COG
292
Cook Islands Exclusive Economic Zone
Costa Rican Exclusive Economic Zone
Croatian Exclusive Economic Zone
Cuban Exclusive Economic Zone
Cypriote Exclusive Economic Zone
Beninese Exclusive Economic Zone
Bornholm Exclusive Economic Zone
Danish Exclusive Economic Zone
Cook Islands
Costa Rica
Croatia
Cuba
Cyprus
Benin
Denmark
Denmark
New Zealand
Costa Rica
Croatia
Cuba
Cyprus
Benin
Denmark
Denmark
COK
CRI
HRV
CUB
CYP
BEN
DNK
DNK
1033
770
1822
956
2653
335
3602
3602
Dominican Exclusive Economic Zone
Dominican Republic Exclusive Economic
Zone
Ecuadorean Exclusive Economic Zone
Dominica
Dominican
Republic
Ecuador
DMA
578
DOM
ECU
818
716
World Bank
World Bank
Galapagos Exclusive Economic Zone
El Salvador Exclusive Economic Zone
Equatorial Guinean Exclusive Economic
Zone
Estonian Exclusive Economic Zone
Dominica
Dominican
Republic
Ecuador
Galapagos
Islands
El Salvador
Equatorial
Guinea
Estonia
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
Ecuador
El Salvador
ECU
SLV
716
696
Equatorial Guinea
Estonia
GNQ
EST
1008
3790
Faeroe Islands Exclusive Economic Zone
Faeroe Islands
Denmark
FRO
4671
Falkland Islands Exclusive Economic Zone
Falkland Islands
South Georgia
and the South
Sandwich Islands
United Kingdom
FLK
4725
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
United Kingdom
SGS
3729
Fiji
Finland
France
Glorioso Islands
Juan de Nova
Island
Bassas da India
Ile Europa
Ile Tromelin
Fiji
Finland
France
France
FJI
FIN
FRA
ATF
665
6420
4294
1062
France
France
France
France
ATF
ATF
ATF
ATF
1062
1062
1062
1062
French Guiana Exclusive Economic Zone
French Polynesian Exclusive Economic
Zone
French Guiana
France
GUF
1413
French Polynesia
France
PYF
1108
Djiboutian Exclusive Economic Zone
Djibouti
Djibouti
DJI
174
Easter Island Exclusive Economic Zone
Desventuradas Isl.(Chile)
J. Fernandez Felix and Ambrosio Isl.
(Chile)
Chinese Exclusive Economic Zone
Taiwanese Exclusive Economic Zone
Christmas Island Exclusive Economic
Zone
Cocos Islands Exclusive Economic Zone
Colombian Exclusive Economic Zone
Comoran Exclusive Economic Zone
Mayotte Exclusive Economic Zone
Democratic Republic of the Congo
Exclusive Economic Zone
South Georgian Exclusive Economic Zone
Fijian Exclusive Economic Zone
Finnish Exclusive Economic Zone
French Exclusive Economic Zone
Glorioso Exclusive Economic Zone
Juan de Nova Exclusive Economic Zone
Bassas da India Exclusive Economic Zone
Ile Europa Exclusive Economic Zone
Ile Tromelin Exclusive Economic Zone
Easter Island
Desventuradas
Island
J. Fernandez
Felix and
Ambrosio Isl.
(Chile)
China
Taiwan
94
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
Reunion Island
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
Gabonese Exclusive Economic Zone
Georgian Exclusive Economic Zone
Gabon
Georgia
Gabon
Georgia
GAB
GEO
1240
630
Gambian Exclusive Economic Zone
Gambia
Palestinian
territories
Germany
Ghana
United Kingdom
GMB
75
Gaza strip
German Exclusive Economic Zone
Ghanaian Exclusive Economic Zone
Gibraltarian Exclusive Economic Zone
Gambia
Palestinian
territories
Germany
Ghana
Gibraltar
PSE
DEU
GHA
GIB
265
4135
397
4429
Line Group Exclusive Economic Zone
Line Group
Kiribati
KIR
92
Phoenix Group Exclusive Economic Zone
Phoenix Group
Kiribati
KIR
92
Kiribati Exclusive Economic Zone
Greek Exclusive Economic Zone
Kiribati
Greece
Kiribati
Greece
KIR
GRC
92
2568
Greenlandic Exclusive Economic Zone
Greenland
Denmark
GRL
3360
Grenadian Exclusive Economic Zone
Grenada
GRD
925
Guadeloupe Exclusive Economic Zone
Guam EEZ
Guatemalan Exclusive Economic Zone
Grenada
Guadeloupe and
Martinique
Guam
Guatemala
France
United States
Guatemala
GLP
GUM
GTM
1503
7827
612
Guinea Bissau Exclusive Economic Zone
Guinea Bissau
Guinea Bissau
GNB
67
Guyanese Exclusive Economic Zone
Haitian Exclusive Economic Zone
Heard and McDonald Islands Exclusive
Economic Zone
Honduran Exclusive Economic Zone
Guyana
Haiti
Heard and
McDonald Islands
Honduras
Guyana
Haiti
GUY
HTI
626
247
Australia
Honduras
HMD
HND
5647
540
Honk Kong
Icelandic Exclusive Economic Zone
Indian Exclusive Economic Zone
Andaman and Nicobar Islands Exclusive
Economic Zone
Indonesian Exclusive Economic Zone
(eastern)
Indonesian Exclusive Economic Zone
(western)
Iranian Exclusive Economic Zone
Iraqi Exclusive Economic Zone
Irish Exclusive Economic Zone
Israeli Exclusive Economic Zone
Italian Exclusive Economic Zone
Ivory Coast Exclusive Economic Zone
Jamaican Exclusive Economic Zone
Japanese Exclusive Economic Zone
Japan Outer Isl.
Johnston Atoll Exclusive Economic Zone
Jordanian Exclusive Economic Zone
Kenyan Exclusive Economic Zone
North Korean Exclusive Economic Zone
South Korean Exclusive Economic Zone
Kuwaiti Exclusive Economic Zone
Lebanese Exclusive Economic Zone
China
Iceland
India
Andaman and
Nicobar
China
Iceland
India
CHN
ISL
IND
1746
11333
455
India
CHN
906
World Bank
Indonesia
Indonesia
IDN
790
World Bank
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Ivory Coast
Jamaica
Japan
Japan
Johnston Atoll
Jordan
Kenya
North Korea
South Korea
Kuwait
Lebanon
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Ivory Coast
Jamaica
Japan
Japan
United States
Jordan
Kenya
North Korea
South Korea
Kuwait
Lebanon
IDN
IRN
IRQ
IRL
ISR
ITA
CIV
JAM
JPN
JPN
USA
JOR
KEN
PRK
KOR
KWT
LBN
790
1972
1102
3452
2911
3014
387
1431
4033
4033
7827
1021
449
865
4074
9142
1326
Latvian Exclusive Economic Zone
Latvia
Latvia
LVA
1453
Liberian Exclusive Economic Zone
Libyan Exclusive Economic Zone
Liberia
Libya
Liberia
Libya
LBR
LBY
61
3063
95
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
2004 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
World Bank
2004 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
Lithuanian Exclusive Economic Zone
Lithuania
Lithuania
LTU
2517
Macao
China
China
CHN
1594
Madagascan Exclusive Economic Zone
Malaysian Exclusive Economic Zone
(west)
Malaysian Exclusive Economic Zone
(east)
Malaysia Sabah
Madagascar
Madagascar
MDG
45
Malaysia
Malaysia
MYS
2098
World Bank
Malaysia
Malaysia
Malaysia
Malaysia
MYS
MYS
2098
2098
Maldives Exclusive Economic Zone
Malaysia Sarawak
Maltese Exclusive Economic Zone
Maldives
Malaysia
Malta
Maldives
Malaysia
Malta
MDV
MYS
MLT
965
2098
1995
Martinique
Martinique
France
MTQ
1577
Mauritanian Exclusive Economic Zone
Mauritania
Mauritania
MRT
165
Mauritian Exclusive Economic Zone
Mexican Exclusive Economic Zone
Hawai borthwest islands
Monégasque Exclusive Economic Zone
Mauritius
Mexico
United States
Monaco
Mauritius
Mexico
United States
Monaco
MUS
MEX
USA
MCO
835
1511
7827
4294
Montserrat Exclusive Economic Zone
Moroccan Exclusive Economic Zone
Mozambican Exclusive Economic Zone
Omani Exclusive Economic Zone
Namibian Exclusive Economic Zone
Montserrat
Morocco
Mozambique
Oman
Namibia
United Kingdom
Morocco
Mozambique
Oman
Namibia
MSR
MAR
MOZ
OMN
NAM
2235
372
400
3499
616
Nauruan Exclusive Economic Zone
Dutch Exclusive Economic Zone
Nauru
Netherlands
Southern SaintMartin
Netherlands
Antilles
Nauru
Netherlands
NRU
NLD
3457
4705
Netherlands
ANT
1204
Netherlands
ANT
1204
New Caledonia
France
NCL
3631
Vanuatu Exclusive Economic Zone
New Zealand Exclusive Economic Zone
Nicaraguan Exclusive Economic Zone
Nigerian Exclusive Economic Zone
Vanuatu
New Zealand
Nicaragua
Nigeria
Vanuatu
New Zealand
Nicaragua
Nigeria
VUT
NZL
NIC
NGA
139
4086
542
730
Niue Exclusive Economic Zone
Norfolk Island Exclusive Economic Zone
Norwegian Exclusive Economic Zone
Jan Mayen Exclusive Economic Zone
New Zealand
Australia
Norway
Norway
NIU
NFK
NOR
SJM
605
5647
5772
5772
Northern Mariana Islands Economic Zone
Micronesian Exclusive Economic Zone
Niue
Norfolk Island
Norway
Jan Mayen
Northern Mariana
Islands and
Guam
Micronesia
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
World Bank
World Bank
France
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
United States
Micronesia
MNP
FSM
7827
605
Marshall Islands Exclusive Economic Zone
Marshall Islands
Marshall Islands
MHL
584
Palau Exclusive Economic Zone
Pakistani Exclusive Economic Zone
Panamanian Exclusive Economic Zone
Papua New Guinean Exclusive Economic
Zone
Peruvian Exclusive Economic Zone
Philippines Exclusive Economic Zone
Pitcairn Exclusive Economic Zone
Polish Exclusive Economic Zone
Palau
Pakistan
Panama
Papua New
Guinea
Peru
Philippines
Pitcairn
Poland
Palau
Pakistan
Panama
Papua New
Guinea
Peru
Philippines
United Kingdom
Poland
PLW
PAK
PAN
3168
460
842
PNG
PER
PHL
PCN
POL
257
464
493
3729
2445
Sint-Maarten Exclusive Economic Zone
Netherlands Antilles Exclusive Economic
Zone
New Caledonian Exclusive Economic
Zone
96
World Bank
2006 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
World Bank
Niue
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
Portuguese Exclusive Economic Zone
Madeiran Exclusive Economic Zone
Azores Exclusive Economic Zone
Portugal
Madeira
Azores
Portugal
Portugal
Portugal
PRT
PRT
PRT
2385
2385
2385
Guinean Exclusive Economic Zone
Guinea
Guinea
GIN
47
East Timor Exclusive Economic Zone
Oecussi Ambeno Exclusive Economic
Zone
East Timor
East Timor
TLS
56
Oecussi Ambeno
Puerto Rico and
Virgin Islands of
the United States
Qatar
East Timor
TLS
56
United States
Qatar
PRI
QAT
165
19354
Puerto Rican Exclusive Economic Zone
Qatari Exclusive Economic Zone
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
World Bank
World Bank
Réunion Exclusive Economic Zone
Romanian Exclusive Economic Zone
Russia (Barents Sea)
Russia (Black Sea)
Russia (Baltic Sea Kalinigrad)
Russia (Pacific)
Russian Exclusive Economic Zone
(Siberia)
Russia (Baltic Sea St Petersburg)
St. Helena Exclusive Economic Zone
Saint Kitts and Nevis Exclusive Economic
Zone
Réunion
Romania
Russia
Russia
Russia
Russia
France
Romania
Russia
Russia
Russia
Russia
REU
ROU
RUS
RUS
RUS
RUS
1062
1799
4293
4293
4293
4293
Russia
Russia
Saint Helena
Saint Kitts and
Nevis
Russia
Russia
United Kingdom
Saint Kitts and
Nevis
RUS
RUS
SHN
4293
4293
3729
KNA
1080
Anguilla Exclusive Economic Zone
Anguilla
United Kingdom
AIA
1242
Saint Lucia Exclusive Economic Zone
Saint-Pierre and Miquelon Exclusive
Economic Zone
Saint Vincent and the Grenadines
Exclusive Economic Zone
Sao Tome and Principe Exclusive
Economic Zone
Saudi Arabian Exclusive Economic Zone
(Red Sea)
Saudi Arabian Exclusive Economic Zone
(persian Gulf)
Senegalese Exclusive Economic Zone
Saint Lucia
Saint Pierre and
Miquelon
Saint Vincent and
the Grenadines
Sao Tome and
Principe
Saint Lucia
LCA
749
France
Saint Vincent and
the Grenadines
Sao Tome and
Principe
SPM
4294
VCT
595
STP
236
Saudi Arabia
Saudi Arabia
SAU
5249
World Bank
Saudi Arabia
Senegal
Saudi Arabia
Senegal
SAU
SEN
5249
237
Seychellois Exclusive Economic Zone
Seychelles
Seychelles
SYC
2877
Sierra Leonian Exclusive Economic Zone
Singaporean Exclusive Economic Zone
Vietnamese Exclusive Economic Zone
Slovenian Exclusive Economic Zone
Sierra Leone
Singapore
Vietnam
Slovenia
Sierra Leone
Singapore
Vietnam
Slovenia
SLE
SGP
VNM
SVN
44
4548
513
3402
Somali Exclusive Economic Zone
South African Exclusive Economic Zone
Prince Edward Islands Exclusive
Economic Zone
Canary Islands Exclusive Economic Zone
Spanish Exclusive Economic Zone
Western Saharan Exclusive Economic
Zone
Sudanese Exclusive Economic Zone
Somalia
South Africa
Prince Edward
Islands
Canary Islands
Spain
Somalia
South Africa
SOM
ZAF
21
2621
World Bank
World Bank
2006 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
South Africa
Spain
Spain
ZAF
ESP
ESP
2621
3059
3059
World Bank
World Bank
World Bank
Western Sahara
Sudan
Morocco
Sudan
ESH
SDN
372
390
Surinamese Exclusive Economic Zone
Svalbard Isl. (Norway)
Suriname
Svalbard Isl.
Suriname
Norway
SUR
GGY
1416
5772
Swedish Exclusive Economic Zone
Syrian Exclusive Economic Zone
Thailand Exclusive Economic Zone
Sweden
Syria
Thailand
Sweden
Syria
Thailand
SWE
SYR
THA
2953
979
1235
97
World Bank
World Bank
World Bank
2004 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
2004 (United Nation
Statistics Division)
World Bank
2004 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
World Bank
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
World Bank
World Bank
Togolese Exclusive Economic Zone
Tokelau Exclusive Economic Zone
Togo
Tokelau
Togo
New Zealand
TGO
TKL
392
605
Tongan Exclusive Economic Zone
Trinidad and Tobago Exclusive Economic
Zone
United Arab Emirates Exclusive Economic
Zone
Tunisian Exclusive Economic Zone
Turkish Exclusive Economic Zone
(Mediterranean Sea)
Turkey Black Sea
Turks and Caicos Exclusive Economic
Zone
Tuvaluan Exclusive Economic Zone
Ukrainian Exclusive Economic Zone
Egyptian Exclusive Economic Zone
United Kingdom Exclusive Economic Zone
Jersey Exclusive Economic Zone
Guernsey Exclusive Economic Zone
Tanzanian Exclusive Economic Zone
Alaskan Exclusive Economic Zone
Hawaiian Exclusive Economic Zone (main
island)
Navassa Isl (Haiti)
Palmyra Atoll Exclusive Economic Zone
Jarvis Island Exclusive Economic Zone
Howland and Baker Island Exclusive
Economic Zone
United States Exclusive Economic Zone
(West Coast)
USA East Coast
USA Golf Of Mexico
Ascension Exclusive Economic Zone
Tristan Da Cunha Exclusive Economic
Zone
Uruguayan Exclusive Economic Zone
Venezuelan Exclusive Economic Zone
Wake Island Exclusive Economic Zone
Wallis and Futuna Exclusive Economic
Zone
Tonga
Trinidad and
Tobago
United Arab
Emirates
Tunisia
Tonga
Trinidad and
Tobago
United Arab
Emirates
Tunisia
TON
555
TTO
8019
World Bank
ARE
TUN
10724
799
World Bank
World Bank
Turkey
Turkey
Turks and Caicos
Islands
Tuvalu
Ukraine
Egypt
United Kingdom
Jersey
Guernsey
Tanzania
Alaska
Turkey
Turkey
TUR
TUR
1118
1118
World Bank
World Bank
United Kingdom
Tuvalu
Ukraine
Egypt
United Kingdom
United Kingdom
United Kingdom
Tanzania
United States
TCA
TUV
UKR
EGY
GBR
GBR
GBR
TZA
USA
3729
-1
2938
686
3729
3729
3729
410
7827
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
World Bank
Hawaii
Haiti
Palmyra Atoll
Jarvis Island
Howland Island
and Baker Island
United States
Haiti
United States
United States
USA
HTI
USA
USA
7827
247
7827
7827
World Bank
World Bank
World Bank
World Bank
United States
USA
7827
World Bank
United States
United States
United States
Ascension
United States
United States
United States
United Kingdom
USA
USA
USA
ASC
7827
7827
7827
3729
World Bank
World Bank
World Bank
World Bank
Tristan da Cunha
Uruguay
Venezuela
Wake Island
United Kingdom
Uruguay
Venezuela
United States
TAA
URY
VEN
WAK
3729
892
2304
7827
Wallis and Futuna
France
WLF
537
Samoa
Yemen
SerbiaMontenegro
Amsterdam
Island and Saint
Paul Island
Crozet Islands
Kerguelen
Islands
Samoa
Yemen
SerbiaMontenegro
WSM
YEM
303
273
SCG
1562
World Bank
World Bank
World Bank
World Bank
2006 (United Nation
Statistics Division)
2006 (United Nation
Statistics Division)
World Bank
2006 (United Nation
Statistics Division)
France
France
ATF
ATF
4294
4294
World Bank
World Bank
France
ATF
4294
World Bank
Clipperton Island
France
Disputed
China/Taiwan/Viet
nam
Disputed
China/Philippines/
Vietnam/Taiwan/M
alaysia
Disputed
Russia/Japan
Joint Regime
Colombia/Jamaic
CPT
4294
World Bank
XXX
906
World Bank
XXX
905
World Bank
XXX
4293
World Bank
XXX
1431
World Bank
Samoan Exclusive Economic Zone
Yemeni Exclusive Economic Zone
Serbia-Montenegrian Exclusive Economic
Zone
Amsterdam Island & St. Paul Island
Exclusive Economic Zone
Crozet Islands Exclusive Economic Zone
Kerguelen Islands Exclusive Economic
Zone
Clipperton Island Exclusive Economic
Zone
Paracel Islands Exclusive Economic Zone
Paracel Islands
Spratly Islands Exclusive Economic Zone
Spratly Islands
Russia-Japan conflict zone
Southern Kuriles
Colombia Jamaica
Colombia - Jamaica (Joint Regime)
98
World Bank
Niue
2006 (United Nation
Statistics Division)
Japan - South Korea Conflict Zone
Nigeria - Sao
Tome and
Principe
Joint Regime
Japan/ South
Korea
Disputed
China/Taiwan
Japan - South
Korea Conflict
Zone
Joint Development Area Australia - East
Timor
Australia - East
Timor
Protected Zone established under the
Torres Strait Treaty
Area en controversia (disputed - Peruvian
point of view)
Antarctic 200NM zone beyond the
coastline
Australia - Papua
New Guinea
Disputed
Chile/Peru
Nigeria - Sao Tome and Principe Joint
Joint Japan - Korea
Conflict Zone
Saint-Martin Exclusive Economic Zone
Azerbaijanis Exclusive Economic Zone
Kazakh Exclusive Economic Zone
Turkmen Exclusive Economic Zone
Antarctica
Northern SaintMartin
Azerbaijan
Kazakhstan
Turkmenistan
a
Joint Regime
Nigeria - Sao
Tome and
Principe
Joint Regime
Japan/ South
Korea
Disputed
China/Taiwan
Disputed
Japan/South
Korea
Joint Regime
Australia/East
Timor
Joint Regime
Australia - Papua
New Guinea
Disputed
Chile/Peru
XXX
730
World Bank
XXX
4074
World Bank
XXX
906
World Bank
XXX
4074
World Bank
XXX
5647
World Bank
XXX
5647
XXX
1475
World Bank
2006 (United Nation
Statistics Division)
Antarctica
ATA
0
World Bank
France
Azerbaijan
Kazakhstan
Turkmenistan
MAF
AZE
KAZ
TKM
1503
1466
3100
3314
Guadeloupe
World Bank
World Bank
World Bank
99
Table 25 Species ranked by overla p. A ll species
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Species
code
NPH
STB
ORB
DUG
STM
LSA
SOC
STI
POT
SYW
TUA
STV
CEH
SPD
STE
LAU
PHG
HGR
STR
LIC
STS
STG
STN
POP
PEG
SPH
LGE
STF
PHV
LOF
LML
LPV
EBJ
SDG
CAT
POS
BAM
EBG
MMN
BEB
BAO
SBG
LHM
DAL
CEE
PUM
Family
cetacean
seabirds
cetacean
cetacean
seabirds
seabirds
cetacean
seabirds
cetacean
seabirds
cetacean
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
marine mammals other
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
marine mammals other
marine mammals other
seabirds
turtle
cetacean
seabirds
seabirds
cetacean
cetacean
cetacean
marine mammals other
cetacean
cetacean
seabirds
seabirds
cetacean
cetacean
seabirds
Species
Neophocaena phocaenoides
Sterna bernsteini
Orcaella brevirostris
Dugong dugon
Sterna maxima
Larus saundersi
Sousa chinensis
Sterna lorata
Sousa teuszii
Synthliboramphus wumizusume
Tursiops aduncus
Sterna sandvicensis
Cephalorhynchus heavisidii
Spheniscus demersus
Sterna balaenarum
Larus audouinii
Phalacrocorax nigrogularis
Halichoerus grypus
Sterna repressa
Larus ichthyaetus
Sterna saundersi
Sterna bengalensis
Sterna nilotica
Phocoena phocoena
Pelecanoides garnotii
Spheniscus humboldti
Larus genei
Sterna albifrons
Phoca vitulina
Lontra felina
Larus melanocephalus
Lepidochelys olivacea
Eubalaena japonica
Sterna dougallii
Sterna caspia
Phocoena spinipinnis
Balaena mysticetus
Eubalaena glacialis
Monachus monachus
Berardius bairdii
Balaenoptera omurai
Sterna bergii
Larus hemprichii
Phocoenoides dalli
Cephalorhynchus eutropia
Puffinus mauretanicus
100
Common name
Finless Porpoise
Chinese Crested Tern
Irrawaddy Dolphin
Dugong Sea Cow Dugong
Royal Tern
Saunder's Gull
Indo-Pacific Humpbacked Dolphin
Peruvian tern
Atlantic Hump-backed Dolphin
Japanese Murrelet
Indian or Bottlenose Dolphin
Sandwich Tern
Heaviside's Dolphin
African Penguin
Damara Tern
Audouin's Gull
Socotra Cormorant
Grey Seal
White-cheeked Tern
Great Black-headed Gull
Saunder's Tern
Lesser Crested Tern
Gull-billed Tern
Common Porpoise
Peruvian diving petrel
Humboldt Penguin
Slender-billed Gull
Little Tern
Common Seal
Marine Otter
Mediterranean Gull
Ridley Turtle
North Pacific Right Whale
Roseate Tern
Caspian Tern
Burmeister Porpoise
Bowhead Whale
Northern Right Whale
Mediterranean Monk Seal
Baird's Beaked Whale
Omura' Whale
Great Crested Tern
Sooty Gull
Dall's Porpoise
Chilean Dolphin
Balearic shearwater
Overlap
index
1.729834
1.717597
1.698112
1.518014
1.515499
1.388563
1.332731
1.271844
1.259429
1.235895
1.206462
1.205789
1.164302
1.158219
1.150589
1.141359
1.116908
1.099358
1.090445
1.089308
1.089156
1.078656
1.061086
1.060545
1.037612
1.028118
1.02097
1.008609
0.988178
0.974533
0.973279
0.972248
0.968866
0.959458
0.956267
0.952267
0.942369
0.935856
0.92759
0.923174
0.920814
0.90351
0.900748
0.899804
0.897024
0.890444
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
LGA
LGB
EIM
CTM
LPK
GRG
CAC
DCC
LAA
STH
PCC
DEL
IPA
PHA
LLE
DDE
LGH
PUC
CHM
RHT
OFL
HYA
CCC
LMN
SNL
SNA
IOX
SNR
TUT
BAE
PTG
BOB
BAP
MNV
PYM
OOR
MMO
BMU
PIR
PCR
POB
LGO
LGS
SNC
PHI
LOP
LAT
GLM
CEC
DIM
DAM
PCW
DNB
PHN
EBA
CAM
BAB
cetacean
cetacean
turtle
shark
turtle
cetacean
turtle
turtle
seabirds
seabirds
seabirds
cetacean
shark
seabirds
seabirds
cetacean
cetacean
seabirds
turtle
shark
marine mammals other
cetacean
shark
shark
cetacean
cetacean
shark
cetacean
cetacean
cetacean
seabirds
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
seabirds
seabirds
cetacean
cetacean
cetacean
cetacean
seabirds
marine mammals other
seabirds
cetacean
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
cetacean
cetacean
Lagenorhynchus acutus
Lagenorhynchus albirostris
Eretmochelys imbricata
Cetorhinus maximus
Lepidochelys kempii
Grampus griseus
Caretta caretta
Dermochelys coriacea
Larus armenicus
Sterna hirundo
Pelecanus onocrotalus
Delphinapterus leucas
Isurus paucus
Phoebastria_albatrus
Larus leucophthalmus
Delphinus delphis
Lagenodelphis hosei
Puffinus creatopus
Chelonia mydas
Rhincodon typus
Arctocephalus australis
Hyperoodon ampullatus
Carcharodon carcharias
Lamna nasus
Stenella longirostris
Stenella attenuata
Isurus oxyrinchus
Stenella coeruleoalba
Tursiops truncatus
Balaenoptera edeni
Pterodroma phaeopygia
Balaenoptera borealis
Balaenoptera physalus
Megaptera novaeangliae
Physeter macrocephalus
Orcinus orca
Monodon monoceros
Balaenoptera musculus
Phoebastria_irrorata
Pelecanus crispus
Pontoporia blainvillei
Lagenorhynchus obscurus
Lagenorhynchus australis
Stenella clymene
Phoebastria_immutabilis
Lontra provocax
Larus atlanticus
Globicephala melas
Cephalorhynchus commersonii
Thalassarche_melanophrys
Diomedea amsterdamensis
Procellaria westlandica
Thalassarche_bulleri
Phoebastria_nigripes
Eubalaena australis
Caperea marginata
Balaenoptera bonaerensis
101
Atlantic White-sided Dolphin
White-beaked Dolphin
Hawksbill Turtle
Basking shark
Kemp's Ridley Turtle
Risso's Dolphin
Loggerhead Turtle
Leatherback Turtle
Armenian Gull
Common Tern
White Pelican
White Whale
Longfin Mako shark
Short-tailed Albatross
White-eyed Gull
Common Dolphin
Fraser's Dolphin
Pink-footed Shearwater
Green Turtle
Whale Shark
South American Seal
Northern Bottlenose Whale
Great White Shark
Porbeagle shark
Spinner Dolphin
Pantropical Spotted Dolphin
Shortfin Mako shark
Striped Dolphin
Bottlenosed Dolphin
Bryde's whale
Dark-rumped Petrel
Sei Whale
Fin Whale
Humpback Whale
Sperm Whale
Killer whale
Narwhal
Blue Whale
Waved Albatross
Dalmatian Pelican
La Plata Dolphin
Dusky Dolphin
Peale's Dolphin
Clymene dolphin
Laysan Albatross
Southern River Otter
Olrog's Gull
Long-finned Pilot Whale
Commerson's Dolphin
Black-browed Albatross
Amsterdam Albatross
Westland Petrel
Buller's Albatross
Black-footed Albatross
Southern Right Whale
Pygmy Right whale
Antarctic Minke whale
0.882536
0.877474
0.872379
0.865391
0.845511
0.839958
0.826912
0.826912
0.820656
0.811912
0.807091
0.803405
0.799951
0.793051
0.786896
0.785438
0.783364
0.782582
0.781022
0.780718
0.776876
0.770532
0.767739
0.764928
0.762594
0.759866
0.754187
0.746145
0.739723
0.737189
0.733426
0.720079
0.718872
0.716756
0.715051
0.714425
0.709832
0.696779
0.690936
0.682034
0.681307
0.64286
0.634419
0.63313
0.600686
0.579696
0.572399
0.570857
0.535107
0.528156
0.525587
0.503979
0.495736
0.495035
0.494585
0.491002
0.462312
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
PRK
POD
PHF
THH
PRO
LRL
THC
PCI
STP
ORH
DIC
MAI
DIP
DIX
MAH
PCO
PXP
PHE
POW
PTT
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Procellaria parkinsoni
Phocoena dioptrica
Phoebetria fusca
Thalassarche_chlororhynchos
Procellaria aequinoctialis
Larus relictus
Thalassarche_cauta
Procellaria cinerea
Sterna paradisaea
Orcaella heinsohni
Thalassarche_chrysostoma
Macronectes giganteus
Diomedea epomophora
Diomedea exulans
Macronectes halli
Procellaria conspicillata
Phalacrocorax pygmeus
Phoebetria palpebrata
Pterodroma cahow
Pterodroma atrata
102
Black Petrel
Spectacled Porpoise
Sooty Albatross
Yellow-nosed Albatross
White-chinned Petrel
Relict Gull
Shy Albatross
Grey Petrel
Arctic Tern
Australian Snubfin dolphin
Grey-headed Albatross
Southern Giant Petrel
Royal Albatross
Wandering Albatross
Northern Giant Petrel
Spectacled Petrel
Pygmy Cormorant
Light-mantled Sooty Albatross
Cahow Bermuda Petrel
Henderson Petrel
0.46143
0.445766
0.436894
0.436009
0.435673
0.430667
0.428971
0.426469
0.426419
0.423199
0.415607
0.410614
0.41002
0.403693
0.403004
0.395583
0.388056
0.382575
0.311002
0.268927
Figure 16 _ EEZs and High Seas FAO a reas s howing wit h t he u n_weighted exposures summed ac ross all s pecies.
A reas wit h co lours furt hest up t he scale ba r (red co lours) had higher s pecies exposures.
Ta ble 26 _ All s pecies ranked by t hei r u n_weighted exposure index
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Species
code
NPH
ORB
DUG
STM
SOC
POT
SYW
TUA
CEH
SPD
LAU
PHG
HGR
LIC
Family
cetacean
cetacean
cetacean
seabirds
cetacean
cetacean
seabirds
cetacean
cetacean
seabirds
seabirds
seabirds
marine mammals other
seabirds
Species
Neophocaena phocaenoides
Orcaella brevirostris
Dugong dugon
Sterna maxima
Sousa chinensis
Sousa teuszii
Synthliboramphus wumizusume
Tursiops aduncus
Cephalorhynchus heavisidii
Spheniscus demersus
Larus audouinii
Phalacrocorax nigrogularis
Halichoerus grypus
Larus ichthyaetus
103
Common name
Finless Porpoise
Irrawaddy Dolphin
Dugong Sea Cow Dugong
Royal Tern
Indo-Pacific Humpbacked Dolphin
Atlantic Hump-backed Dolphin
Japanese Murrelet
Indian or Bottlenose Dolphin
Heaviside's Dolphin
African Penguin
Audouin's Gull
Socotra Cormorant
Grey Seal
Great Black-headed Gull
Un-weighted
exposure
index
2.090
2.052
1.834
1.831
1.610
1.522
1.493
1.458
1.407
1.399
1.379
1.349
1.328
1.316
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
POP
PEG
SPH
LGE
PHV
LOF
LML
LPV
EBJ
POS
BAM
EBG
MMN
BEB
BAO
SBG
LHM
DAL
CEE
PUM
LGA
LGB
EIM
CTM
LPK
GRG
CAC
DCC
LAA
PCC
DEL
IPA
PHA
LLE
DDE
LGH
PUC
CHM
RHT
OFL
HYA
CCC
LMN
SNL
SNA
IOX
SNR
TUT
PTG
BOB
BAP
MNV
PYM
OOR
MMO
BMU
PIR
cetacean
seabirds
seabirds
seabirds
marine mammals other
marine mammals other
seabirds
turtle
cetacean
cetacean
cetacean
cetacean
marine mammals other
cetacean
cetacean
seabirds
seabirds
cetacean
cetacean
seabirds
cetacean
cetacean
turtle
shark
turtle
cetacean
turtle
turtle
seabirds
seabirds
cetacean
shark
seabirds
seabirds
cetacean
cetacean
seabirds
turtle
shark
marine mammals other
cetacean
shark
shark
cetacean
cetacean
shark
cetacean
cetacean
seabirds
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
seabirds
Phocoena phocoena
Pelecanoides garnotii
Spheniscus humboldti
Larus genei
Phoca vitulina
Lontra felina
Larus melanocephalus
Lepidochelys olivacea
Eubalaena japonica
Phocoena spinipinnis
Balaena mysticetus
Eubalaena glacialis
Monachus monachus
Berardius bairdii
Balaenoptera omurai
Sterna bergii
Larus hemprichii
Phocoenoides dalli
Cephalorhynchus eutropia
Puffinus mauretanicus
Lagenorhynchus acutus
Lagenorhynchus albirostris
Eretmochelys imbricata
Cetorhinus maximus
Lepidochelys kempii
Grampus griseus
Caretta caretta
Dermochelys coriacea
Larus armenicus
Pelecanus onocrotalus
Delphinapterus leucas
Isurus paucus
Phoebastria_albatrus
Larus leucophthalmus
Delphinus delphis
Lagenodelphis hosei
Puffinus creatopus
Chelonia mydas
Rhincodon typus
Arctocephalus australis
Hyperoodon ampullatus
Carcharodon carcharias
Lamna nasus
Stenella longirostris
Stenella attenuata
Isurus oxyrinchus
Stenella coeruleoalba
Tursiops truncatus
Pterodroma phaeopygia
Balaenoptera borealis
Balaenoptera physalus
Megaptera novaeangliae
Physeter macrocephalus
Orcinus orca
Monodon monoceros
Balaenoptera musculus
Phoebastria_irrorata
104
Common Porpoise
Peruvian diving petrel
Humboldt Penguin
Slender-billed Gull
Common Seal
Marine Otter
Mediterranean Gull
Ridley Turtle
North Pacific Right Whale
Burmeister Porpoise
Bowhead Whale
Northern Right Whale
Mediterranean Monk Seal
Baird's Beaked Whale
Omura' Whale
Great Crested Tern
Sooty Gull
Dall's Porpoise
Chilean Dolphin
Balearic shearwater
Atlantic White-sided Dolphin
White-beaked Dolphin
Hawksbill Turtle
Basking shark
Kemp's Ridley Turtle
Risso's Dolphin
Loggerhead Turtle
Leatherback Turtle
Armenian Gull
White Pelican
White Whale
Longfin Mako shark
Short-tailed Albatross
White-eyed Gull
Common Dolphin
Fraser's Dolphin
Pink-footed Shearwater
Green Turtle
Whale Shark
South American Seal
Northern Bottlenose Whale
Great White Shark
Porbeagle shark
Spinner Dolphin
Pantropical Spotted Dolphin
Shortfin Mako shark
Striped Dolphin
Bottlenosed Dolphin
Dark-rumped Petrel
Sei Whale
Fin Whale
Humpback Whale
Sperm Whale
Killer whale
Narwhal
Blue Whale
Waved Albatross
1.281
1.254
1.242
1.233
1.194
1.177
1.176
1.175
1.171
1.150
1.138
1.131
1.121
1.115
1.112
1.092
1.088
1.087
1.084
1.076
1.066
1.060
1.054
1.045
1.021
1.015
0.999
0.999
0.991
0.975
0.971
0.966
0.958
0.951
0.949
0.946
0.945
0.944
0.943
0.939
0.931
0.928
0.924
0.921
0.918
0.911
0.901
0.894
0.886
0.870
0.868
0.866
0.864
0.863
0.858
0.842
0.835
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
PCR
POB
LGO
LGS
SNC
PHI
LOP
LAT
GLM
CEC
DIM
PCW
DNB
PHN
EBA
BAB
PRK
POD
PHF
THH
PRO
THC
PCI
ORH
DIC
MAI
DIP
DIX
MAH
PCO
PXP
PHE
POW
PTT
STB
LSA
STI
STV
STE
STR
STS
STG
STN
STF
SDG
CAT
STH
BAE
DAM
CAM
LRL
STP
seabirds
cetacean
cetacean
cetacean
cetacean
seabirds
marine mammals other
seabirds
cetacean
cetacean
seabirds
seabirds
seabirds
seabirds
cetacean
cetacean
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
cetacean
seabirds
cetacean
seabirds
seabirds
Pelecanus crispus
Pontoporia blainvillei
Lagenorhynchus obscurus
Lagenorhynchus australis
Stenella clymene
Phoebastria_immutabilis
Lontra provocax
Larus atlanticus
Globicephala melas
Cephalorhynchus commersonii
Thalassarche_melanophrys
Procellaria westlandica
Thalassarche_bulleri
Phoebastria_nigripes
Eubalaena australis
Balaenoptera bonaerensis
Procellaria parkinsoni
Phocoena dioptrica
Phoebetria fusca
Thalassarche_chlororhynchos
Procellaria aequinoctialis
Thalassarche_cauta
Procellaria cinerea
Orcaella heinsohni
Thalassarche_chrysostoma
Macronectes giganteus
Diomedea epomophora
Diomedea exulans
Macronectes halli
Procellaria conspicillata
Phalacrocorax pygmeus
Phoebetria palpebrata
Pterodroma cahow
Pterodroma atrata
Sterna bernsteini
Larus saundersi
Sterna lorata
Sterna sandvicensis
Sterna balaenarum
Sterna repressa
Sterna saundersi
Sterna bengalensis
Sterna nilotica
Sterna albifrons
Sterna dougallii
Sterna caspia
Sterna hirundo
Balaenoptera edeni
Diomedea amsterdamensis
Caperea marginata
Larus relictus
Sterna paradisaea
105
Dalmatian Pelican
La Plata Dolphin
Dusky Dolphin
Peale's Dolphin
Clymene dolphin
Laysan Albatross
Southern River Otter
Olrog's Gull
Long-finned Pilot Whale
Commerson's Dolphin
Black-browed Albatross
Westland Petrel
Buller's Albatross
Black-footed Albatross
Southern Right Whale
Antarctic Minke whale
Black Petrel
Spectacled Porpoise
Sooty Albatross
Yellow-nosed Albatross
White-chinned Petrel
Shy Albatross
Grey Petrel
Australian Snubfin dolphin
Grey-headed Albatross
Southern Giant Petrel
Royal Albatross
Wandering Albatross
Northern Giant Petrel
Spectacled Petrel
Pygmy Cormorant
Light-mantled Sooty Albatross
Cahow Bermuda Petrel
Henderson Petrel
Chinese Crested Tern
Saunder's Gull
Peruvian tern
Sandwich Tern
Damara Tern
White-cheeked Tern
Saunder's Tern
Lesser Crested Tern
Gull-billed Tern
Little Tern
Roseate Tern
Caspian Tern
Common Tern
Bryde's whale
Amsterdam Albatross
Pygmy Right whale
Relict Gull
Arctic Tern
0.824
0.823
0.777
0.766
0.765
0.726
0.700
0.692
0.690
0.646
0.638
0.609
0.599
0.598
0.598
0.559
0.557
0.539
0.528
0.527
0.526
0.518
0.515
0.511
0.502
0.496
0.495
0.488
0.487
0.478
0.469
0.462
0.376
0.325
0.021
0.017
0.015
0.015
0.014
0.013
0.013
0.013
0.013
0.012
0.012
0.012
0.010
0.009
0.006
0.006
0.005
0.005
Figure 17 ¯ EEZs and High Seas FAO areas s howi ng with the un¯weighted exposures summed across seabi rds.
A reas with colours furthest up the scale bar (red colours) had higher seabi rd exposures.
Table 27 ¯ Seabi rds ranked by thei r un¯weighted exposure i ndex
Rank
4
7
10
11
12
14
16
17
18
21
30
31
34
43
44
47
48
Species
code
STM
SYW
SPD
LAU
PHG
LIC
PEG
SPH
LGE
LML
SBG
LHM
PUM
LAA
PCC
PHA
LLE
Family
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Species
Sterna maxima
Synthliboramphus wumizusume
Spheniscus demersus
Larus audouinii
Phalacrocorax nigrogularis
Larus ichthyaetus
Pelecanoides garnotii
Spheniscus humboldti
Larus genei
Larus melanocephalus
Sterna bergii
Larus hemprichii
Puffinus mauretanicus
Larus armenicus
Pelecanus onocrotalus
Phoebastria_albatrus
Larus leucophthalmus
Common name
Royal Tern
Japanese Murrelet
African Penguin
Audouin's Gull
Socotra Cormorant
Great Black-headed Gull
Peruvian diving petrel
Humboldt Penguin
Slender-billed Gull
Mediterranean Gull
Great Crested Tern
Sooty Gull
Balearic shearwater
Armenian Gull
White Pelican
Short-tailed Albatross
White-eyed Gull
106
Un-weighted
exposure
index
1.831
1.493
1.399
1.379
1.349
1.316
1.254
1.242
1.233
1.176
1.092
1.088
1.076
0.991
0.975
0.958
0.951
51
63
71
72
77
79
82
83
84
85
88
90
91
92
93
94
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
120
122
123
PUC
PTG
PIR
PCR
PHI
LAT
DIM
PCW
DNB
PHN
PRK
PHF
THH
PRO
THC
PCI
DIC
MAI
DIP
DIX
MAH
PCO
PXP
PHE
POW
PTT
STB
LSA
STI
STV
STE
STR
STS
STG
STN
STF
SDG
CAT
STH
DAM
LRL
STP
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
Puffinus creatopus
Pterodroma phaeopygia
Phoebastria_irrorata
Pelecanus crispus
Phoebastria_immutabilis
Larus atlanticus
Thalassarche melanophrys
Procellaria westlandica
Thalassarche bulleri
Phoebastria nigripes
Procellaria parkinsoni
Phoebetria fusca
Thalassarche chlororhynchos
Procellaria aequinoctialis
Thalassarche cauta
Procellaria cinerea
Thalassarche chrysostoma
Macronectes giganteus
Diomedea epomophora
Diomedea exulans
Macronectes halli
Procellaria conspicillata
Phalacrocorax pygmeus
Phoebetria palpebrata
Pterodroma cahow
Pterodroma atrata
Sterna bernsteini
Larus saundersi
Sterna lorata
Sterna sandvicensis
Sterna balaenarum
Sterna repressa
Sterna saundersi
Sterna bengalensis
Sterna nilotica
Sterna albifrons
Sterna dougallii
Sterna caspia
Sterna hirundo
Diomedea amsterdamensis
Larus relictus
Sterna paradisaea
Pink-footed Shearwater
Dark-rumped Petrel
Waved Albatross
Dalmatian Pelican
Laysan Albatross
Olrog's Gull
Black-browed Albatross
Westland Petrel
Buller's Albatross
Black-footed Albatross
Black Petrel
Sooty Albatross
Yellow-nosed Albatross
White-chinned Petrel
Shy Albatross
Grey Petrel
Grey-headed Albatross
Southern Giant Petrel
Royal Albatross
Wandering Albatross
Northern Giant Petrel
Spectacled Petrel
Pygmy Cormorant
Light-mantled Sooty Albatross
Cahow Bermuda Petrel
Henderson Petrel
Chinese Crested Tern
Saunder's Gull
Peruvian tern
Sandwich Tern
Damara Tern
White-cheeked Tern
Saunder's Tern
Lesser Crested Tern
Gull-billed Tern
Little Tern
Roseate Tern
Caspian Tern
Common Tern
Amsterdam Albatross
Relict Gull
Arctic Tern
107
0.945
0.886
0.835
0.824
0.726
0.692
0.638
0.609
0.599
0.598
0.557
0.528
0.527
0.526
0.518
0.515
0.502
0.496
0.495
0.488
0.487
0.478
0.469
0.462
0.376
0.325
0.021
0.017
0.015
0.015
0.014
0.013
0.013
0.013
0.013
0.012
0.012
0.012
0.010
0.006
0.005
0.005
Figure 18 Þ EEZs and High Seas FAO areas s howi ng with the unÞweighted exposures summed across turtles.
A reas with co lours furthest up the sca le bar (red co lours) had higher turtle exposures.
Table 28 Þ Turtles ranked by thei r unÞweighted exposure i ndex
Rank
22
37
39
41
42
52
Species
code
LPV
EIM
LPK
CAC
DCC
CHM
Family
turtle
turtle
turtle
turtle
turtle
turtle
Species
Lepidochelys olivacea
Eretmochelys imbricata
Lepidochelys kempii
Caretta caretta
Dermochelys coriacea
Chelonia mydas
Common name
Ridley Turtle
Hawksbill Turtle
Kemp's Ridley Turtle
Loggerhead Turtle
Leatherback Turtle
Green Turtle
108
Un-weighted
exposure index
1.175
1.054
1.021
0.999
0.999
0.944
Figure 19 EEZs and High Seas FAO areas s howi ng with the un
weighted exposures summed across s harks.
A reas with colours furthest up the scale bar (red colours) had higher s hark exposures.
Table 29 Sharks ranked by thei r un
weighted exposure i ndex
Rank
38
46
53
56
57
60
Species
code
CTM
IPA
RHT
CCC
LMN
IOX
Family
shark
shark
shark
shark
shark
shark
Species
Cetorhinus maximus
Isurus paucus
Rhincodon typus
Carcharodon carcharias
Lamna nasus
Isurus oxyrinchus
Common name
Basking shark
Longfin Mako shark
Whale Shark
Great White Shark
Porbeagle shark
Shortfin Mako shark
109
Un-weighted
exposure index
1.045
0.966
0.943
0.928
0.924
0.911
Figure 20 5 EEZs and High Seas FAO areas s howi ng with the un5weighted exposures summed across pi nni peds
and otters. A reas with colours furthest up the scale bar (red colours) had higher pi nni ped and otter exposures.
Table 30 5 Seal, sea lions and otters ranked by thei r un5weighted exposure i ndex
Rank
13
19
20
27
54
Species
code
HGR
PHV
LOF
MMN
OFL
Family
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
Species
Halichoerus grypus
Phoca vitulina
Lontra felina
Monachus monachus
Arctocephalus australis
Common name
Grey Seal
Common Seal
Marine Otter
Mediterranean Monk Seal
South American Seal
110
Un-weighted
exposure index
1.328
1.194
1.177
1.121
0.939
Table 31 _ EEZs and high seas FAO areas sorted presenti ng t he highest u n_weighted ex posu re for all s pecies
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
EEZ or High Seas FAO area
Myanmar
Vietnam
India
Russia Pacific
China
Peru
Chile
Norway
Bangladesh
Morocco
Indonesia (Western)
Namibia
Japan Main Isl.
Indonesia (Eastern)
Western Sahara (Morocco)
Mauritania
Iceland
South Africa
Angola
Nigeria
Sierra Leone
Guinea
United Kingdom
Philippines
Pacific Northwest - High seas Areas
Bahrain
Japan Outer Isl.
Senegal
Greece
Cameroon
Pacific Western Central - High seas Areas
Malaysia West
Malaysia East
Thailand
Korea South
Pakistan
Iran
Yemen
Malaysia Sarawak
Russia Barrents Sea
United Arab Emirates
Indian Ocean Eastern - High seas Areas
Korea North
Saudi Arabia Persian Gulf
Malaysia Sabah
Spain
Svalbard Isl. (Norway)
Alaska
Galapagos Isl.(Ecuador)
Turkey Mediterranean Sea
Somalia
Denmark
Algeria
Sum of all species
un-weighted
exposure index
1.530
1.497
1.478
1.325
1.240
1.218
1.190
1.173
1.157
1.146
1.106
1.103
1.102
1.072
1.063
1.051
1.006
0.992
0.950
0.917
0.890
0.883
0.875
0.834
0.825
0.823
0.823
0.805
0.804
0.797
0.795
0.793
0.787
0.778
0.771
0.765
0.758
0.747
0.743
0.742
0.742
0.740
0.738
0.737
0.736
0.734
0.728
0.713
0.697
0.688
0.678
0.671
0.666
111
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
Tunisia
Ghana
Gambia
Brazil
Oman
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Argentina
Greenland
Turkey Black Sea
Madagascar
Cambodia
Canada
New Zealand
France
Taiwan
Sweden
Ireland
Cote d'Ivoire
Faeroe Isl.(Denmark)
Gabon
Italy
Pacific Southeast - High seas Areas
Sudan
Mexico
Saudi Arabia Red Sea
Croatia
Australia
Papua New Guinea
Qatar
USA East Coast
Egypt
Uruguay
Indian Ocean Western - High seas Areas
Lebanon
Pacific Eastern Central - High seas Areas
Atlantic Southwest - High seas Areas
Congo Republic
Pacific Southwest - High seas Areas
Kuwait
Tanzania
Poland
Netherlands
Germany
Ecuador
Atlantic Eastern Central - High seas Areas
Atlantic Western Central - High seas Areas
Libya
Syria
Israel
Finland
Guyana
Portugal
Congo
Pacific Northeast - High seas Areas
Solomon Isl.
Atlantic Northeast - High seas Areas
Canary Isl.(Spain)
USA West Coast
Venezuela
Mozambique
Liberia
Andaman & Nicobar Isl. (India)
Sri Lanka
Latvia
Suriname
Hong Kong
Montenegro
Eritrea
Russia Baltic Sea Kaliningrad
Atlantic Northwest - High seas Areas
0.656
0.655
0.650
0.647
0.625
0.624
0.623
0.620
0.620
0.614
0.610
0.609
0.608
0.603
0.602
0.577
0.573
0.572
0.567
0.564
0.563
0.561
0.542
0.533
0.531
0.527
0.525
0.523
0.511
0.510
0.507
0.502
0.502
0.487
0.484
0.449
0.448
0.441
0.441
0.434
0.433
0.428
0.419
0.406
0.402
0.400
0.395
0.392
0.381
0.378
0.378
0.359
0.355
0.352
0.352
0.352
0.348
0.347
0.342
0.340
0.339
0.339
0.337
0.335
0.328
0.324
0.323
0.321
0.318
0.318
112
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
Togo
Benin
Jan Mayen Isl. (Norway)
Atlantic SouthEast - High seas Areas
Maldives
Cyprus
Colombia
USA Golf Of Mexico
Malta
Falkland Isl.(UK)
Estonia
Ukraine
Brunei
Channel Isl.(UK)
Jamaica
Fiji
Guinea-Bissau
Desventuradas Isl.(Chile)
Albania
Cuba
Haiti
Singapore
Lithuania
Haiwaii NorthWest Isl.
Dominican Rep.
Kenya
Gaza Strip
Russia Siberia
Mayotte (FR)
Panama
Cape Verde
Sao Tome & Principe
French Polynesia
Equatorial Guinea
Kiribati
French Guyana
Macau (China)
Mauritius
Madeira Isl.(Portugal)
Trinidad & Tobago
Belgium
Azores Isl.(Portugal)
Iraq
Martinique
Timor Leste
Honduras
Christmas Isl.(Australia)
St Pierre & Miquelon (FR)
Bermuda (UK)
Vanuatu
Costa Rica
Micronesia
Jordan
Bosnia
Brit. Virgin Isl.(UK)
Russia Black Sea
Djibouti
Cocos Isl.(Australia)
Guadeloupe (FR)
Comoros Isl.
Trindade & Matin Isl (BR)
New Caledonia
St Lucia
Lord Howe Isl. (Australia)
El Salvador
Dominica
Puerto Rico (US)
Seychelles
Palau
Georgia
0.317
0.316
0.314
0.312
0.302
0.298
0.291
0.291
0.282
0.279
0.272
0.270
0.267
0.262
0.261
0.256
0.247
0.245
0.244
0.243
0.243
0.243
0.239
0.230
0.230
0.225
0.223
0.223
0.218
0.214
0.213
0.206
0.205
0.204
0.201
0.197
0.194
0.192
0.190
0.180
0.179
0.178
0.169
0.164
0.164
0.163
0.161
0.159
0.158
0.156
0.155
0.155
0.155
0.152
0.150
0.150
0.150
0.148
0.144
0.143
0.140
0.140
0.137
0.136
0.135
0.133
0.131
0.126
0.121
0.119
113
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
St Paul & Amsterdam (FR)
Monaco
Marshall Isl.
Norfolk Isl. (Australia)
Tuvalu
Easter Isl.(Chile)
Nicaragua
Antigua & Barbuda
Grenada
Prince Edward Isl. (SA)
Anguila (UK)
Wallis & Futuna (FR)
Haiwaii Main Isl.
Kerguelen Isl. (FR)
St Vincent & The Grenadines
Romania
Bulgaria
Pitcairn (UK)
Crozet Isl.(FR)
Mozambique Channel Isl. (FR)
Leeward Netherland Antilles
Bahamas
St Kitts & Nevis
Indian Ocean Antarctic - High seas Areas
Windward Netherlands Antilles
Tonga
Montserrat (UK)
Cook Isl.(New Zealand)
Brit. Indian Oce (UK)
Slovenia
Cayman Isl.(UK)
Guam (US)
Ascencion Isl.
Arctic Sea - High seas Areas
American Samoa
Nauru
Tromelin Isl.(FR)
Barbados
Palmyra Atoll & Kingman Reef (US)
Belize
South Georgia & Sandwich Isl. (UK)
Northern Marianas (US)
Guatemala
Clipperton Isl.(FR)
Reunion (FR)
Samoa
Johnston Atoll (US)
Tokelau (NZ)
Jarvis Isl.(US)
Howland & Baker Isl.(US)
St Helena (UK)
Atlantic Antarctic - High seas Areas
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Niue (NZ)
Russia Baltic Sea St Petersburg
Turks & Caicos Isl (UK)
Navassa Isl. (Haiti)
Wake Isl.(US)
Pacific Antarctic - High seas Areas
0.118
0.116
0.115
0.115
0.111
0.110
0.109
0.105
0.105
0.105
0.104
0.100
0.099
0.095
0.093
0.091
0.089
0.089
0.084
0.083
0.083
0.081
0.081
0.080
0.079
0.077
0.075
0.073
0.070
0.070
0.069
0.068
0.068
0.067
0.065
0.063
0.063
0.061
0.060
0.059
0.057
0.057
0.056
0.056
0.055
0.052
0.046
0.044
0.041
0.028
0.026
0.021
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
114
Table 32 ƒ EEZs and high seas FAO areas sorted presenti ng t he highest IUCN weighted ex posure for all s pecies
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
EEZ or High Seas FAO area
Myanmar
Vietnam
Peru
India
Russia Pacific
Chile
South Africa
China
Namibia
Greece
Galapagos Isl.(Ecuador)
Bangladesh
Japan Main Isl.
Indonesia (Western)
Indonesia (Eastern)
Norway
Mauritania
United Kingdom
Algeria
Morocco
Western Sahara (Morocco)
Pacific Western Central - High seas Areas
Iceland
Tunisia
Japan Outer Isl.
Turkey Mediterranean Sea
Pacific Northwest - High seas Areas
Philippines
Bahrain
Korea South
Malaysia East
Malaysia West
Angola
Thailand
Croatia
Korea North
Malaysia Sarawak
Denmark
Indian Ocean Eastern - High seas Areas
Malaysia Sabah
Nigeria
Guinea
Sierra Leone
Saudi Arabia Persian Gulf
Senegal
Spain
Mexico
United Arab Emirates
Pacific Southeast - High seas Areas
Alaska
France
Iran
Brazil
Ireland
USA East Coast
Cameroon
Pakistan
Yemen
Sum of all species
IUCN weighted
exposure index
1.539
1.518
1.488
1.432
1.294
1.280
1.271
1.268
1.246
1.195
1.164
1.132
1.121
1.115
1.075
1.057
1.011
0.987
0.976
0.949
0.947
0.917
0.908
0.873
0.860
0.851
0.848
0.836
0.826
0.808
0.805
0.802
0.795
0.794
0.792
0.777
0.767
0.762
0.753
0.742
0.741
0.735
0.727
0.725
0.721
0.710
0.687
0.687
0.684
0.681
0.672
0.669
0.668
0.667
0.667
0.663
0.639
0.636
115
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Madagascar
Argentina
Cambodia
Taiwan
New Zealand
Canada
Ecuador
Somalia
Pacific Eastern Central - High seas Areas
Oman
Papua New Guinea
Gambia
Indian Ocean Western - High seas Areas
Ghana
Atlantic Southwest - High seas Areas
Canary Isl.(Spain)
Qatar
Montenegro
Venezuela
Uruguay
Gabon
Russia Barrents Sea
Italy
Netherlands
Germany
Atlantic Western Central - High seas Areas
Svalbard Isl. (Norway)
Faeroe Isl.(Denmark)
Atlantic Eastern Central - High seas Areas
Cote d'Ivoire
Australia
Sweden
Pacific Southwest - High seas Areas
Portugal
Guyana
Kuwait
Mozambique
USA Golf Of Mexico
Greenland
Sudan
Egypt
Saudi Arabia Red Sea
Colombia
Suriname
Pacific Northeast - High seas Areas
Tanzania
Solomon Isl.
Libya
Atlantic Northwest - High seas Areas
Andaman & Nicobar Isl. (India)
USA West Coast
Atlantic SouthEast - High seas Areas
Congo Republic
Sri Lanka
Malta
Hong Kong
Atlantic Northeast - High seas Areas
Cape Verde
Fiji
Jamaica
Madeira Isl.(Portugal)
Maldives
Haiwaii NorthWest Isl.
Channel Isl.(UK)
Congo
Falkland Isl.(UK)
Haiti
Panama
Cuba
0.628
0.626
0.623
0.618
0.612
0.587
0.578
0.572
0.553
0.544
0.540
0.536
0.533
0.524
0.524
0.505
0.502
0.499
0.496
0.489
0.486
0.485
0.485
0.485
0.471
0.467
0.465
0.461
0.459
0.457
0.456
0.451
0.449
0.446
0.435
0.430
0.425
0.423
0.420
0.407
0.398
0.379
0.378
0.376
0.373
0.372
0.370
0.369
0.367
0.365
0.364
0.363
0.363
0.355
0.335
0.333
0.327
0.322
0.308
0.305
0.299
0.295
0.295
0.292
0.291
0.281
0.281
0.276
0.275
0.274
116
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
Liberia
Brunei
Poland
French Polynesia
Dominican Rep.
Azores Isl.(Portugal)
Turkey Black Sea
Togo
Benin
Trinidad & Tobago
Lebanon
Singapore
Kiribati
Desventuradas Isl.(Chile)
Eritrea
Finland
Jan Mayen Isl. (Norway)
Albania
Bosnia
Mayotte (FR)
French Guyana
Sao Tome & Principe
Israel
Bermuda (UK)
Cyprus
Latvia
Costa Rica
Guinea-Bissau
Belgium
Macau (China)
Mauritius
Russia Baltic Sea Kaliningrad
Syria
Kenya
Honduras
Martinique
El Salvador
Equatorial Guinea
Gaza Strip
Micronesia
Brit. Virgin Isl.(UK)
Estonia
Vanuatu
Trindade & Matin Isl (BR)
Timor Leste
Ukraine
Christmas Isl.(Australia)
Guadeloupe (FR)
St Pierre & Miquelon (FR)
Iraq
New Caledonia
St Lucia
Grenada
Dominica
Puerto Rico (US)
Cocos Isl.(Australia)
Russia Siberia
Comoros Isl.
Lithuania
Lord Howe Isl. (Australia)
Seychelles
Nicaragua
St Paul & Amsterdam (FR)
Norfolk Isl. (Australia)
Tuvalu
Palau
Marshall Isl.
Antigua & Barbuda
Leeward Netherland Antilles
Pitcairn (UK)
0.272
0.270
0.268
0.262
0.262
0.259
0.252
0.251
0.250
0.249
0.247
0.245
0.241
0.237
0.237
0.237
0.229
0.228
0.227
0.224
0.224
0.217
0.215
0.212
0.209
0.207
0.206
0.197
0.196
0.196
0.196
0.195
0.190
0.190
0.190
0.186
0.184
0.183
0.179
0.174
0.171
0.168
0.167
0.166
0.165
0.164
0.164
0.164
0.162
0.162
0.157
0.156
0.152
0.151
0.149
0.148
0.147
0.146
0.146
0.143
0.138
0.136
0.134
0.134
0.132
0.132
0.131
0.121
0.120
0.119
117
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
St Vincent & The Grenadines
Wallis & Futuna (FR)
Anguila (UK)
Prince Edward Isl. (SA)
Easter Isl.(Chile)
Djibouti
Bahamas
Haiwaii Main Isl.
Monaco
Mozambique Channel Isl. (FR)
St Kitts & Nevis
Tonga
Windward Netherlands Antilles
Russia Black Sea
Crozet Isl.(FR)
Montserrat (UK)
Jordan
Cook Isl.(New Zealand)
Kerguelen Isl. (FR)
Guam (US)
Cayman Isl.(UK)
Ascencion Isl.
Indian Ocean Antarctic - High seas Areas
Belize
American Samoa
Brit. Indian Oce (UK)
Nauru
Guatemala
Clipperton Isl.(FR)
Palmyra Atoll & Kingman Reef (US)
Tromelin Isl.(FR)
Barbados
Slovenia
Northern Marianas (US)
Samoa
Reunion (FR)
South Georgia & Sandwich Isl. (UK)
Georgia
Tokelau (NZ)
Romania
Johnston Atoll (US)
Bulgaria
Jarvis Isl.(US)
Arctic Sea - High seas Areas
Howland & Baker Isl.(US)
St Helena (UK)
Atlantic Antarctic - High seas Areas
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Niue (NZ)
Russia Baltic Sea St Petersburg
Turks & Caicos Isl (UK)
Navassa Isl. (Haiti)
Wake Isl.(US)
Pacific Antarctic - High seas Areas
0.119
0.119
0.118
0.114
0.114
0.111
0.100
0.099
0.095
0.093
0.092
0.091
0.090
0.089
0.088
0.086
0.083
0.081
0.081
0.079
0.078
0.077
0.077
0.076
0.075
0.075
0.074
0.074
0.074
0.071
0.070
0.070
0.063
0.063
0.062
0.057
0.053
0.053
0.052
0.052
0.051
0.049
0.047
0.045
0.033
0.031
0.021
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
118
Table 33 ª High Seas FAO areas EEZ sorted by t hei r cont ri bution i n t he different exposures for all cetacean
sorted by IUCN weighted exposure
EEZ, High Seas FAO area
Vietnam
Myanmar
India
China
Indonesia (Western)
Russia Pacific
Indonesia (Eastern)
Japan Main Isl.
Norway
Bangladesh
Chile
Philippines
Pacific Northwest - High seas Areas
Indian Ocean Eastern - High seas Areas
Iceland
Malaysia Sarawak
Korea South
Malaysia East
Thailand
Malaysia Sabah
Malaysia West
Japan Outer Isl.
Korea North
Canada
United Kingdom
Angola
Pacific Western Central - High seas Areas
South Africa
Brazil
Mauritania
Cambodia
Taiwan
Peru
Western Sahara (Morocco)
Alaska
Namibia
Madagascar
Argentina
Australia
Pacific Southeast - High seas Areas
Morocco
Nigeria
Pakistan
Papua New Guinea
Sierra Leone
Guinea
USA East Coast
Mexico
Greenland
Indian Ocean Western - High seas Areas
Senegal
Svalbard Isl. (Norway)
Atlantic Southwest - High seas Areas
Cameroon
Pacific Eastern Central - High seas Areas
Ireland
Overall rank
937
127
462
187
477
857
472
517
732
57
167
782
1257
1232
457
612
547
597
1002
602
592
522
542
147
1067
17
1272
952
87
627
137
192
777
972
1082
672
587
27
32
1262
657
717
762
772
927
427
1117
637
402
1237
917
987
1217
142
1247
492
Family
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
119
Overlap
index
0.935
0.892
0.859
0.766
0.703
0.783
0.707
0.663
0.664
0.614
0.58
0.548
0.589
0.588
0.515
0.496
0.486
0.48
0.474
0.47
0.466
0.466
0.415
0.438
0.433
0.399
0.422
0.432
0.396
0.417
0.359
0.373
0.397
0.402
0.366
0.412
0.372
0.339
0.367
0.39
0.358
0.333
0.327
0.318
0.327
0.327
0.327
0.332
0.344
0.351
0.32
0.359
0.319
0.298
0.32
0.292
Unweighted
exposure
index
1.064
1.013
0.974
0.875
0.8
0.928
0.802
0.76
0.787
0.694
0.642
0.622
0.662
0.626
0.61
0.562
0.561
0.544
0.538
0.535
0.529
0.527
0.491
0.515
0.513
0.454
0.462
0.47
0.45
0.471
0.408
0.423
0.448
0.453
0.434
0.446
0.418
0.383
0.405
0.409
0.403
0.374
0.367
0.358
0.367
0.367
0.371
0.371
0.407
0.369
0.361
0.425
0.344
0.335
0.356
0.346
IUCN
weighted
exposure
index
1
0.953
0.903
0.801
0.751
0.743
0.733
0.655
0.642
0.635
0.571
0.57
0.549
0.536
0.521
0.518
0.516
0.507
0.502
0.502
0.497
0.486
0.468
0.419
0.416
0.405
0.403
0.394
0.388
0.386
0.384
0.383
0.378
0.374
0.373
0.373
0.354
0.348
0.34
0.333
0.328
0.324
0.322
0.317
0.317
0.317
0.309
0.309
0.308
0.306
0.297
0.296
0.291
0.289
0.288
0.283
Pacific Southwest - High seas Areas
Iran
Russia Barrents Sea
Faeroe Isl.(Denmark)
France
Somalia
Spain
United Arab Emirates
Denmark
Atlantic Eastern Central - High seas Areas
Oman
Yemen
Gambia
Atlantic Western Central - High seas Areas
New Zealand
Ghana
Saudi Arabia Persian Gulf
Atlantic Northeast - High seas Areas
Gabon
Atlantic Northwest - High seas Areas
Uruguay
Solomon Isl.
Tanzania
Sri Lanka
Cote d'Ivoire
Guyana
Brunei
Pacific Northeast - High seas Areas
Hong Kong
Atlantic SouthEast - High seas Areas
Andaman & Nicobar Isl. (India)
Bahrain
USA West Coast
Suriname
Sweden
Canary Isl.(Spain)
Netherlands
Portugal
Venezuela
Germany
Kuwait
Singapore
Mozambique
Egypt
Ecuador
Maldives
Colombia
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Congo Republic
Saudi Arabia Red Sea
Jamaica
Jan Mayen Isl. (Norway)
Sudan
Qatar
USA Golf Of Mexico
Falkland Isl.(UK)
Mayotte (FR)
Galapagos Isl.(Ecuador)
Desventuradas Isl.(Chile)
Haiti
Fiji
Cuba
Liberia
Dominican Rep.
Italy
Greece
Congo
Togo
Tunisia
Benin
1267
482
842
302
327
947
967
1027
262
1197
667
1157
367
1222
707
382
912
1202
357
1207
1132
107
1077
162
507
432
117
1252
452
1212
467
52
1112
982
992
962
682
797
1137
377
552
932
662
1062
277
607
207
182
222
907
512
737
977
827
1122
307
217
282
177
437
317
247
567
272
502
397
227
1007
1032
257
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
120
0.314
0.279
0.322
0.275
0.27
0.265
0.242
0.253
0.293
0.265
0.255
0.25
0.255
0.247
0.254
0.233
0.21
0.244
0.226
0.225
0.213
0.202
0.203
0.197
0.205
0.225
0.172
0.173
0.175
0.205
0.177
0.165
0.181
0.191
0.163
0.179
0.186
0.146
0.177
0.18
0.145
0.141
0.162
0.148
0.167
0.161
0.163
0.154
0.146
0.132
0.155
0.154
0.126
0.123
0.147
0.118
0.129
0.149
0.128
0.142
0.129
0.139
0.121
0.134
0.12
0.137
0.115
0.113
0.117
0.112
0.327
0.317
0.381
0.326
0.32
0.297
0.287
0.29
0.347
0.294
0.286
0.281
0.287
0.274
0.268
0.262
0.248
0.288
0.254
0.257
0.237
0.227
0.229
0.222
0.23
0.249
0.196
0.196
0.198
0.217
0.198
0.196
0.205
0.212
0.193
0.199
0.221
0.173
0.196
0.213
0.172
0.16
0.177
0.176
0.184
0.176
0.18
0.15
0.163
0.157
0.172
0.182
0.15
0.146
0.163
0.13
0.145
0.163
0.14
0.157
0.141
0.154
0.136
0.149
0.142
0.162
0.129
0.127
0.138
0.126
0.278
0.276
0.273
0.265
0.265
0.26
0.259
0.259
0.256
0.247
0.245
0.243
0.236
0.231
0.227
0.226
0.222
0.22
0.218
0.209
0.207
0.204
0.2
0.199
0.199
0.198
0.183
0.182
0.182
0.179
0.175
0.175
0.172
0.168
0.162
0.16
0.158
0.156
0.155
0.153
0.153
0.151
0.15
0.15
0.143
0.142
0.142
0.139
0.139
0.138
0.136
0.136
0.131
0.13
0.129
0.128
0.127
0.125
0.125
0.124
0.122
0.122
0.118
0.118
0.112
0.112
0.11
0.11
0.109
0.109
Macau (China)
French Guyana
Cape Verde
Channel Isl.(UK)
Sao Tome & Principe
Panama
Algeria
Mauritius
Christmas Isl.(Australia)
Kenya
Timor Leste
Equatorial Guinea
French Polynesia
Kiribati
Guinea-Bissau
Cocos Isl.(Australia)
Honduras
Eritrea
Trinidad & Tobago
Martinique
Vanuatu
New Caledonia
Comoros Isl.
Lord Howe Isl. (Australia)
Croatia
St Pierre & Miquelon (FR)
Brit. Virgin Isl.(UK)
Trindade & Matin Isl (BR)
Turkey Mediterranean Sea
Libya
Azores Isl.(Portugal)
Costa Rica
Guadeloupe (FR)
Poland
Micronesia
Russia Siberia
St Lucia
Norfolk Isl. (Australia)
Dominica
Puerto Rico (US)
Seychelles
Palau
Madeira Isl.(Portugal)
Belgium
Finland
Easter Isl.(Chile)
Iraq
Latvia
El Salvador
Nicaragua
Russia Baltic Sea Kaliningrad
Malta
Antigua & Barbuda
Anguila (UK)
Djibouti
St Paul & Amsterdam (FR)
Marshall Isl.
Tuvalu
Wallis & Futuna (FR)
Haiwaii NorthWest Isl.
Mozambique Channel Isl. (FR)
Estonia
Grenada
St Vincent & The Grenadines
Montenegro
Indian Ocean Antarctic - High seas Areas
Bahamas
Haiwaii Main Isl.
Albania
St Kitts & Nevis
582
342
152
1072
902
767
7
632
197
537
817
292
347
392
812
202
447
132
1022
622
702
697
212
42
242
892
112
92
1037
572
807
237
412
792
747
862
887
727
267
822
922
757
802
67
322
172
487
562
287
712
852
617
22
882
352
1167
752
1052
1147
642
332
297
407
897
1162
1227
47
1087
2
877
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
121
0.104
0.119
0.114
0.118
0.109
0.119
0.105
0.112
0.099
0.101
0.096
0.093
0.095
0.093
0.089
0.084
0.098
0.081
0.096
0.095
0.087
0.09
0.082
0.099
0.091
0.081
0.088
0.08
0.098
0.086
0.07
0.085
0.084
0.057
0.076
0.08
0.08
0.081
0.078
0.076
0.069
0.066
0.072
0.077
0.051
0.065
0.055
0.045
0.066
0.063
0.043
0.062
0.061
0.061
0.053
0.05
0.055
0.054
0.05
0.055
0.053
0.037
0.053
0.052
0.052
0.039
0.047
0.049
0.047
0.047
0.118
0.132
0.127
0.139
0.122
0.131
0.124
0.123
0.112
0.113
0.108
0.104
0.099
0.101
0.099
0.093
0.108
0.095
0.106
0.106
0.097
0.099
0.092
0.102
0.108
0.096
0.097
0.088
0.116
0.102
0.08
0.094
0.093
0.068
0.084
0.094
0.088
0.083
0.086
0.084
0.076
0.073
0.079
0.092
0.06
0.068
0.065
0.053
0.073
0.07
0.051
0.073
0.068
0.067
0.06
0.054
0.059
0.059
0.055
0.06
0.059
0.043
0.059
0.057
0.061
0.042
0.052
0.053
0.056
0.052
0.108
0.105
0.105
0.104
0.104
0.103
0.102
0.101
0.099
0.099
0.095
0.088
0.086
0.086
0.086
0.086
0.085
0.085
0.084
0.084
0.083
0.083
0.081
0.08
0.08
0.08
0.077
0.077
0.076
0.075
0.075
0.074
0.073
0.073
0.073
0.071
0.07
0.068
0.068
0.067
0.066
0.066
0.066
0.065
0.065
0.062
0.057
0.057
0.056
0.055
0.055
0.054
0.054
0.053
0.052
0.052
0.051
0.051
0.048
0.047
0.047
0.047
0.047
0.045
0.045
0.043
0.043
0.042
0.041
0.041
Lebanon
Lithuania
Windward Netherlands Antilles
Montserrat (UK)
Ascencion Isl.
Israel
Leeward Netherland Antilles
Tonga
Brit. Indian Oce (UK)
Kerguelen Isl. (FR)
Cayman Isl.(UK)
Cook Isl.(New Zealand)
Cyprus
Guam (US)
Tromelin Isl.(FR)
Gaza Strip
Barbados
American Samoa
Syria
Prince Edward Isl. (SA)
Belize
Reunion (FR)
Jordan
Crozet Isl.(FR)
Bermuda (UK)
Palmyra Atoll & Kingman Reef (US)
Northern Marianas (US)
Guatemala
Nauru
Samoa
Turkey Black Sea
Monaco
Clipperton Isl.(FR)
Johnston Atoll (US)
Bosnia
Tokelau (NZ)
Jarvis Isl.(US)
South Georgia & Sandwich Isl. (UK)
Ukraine
Pitcairn (UK)
St Helena (UK)
Atlantic Antarctic - High seas Areas
Howland & Baker Isl.(US)
Slovenia
Arctic Sea - High seas Areas
Russia Black Sea
Romania
Bulgaria
Georgia
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Niue (NZ)
Russia Baltic Sea St Petersburg
Turks & Caicos Isl (UK)
Navassa Isl. (Haiti)
Wake Isl.(US)
Pacific Antarctic - High seas Areas
557
577
687
652
1127
497
692
1017
102
1177
157
232
252
417
337
372
62
12
997
957
97
832
532
1172
72
1097
742
422
677
1152
1042
647
1182
527
77
1012
1102
312
1057
787
872
1192
1107
942
1187
847
837
122
362
37
82
387
442
722
867
1047
1092
1142
1242
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
cetacean
122
0.05
0.032
0.046
0.044
0.04
0.045
0.042
0.039
0.039
0.033
0.04
0.037
0.04
0.035
0.036
0.038
0.036
0.033
0.037
0.028
0.034
0.033
0.027
0.027
0.029
0.03
0.029
0.03
0.028
0.026
0.049
0.025
0.028
0.023
0.022
0.02
0.02
0.015
0.036
0.016
0.014
0.011
0.013
0.014
0.012
0.019
0.012
0.011
0.01
0
0
0
0
0
0
0
0
0
0
0.059
0.038
0.051
0.049
0.043
0.053
0.047
0.042
0.042
0.036
0.045
0.04
0.048
0.038
0.04
0.045
0.04
0.036
0.043
0.03
0.038
0.036
0.032
0.028
0.032
0.033
0.031
0.034
0.03
0.029
0.059
0.029
0.031
0.025
0.026
0.022
0.022
0.016
0.042
0.017
0.015
0.012
0.014
0.017
0.015
0.022
0.014
0.013
0.011
0
0
0
0
0
0
0
0
0
0
0.041
0.041
0.041
0.039
0.038
0.037
0.037
0.036
0.036
0.036
0.035
0.035
0.033
0.033
0.033
0.032
0.031
0.031
0.03
0.03
0.03
0.03
0.029
0.029
0.028
0.028
0.027
0.026
0.026
0.025
0.024
0.024
0.024
0.021
0.019
0.019
0.019
0.016
0.016
0.016
0.013
0.013
0.012
0.012
0.01
0.009
0.005
0.005
0.004
0
0
0
0
0
0
0
0
0
0
Table 34 × High Seas FAO areas EEZ sorted by t hei r cont ri bution i n t he different exposures for all seabi rds
sorted by IUCN weighted exposure
EEZ, High Seas FAO area
Peru
Chile
South Africa
Pacific Southeast - High seas Areas
Namibia
Indian Ocean Eastern - High seas Areas
New Zealand
Galapagos Isl.(Ecuador)
Atlantic Southwest - High seas Areas
Japan Main Isl.
Pacific Southwest - High seas Areas
Russia Pacific
Pacific Eastern Central - High seas Areas
Argentina
Morocco
Japan Outer Isl.
Indian Ocean Western - High seas Areas
Iran
Atlantic SouthEast - High seas Areas
Yemen
Australia
India
Angola
Brazil
Greece
Turkey Mediterranean Sea
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Pacific Northwest - High seas Areas
Mexico
Egypt
Alaska
Mauritania
Spain
United Arab Emirates
Ecuador
Somalia
Uruguay
China
Pacific Western Central - High seas Areas
Pakistan
Western Sahara (Morocco)
Bahrain
Oman
Saudi Arabia Persian Gulf
Korea South
Italy
Tunisia
Saudi Arabia Red Sea
Algeria
France
Senegal
Croatia
Sudan
Kuwait
Qatar
Pacific Northeast - High seas Areas
Canada
Falkland Isl.(UK)
Lebanon
Overall rank
776
166
951
1261
671
1231
706
281
1216
516
1266
856
1246
26
656
521
1236
481
1211
1156
31
461
16
86
396
1036
181
1256
636
1061
1081
626
966
1026
276
946
1131
186
1271
761
971
51
666
911
546
501
1031
906
6
326
916
241
976
551
826
1251
146
306
556
Family
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
123
Overlap
index
0.459
0.491
0.513
0.3
0.412
0.382
0.311
0.133
0.215
0.288
0.257
0.3
0.152
0.186
0.5
0.243
0.262
0.48
0.15
0.403
0.277
0.763
0.332
0.116
0.246
0.292
0.131
0.117
0.126
0.369
0.116
0.501
0.255
0.333
0.131
0.431
0.109
0.533
0.157
0.548
0.385
0.204
0.351
0.281
0.216
0.187
0.265
0.291
0.242
0.174
0.364
0.149
0.295
0.214
0.19
0.065
0.064
0.076
0.147
Unweighted
exposure
index
0.421
0.511
0.382
0.336
0.315
0.35
0.33
0.158
0.245
0.225
0.269
0.211
0.181
0.211
0.379
0.205
0.204
0.297
0.166
0.282
0.201
0.338
0.2
0.137
0.23
0.256
0.155
0.139
0.117
0.266
0.135
0.303
0.203
0.209
0.081
0.226
0.129
0.147
0.144
0.26
0.264
0.146
0.207
0.17
0.105
0.183
0.173
0.223
0.16
0.149
0.202
0.155
0.186
0.124
0.125
0.077
0.067
0.082
0.146
IUCN
weighted
exposure
index
0.576
0.566
0.436
0.384
0.366
0.321
0.314
0.279
0.275
0.264
0.257
0.242
0.226
0.222
0.222
0.221
0.201
0.188
0.185
0.18
0.176
0.175
0.172
0.172
0.161
0.16
0.159
0.156
0.155
0.152
0.149
0.146
0.142
0.142
0.141
0.141
0.14
0.135
0.134
0.131
0.129
0.125
0.125
0.123
0.123
0.12
0.117
0.112
0.108
0.106
0.099
0.097
0.092
0.091
0.089
0.088
0.086
0.085
0.083
Gambia
Mozambique
Turkey Black Sea
United Kingdom
Libya
USA West Coast
Syria
Israel
Bangladesh
Norway
Guinea
Colombia
Denmark
Taiwan
Desventuradas Isl.(Chile)
Haiwaii NorthWest Isl.
Cyprus
Albania
Eritrea
Ukraine
Montenegro
French Polynesia
Myanmar
Portugal
Ireland
Prince Edward Isl. (SA)
St Paul & Amsterdam (FR)
Panama
Netherlands
Crozet Isl.(FR)
Nigeria
Kerguelen Isl. (FR)
Germany
Atlantic Western Central - High seas Areas
Atlantic Northwest - High seas Areas
Indian Ocean Antarctic - High seas Areas
Gaza Strip
Iraq
Philippines
Malta
Sierra Leone
Costa Rica
Ghana
Faeroe Isl.(Denmark)
El Salvador
Cameroon
Vietnam
Russia Black Sea
Kiribati
Bermuda (UK)
South Georgia & Sandwich Isl. (UK)
Gabon
Channel Isl.(UK)
Djibouti
Congo Republic
Hong Kong
Tanzania
Cote d'Ivoire
Indonesia (Eastern)
Monaco
Haiwaii Main Isl.
Indonesia (Western)
Congo
Madagascar
Nicaragua
Lord Howe Isl. (Australia)
Bosnia
Belgium
Russia Siberia
USA East Coast
366
661
1041
1066
571
1111
996
496
56
731
426
206
261
191
176
641
251
1
131
1056
1161
346
126
796
491
956
1166
766
681
1171
716
1176
376
1221
1206
1226
371
486
781
616
926
236
381
301
286
141
936
846
391
71
311
356
1071
351
221
451
1076
506
471
646
1086
476
226
586
711
41
76
66
861
1116
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
124
0.289
0.134
0.145
0.133
0.166
0.065
0.114
0.141
0.358
0.101
0.331
0.045
0.126
0.18
0.046
0.039
0.092
0.085
0.184
0.151
0.064
0.034
0.337
0.079
0.105
0.043
0.051
0.031
0.088
0.041
0.334
0.041
0.1
0.022
0.021
0.038
0.076
0.073
0.265
0.039
0.29
0.025
0.261
0.031
0.016
0.242
0.517
0.078
0.032
0.014
0.025
0.178
0.027
0.089
0.151
0.096
0.165
0.212
0.345
0.026
0.016
0.278
0.122
0.21
0.012
0.036
0.031
0.034
0.061
0.03
0.165
0.086
0.158
0.078
0.107
0.059
0.117
0.132
0.175
0.055
0.163
0.042
0.065
0.072
0.055
0.047
0.092
0.084
0.11
0.104
0.069
0.04
0.127
0.064
0.052
0.048
0.043
0.028
0.053
0.045
0.111
0.045
0.046
0.026
0.025
0.04
0.064
0.049
0.06
0.046
0.089
0.022
0.087
0.027
0.019
0.078
0.071
0.056
0.03
0.017
0.028
0.067
0.03
0.051
0.064
0.03
0.06
0.058
0.057
0.028
0.018
0.052
0.051
0.043
0.012
0.029
0.033
0.022
0.033
0.012
0.081
0.08
0.079
0.079
0.076
0.073
0.072
0.071
0.068
0.064
0.063
0.063
0.06
0.06
0.057
0.057
0.056
0.056
0.054
0.054
0.051
0.049
0.049
0.049
0.048
0.046
0.045
0.045
0.044
0.043
0.043
0.043
0.041
0.041
0.038
0.038
0.037
0.036
0.036
0.035
0.035
0.034
0.034
0.031
0.031
0.031
0.029
0.029
0.029
0.027
0.026
0.026
0.026
0.025
0.025
0.024
0.023
0.023
0.022
0.021
0.021
0.02
0.02
0.02
0.02
0.019
0.019
0.018
0.018
0.018
Clipperton Isl.(FR)
Jordan
Benin
Togo
Honduras
Macau (China)
Malaysia Sarawak
Kenya
Norfolk Isl. (Australia)
Guinea-Bissau
Malaysia East
Thailand
Pitcairn (UK)
Sri Lanka
Malaysia West
Bulgaria
Marshall Isl.
Atlantic Northeast - High seas Areas
Liberia
Malaysia Sabah
Guatemala
Romania
Trindade & Matin Isl (BR)
Georgia
Papua New Guinea
Slovenia
Cambodia
Cook Isl.(New Zealand)
Atlantic Antarctic - High seas Areas
Poland
Maldives
Northern Marianas (US)
Johnston Atoll (US)
Guam (US)
Solomon Isl.
Equatorial Guinea
Fiji
Tonga
Brunei
American Samoa
Mauritius
New Caledonia
Micronesia
Singapore
Christmas Isl.(Australia)
Vanuatu
Easter Isl.(Chile)
Tuvalu
Mozambique Channel Isl. (FR)
Timor Leste
Wallis & Futuna (FR)
Palau
Seychelles
Nauru
Samoa
Tokelau (NZ)
Jarvis Isl.(US)
Reunion (FR)
Howland & Baker Isl.(US)
Korea North
Sweden
Finland
Andaman & Nicobar Isl. (India)
Canary Isl.(Spain)
Comoros Isl.
Mayotte (FR)
Cuba
Dominican Rep.
Estonia
Haiti
1181
531
256
1006
446
581
611
536
726
811
596
1001
786
161
591
121
751
1201
566
601
421
836
91
361
771
941
136
231
1191
791
606
741
526
416
106
291
316
1016
116
11
631
696
746
931
196
701
171
1051
331
816
1146
756
921
676
1151
1011
1101
831
1106
541
991
321
466
961
211
216
246
271
296
436
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
125
0.01
0.036
0.127
0.127
0.02
0.076
0.251
0.122
0.02
0.09
0.195
0.24
0.008
0.14
0.178
0.033
0.017
0.01
0.127
0.154
0.01
0.032
0.006
0.021
0.148
0.019
0.117
0.01
0.01
0.056
0.091
0.008
0.006
0.008
0.077
0.059
0.022
0.008
0.064
0.006
0.036
0.029
0.015
0.053
0.012
0.023
0.002
0.007
0.013
0.041
0.006
0.016
0.03
0.005
0.003
0.003
0.002
0.009
0.002
0.057
0.067
0.033
0.036
0.045
0.014
0.022
0.015
0.016
0.026
0.017
0.012
0.036
0.045
0.046
0.011
0.02
0.04
0.041
0.019
0.04
0.04
0.038
0.01
0.037
0.037
0.025
0.017
0.012
0.034
0.033
0.008
0.02
0.008
0.018
0.028
0.016
0.028
0.012
0.01
0.024
0.024
0.008
0.007
0.008
0.02
0.019
0.019
0.009
0.013
0.007
0.012
0.01
0.011
0.011
0.009
0.009
0.002
0.008
0.004
0.008
0.007
0.007
0.005
0.005
0.004
0.003
0.003
0.001
0.002
0.001
0.001
0
0
0
0
0
0
0
0
0
0.018
0.018
0.018
0.018
0.017
0.017
0.016
0.016
0.016
0.015
0.015
0.015
0.015
0.014
0.014
0.014
0.014
0.014
0.013
0.013
0.012
0.012
0.012
0.011
0.011
0.011
0.011
0.01
0.01
0.009
0.009
0.008
0.008
0.008
0.008
0.007
0.007
0.006
0.005
0.005
0.005
0.004
0.004
0.004
0.004
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0
0
0
0
0
0
0
0
0
0
0
Iceland
Jamaica
Latvia
Lithuania
Azores Isl.(Portugal)
Russia Barrents Sea
Russia Baltic Sea Kaliningrad
USA Golf Of Mexico
Antigua & Barbuda
Macquarie Isl.(Australia)
Bahamas
Barbados
Bouvet Isl.(Norway)
Belize
Brit. Indian Oce (UK)
Brit. Virgin Isl.(UK)
Cape Verde
Cayman Isl.(UK)
Cocos Isl.(Australia)
Dominica
Tromelin Isl.(FR)
French Guyana
Gibraltar (UK)
Greenland
Grenada
Guadeloupe (FR)
Guyana
Heard & McDonald Isl.(Australia)
Martinique
Montserrat (UK)
Windward Netherlands Antilles
Leeward Netherland Antilles
Niue (NZ)
Jan Mayen Isl. (Norway)
Madeira Isl.(Portugal)
Puerto Rico (US)
Russia Baltic Sea St Petersburg
St Helena (UK)
St Kitts & Nevis
Anguila (UK)
St Lucia
St Pierre & Miquelon (FR)
St Vincent & The Grenadines
Sao Tome & Principe
Suriname
Svalbard Isl. (Norway)
Trinidad & Tobago
Turks & Caicos Isl (UK)
Navassa Isl. (Haiti)
Palmyra Atoll & Kingman Reef (US)
Ascencion Isl.
Venezuela
Wake Isl.(US)
Arctic Sea - High seas Areas
Atlantic Eastern Central - High seas Areas
Pacific Antarctic - High seas Areas
456
511
561
576
806
841
851
1121
21
36
46
61
81
96
101
111
151
156
201
266
336
341
386
401
406
411
431
441
621
651
686
691
721
736
801
821
866
871
876
881
886
891
896
901
981
986
1021
1046
1091
1096
1126
1136
1141
1186
1196
1241
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
seabirds
126
0.012
0.013
0.02
0.014
0.013
0.019
0.026
0.014
0.004
0
0.003
0.002
0
0.003
0.002
0
0
0.003
0
0.006
0.009
0.007
0
0.01
0
0
0
0
0.007
0
0.003
0.003
0
0.003
0.009
0.004
0
0
0.003
0
0.007
0
0
0.01
0
0.01
0
0
0
0
0
0.007
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Table 35 Hig h Seas FAO a reas EEZ so rted by t hei r co nt ri butio n i n t he different exposu res for all s harks sorted
by I UC N weig hted ex posu re
EEZ, High Seas FAO area
China
Japan Main Isl.
Vietnam
India
Pacific Western Central - High seas Areas
Morocco
Myanmar
Indian Ocean Eastern - High seas Areas
Pacific Northwest - High seas Areas
Russia Pacific
Pacific Southeast - High seas Areas
Mauritania
Indonesia (Eastern)
Western Sahara (Morocco)
Korea South
Chile
Peru
South Africa
Bangladesh
Indonesia (Western)
Guinea
Japan Outer Isl.
USA East Coast
Taiwan
Korea North
Spain
United Kingdom
Mexico
Philippines
Greece
Namibia
Indian Ocean Western - High seas Areas
Norway
Senegal
Brazil
Pacific Eastern Central - High seas Areas
Madagascar
France
Italy
Tunisia
Malaysia Sarawak
Australia
Iceland
Atlantic Eastern Central - High seas Areas
Atlantic Southwest - High seas Areas
Malaysia East
Thailand
Canada
Canary Isl.(Spain)
Atlantic Western Central - High seas Areas
Malaysia West
Algeria
Gambia
Turkey Mediterranean Sea
Croatia
Malaysia Sabah
Sierra Leone
Ecuador
Angola
Overall rank
188
518
938
463
1273
658
128
1233
1258
858
1263
628
473
973
548
168
778
953
58
478
428
523
1118
193
543
968
1068
638
783
398
673
1238
733
918
88
1248
588
328
503
1033
613
33
458
1198
1218
598
1003
148
963
1223
593
8
368
1038
243
603
928
278
18
Family
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
127
Overlap
index
0.175
0.154
0.147
0.144
0.144
0.139
0.139
0.138
0.133
0.124
0.119
0.115
0.113
0.113
0.111
0.111
0.11
0.108
0.106
0.105
0.104
0.104
0.104
0.102
0.102
0.101
0.1
0.098
0.098
0.098
0.097
0.096
0.096
0.094
0.094
0.093
0.092
0.086
0.085
0.085
0.081
0.08
0.08
0.08
0.079
0.079
0.077
0.076
0.075
0.074
0.073
0.073
0.073
0.072
0.071
0.07
0.07
0.069
0.068
Unweighted
exposure
index
0.207
0.183
0.174
0.171
0.17
0.165
0.165
0.164
0.157
0.147
0.141
0.136
0.134
0.134
0.131
0.131
0.131
0.128
0.126
0.124
0.124
0.124
0.123
0.121
0.121
0.12
0.119
0.116
0.116
0.116
0.114
0.114
0.113
0.112
0.111
0.11
0.109
0.101
0.101
0.101
0.096
0.095
0.095
0.095
0.094
0.093
0.091
0.09
0.089
0.088
0.086
0.086
0.086
0.086
0.084
0.083
0.083
0.081
0.081
IUCN
weighted
exposure
index
0.241
0.213
0.202
0.199
0.198
0.192
0.192
0.19
0.183
0.171
0.164
0.158
0.156
0.156
0.153
0.153
0.152
0.149
0.146
0.145
0.144
0.144
0.144
0.141
0.141
0.14
0.138
0.136
0.135
0.135
0.133
0.133
0.132
0.13
0.129
0.128
0.127
0.118
0.117
0.117
0.112
0.111
0.11
0.11
0.11
0.109
0.106
0.105
0.104
0.102
0.101
0.1
0.1
0.1
0.098
0.096
0.096
0.095
0.094
Nigeria
Libya
Pakistan
Pacific Southwest - High seas Areas
Egypt
Galapagos Isl.(Ecuador)
Ireland
Atlantic Northeast - High seas Areas
Ghana
New Zealand
Cameroon
Portugal
Atlantic Northwest - High seas Areas
Papua New Guinea
Atlantic SouthEast - High seas Areas
USA West Coast
Russia Barrents Sea
Cambodia
Faeroe Isl.(Denmark)
Guyana
Denmark
Oman
USA Golf Of Mexico
Somalia
Iran
Yemen
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Alaska
Argentina
Gabon
Maldives
Malta
Colombia
Suriname
Cuba
Tanzania
Venezuela
Lebanon
Uruguay
Netherlands
Cote d'Ivoire
United Arab Emirates
Sri Lanka
Montenegro
Solomon Isl.
Andaman & Nicobar Isl. (India)
Sweden
Israel
Jamaica
Azores Isl.(Portugal)
Albania
Congo Republic
Greenland
Cyprus
Haiti
Hong Kong
Gaza Strip
Mauritius
Madeira Isl.(Portugal)
Channel Isl.(UK)
Panama
Dominican Rep.
Cape Verde
Kiribati
Syria
Pacific Northeast - High seas Areas
Mozambique
Desventuradas Isl.(Chile)
Germany
French Polynesia
718
573
763
1268
1063
283
493
1203
383
708
143
798
1208
773
1213
1113
843
138
303
433
263
668
1123
948
483
1158
183
1083
28
358
608
618
208
983
248
1078
1138
558
1133
683
508
1028
163
1163
108
468
993
498
513
808
3
223
403
253
438
453
373
633
803
1073
768
273
153
393
998
1253
663
178
378
348
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
128
0.067
0.067
0.065
0.064
0.064
0.063
0.063
0.062
0.061
0.06
0.06
0.059
0.059
0.057
0.057
0.057
0.057
0.056
0.056
0.054
0.054
0.054
0.054
0.053
0.053
0.052
0.051
0.051
0.051
0.05
0.049
0.048
0.048
0.047
0.047
0.045
0.044
0.043
0.043
0.042
0.041
0.041
0.04
0.041
0.04
0.04
0.04
0.039
0.038
0.038
0.037
0.037
0.036
0.035
0.035
0.035
0.034
0.034
0.033
0.033
0.033
0.033
0.033
0.033
0.032
0.032
0.032
0.032
0.032
0.031
0.079
0.079
0.077
0.076
0.076
0.075
0.075
0.073
0.072
0.071
0.071
0.07
0.07
0.068
0.068
0.067
0.067
0.067
0.066
0.064
0.064
0.064
0.064
0.063
0.062
0.062
0.061
0.061
0.06
0.059
0.058
0.057
0.057
0.056
0.055
0.053
0.052
0.051
0.051
0.049
0.049
0.049
0.048
0.048
0.048
0.047
0.047
0.047
0.045
0.045
0.044
0.044
0.042
0.042
0.042
0.041
0.041
0.04
0.04
0.04
0.039
0.039
0.039
0.039
0.038
0.038
0.038
0.038
0.037
0.037
0.092
0.092
0.089
0.089
0.088
0.087
0.087
0.085
0.084
0.083
0.083
0.081
0.081
0.079
0.079
0.079
0.078
0.078
0.077
0.075
0.075
0.075
0.074
0.073
0.073
0.072
0.071
0.07
0.07
0.069
0.068
0.066
0.066
0.065
0.064
0.062
0.06
0.06
0.059
0.057
0.057
0.057
0.056
0.056
0.055
0.055
0.055
0.054
0.053
0.052
0.051
0.051
0.049
0.049
0.048
0.048
0.047
0.046
0.046
0.046
0.046
0.046
0.045
0.045
0.045
0.045
0.045
0.044
0.044
0.043
Fiji
Svalbard Isl. (Norway)
Mayotte (FR)
Congo
Sudan
Liberia
French Guyana
Saudi Arabia Red Sea
Brunei
Brit. Virgin Isl.(UK)
Saudi Arabia Persian Gulf
Honduras
Martinique
Trinidad & Tobago
Micronesia
Kenya
Trindade & Matin Isl (BR)
Guinea-Bissau
Togo
Falkland Isl.(UK)
Sao Tome & Principe
Benin
Guadeloupe (FR)
Costa Rica
Singapore
Lord Howe Isl. (Australia)
Belgium
Macau (China)
Haiwaii Main Isl.
Christmas Isl.(Australia)
Haiwaii NorthWest Isl.
New Caledonia
St Lucia
Cocos Isl.(Australia)
Bahrain
Easter Isl.(Chile)
Equatorial Guinea
Dominica
Poland
Puerto Rico (US)
El Salvador
Marshall Isl.
Vanuatu
Comoros Isl.
Antigua & Barbuda
Anguila (UK)
Seychelles
Timor Leste
Eritrea
Kuwait
Bosnia
St Pierre & Miquelon (FR)
Finland
Monaco
Norfolk Isl. (Australia)
Bahamas
Tuvalu
Jan Mayen Isl. (Norway)
Nicaragua
Palau
Latvia
Qatar
Russia Baltic Sea Kaliningrad
Grenada
Mozambique Channel Isl. (FR)
St Vincent & The Grenadines
Bermuda (UK)
Brit. Indian Oce (UK)
Estonia
Wallis & Futuna (FR)
318
988
218
228
978
568
343
908
118
113
913
448
623
1023
748
538
93
813
1008
308
903
258
413
238
933
43
68
583
1088
198
643
698
888
203
53
173
293
268
793
823
288
753
703
213
23
883
923
818
133
553
78
893
323
648
728
48
1053
738
713
758
563
828
853
408
333
898
73
103
298
1148
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
129
0.03
0.03
0.03
0.029
0.029
0.029
0.028
0.028
0.026
0.026
0.025
0.024
0.024
0.024
0.023
0.023
0.023
0.023
0.023
0.023
0.023
0.023
0.022
0.022
0.022
0.021
0.021
0.021
0.02
0.02
0.02
0.02
0.02
0.019
0.019
0.019
0.019
0.019
0.019
0.019
0.018
0.018
0.018
0.018
0.018
0.018
0.018
0.017
0.017
0.017
0.017
0.017
0.017
0.017
0.016
0.016
0.016
0.016
0.016
0.015
0.015
0.015
0.014
0.013
0.013
0.013
0.013
0.012
0.012
0.012
0.036
0.035
0.035
0.035
0.034
0.034
0.034
0.034
0.031
0.03
0.029
0.029
0.028
0.028
0.028
0.027
0.027
0.027
0.027
0.027
0.027
0.027
0.026
0.026
0.026
0.025
0.024
0.024
0.024
0.024
0.024
0.024
0.023
0.023
0.023
0.023
0.023
0.023
0.022
0.022
0.022
0.022
0.022
0.022
0.021
0.021
0.021
0.021
0.02
0.02
0.02
0.02
0.02
0.02
0.02
0.019
0.019
0.019
0.019
0.018
0.018
0.017
0.017
0.016
0.015
0.015
0.015
0.015
0.014
0.014
0.041
0.041
0.041
0.04
0.04
0.04
0.039
0.039
0.036
0.035
0.034
0.033
0.033
0.033
0.032
0.032
0.032
0.031
0.031
0.031
0.031
0.031
0.03
0.03
0.03
0.029
0.028
0.028
0.028
0.028
0.028
0.027
0.027
0.027
0.027
0.027
0.027
0.026
0.026
0.026
0.025
0.025
0.025
0.025
0.025
0.025
0.024
0.024
0.024
0.024
0.023
0.023
0.023
0.023
0.023
0.023
0.022
0.022
0.022
0.021
0.02
0.02
0.02
0.018
0.018
0.018
0.017
0.017
0.017
0.016
St Kitts & Nevis
Windward Netherlands Antilles
Nauru
Cook Isl.(New Zealand)
Ascencion Isl.
Montserrat (UK)
Palmyra Atoll & Kingman Reef (US)
Djibouti
Lithuania
Leeward Netherland Antilles
Tromelin Isl.(FR)
Guam (US)
Cayman Isl.(UK)
Northern Marianas (US)
Reunion (FR)
Slovenia
Johnston Atoll (US)
St Paul & Amsterdam (FR)
Barbados
Tonga
Belize
Clipperton Isl.(FR)
American Samoa
Guatemala
Tokelau (NZ)
Jarvis Isl.(US)
Iraq
Samoa
Jordan
Pitcairn (UK)
St Helena (UK)
Howland & Baker Isl.(US)
Crozet Isl.(FR)
Kerguelen Isl. (FR)
Prince Edward Isl. (SA)
Indian Ocean Antarctic - High seas Areas
South Georgia & Sandwich Isl. (UK)
Turkey Black Sea
Atlantic Antarctic - High seas Areas
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Bulgaria
Georgia
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Niue (NZ)
Romania
Russia Black Sea
Russia Siberia
Russia Baltic Sea St Petersburg
Turks & Caicos Isl (UK)
Ukraine
Navassa Isl. (Haiti)
Wake Isl.(US)
Arctic Sea - High seas Areas
Pacific Antarctic - High seas Areas
878
688
678
233
1128
653
1098
353
578
693
338
418
158
743
833
943
528
1168
63
1018
98
1183
13
423
1013
1103
488
1153
533
788
873
1108
1173
1178
958
1228
313
1043
1193
38
83
123
363
388
443
723
838
848
863
868
1048
1058
1093
1143
1188
1243
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
shark
130
0.012
0.011
0.011
0.011
0.011
0.011
0.011
0.011
0.011
0.01
0.01
0.01
0.01
0.01
0.009
0.009
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.006
0.006
0.005
0.004
0.004
0.003
0.003
0.003
0.003
0.002
0.002
0.001
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.014
0.014
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.012
0.012
0.012
0.012
0.011
0.011
0.011
0.011
0.011
0.01
0.01
0.01
0.009
0.009
0.009
0.008
0.008
0.008
0.007
0.007
0.006
0.005
0.005
0.004
0.004
0.003
0.003
0.003
0.002
0.001
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.016
0.016
0.015
0.015
0.015
0.015
0.015
0.015
0.015
0.014
0.014
0.014
0.014
0.013
0.013
0.013
0.013
0.012
0.012
0.012
0.012
0.011
0.011
0.011
0.009
0.009
0.009
0.008
0.008
0.007
0.006
0.006
0.004
0.004
0.004
0.004
0.003
0.002
0.001
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Table 36 5 Hig h Seas FAO a reas EEZ so rted by t hei r co nt ri bution i n t he different ex posures for all pi nni peds
and otters so rted by IUC N weig hted ex posu re
EEZ, High Seas FAO area
Chile
Peru
Greece
Algeria
Argentina
Tunisia
Turkey Mediterranean Sea
Croatia
Norway
Montenegro
Iceland
United Kingdom
Sweden
Russia Barrents Sea
Denmark
Madeira Isl.(Portugal)
Canada
Faeroe Isl.(Denmark)
Bosnia
Poland
Ireland
Russia Pacific
Finland
France
Albania
Germany
Netherlands
Latvia
USA East Coast
Russia Baltic Sea Kaliningrad
Cyprus
Estonia
Alaska
Greenland
Lithuania
Svalbard Isl. (Norway)
Japan Main Isl.
Channel Isl.(UK)
Ecuador
Uruguay
Belgium
USA West Coast
St Pierre & Miquelon (FR)
Mexico
Falkland Isl.(UK)
Brazil
Atlantic Southwest - High seas Areas
American Samoa
Angola
Antigua & Barbuda
Australia
Macquarie Isl.(Australia)
Lord Howe Isl. (Australia)
Bahamas
Bahrain
Bangladesh
Barbados
Bermuda (UK)
Bouvet Isl.(Norway)
Trindade & Matin Isl (BR)
Overall rank
169
779
399
9
29
1034
1039
244
734
1164
459
1069
994
844
264
804
149
304
79
794
494
859
324
329
4
379
684
564
1119
854
254
299
1084
404
579
989
519
1074
279
1134
69
1114
894
639
309
89
1219
14
19
24
34
39
44
49
54
59
64
74
84
94
Family
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
131
Overlap
index
0.172
0.124
0.065
0.053
0.085
0.047
0.046
0.043
0.136
0.027
0.114
0.095
0.081
0.075
0.074
0.014
0.069
0.067
0.012
0.061
0.06
0.058
0.054
0.051
0.01
0.048
0.048
0.048
0.046
0.045
0.008
0.039
0.038
0.035
0.034
0.032
0.031
0.03
0.025
0.024
0.02
0.019
0.019
0.018
0.017
0.015
0.013
0
0
0
0
0
0
0
0
0
0
0
0
0
Un-weighted
exposure index
0.203
0.147
0.077
0.063
0.101
0.055
0.055
0.051
0.162
0.032
0.135
0.112
0.096
0.089
0.088
0.017
0.081
0.079
0.015
0.072
0.072
0.068
0.064
0.06
0.012
0.057
0.057
0.056
0.054
0.054
0.01
0.046
0.045
0.041
0.04
0.038
0.037
0.035
0.03
0.028
0.024
0.023
0.022
0.021
0.02
0.018
0.015
0
0
0
0
0
0
0
0
0
0
0
0
0
IUCN weighted
exposure
index
0.242
0.152
0.149
0.122
0.114
0.107
0.106
0.099
0.063
0.062
0.052
0.043
0.037
0.035
0.034
0.033
0.032
0.031
0.028
0.028
0.028
0.026
0.025
0.023
0.023
0.022
0.022
0.022
0.021
0.021
0.018
0.018
0.017
0.016
0.016
0.015
0.014
0.014
0.012
0.011
0.009
0.009
0.009
0.008
0.008
0.007
0.006
0
0
0
0
0
0
0
0
0
0
0
0
0
Belize
Brit. Indian Oce (UK)
Solomon Isl.
Brit. Virgin Isl.(UK)
Brunei
Bulgaria
Myanmar
Eritrea
Cambodia
Cameroon
Cape Verde
Cayman Isl.(UK)
Sri Lanka
Easter Isl.(Chile)
Desventuradas Isl.(Chile)
J. Fernandez, Felix and Ambrosio Isl. (Chile)
China
Taiwan
Christmas Isl.(Australia)
Cocos Isl.(Australia)
Colombia
Comoros Isl.
Mayotte (FR)
Congo Republic
Congo
Cook Isl.(New Zealand)
Costa Rica
Cuba
Benin
Dominica
Dominican Rep.
Galapagos Isl.(Ecuador)
El Salvador
Equatorial Guinea
South Georgia & Sandwich Isl. (UK)
Fiji
Mozambique Channel Isl. (FR)
Tromelin Isl.(FR)
French Guyana
French Polynesia
Djibouti
Gabon
Georgia
Gambia
Gaza Strip
Ghana
Gibraltar (UK)
Kiribati
Grenada
Guadeloupe (FR)
Guam (US)
Guatemala
Guinea
Guyana
Haiti
Heard & McDonald Isl.(Australia)
Honduras
Hong Kong
India
Andaman & Nicobar Isl. (India)
Indonesia (Eastern)
Indonesia (Western)
Iran
Iraq
Israel
Italy
Cote d'Ivoire
Jamaica
Japan Outer Isl.
Johnston Atoll (US)
99
104
109
114
119
124
129
134
139
144
154
159
164
174
179
184
189
194
199
204
209
214
219
224
229
234
239
249
259
269
274
284
289
294
314
319
334
339
344
349
354
359
364
369
374
384
389
394
409
414
419
424
429
434
439
444
449
454
464
469
474
479
484
489
499
504
509
514
524
529
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
132
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Jordan
Kenya
Korea North
Korea South
Kuwait
Lebanon
Liberia
Libya
Macau (China)
Madagascar
Malaysia West
Malaysia East
Malaysia Sabah
Maldives
Malaysia Sarawak
Malta
Martinique
Mauritania
Mauritius
Haiwaii NorthWest Isl.
Monaco
Montserrat (UK)
Morocco
Mozambique
Oman
Namibia
Nauru
Windward Netherlands Antilles
Leeward Netherland Antilles
New Caledonia
Vanuatu
New Zealand
Nicaragua
Nigeria
Niue (NZ)
Norfolk Isl. (Australia)
Jan Mayen Isl. (Norway)
Northern Marianas (US)
Micronesia
Marshall Isl.
Palau
Pakistan
Panama
Papua New Guinea
Philippines
Pitcairn (UK)
Portugal
Azores Isl.(Portugal)
Guinea-Bissau
Timor Leste
Puerto Rico (US)
Qatar
Reunion (FR)
Romania
Russia Black Sea
Russia Siberia
Russia Baltic Sea St Petersburg
St Helena (UK)
St Kitts & Nevis
Anguila (UK)
St Lucia
St Vincent & The Grenadines
Sao Tome & Principe
Saudi Arabia Red Sea
Saudi Arabia Persian Gulf
Senegal
Seychelles
Sierra Leone
Singapore
Vietnam
534
539
544
549
554
559
569
574
584
589
594
599
604
609
614
619
624
629
634
644
649
654
659
664
669
674
679
689
694
699
704
709
714
719
724
729
739
744
749
754
759
764
769
774
784
789
799
809
814
819
824
829
834
839
849
864
869
874
879
884
889
899
904
909
914
919
924
929
934
939
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
133
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Slovenia
Somalia
South Africa
Prince Edward Isl. (SA)
Canary Isl.(Spain)
Spain
Western Sahara (Morocco)
Sudan
Suriname
Syria
Thailand
Togo
Tokelau (NZ)
Tonga
Trinidad & Tobago
United Arab Emirates
Turkey Black Sea
Turks & Caicos Isl (UK)
Tuvalu
Ukraine
Egypt
Tanzania
Haiwaii Main Isl.
Navassa Isl. (Haiti)
Palmyra Atoll & Kingman Reef (US)
Jarvis Isl.(US)
Howland & Baker Isl.(US)
USA Golf Of Mexico
Ascencion Isl.
Venezuela
Wake Isl.(US)
Wallis & Futuna (FR)
Samoa
Yemen
St Paul & Amsterdam (FR)
Crozet Isl.(FR)
Kerguelen Isl. (FR)
Clipperton Isl.(FR)
Arctic Sea - High seas Areas
Atlantic Antarctic - High seas Areas
Atlantic Eastern Central - High seas Areas
Atlantic Northeast - High seas Areas
Atlantic Northwest - High seas Areas
Atlantic SouthEast - High seas Areas
Atlantic Western Central - High seas Areas
Indian Ocean Antarctic - High seas Areas
Indian Ocean Eastern - High seas Areas
Indian Ocean Western - High seas Areas
Pacific Antarctic - High seas Areas
Pacific Eastern Central - High seas Areas
Pacific Northeast - High seas Areas
Pacific Northwest - High seas Areas
Pacific Southeast - High seas Areas
Pacific Southwest - High seas Areas
Pacific Western Central - High seas Areas
944
949
954
959
964
969
974
979
984
999
1004
1009
1014
1019
1024
1029
1044
1049
1054
1059
1064
1079
1089
1094
1099
1104
1109
1124
1129
1139
1144
1149
1154
1159
1169
1174
1179
1184
1189
1194
1199
1204
1209
1214
1224
1229
1234
1239
1244
1249
1254
1259
1264
1269
1274
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
marine mammals other
134
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Table 37 c Hig h Seas FAO a reas EEZ so rted by t hei r co nt ri butio n i n t he different exposu res for all tu rt les so rted
by I UC N weig hted ex posu re
EEZ, High Seas FAO area
India
Vietnam
Myanmar
China
Indonesia (Eastern)
Mauritania
Pacific Western Central - High seas Areas
Bangladesh
Indonesia (Western)
Morocco
Western Sahara (Morocco)
Mexico
Philippines
United Kingdom
Malaysia Sarawak
Senegal
Malaysia East
Thailand
Japan Main Isl.
Japan Outer Isl.
Korea South
Malaysia West
Spain
Pacific Northwest - High seas Areas
Korea North
Malaysia Sabah
Madagascar
Indian Ocean Eastern - High seas Areas
Nigeria
USA East Coast
France
Sierra Leone
Guinea
Pakistan
Taiwan
Venezuela
Atlantic Eastern Central - High seas Areas
Namibia
Brazil
Cameroon
Angola
South Africa
Papua New Guinea
Denmark
Cambodia
Canary Isl.(Spain)
Atlantic Western Central - High seas Areas
Tunisia
Peru
Guyana
Oman
Yemen
Somalia
Iran
Indian Ocean Western - High seas Areas
Norway
Ireland
Italy
Pacific Eastern Central - High seas Areas
Overall rank
465
940
130
190
475
630
1275
60
480
660
975
640
785
1070
615
920
600
1005
520
525
550
595
970
1260
545
605
590
1235
720
1120
330
930
430
765
195
1140
1200
675
90
145
20
955
775
265
140
965
1225
1035
780
435
670
1160
950
485
1240
735
495
505
1250
Family
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
135
Overlap
index
0.221
0.219
0.217
0.182
0.178
0.158
0.163
0.165
0.164
0.137
0.129
0.134
0.138
0.118
0.127
0.12
0.123
0.12
0.116
0.117
0.114
0.114
0.101
0.112
0.111
0.109
0.109
0.109
0.104
0.093
0.091
0.102
0.102
0.101
0.1
0.092
0.093
0.096
0.095
0.093
0.093
0.093
0.089
0.079
0.088
0.078
0.083
0.078
0.087
0.085
0.084
0.083
0.083
0.083
0.08
0.071
0.071
0.072
0.077
Unweighted
exposure
index
0.262
0.26
0.257
0.216
0.21
0.187
0.193
0.196
0.194
0.162
0.153
0.159
0.164
0.14
0.15
0.143
0.146
0.143
0.138
0.138
0.135
0.135
0.12
0.132
0.132
0.129
0.129
0.13
0.124
0.11
0.108
0.121
0.121
0.12
0.118
0.109
0.11
0.114
0.112
0.111
0.11
0.11
0.105
0.093
0.104
0.092
0.099
0.092
0.103
0.101
0.099
0.098
0.098
0.098
0.095
0.084
0.084
0.085
0.091
IUCN
weighted
exposure
index
0.422
0.42
0.415
0.347
0.34
0.323
0.319
0.316
0.313
0.295
0.277
0.269
0.264
0.254
0.243
0.241
0.235
0.23
0.224
0.224
0.219
0.218
0.217
0.212
0.211
0.209
0.208
0.208
0.2
0.2
0.196
0.196
0.195
0.193
0.191
0.187
0.185
0.184
0.182
0.178
0.178
0.178
0.17
0.17
0.168
0.167
0.166
0.166
0.165
0.162
0.159
0.158
0.158
0.157
0.154
0.153
0.152
0.151
0.147
Canada
Russia Pacific
Colombia
Suriname
Gambia
Ghana
USA Golf Of Mexico
Gabon
Australia
Pacific Southeast - High seas Areas
Atlantic Southwest - High seas Areas
Portugal
United Arab Emirates
Saudi Arabia Persian Gulf
Cote d'Ivoire
Pacific Southwest - High seas Areas
Andaman & Nicobar Isl. (India)
Tanzania
Alaska
Netherlands
Sudan
Germany
Saudi Arabia Red Sea
Libya
Solomon Isl.
Algeria
Fiji
New Zealand
Egypt
Jamaica
Chile
Sri Lanka
Cape Verde
Greece
Haiti
Cuba
Ecuador
Malta
Trinidad & Tobago
Dominican Rep.
Atlantic Northeast - High seas Areas
Bahrain
Sweden
Congo Republic
Maldives
Faeroe Isl.(Denmark)
Galapagos Isl.(Ecuador)
Atlantic SouthEast - High seas Areas
Hong Kong
Azores Isl.(Portugal)
Channel Isl.(UK)
Kuwait
Kiribati
French Guyana
Mozambique
Atlantic Northwest - High seas Areas
Panama
Brunei
Turkey Mediterranean Sea
Madeira Isl.(Portugal)
Congo
Croatia
Mayotte (FR)
Qatar
Liberia
USA West Coast
Martinique
Eritrea
Togo
Uruguay
150
860
210
985
370
385
1125
360
35
1265
1220
800
1030
915
510
1270
470
1080
1085
685
980
380
910
575
110
10
320
710
1065
515
170
165
155
400
440
250
280
620
1025
275
1205
55
995
225
610
305
285
1215
455
810
1075
555
395
345
665
1210
770
120
1040
805
230
245
220
830
570
1115
625
135
1010
1135
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
136
0.074
0.072
0.073
0.074
0.073
0.073
0.065
0.072
0.071
0.071
0.068
0.06
0.068
0.066
0.064
0.063
0.062
0.062
0.065
0.054
0.06
0.053
0.059
0.054
0.057
0.054
0.056
0.057
0.057
0.056
0.056
0.057
0.052
0.053
0.055
0.052
0.053
0.047
0.049
0.052
0.047
0.052
0.044
0.05
0.05
0.045
0.049
0.047
0.047
0.041
0.04
0.046
0.043
0.044
0.044
0.04
0.041
0.041
0.039
0.036
0.04
0.038
0.039
0.039
0.038
0.04
0.037
0.036
0.035
0.033
0.088
0.085
0.086
0.087
0.087
0.087
0.077
0.086
0.084
0.084
0.08
0.071
0.081
0.078
0.076
0.074
0.074
0.073
0.076
0.064
0.071
0.063
0.07
0.064
0.067
0.063
0.067
0.067
0.068
0.066
0.066
0.067
0.061
0.063
0.065
0.062
0.063
0.055
0.058
0.061
0.056
0.061
0.052
0.059
0.059
0.053
0.058
0.056
0.056
0.049
0.048
0.054
0.051
0.052
0.052
0.048
0.049
0.049
0.046
0.042
0.047
0.045
0.046
0.046
0.045
0.047
0.044
0.042
0.042
0.039
0.146
0.145
0.145
0.141
0.14
0.14
0.139
0.138
0.136
0.135
0.131
0.13
0.129
0.124
0.123
0.123
0.119
0.118
0.117
0.116
0.115
0.114
0.112
0.112
0.112
0.111
0.111
0.11
0.109
0.109
0.108
0.108
0.108
0.106
0.104
0.101
0.101
0.099
0.099
0.099
0.098
0.098
0.096
0.096
0.096
0.093
0.093
0.092
0.09
0.088
0.088
0.086
0.085
0.084
0.084
0.082
0.079
0.078
0.077
0.076
0.076
0.076
0.075
0.074
0.073
0.072
0.07
0.069
0.068
0.068
Sao Tome & Principe
Benin
Honduras
Singapore
Brit. Virgin Isl.(UK)
Mauritius
Iceland
French Polynesia
Guadeloupe (FR)
Micronesia
Kenya
St Lucia
Grenada
Costa Rica
Dominica
Puerto Rico (US)
Trindade & Matin Isl (BR)
Equatorial Guinea
Pacific Northeast - High seas Areas
New Caledonia
Christmas Isl.(Australia)
Macau (China)
Guinea-Bissau
Timor Leste
Vanuatu
El Salvador
Lord Howe Isl. (Australia)
St Vincent & The Grenadines
Tuvalu
Belgium
J. Fernandez, Felix and Ambrosio Isl. (Chile)
Lebanon
Comoros Isl.
Seychelles
Antigua & Barbuda
Leeward Netherland Antilles
Anguila (UK)
Marshall Isl.
Palau
Nicaragua
Norfolk Isl. (Australia)
Wallis & Futuna (FR)
Montenegro
Israel
Bahamas
Albania
Cyprus
Desventuradas Isl.(Chile)
Cocos Isl.(Australia)
Gaza Strip
Argentina
Syria
St Kitts & Nevis
Mozambique Channel Isl. (FR)
Poland
Windward Netherlands Antilles
Iraq
Tonga
Montserrat (UK)
Djibouti
Easter Isl.(Chile)
Finland
Bermuda (UK)
Cayman Isl.(UK)
Belize
Guam (US)
Ascencion Isl.
American Samoa
Nauru
Barbados
905
260
450
935
115
635
460
350
415
750
540
890
410
240
270
825
95
295
1255
700
200
585
815
820
705
290
45
900
1055
70
185
560
215
925
25
695
885
755
760
715
730
1150
1165
500
50
5
255
180
205
375
30
1000
880
335
795
690
490
1020
655
355
175
325
75
160
100
420
1130
15
680
65
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
137
0.035
0.035
0.033
0.034
0.034
0.033
0.03
0.032
0.032
0.031
0.031
0.031
0.028
0.03
0.03
0.029
0.029
0.029
0.03
0.028
0.028
0.028
0.028
0.027
0.026
0.027
0.026
0.025
0.024
0.022
0.024
0.024
0.024
0.024
0.024
0.022
0.023
0.023
0.023
0.023
0.022
0.022
0.021
0.021
0.02
0.02
0.019
0.019
0.02
0.018
0.018
0.017
0.018
0.018
0.017
0.018
0.018
0.017
0.017
0.017
0.016
0.014
0.014
0.015
0.013
0.014
0.014
0.014
0.013
0.014
0.042
0.042
0.039
0.04
0.04
0.04
0.036
0.038
0.038
0.037
0.037
0.036
0.034
0.035
0.035
0.035
0.034
0.034
0.036
0.033
0.034
0.033
0.033
0.032
0.031
0.031
0.031
0.03
0.029
0.027
0.029
0.028
0.029
0.028
0.028
0.027
0.028
0.027
0.027
0.027
0.026
0.026
0.025
0.025
0.024
0.023
0.023
0.023
0.024
0.022
0.021
0.021
0.021
0.021
0.02
0.021
0.021
0.02
0.02
0.02
0.019
0.017
0.016
0.018
0.016
0.017
0.016
0.016
0.016
0.016
0.067
0.067
0.065
0.065
0.064
0.064
0.063
0.062
0.062
0.061
0.06
0.059
0.057
0.057
0.057
0.056
0.056
0.056
0.055
0.054
0.054
0.053
0.053
0.052
0.052
0.051
0.051
0.051
0.048
0.048
0.048
0.047
0.046
0.046
0.045
0.045
0.045
0.044
0.044
0.044
0.043
0.043
0.043
0.043
0.041
0.039
0.038
0.038
0.038
0.036
0.036
0.035
0.035
0.034
0.034
0.034
0.034
0.033
0.032
0.032
0.031
0.03
0.029
0.029
0.029
0.028
0.027
0.027
0.026
0.026
Cook Isl.(New Zealand)
Tromelin Isl.(FR)
Greenland
Brit. Indian Oce (UK)
Haiwaii NorthWest Isl.
Haiwaii Main Isl.
St Pierre & Miquelon (FR)
Jordan
Palmyra Atoll & Kingman Reef (US)
Latvia
Samoa
Guatemala
Northern Marianas (US)
Estonia
Tokelau (NZ)
Reunion (FR)
Monaco
Russia Baltic Sea Kaliningrad
Bosnia
Johnston Atoll (US)
Jarvis Isl.(US)
Clipperton Isl.(FR)
Slovenia
Lithuania
Howland & Baker Isl.(US)
Pitcairn (UK)
St Helena (UK)
St Paul & Amsterdam (FR)
Falkland Isl.(UK)
Crozet Isl.(FR)
Prince Edward Isl. (SA)
Indian Ocean Antarctic - High seas Areas
Macquarie Isl.(Australia)
Bouvet Isl.(Norway)
Bulgaria
South Georgia & Sandwich Isl. (UK)
Georgia
Gibraltar (UK)
Heard & McDonald Isl.(Australia)
Niue (NZ)
Jan Mayen Isl. (Norway)
Romania
Russia Barrents Sea
Russia Black Sea
Russia Siberia
Russia Baltic Sea St Petersburg
Svalbard Isl. (Norway)
Turkey Black Sea
Turks & Caicos Isl (UK)
Ukraine
Navassa Isl. (Haiti)
Wake Isl.(US)
Kerguelen Isl. (FR)
Arctic Sea - High seas Areas
Atlantic Antarctic - High seas Areas
Pacific Antarctic - High seas Areas
235
340
405
105
645
1090
895
535
1100
565
1155
425
745
300
1015
835
650
855
80
530
1105
1185
945
580
1110
790
875
1170
310
1175
960
1230
40
85
125
315
365
390
445
725
740
840
845
850
865
870
990
1045
1050
1060
1095
1145
1180
1190
1195
1245
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
turtle
138
0.013
0.014
0.012
0.013
0.013
0.013
0.011
0.012
0.012
0.011
0.011
0.011
0.01
0.009
0.01
0.01
0.009
0.009
0.009
0.008
0.008
0.007
0.006
0.006
0.006
0.006
0.006
0.005
0.003
0.003
0.002
0.001
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.016
0.016
0.014
0.015
0.016
0.015
0.014
0.014
0.014
0.013
0.013
0.013
0.012
0.011
0.011
0.012
0.011
0.01
0.011
0.01
0.009
0.008
0.008
0.007
0.007
0.007
0.007
0.006
0.004
0.003
0.003
0.002
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.026
0.026
0.025
0.024
0.024
0.024
0.023
0.023
0.023
0.023
0.022
0.022
0.02
0.019
0.019
0.019
0.018
0.018
0.018
0.016
0.015
0.013
0.013
0.013
0.012
0.011
0.011
0.011
0.006
0.005
0.005
0.003
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Table 38 ’ Gi llnet survey fo rm add ressed to eac hj u risdictio n
DATA REQUESTED
Fishery
Fi hery name
s
Fishing season (starting month ,ending month)
Fishery target species for up to five main target species
Target 1
Target 2
Target 3
Target 4
Target 5
Vessels
Number of vessels in the fishery
Vessel length (m)*
Vessel type (artisinal/industrial)
Number of crew
Effort
Effort (km/h/yr)*
number of sets/yr (note that catch data are not requested)
Distance from the coast fished (km)* (or please join an effort map if available)
Spatial descriptors of fishing effort
Does the fishery occur exclusively within the EEZ, straddling this boundary or in high seas exclusively?
Fishing gear
Gear type (name)
Net length (m)*
Setting depth (m)*
Mesh size (cm)*
Net height (m)*
Soak time (min)*
Fishery gear setting details
Depth of water fished (m)*
Depth from the bottom fished (categories : pelagic, epipelagic , middleÓdepths , epibenthic , benthic)
Mitigation
Are mitigation strategies used to avoid nonÓtarget species captures (see species list for species of interest in the study)?
a) turtles – what and how are they deployed
b) sharks Ó what and how are they deployed
c) marine mammals Ó what and how are they deployed
d) seabirds Ó what and how are they deployed
* specify the unit if different
139
Ta ble 39 à Gillnet fis he ries s urvey res ults. Bette r printed in A 3
Fish
adis am
y Co
y Na
ocefr ishFni
er
me
de
MALAYSIA
MYS
MY1
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
MYS
nt x
er
MY1
MY1
MY1
MY1
MY1
MY1
MY1
MY1
MY1
MY2
MY
MY22
Pelagic Fishery
m g
9
adis min
nt
Av
Fish
in
ocefr ishFni
g aS
c
m g
le
am
(m B
e
P
oa
g oa
oxa
b
b
B
) tS
iz
tH
SSF
tG
tG
RT
RT
0
Gi
Gi
( GN
oB et
t
Ves N
min
Av
g oa
ishF sse um
er nli ob
y ht erf
e
40
eot/ S
et
t
)
m
b
Demersal Fishery
9
SSF
0
40
b
Prawn Fishery
9
SSF
0
40
b
MY4
Other Fisheries
9
SSF
0
40
b
MY4
b
aTr
( GT mm
) R lNe
et
b
b
b
b
b
TURKEY
TR1
Turkey Gillnet
Fishery
SSF
9
15201
b
TUR TR1
TUR TR1
TUR TR1
TUR TR1
REFERENCES : (Sextant Turkey Survey
2011)
ISL
ICELAND
IS1
Bottom Gillnet
Fishery
ISL
IS1
ISL
IS1
ISL
IS1
ISL
IS1
ISL
IS1
REFERENCES : (Icelandic Fisheries
2011)
SWEDEN
SWE
SE1
SWE
SWE
SE1
SE1
SWE
SE2
SWE
SE2
SWE
SWE
SWE
SWE
SE3
SE
SE33
SE4
om
s
y
tLik
ke
Co yp T
m e/Fish aGe
men r
t y er
(p 0 o
a:e Zn
g lic se
Cod Fishery Baltic
Sea
b
9.14
299
mostly
small scale
fishing.
b
Mostly
Artisanal
Fishery
Herring Fishery
Baltic Sea
SSF
8.7
127
b
Mostly
Artisanal
Fishery
Demersal
Skagerrak/Kattegatt
SSF
9.06
66
b
Mostly
Artisanal
Fishery
Gadus morhua
Pollachius virens
SWE SE4
SWE SE4
REFERENCES : (Sextant Sweden
Survey 2011)
8.62
32
ha Co
D
abi mo p het
ttM mn aR
in Fish g n
e x
20
10
5
0
20
2
100
0
am
min
abi mo
ttMa mn
Fish
( m Mshe
m s
) iz
e
min
am
( m eLt
) en
g ht
( m et
) enl
g ht
Av
n
gM
( m xMhse
m s
( m she
m
) iz
e
65
101
38
70
140
140
180
460
165
4
20
150
270
46
0
200
) Siz
e
xn
M
Av
gN
( ni e
m) Ltne
g ht
h
in
am
g hei
( m eHt
) hei
g
N
t
xn
( tm e
) t
Av
min
gN
( m eHt
) hei
g
t
p Dhe S
t
( m etin
) g
am
Av
p dhe xS De g S
p
h
t
( m eint t enti
) g
g
Fish
Fishh
i ho
nE g a (
d Soes urs
)
aS in
rt g aS
t eos
n
n
90
70
150
100
0
150
200
b
50
60
35
50
80
10
10
200
200
130
00
100
35
35
150
10
50
50
200
1200
50
2000
90
Clupea harengus.
SSF
01
2
2
Bottom Gillnet is widely used by small-intermediate boats to
catch the Atlantic Cod in the S/SW of iceland.
Gadus morhua
Melanogrammus aeglefinus
Cyclopterus lumpus.
Hippoglossus hippoglossus
other Flatfishes
Gadus morhua
other Flatfishes
Pelagic
Skagerrak/Kattegatt
125
20
30
14
45
264
0
6700
ha Co
2
2
5
2
5
2
2
SSF/LSF
SSF
)
Gillnet/Driftnet widely used for pelagic fishing and
mostly in coastal waters
Rastrelliger spp.
Scomberomorus spp.
Ilisha elongata
Anodontostoma chacunda
Megalaspis cordyla
Selar crumenopthalmus
Chirocentrus spp.
Thunnus tonggol
Euthynnus affinis
Marine Catfish and Jewfish also uses set gillnet.
Fishing operations in coastal waters
Croakers
Sea Catfish
The prawn drift and gill nets are actually trammel
nets. Fishing operations in coastal waters
prawns
Sharks and
Rays
Himantura spp./ Gymnura spp. / Myliobatis spp./ Aetobatus
spp./Carcharhinus spp./Sphyrna spp.
Sarda Sarda
Pomatomus saltatrix
Sparus auratus
Dicentrarchus labrax
SSF
len
g ht g vAf
( cm ish
2
REFERENCES : (Squires et al. 2003) (Project Global 2011) (SEAFDEC Stats 2011) (DoF
Malaysia 2006) (SEAFDEC Framework 2008)
TUR
g in oC
les
ta m
rt bin
mm ed
el
0
0
0
0
04
1
1
1
MY3
MY3
nE
nt ( G circ ( G Fixe
e N inl N dG
( GtN ) C g Gi ) F in
le
nl
t
)D
et
Drif
nl
nl
Main Targets
ISO
Fish
Mostly
Artisanal
Fishery
Scomber scombrus.
Clupea harengus.
140
5
2
100
150
5
30
0
200
5
2
100
60
150
37
200
364
0
5
30
30
0
0
200
200
200
50
500
10
1
5
1
1
1
1
1
1
1
1
200
60
90
60
me
Ti
k
aS
Avo
MAURITIUS
MUS
MU1
Mauritius Gillnet
Fishery
SSF
7
6
b
Artisanal
and Costal
Fishery.
MUS MU1
MUS MU1
MUS MU1
MUS MU1
MUS MU1
REFERENCES : (Sextant Mauritius
Survey 2011)
BELGIUM
BEL
BE1
BEL
BEL
BE1
BE1
BEL
BE2
FRA
FRA
FRA
FRA
FRANCE
FR1
FR1
FR1
FR1
FR2
Sole and Cod
Fishery, zone IVC
13.5
6
b
Sole and Cod
Fishery, zone VIID
13.5
2
b
MALTA
MT1
France Atlantic Set
Nets
France
Mediterranean Set
Nets
Set Gillnet Fishery
MLT
MT2
MLT
MLT
MLT
MLT
MT
MT22
MT2
MT2
Combined
Gillnet/Trammel
Fishery
MT3
50
SSF
10.5
1200
150
10
5
2
100
35
2
2
2
35
Sparus aurata
Solea solea
Merluccius merluccius
Mullus surmuletus
Mullus barbatus
Palinurus elephas
2
2
2
2
2
3
Auxis thazard
Seriola dumerili
Oblada melanura
Boops boops
Auxis Rochei Rochei
adus morhua
SGolea solea
b
30
SSF
8
742
b
SSF
SSF
5.89
6.4
34
b
b
b
23
b
trammel Net
SSF
6.39
603
b
Scorpaena spp.
Sepia officinalis
Mullus surmuletus
Shark Gillnet and
Shark Hook
Sectors
44
b
Coastal Reef
Fishery
REFERENCES : (Sextant Vanuatu
Survey 2011)
b
150
10
200
60
140
90
10
0
60
75
35
35
45
25
20
40
1
10
70
1500
10
30
60
400
409
300
70
0
4
5
2
0
160
00
20
20
50
18
2
2
2
2
25
20
2
2
2
25
100
5
0
100
5
Reef Associated Fisheries by coastal
communities..Drifnet is banned.
141
75
125
160
0
37
37
2
3
3
9
1
1
10
11
11
2.5
2
10
200
1
1
10
400
1
1
11
45
150
12
0
100
1
12
10
22
40
153
6.6
20
100
1
12
11
22
45
150
1.6
20
100
1
12
11
183
5
4
72
130
00
200
409
100
200
409
152.4
2
2
2
2
5
2.5
1.5
Demersal Fishing. West Coast Tasmania, Set Depth
can not exceed 130m
Callorhinchus milii
Mustelus antarcticus
Pristiophorus cirratus
Pristiophorus nudipinnis
Galeorhinus galeus
SSF
200
60
100
250
175
00
150
20
140
90
b
b
AUS AU1
AUS AU1
AUS AU1
AUS AU1
AUS AU1
REFERENCES : (Wilson et al. 2010)
VANUATU
VUT
VU1
5
2
100
35
Sepia officinalis
Mullus surmuletus
Boops boops
Scorpaena spp.
Fishery
MLT
MT
MLT
MT33
MLT
MT3
REFERENCES : (Sextant Malta Survey
2011)
AUSTRALIA
AUS
AU1
10
2
20
0
Solea solea
Lophius sp.
Maja Squinado
MT1
MT1
MT1
MT1
MT1
MLT
70
40
30
50
40
Gadus morhua
Solea solea
FRA
FR
FRA
FR22
FRA
FR2
FRA
FR2
FRA
FR2
FRA
FR2
REFERENCES : (Sextant France Survey
2011)
MLT
MLT
MLT
MLT
MLT
MLT
4
4
4
5
4
Lethrinus nebulosus
Lethrinus mahsena
Siganus sutor
Mugil cephalus
Valamugil seheli
BEL
BE
BEL
BE22
REFERENCES : (Sextant Belgium
Survey 2011)
FRA
110
227
80
146
165
470
4200
St HELENA
SHN
SH1
no gill-net fishery is carried out within the EEZ’s of St
Helena
REFERENCES : (Sextant St Helena
Survey 2011)
BANGLADESH
BGD
BD1
BGD
BGD
BD1
BD1
BGD
BD2
BGD
BGD
BD2
BD2
BGD
BD3
Mechanised
Gillnetters Fishery
SSF
18,992
b
Main Target
is the
pelagic
Tenualosa
ilisha
Tenualosa ilisha
promfret,jewfish,catfish,ray,sharks
Non-Mechanised
Gillnetters Fishery
SSF
6,377
b
Main Target
is the
pelagic
Tenualosa
ilisha
Tenualosa ilisha
promfret,Bambay
Duck,jewfish,ray,sharks
Trammel Net
Fishery
SSF
1,103
b
Please note that driftnet are used for Hilsha shad, large Mesh drift net for the indian salmon, bottom gillnet for shrimps, croakers,
ribon fish, bombay duck and Mullet gillnet for grey mullet.
REFERENCES : (Hossain 2004) (DoF
Bangladesh 2007)
THAILAND
THA
TH1
THA
TH1
THA
TH2
THA
TH2
THA
TH3
THA
TH3
THA
TH4
THA
THA
THA
THA
THA
THA
TH4
TH4
TH4
TH4
TH4
TH4
THA
TH5
THA
THA
THA
THA
THA
THA
TH5
TH5
TH5
TH5
TH5
TH5
Indian Ocean
Driftnet Fishery
22
Indian Ocean
Encircling Gillnet
Fishery
22
LSF
10.5
LSF
12
SSF
9.5
22
36
200
0
36
200
Main
Targets are
jewfish and
shrimps
promfret,shrimp,jewfish,catfish,ray,sharks
b
5
Pelagic fish
mostly
b
Main Target
Indo-Pacific
mackerel
60
Indo Pacific Mackerel,Scad,dorad wolf-hering,croaker,Fourfingers threadfin,spanish
mackerel,sardine,pomfret,mullet
40
Scomberomorus guttatus
Indian Ocean
Trammel Net
Fishery
5
0
55
20
100
45
90
b
40
260
5
20
3
40
3
3
3
40
40
40
prawns, drums & croakers, indo-pacific mackerel, anchovies, swimming crabs, red
snapper, indian mackerel
Indian Ocean Other
Gillnet Fishery
22
SSF
5
b
b
b
7.5
Gulf of Thaillan
Other Gillnet
Fishery
22
surface
gillnet
b
11
b
11
11
11
b
b
b
b
SSF
5
b
7.5
surface
gillnet
b
11
b
b
b
b
5
5
THA
TH6
TH6
Gulf of Thailland
Driftnet Fishery
22
LSF
THA
TH7
22
LSF
12
THA
THA
TH7
TH7
Gulf of Thailland
Encircling Gillnet
Fishery
THA
TH8
Indo-Pacific mackerel, swimming crab, Sillago Whitings, mullet,
sardine
Fourfingers threadfin, mullet, sardine
22
SSF
THA
TH8
REFERENCES : (SEAFDEC Stats 2011) (SEAFDEC Framework
2008) (SEAFDEC Monograph 2011)
9.5
seabass,mangrove crabs,red snapper,spinny
lobster,threadfin,snapper,emperor,red frog crab,seabass
swimming crabs
giant queenfish
whiting
b
Main Target
Indo-Pacific
mackerel
120
95
30
100
90
25
60
120
95
30
100
Longtail Tuna, Eastern Little Tuna, Narrow-barred king mackerel, Trash Fish, IndoPacific mackerel, indian mackerel
40
45
Pelagic fish
mostly
b
5
100
90
25
85
Indo-Pacific mackerel, swimming crab, mangrove crabs, Sillago Whitings, Threadfin, mullet,
sardine, indian mackerel
Fourfingers threadfin, mullet, sardine
40
85
Scomberomorus guttatus
Jacks, Cavalla, Trevallies, Trash Fish
Gulf of Thailland
Trammel Net
Fishery
40
seabass,mangrove crabs,red snapper,spinny
lobster,threadfin,snapper,emperor,red frog crab,seabass
swimming crabs
giant queenfish
whiting
b
11
11
11
10.5
THA
5
0
b
0
55
20
142
40
40
40
40
5
20
90
40
prawns, Narrow-barred king mackerel, crabs
3
3
3
3
260
VIETNAM
VNM
VN1
VNM
VNM
Driftnet Fisheries
SSF
VN1
VN1
VNM
15
40
b
Mostly
pelagic
targets
some
largng
e
scn at le fishi
iNang
he Da
province.
SSF/LSF
VNM
VN2
VN2
Drift Bottom Gillnet
Fisheries
SSF
40
VNM
VNM
VN3
VN3
Bag Gillnet
Fisheries
SSF
13
40
VNM
VN4
Trammel Net
Fisheries
SSF
10
40
b
b
PHL
PHL
PHL
PHL
PHL
PHL
PHL
PHL
PH1
PH1
PH1
PH1
PH1
PH1
PH2
PH2
PHL
Surface Gillnet
Fisheries
15
SSF
8
3
b
PHL
PH3
PH3
Bottom Gillnet
Fisheries
15
SSF
PHL
PHL
PHL
PH4
PH4
PH4
Trammel Net
Fisheries
15
SSF
8.5
3
PHL
PH5
Encircling Gillnet
Fisheries
15
SSF
9
3
b
BRN
BN1
BRN
10
3
20
3
44
75
800
480
30
40
42
45
14.5
30
25
90
Black Fin Mullet, Big-Eye/Yellowstripe/Round Scad, FLying Fish, Fresh water Herring,Skipjack, Tuna, Blue Marlin, Spanish/Indian/Stripped/Short-bodied/Frigate
Mackerel,Leather Jacket, Squid, Milkfis
Manta Ray
650
30
150
b
b
30
crabs, nimipterids, lizard fish, slipmouths, hairtail, snapper, white
shrimp, prawn
b
halfbeak fish, Spotted halfbeak,
garfish
b
38.1
43.5
28
76.2
60.9
40
51
76
35
270
270
460
1.5
40
35
35
35
35
45
40
90
90
90
600
600
100
100
100
800
800
300
300
300
14
12
6
6
6
16
5.5
SSF
7.5
5
b
Demersal
and small
pelagic
fishes
BRN
BN2
BN2
Trammel Net
Fisheries
5.5
SSF
6
2
b
Mostly
Shrimps
BRN
BRN
BN3
BN3
Crab Gillnet
Fisheries
5.5
SSF
BRN
BN4
Trammel Net
Fisheries
5.5
SSF
7
pony fish, hard-tail scads, croakers, etc
Schrimps and Crabs
b
Crabs
BRN BN4
REFERENCES : (SEAFDEC Stats 2011) (SEAFDEC Framework
2008) (SEAFDEC Monograph 2011)
Gillnet Fisheries
CMR CM1
CMR CM1
CMR CM1
CMR CM1
CMR CM1
REFERENCES : (Project Global 2011)
3.2
24
Mackerel,Milkfish,Round Scad, Herring, Scad, Sting Ray, Shark,
Sardine
Bottom Gillnet
Fisheries
CAMEROON
CMR
CM1
400
12
pelagic
fishing
REFERENCES : (SEAFDEC Stats 2011) (SEAFDEC Framework
2008) (SEAFDEC Monograph 2011)
BRUNEI
BN1
48
Operated
mostly in
shallow
waters
Long torn,big-eye Scad
anchovy
Sardine/Mackerel
Garfish
Flying Fish
SSF
BRN
50
105
6
Bag Gillnet
Tiggertoothed Croaker,Lobster
Shrimps
Cuttlefish
15
PH5
30
70
0
Crabs, Blue swimming crab, Tigertooth croake
Driftnet Fisheries
PHL
Sardine, Flying Fish
Tuna and Mackerel
20
grouper, croaker, bream, swimming crab
b
VNM VN4
VNM VN4
VNM VN4
REFERENCES : (SEAFDEC Stats 2011) (SEAFDEC Framework
2008) (SEAFDEC Monograph 2011)
PHILIPPINES
PHL
PH1
2
7.66
SSF
2
b
b
9
9
7.5
7.5
7.5
b
b
b
b
b
b
b
pelagic fish
pomfret,bonito,scomberoides
Scomberomorus commerson
0
120
10
70
Ethmalosa fimbriata
Sardinella maderensis
Pseudotolithus senegalensis
Pseudotolithus typus
Galoides/Pentanemus/Polydactylus
0
0
2
2
2
25
25
50
50
0
0
0
0
50
80
70
150
70-80%
pelagic
feishing,
20-30%
Demersal
SOUTH
143
AFRICA
ZAF
ZA1
Shark Gillnet
Fisheries
0.4
SSF
15
b
b
Fishery to
protect
swimmers
from shark
attack
ZAF
ZA1
REFERENCES : (KwazuluNatal Sharks
Board
2011)
DENMARK
DNK
DK1
DNK
DNK
DNK
DK1
DK1
DK2
Kattegat Gillnet
Fisheries
Baltic Gillnet
NK DK2 Fisheries
REFERENCES : (Project Global 2011)
Sharks
SSF
SSF
10.9
10.9
96.1
b
96.1
b
D
SLOVENIA
SVN
SI1
Gillnet Fisheries
SSF
41
41
416
b
b
b
b
N
GIN
GIN
GIN
GUINEA
GN1
N1
N1
GN1
G
Gillnet Fisheries
b
N
JPN
1
b
b
b
b
b
MOZAMBIQUE
MOZ
MZ1
M
Z
Z1 Gillnet Fisheries
Z MZ1
REFERENCES : (Faife 2003) (FAO
6
10
14
775.77
1018.43
600
710.56
600
Bonga shads
Bonga Shads,Otholtis
Leptocharias smithii,Rhinobatos cemiculus, Sphyrna
lewini,Rhinobatos rhinobatos
b
b
b
skipjack tuna,yellowfin tuna,bigeye tuna,Pacific bluefin
tuna,Albacore
SSF
MO
6
b
b
b
b
Grouper, sea bream, sharks
Sardines
b
Profile)
PER
PERU
PE
P
P
ER
PER
PER
PER
PER
PER
E1
PE1
PE1
PE1
PE1
PE
Shark and Ryas
Driftnet Fisheries
Salaverry and San
Jose Gillnet
Fisheries
SSF
SSF
b
SPAIN
ES1
ESP
ES1
Anglerfish Gillnet
Fisheries
SSF
1
1
1
1
335
335
2750
40
0
1
0
0
200
350
740
55
0
Paralonchurus peruanus
Genypterus maculatus
Mustelus whitneyi
2
2
2
30
5
0
10
16
221
b
REFERENCES : (Ayala 2008) (Mangel
)
et al
. 2009
ESP
Sphyrna zygaena
Myliobatis spp.
Prionace glauca
Isurus oxyrinchus
Alopias vulpinus
b
Operates in
ICES Div.
VIIIc
280
Lophius piscatorius
Lophius budegassa
144
2
2
100
5
0
20
300
1000
1013
1
1
15
160
18
18
6.9
11.8
2
1.1
3
b
REFERENCES : (WCPFC 2010)
MO
214
110
50
52
38
62
80
b
SSF
SSF
110
b
b
Gillnet Fisheries
Cod
b
G
JAPAN
JP1
JP
90
130
23400
European Pilchard, Comomon Sole,
European Flounder
REFERENCES : (Diop et al. 2009)
JP
Sole
Cod
b
REFERENCES : (Sextant Slovenia
Survey 2011)
GI
b
510
200
900
REFERENCES : (Costas et al
007)
. 2
EU
EU deep sea gillnet
fisheries
SSF
b
Hake Gillnet
Fisheries
b
ishing in
f
ICES sub
area IVa,
43
Merluccius merluccius
2
Lophius spp.
2
Centrophorus squamosus
2
Chaceon affinis
3
45
3
0
107
0
1000
5
120
1500
2500
12
100
600
1
1
16
250
7000
22500
3.64
100
800
84
220
6500
9000
6.4
800
1600
84
3.64
600
1200
VII, VIII, Ixa
onk ish Tangle net
M
f
Fisheries
ishing in
f
ICES sub
area IIa,
9
2
IVa,b, VI,
VII, VIII
Deepwater Shark
Gillnet Fisheries
ishing in
f
ICES sub
area VI, VII,
2
1
45
24
00
VIII, IX, X,
XII
Crab Tangle Net
f
ishing in
f
ICES sub
area IVa,
isheries
1 0
3
0 7
2 4
220
Vb, VI,VII,
VIII, XII
REFERENCES : (STECF
CAMBODIA
KHM
KH1
KH
M
KH1
KHM
KH2
KH
M
2
006)
Shrimp Trammel
Fisheries
b
Mackerel Gillnet
Fisheries
38
No ishing
f
allowed
between 1
b
100
Shrimp. Catfish, sivler and black
pomfrets
1
5
january and
1 march
3
KHM
KH2
KH3
KH
M
KH
3
KH
M
KH
3
KHM
KH4
KH
M
KH
4
Mackerel
Scomberomorus
Gillnet Fisheries
b
b
2
SSF
L
Boats less
0HP
o
f
Boats
9
SF
greater than
0HP
Crab Gillnet
Fisheries
mostly
2
9
18
2
Fishing
10000
Scomberomorus, scads and shack.
9
b
1000
Scomberomorus, scads and shack.
40
0
100
Portunus spp., Scylla serrata
operates in
the shallow
or inshore
water
KHM
KH5
KH
M
KH
5
Clupea Gillnet
Fisheries
b
2
Fishing
mostly
35
150
200
1
1
Clupea
operates in
the shallow
or inshore
water
REFERENCES : (SEAFDEC Stats 011) (SEAFDEC Framework
2
008) (SEAFDEC
onograph 011)
2
2
M
CHL
CHILE
CL1
CH
L
C 1
L
CHL
CL2
CH
L
CH
L
CH
L
C
L2
C
L2
C
L2
CHL
CL3
Industrial
Swordfish Driftnet
Fisheries
LSF
b
Boats are
greater than
18m in
560
510
560
2470
60
8
length,
typically
1mg6 m
2
2
Artisanal Swordfish
Driftnet Fisheries
SSF
15
b
Boats are
3.2
SSF
b
Xiphias gladius
1
3
00
0
800
less than
18m in
length
Artisanal Coastal
Gillnet Fisheries
510
.
Boats are
Xiphias gladius
Merluccius australis
Merluccius gayi
5
00
3
80
5
0
0
2
5
8
0
800
1000
5
00
200
less than
18m in
length
1
1100
.
jack mackerel,Sardines,Anchovies
REFERENCES : (SEAFDEC Stats 2011) (SEAFDEC Framework
2008) (SEAFDEC Monograph 2011)
14 5
9
60
30
MOROCCO
MAR
MA1
MAR
MA1
Artisanal Gillnet
Fisheries
SSF
6
b
catch are
sold directly
for fresh
Target small fish species
consumption
MAR
MA2
Deep-sea Gillnet
Fisheries
LSF
173
177
b
This Fishery
is being
6500
14000
6800
25
30
27.5
12
Swordfish
phased out.
REFERENCES : (Tudela et al. 2005)
(Franquesa et al. 2001) (WW F 2011)
ARGENTINA
ARG
AR1
ARG
AR1
Set Gillnet
Fisheries
SSF
13.5
b
b
Each
fisherman
with a permit
120
140
30
50
1.8
2.5
12
100
160
2000
6860
8.5
16
12
300
400
2000
7400
8
30
12
140
400
4.5
27
130
140
60
270
40
70
Patagonian blenny, silverside, parona
leatherjack, southern king crab
is allowed to
operate up
to
12 nets,
each with 30
to 50m
length and
1.8 to 2.5m
height.
REFERENCES : (Project Global 2011)
BRA
BRAZIL
BR1
BRA
BR1
BRA
BR2
BRA
BR2
BRA
BR3
BRA
BR3
BRA
BR3
Port of Ubatuba
Driftnet Fisheries
80
LSF
13
12
b
hammerhead sharks and bony fishes
Ports of Itajaí, Navegantes, Porto
Belo and Laguna Drifnet
Fisheries
LSF
18.75
Bottom Set Gillnet
Fisheries
LSF
20
40
b
hammerhead sharks and bony fishes
ports of Itajaí, Navegantes,
Porto Belo and Laguna
b
19
croaker, weakfish, and lobster
Micropogonias furnieri
>150
2
45
20
40
1850
25928
3.06
REFERENCES : (Project Global 2011)
ERI
ERITREA
ER1
Artisanal pelagic
gillnet fisheries
SSF
b
Sardines and Anchovies
ERI
ER2
Artisanal Shark
Gillnet fisheries
SSF
b
Coastal Shark
REFERENCES : (Project Global 2011)
COSTA RICA
CRI
CR1
Artisanal gillnet
fisheries
SSF
8
b
REFERENCES : (Project Global 2011)
IND
INDIA
IN1
IND
IN1
Kakinada Gillnet
Fisheries
IND
IN1
Chenai Gillnet
Fisheries
IND
IN1
Mangalore Gillnet
Fisheries
India gillnet
fisheries
b
4
10
9
25
20
70
12.5
79
12.5
75
b
b
b
b
b
b
seerfish, perches
60
seerfish, sharks, carangids, tuna
seerfish, sharks, carangids
REFERENCES : (Yousuf et al. 2008)
14 6
25
75
1000
1500
1000
6000
500
1500
6
8
12
20
100
5
30
200
7
25
70
8