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Je li se populacija sabljarke u potpunosti oporavila?

Je li se populacija sabljarke u potpunosti oporavila?



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U vezi sa sabljarkom Xiphias gladius:

Čitao sam Richarda Ellisa"Sabljarka: Biografija oceanskog gladijatora", Chicago University Press, 2013. U poglavlju o industrijskom ribolovu opisano je da je do kasnog 20. stoljeća populacija sabljarke bila desetkovana zbog prekomjernog izlova. U 11. poglavlju raspravlja o tome je li sabljarka ugrožena i opisuje napore za očuvanje kasnih 1990-ih. Kaže da postoji porast populacije sabljarke u sjevernom Atlantiku (ali kažemo da ne znamo je li se populacija u potpunosti oporavila do svojih vrhunaca) i kaže da ima malo informacija o populaciji Pacifika i Mediterana.

Našao sam neke informacije na https://www.fishwatch.gov za populaciju sjevernog Atlantika i sjevernog Pacifika, govoreći da sjeverni Atlantik i zapadni sjeverni Pacifik nisu prelovljeni i nisu podložni prekomjernom izlovu (mislim da je to dobro), dok istočni Sjeverni Pacifik nije pretjerano izlovljen, ali podložan prekomjernom izlovu. ICCAT je objavio izvješće Atlantic, ICCAT 2017 koje je teško čitati. Ono što sam shvatio, sjeverni Atlantik nije pretjerano izlovljen, dok je populacija južnog Atlantika prelovljena i u opasnosti. Za Pacifik pogledajte Pacifik, ICCAT 2018, koji kaže da sjeverni središnji i zapadni Pacifik nisu prelovljeni:

Općenito, model osnovnog slučaja pokazao je da zalihe sabljarke WCNPO nisu vjerojatno prelovljene i da nije vjerojatno da će doživjeti prekomjeran izlov u odnosu na referentne točke temeljene na MSY-u ili 20% neulovljene mriještene biomase.

Ova izvješća je teško pročitati nestručnjacima, pa ovdje postavljam nekoliko pitanja o populaciji sabljarke:

  1. Je li sabljarka ugrožena vrsta?
  2. Je li populacija sabljarke održiva?
  3. Po populaciji P = { Sjeverni Atlantik, Južni Atlantik, Sjeverni Pacifik, Južni Pacifik, Indija, Mediteran}:

    3.1 Je li populacija P ugrožena?

    3.2 Je li stanovništvo sigurno (nije ugroženo) ili je najmanje zabrinuto?

    3.3 Je li se populacija potpuno oporavila i dosegla zdravu veličinu?


Pokreti i ponašanja sabljarke u Atlantskom i Tihom oceanu ispitani pomoću pop-up satelitskih arhivskih oznaka

Sadašnja adresa: Marine Conservation Science Institute, Offield Center for Billfish Studies, 2809 South Mission Road, Suite G, Fallbrook, CA 92028, SAD.

Pfleger Institute of Environmental Research, 315 North Clementine Street, Oceanside, CA 92054 SAD

Sadašnja adresa: Marine Conservation Science Institute, Offield Center for Billfish Studies, 2809 South Mission Road, Suite G, Fallbrook, CA 92028, SAD.

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Savjetnik za oceanografe u ribarstvu, LLC, Jacksonville, OR 97530, SAD

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Centar za istraživanje i očuvanje tune, pomorska postaja Hopkins, Sveučilište Stanford, Oceanview Blvd, Pacific Grove, CA 92950, ​​SAD

Sveučilište Hawaii, Joint Institute Marine and Atmospheric Research, Kewalo Research Facility/NOAA, 1125B Ala Moana Boulevard, Honolulu, HI 96814, SAD

Nacionalna služba za morsko ribarstvo, Southwest Fisheries Science Center, 8604 La Jolla Shore Dr., La Jolla, CA 92037, SAD

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Sveučilište Hawaii, Joint Institute Marine and Atmospheric Research, Kewalo Research Facility/NOAA, 1125B Ala Moana Boulevard, Honolulu, HI 96814, SAD

Nacionalna služba za morsko ribarstvo, Northeast Fisheries Science Center, 166 Water Street, Woods Hole, MA 02543, U.S.A

Pfleger Institute of Environmental Research, 315 North Clementine Street, Oceanside, CA 92054 SAD

Sveučilište u Miamiju, RSMAS, 4600 Rickenbacker Causeway, Miami, FL 33149, SAD

Sveučilište Hawaii, Joint Institute Marine and Atmospheric Research, NOAA Fisheries Environmental Research Division, Pacific Grove, CA 93950 SAD

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Pfleger Institute of Environmental Research, 315 North Clementine Street, Oceanside, CA 92054 SAD

Sadašnja adresa: Marine Conservation Science Institute, Offield Center for Billfish Studies, 2809 South Mission Road, Suite G, Fallbrook, CA 92028, SAD.

Pfleger Institute of Environmental Research, 315 North Clementine Street, Oceanside, CA 92054 SAD

Sadašnja adresa: Marine Conservation Science Institute, Offield Center for Billfish Studies, 2809 South Mission Road, Suite G, Fallbrook, CA 92028, SAD.

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Savjetnik za oceanografe u ribarstvu, LLC, Jacksonville, OR 97530, SAD

Nacionalna služba za morsko ribarstvo, Southeast Fisheries Science Center, 75 Virginia Beach Drive, Miami, FL 33149, SAD

Centar za istraživanje i očuvanje tune, pomorska postaja Hopkins, Sveučilište Stanford, Oceanview Blvd, Pacific Grove, CA 92950, ​​SAD

Sveučilište Hawaii, Joint Institute Marine and Atmospheric Research, Kewalo Research Facility/NOAA, 1125B Ala Moana Boulevard, Honolulu, HI 96814, SAD

Sažetak

Sabljarke su visoko specijalizirani vrhunski grabežljivci koje je bilo teško proučavati. U ovom radu analizirani su podaci iz 31 skočne satelitske arhivske oznake pričvršćene za sabljarku iz (i) istočnog Pacifika, (ii) središnjeg Pacifika i (iii) zapadnog sjevernog Atlantika-Kariba. Uobičajen na svim lokacijama bio je izražen vertikalni uzorak diela s dnevnim satima provedenim prvenstveno ispod termokline, a noćnim satima provedenim u toplijim vodama, blizu površine. Jedna iznimka od ovog obrasca bila su periodična dnevna kupanja koja su bila najčešća u hladnijim vodama kod Kalifornije. Maksimalne dnevne dubine bile su u značajnoj korelaciji s penetracijom svjetlosti mjereno koeficijentom difuznog prigušenja na 490 nm. Čini se da temperatura nije utjecala na dnevne dubine, a sabljarke su podnosile i ekstremno niske temperature (4°C) i brze i dramatične promjene temperature (>20°C). Čini se da je temperatura utjecala na noćne dubine u Pacifiku gdje su ribe obično ostajale u površinskom miješanom sloju. Nasuprot tome, u toplom tropskom Atlantiku to nije bio slučaj, a noćne dubine bile su mnogo dublje. U svim područjima noćna dubina se povećavala oko punog mjeseca. S obzirom na paralele između uzoraka vertikalnog kretanja sabljarke i onih u dubokom sloju raspršivanja zvuka, sugeriramo da su uzorci vertikalne distribucije sabljarke, osobito tijekom dana, u velikoj mjeri pod utjecajem dostupnosti resursa. Noću, kada je riba sabljarka obično meta ribolova, i ambijentalno svjetlo i temperatura utječu na kretanje. Razumijevanje vertikalnih obrazaca kretanja sabljarke može pomoći u procjeni ranjivosti opreme, poboljšati procjenu populacije i potencijalno smanjiti ribolovni usputni ulov.


Uvod

Zemljopisna distribucija ribarstva inherentno sadrži prostorne heterogenosti zbog raspodjele karakteristika riblje populacije (npr. dobna struktura, spol, rast i kretanje) i karakteristika flote (npr. selektivnost i napor Booth, 2000.). Prostorna heterogenost je osobito relevantna za procjenu i upravljanje mnogim velikim pelagijskim vrstama (npr. tune, školjke, morski psi), budući da su te vrste vrlo raspršene i sposobne za ekstenzivne migracije. Ribarstvo usmjereno na ove vrste pokriva velika područja i potencijalno može ciljati na brojne stokove ili podpopulacije čije su granice i povezanost slabo shvaćene (Caton, 1991., Ward i sur., 2000.).

Procjene stoka za većinu pelagičnih vrsta pokušavaju objasniti neke izvore prostorne heterogenosti podjelom populacije i ribarstva na više geografskih komponenti (npr. Fournier et al., 1998.). Međutim, nekoliko procjena uključuje prostornu strukturu (osobito na razini podpopulacije) i kretanje (Cadrin i Secor, 2009., Stephenson, 1999.) populacija, jer podaci često nisu dovoljni za pouzdano ocrtavanje prostorne strukture, procjenu stopa kretanja i procjenu ranjivosti na ribolovnu opremu. Osim toga, mnogim pristupima procjene zaliha nedostaje kvantitativni okvir koji bi omogućio uključivanje prostorne strukture i kretanja. Granice modela procjene stokova i svako unutarnje podjele često se definiraju na temelju dostupnih podataka o ribarstvu i političke stvarnosti upravljanja (npr. državna i regionalna upravljačka jurisdikcija), a ne na temelju prostornih karakteristika riblje populacije. Neuvažavanje prostornih karakteristika populacije može dovesti do neprikladnih pretpostavki u pogledu dinamike populacije, kretanja i ranjivosti na ribolov, što rezultira lošim savjetima za upravljanje ribarstvom (Cadrin i Secor, 2009.).

Sabljarka (Xiphias gladius u daljnjem tekstu sabljarke) su globalno rasprostranjene u umjerenim, suptropskim i tropskim vodama i važne su ciljne i usputne vrste za domaće obalne i udaljene flote parangala (Ward i sur., 2000.). Raspodjela ulova po slivovima sugerira da se populacije kreću sezonskim širenjem i povlačenjem toplijih voda u veće geografske širine i sezonskim pomacima u produktivnosti (Neilson i sur., 2009., Neilson i sur., 2013., Palko i sur., 1981.). Čini se da postoji određena heterogenost u kretanju mužjaka i ženki, pri čemu je više mužjaka ulovljeno u ribolovu u toplijim, nižim geografskim širinama, a ženke dominiraju ulovom u hladnijim, višim geografskim širinama (DeMartini i sur., 2000., Palko i sur., 1981.). Istraživanja ulova i molekularnih podataka sugerirala su strukturu populacije sabljarke na razini oceanskih bazena u Tihom, Indijskom i Atlantskom oceanu (Alvarado-Bremer et al., 2005., Reeb et al., 2000.), ali strukturu finijeg razmjera unutar bazena je manje siguran.

Genetske studije sabljarke u Tihom oceanu pronašle su i male dokaze o genetskoj diferencijaciji u uzorcima prikupljenim diljem sliva (Kasapidis et al., 2008., Rosel i Block, 1995., Ward i sur., 2001.) i neke dokaze o podjelu populacije ( Reeb i sur., 2000.). Uočene podjele upućuju na niske razine protoka mitohondrijalnih gena za koje se čini da imaju uzorak u obliku ⊃, sa vezom životinja istok-zapad na sjevernoj i južnoj hemisferi i vezama preko ekvatorijalne zone duž zapadne obale Amerike (Reeb i sur., 2000.). To je u skladu s hipotezom o odvojenim stokovima u sjevernom i jugozapadnom Tihom oceanu (Sakagawa i Bell, 1980.). Raspodjele ličinki, koje odražavaju područja mrijesta preko Tihog oceana, također sugeriraju neke dokaze za odvajanje stokova u zapadnom Tihom oceanu (Grall i sur., 1983., Nishikawa i sur., 1985.). Iako su i prostorno i vremenski neodređeni, ova istraživanja upućuju na to da se mrijest događa na sjevernoj hemisferi tijekom borealnog ljeta u vodama 0-30° N u zapadnom i središnjem Tihom oceanu (WCPO) i na južnoj hemisferi tijekom australnog ljeta u vodama do sjeveroistoku Australije.

Do danas je bilo dostupno malo informacija o kretanju sabljarke preko Tihog oceana. Studije označavanja iz kojih su zabilježeni pokreti uglavnom su ograničene na mali broj konvencionalnih postavljanja oznaka u jugozapadnom Tihom oceanu (Holdsworth i Saul, 2011., Stanley, 2006.), te u središnjem i istočnom sjevernom Tihom oceanu (Ito i Coan, 2005., Wraith i Kohin, 2011.), ograničena primjena elektroničkih oznaka uz istočne obale Sjeverne i Južne Amerike i jedna arhivska oznaka postavljena uz istočnu obalu Japana (Abascal et al., 2010., Carey i Robison, 1981., Dewar i sur., 2011., Takahashi i sur., 2003.). Konvencionalni povrati oznaka ograničeni su na vrlo niske stope povrata, a implementacije elektroničkih oznaka uglavnom su ograničene kratkim razdobljima implementacije. Sigurnost o opsegu povezanosti populacija između istočnih i zapadnih dijelova i nedostatak povezanosti između sjevernog i južnog dijela Tihog oceana kao što sugeriraju genetski podaci još uvijek su uglavnom nepoznati.

Uvođenje skočnih satelitskih oznaka (PSAT) na sabljarke u južnom Tihom oceanu od strane brojnih istraživačkih programa (Abascal et al., 2010., Evans, 2010., Holdsworth et al., 2007.) pružilo je priliku za istraživanje prostornih dinamika sabljarke i povezanosti, osobito u jugozapadnom i južno-središnjem Tihom oceanu. Elementi ovih podataka o označavanju korišteni su za istraživanje prikladnosti prostorne podjele korištene u procjenama stoka za sabljarku u WCPO-u i za pružanje preporuka za tekuće procjene stokova od strane Komisije za ribarstvo zapadnog i središnjeg Pacifika (WCPFC Evans et al., 2012a). U ovom radu dajemo detaljan sažetak kombiniranih podataka, uključujući sintezu horizontalnih i vertikalnih pokreta te kvalitativni opis potencijalnih utjecaja okoline i fizioloških osobina koje bi mogle doprinijeti varijabilnosti u promatranim pokretima i ponašanju. Raspravlja se o trenutnim hipotezama o povezanosti sabljarke u Tihom oceanu io budućim kvantitativnim analizama uključujući procjenu stoka.


Uvod

Razvoj metoda za precizno opisivanje kretanja morskih vrsta na proširenim vremenskim i prostornim razmjerima traje tijekom posljednja dva desetljeća i dao je važan uvid u kretanja, migracijske rute i staništa od značaja za morske životinje (Evans i Arnold, 2009. ). Nedavni razvoj uređaja koji omogućuju brzo stjecanje signala GPS konstelacije tijekom kratkih razdoblja ponašanja na površini znači da je sada moguće praćenje visoke vremenske i prostorne rezolucije niza morskih vrsta uključujući sisavce, morske ptice i gmazove (Weimerskirch i sur., 2002., Schofield i sur., 2007., Costa i sur., 2010.). Iako je bilo pokušaja korištenja GPS tehnologije na ribama (Sims i sur., 2009.a), ovo je relativno noviji fenomen i razvoj ove metodologije je još uvijek u povojima.

Sabljarka (Xiphias gladius), u daljnjem tekstu sabljarke, imaju raširenu geografsku rasprostranjenost u umjerenim, suptropskim i tropskim područjima svijeta (Palko i sur., 1981.). Vrsta se komercijalno lovi u cijelom svom rasponu, prvenstveno pelagijskim parangalima, s manjim ulovom koji se ulovljavaju plovilima pomoću lebdećih mreža i harpuna i povremenim ulovom koji se lovi uz pomoć rukohvata, trolova, zamki, mrežastih plivarica i motki (Folsom et al. ., 1997., Ward i sur., 2000.). U jugozapadnom Pacifiku, sabljarka je sastavni dio ulova parangala od 1950-ih, iako je tek sredinom 1990-ih poboljšan pristup inozemnim tržištima rezultirao specifičnim ciljanjem sabljarke od strane plovila s parangalom kako u Australiji, tako iu Novom Zbog toga su se ribarstvo i regionalni ulovi u Zelandu znatno povećali.

Ulovi kod istočne Australije unutar Istočnog ribolova tune i školjaka (ETBF) uvelike su povezani s tri oceanografske/geografske regije: aktivnosti na obali duž epikontinentalnog pojasa povezane s oceanografskim frontama i vrtlozima Istočnoaustralske struje (EAC) obalne aktivnosti povezane s podmorskim planinama i aktivnosti na moru povezane s oceanografskim frontama i podmorskim planinama (Ward i sur., 2000.). Slično mnogim ribolovima koji ciljaju na ribu sabljarku, ulov sabljarke u cijelom ETBF-u pokazao je serijski uzorak iscrpljivanja, pri čemu ulov koji opada postupno se kreće od priobalnih ribolovnih područja do onih dalje od obale (Ward i sur., 2000., Campbell i Hobday, 2003.).

Kao odgovor na zabrinutost zbog smanjenja ulova i statusa ribolova sabljarke u regiji zapadnog Tihog oceana (WPO), 2006. poduzeta je procjena fonda sabljarke. Međutim, niz temeljnih nesigurnosti impliciranih u korištenim modelima, posebno u vezi s kretanjem, boravište oko batimetrijskih značajki i stupanj miješanja sabljarke u cijeloj regiji izazvali su zabrinutost oko sposobnosti korištenih modela da pruže realne indikacije statusa ribarstva (Kolody i sur., 2006.). U nastojanju da se riješi ova neizvjesnost, pokrenut je program elektroničkog označavanja koji koristi skočne satelitske arhivske oznake (PSAT) s ciljem boljeg definiranja prostorne dinamike sabljarke u WPO-u.

Početni rezultati postavljanja PSAT-a u zapadnom Tasmanskom moru otkrili su da je ronilačko ponašanje sabljarke utjecalo na sposobnost izračunavanja geopoložaja iz svjetlosnih podataka. 1 Uočeno je da je ponašanje u ronjenju gotovo strogo diel u prirodi, s većinom vremena tijekom dana koje pojedinci provode na dubinama od približno 600-800 m, a većinu vremena noću provode u vodama obično manjim od 200 m (Sl. 1). Spuštanje u duboke vode događa se u zoru, a uspon u površinske vode u sumrak, slično kao što je zabilježeno za sabljarku u studijama elektroničkog označavanja u drugim regijama (Carey i Robison, 1981., Takahashi et al., 2003., Canese i sur., 2008., Abascal i sur., 2010.). Tako velik udio vremena provedenog na dubini tijekom dana rezultirao je malim brojem podataka o svjetlosti koje su raspoređeni PSAT-ovi prikupili i, kao posljedica toga, procjene položaja bile su rijetke i udaljene. Time je smanjen razmjer na kojem bi se moglo zaključiti kretanje, prebivalište i interakcija staništa.

Međutim, uočeno je da sabljarke provode značajnu količinu vremena na površini oceana ili blizu nje noću (slika 1), slično kao što je zabilježeno za sabljarku u studijama elektroničkog označavanja na drugim mjestima (Carey i Robison, 1981., Takahashi et al., 2003., Canese i sur., 2008.). Također je zabilježeno da sabljarke drugdje pokazuju ponašanje kupanja na površini oceana tijekom dana (Ward i sur., 2000.). Sposobnost da se neko vrijeme provede na površini oceana i mogućnost kupanja sabljarke potaknule su početne rasprave s proizvođačima elektroničkih oznaka o održivosti alternativnih tehnologija za korištenje u određivanju kretanja sabljarke.


Uvod

oceanska riba sunca [Mola mola (Linnaeus, 1758)] nalaze se u svim tropskim i umjerenim oceanskim bazenima i najteže su koštane ribe na svijetu, dosežući više od 2200 kg (Carwardine, 1995., Roach, 2003.). Prema fosilnim dokazima, obitelj Molidae odvojila se od svojih srodnika riba puhačica prije otprilike 40 milijuna godina, napustila život na grebenu i otišla na otvoreno more (Tyler i Bannikov, 1992., Tyler i Santini, 2002.). Trenutno su prepoznate tri vrste (Nelson, 1994.), a sve nemaju pravi rep (Bigelow i Welsh, 1924., Fraser-Brunner, 1951., McCann, 1961.): M. mola (obična mola), Masturus lanceolatus (Liénard 1840) (mola s oštrim repom) i Ranzania laevis (Zastavica 1776.) (vitka mola). Englesko uobičajeno ime skupine, ocean sunfish, proizlazi iz karakterističnog ponašanja riba koje leže na površini mora, očito se kupaju (Norman i Fraser, 1938.).

Molas se hrani blizu baze hrane poput većine najvećih kitova, morskih pasa i raža. Mogu jesti kril i druge rakove (Aflalo, 1904.), ali čini se da je njihov primarni izvor hrane miješani skup želatinoznog zooplanktona, koji se ovdje naziva žele (Fraser-Brunner, 1951.). Jedan od rijetkih velikih pelagičnih organizama koji dijele ovu jedinstvenu trofičku nišu je kožasta morska kornjača, najveća od postojećih morskih kornjača. Želei čine jedan od najdominantnijih, ali slabo razumljivih skupova pelagične faune (Mills, 1995., Mills, 2001.), a njihova globalna brojnost i distribucija mogu se mijenjati zbog brojnih čimbenika uključujući klimatske promjene, zagađenje i prekomjerni izlov (Brodeur i sur., 1999., Purcell i sur., 2007., Richardson i sur., 2009.). Zauzvrat, promjene u obilju i distribuciji želea mogu utjecati na organizme koji se oslanjaju na njih, kao što je mola.

Dok su opći obrasci distribucije poznati, podaci o kretanjima od M. mola temelji se na relativno malom broju studija. Godine 2004. Cartamil i Lowe (2004.) izvijestili su o horizontalnim i vertikalnim kretanjima osam akustično praćenih mola u blizini južne Kalifornije u razdobljima od 24 do 72 sata. U novije vrijeme, Hays i sur. (2009.) objavili su studiju u kojoj su uspoređivali geografska kretanja i vertikalne tragove četiriju M. mola onima kožnih morskih kornjača (Dermochelys coriacea) u blizini Capetowna, Južna Afrika, s rezultatima koji podupiru tvrdnju da su mola dubinski ronioci (Norman i Fraser, 1938., Wheeler, 1969.). U sličnoj studiji, Sims i sur. (2009.) pružili su dokaze za sezonsku migraciju trojice M. mola u sjeveroistočnom Atlantiku i vrlo promjenjivi obrasci ronjenja. Ove studije sugeriraju da mola vjerojatno mijenja svoje vertikalno ponašanje kao odgovor na uvjete okoliša i distribuciju plijena (Hays i sur., 2009., Sims i sur., 2009.). Iako su dosadašnja istraživanja pružila važan uvid u njihovu geografsku i vertikalnu upotrebu staništa, prethodne studije bile su ograničene u vremenu, prostoru i/ili veličini uzorka i trenutno nema dostupnih informacija za zapadni Pacifik gdje se mola lovi u ribarstvu.

Iako je uhvaćen i prodan na samo nekoliko lokacija širom svijeta, kao što su Japan i Tajvan, M. mola hvataju se slučajno u velikom broju ribolova. Oni su najčešći usputni ulov širokokljune sabljarke koja se lovi lebdećom mrežom oko Kalifornije i Oregona. Prema izvješćima jugozapadne regije Nacionalne službe za morsko ribarstvo (NMFS), između 1990. i 1998. 26,1% ulova lebdeće mreže sastojalo se od M. mola. To znači ulov od više od 26.000 jedinki (Rand Rasmussen, NMFS Southwest Fisheries Science Center, pers. com.). na Mediteranu, M. mola čine do 90% ulova ilegalnog španjolskog lova sabljarke na lebdeće mreže u blizini Gibraltarskog tjesnaca (Silvani et al., 1999.). Uz obalu Južne Afrike, stope prilova oceanske ribe suncem iz ribolova tune i sabljarke parangalom procjenjuju se na 340 000 riba sunčanica godišnje (Petersen, 2005., Sims i sur., 2009.). Nažalost, bez čak i grubih procjena strukture populacije, povezanosti ili veličine, teško je procijeniti utjecaj ovih ribolova. Također, dok se mola smatra visoko plodnim (Fraser-Brunner, 1951), regrutacija je nepoznata.


Reproduktivna biologija plavog marlina (Makaira nigricans) u zapadnom Tihom oceanu.

Plavi marlin (Makaira nigricans) je široko rasprostranjen u tropskim i suptropskim vodama Tihog i Indijskog oceana (Nakamura, 1985.). U Pacifiku, plavi marlin se lovi uglavnom parangalom koji cilja na tunu. Genetske studije (Buonaccorsi et al., 1999.) i podaci o ribarstvu (Kleiber et al., 2003.) ukazuju da postoji samo jedna zaliha plavog marlina u Tihom oceanu. Godišnje iskrcavanje plavog marlina u zapadnom i središnjem Pacifiku tijekom posljednjeg desetljeća bilo je stabilno na oko 13.000 metričkih tona. Međutim, procjene zaliha pacifičkog plavog marlina su neizvjesne, a rezultati se kreću od toga da je stok blizu potpunog iskorištavanja (Kleiber i sur., 2003.), prekomjernog izlova (Yuen i Miyake, 1980.) ili u zdravom stanju (Hinton, 2001).

Kvantificiranje reproduktivnog potencijala plavog marlina važno je za razumijevanje dinamike populacije ove vrste i za potrebe procjene zaliha. Na primjer, procjene veličine i dobi kod spolne zrelosti neophodni su inputi za modele procjene dionica strukturiranih po dobi i veličini (Quinn i Deriso, 1999.). Unatoč veličini ribolova za stoku plavog marlina u Tihom oceanu, bilo je nekoliko objavljenih studija o reproduktivnoj biologiji ovog stoka. U istočnom Pacifiku, Kume i Joseph (1969.) procijenili su veličinu plavog marlina na temelju podataka iz japanskog ribolova s ​​parangali, a Hopper (1990.) je opisao aktivnost mrijesta oko Havajskih otoka. U zapadnom Pacifiku, Nakamura (1944.) je izvijestio da se plavi marlin izmrijetio kod Tajvana. Međutim, nijedna od ovih studija nije pružila detaljne informacije o razvoju jajnika, iako je potrebno znanje o razvoju spolnih žlijezda u pojedinačnih riba da bi se utvrdila sezona mrijesta, veličina i dob u zrelosti te obrazac mriještenja. Reproduktivna biologija plavog marlina opširnije je proučavana u Atlantskom oceanu nego u Tihom oceanu. Na primjer, La Monte (1958) prvi je opisao gonadu plavog marlina u Atlantskom oceanu, Erdman (1968) je promatrao reproduktivni ciklus kod Portorika, Cyr (1987) definirao razvoj gonada i ciklus mrijesta u sjeverozapadnom Atlantskom oceanu, i Arocha i Marcano (2008.) procijenili su veličinu ove vrste u zrelosti u zapadnom središnjem Atlantiku. Ciljevi ovog istraživanja bili su procijeniti reproduktivnu biologiju plavog marlina u zapadnom Tihom oceanu. Histološkim tehnikama utvrđujemo reproduktivnu aktivnost i opisujemo razvoj jajnika. Također se procjenjuju ključni parametri potrebni za procjenu zaliha, uključujući omjer spolova, reproduktivnu sezonu i veličinu u zrelosti.

Zbirke s ribarnica i mjerenja ribe

Uzorci od 1001 plavog marlina su nasumično prikupljeni od rujna 2000. do prosinca 2001. na ribljoj tržnici Tungkang na jugozapadu Tajvana. Svi uzorci ulovljeni su brodovima s parangalom na moru koji rade između 16-23°N geografske širine i 115-135°E geografske dužine. Spol (određen na temelju makroskopskih karakteristika spolnih žlijezda i histoloških presjeka za male jedinke), duljina od oka do vilice (EFL stražnji rub koštane orbite oka do distalnog kraja središnje zrake repne peraje, cm) , a za svaku ribu zabilježena je okrugla težina (RW, kg). Uzorak tkiva nasumično je uzet iz prednjeg (ženke) i srednjeg (muškarci) desnog ili lijevog režnja spolne žlijezde i odmah fiksiran u 10% puferiranom formalinu za kasnije mjerenje oocita i histološku analizu. Tri para jajnika prikupljena su u srpnju 2004. kako bi se procijenila sinkronicitet razvoja jajašca unutar i između parova jajnika. Svaki lijevi i desni režanj ovih jajnika podijeljeni su na prednji, središnji i stražnji dio, a svaki dio dalje podijeljen na vanjski, srednji i središnji sloj. Ukupno 54 poduzorka od 0,05 g (3 jajnika x 2 režnja x 3 dijela x 3 sloja) prikupljeno je nasumično i procijenjen je broj cijelih oocita i srednji promjer jajne stanice (MOD) za svaki poduzorak. Točnije, MOD je procijenjen kao prosjek promjera najnaprednije skupine jajnih stanica izračunat pomoću softvera Image-Pro Plus (Media Cybernetics, Silver Spring, MD), nakon kalibracije prema optičkom mikrometru. Međutim, histološkim presjekom jajne stanice se deformiraju iz oblika u obliku kugle, pa su stoga korištene tri vrste mjerenja za dobivanje pouzdanih rezultata (Arocha, 2002.). Rano razvijene oocite mjerene su na glavnoj osi koja je križala, jajne stanice koje sazrijevaju jezgre mjerene su preko jezgre iz dobro oblikovanih sfera, a promjeri potpuno zrelih oocita izračunati su iz opsega jajne stanice podijeljeno s [pi].

Faktor uvjeta, C, određen je za svaku ribu korištenjem odnosa

gdje je b = nagib odnosa duljine i težine (King, 1995.).

Vrijednost za b procijenjena je primjenom linearne regresije nakon logaritamske transformacije podataka. Parametar b nije se značajno razlikovao od 3 za ženke (t=0,53, df=172, P >0,05) i muškarce (t=-0,99, df=210, P >0,05). Faktor stanja bio je povezan s gonadosomatskim indeksom (GSI), koji je određen na sljedeći način (Uosaki i Bayliff, 1999.):

GSI = (GW / [EFL.sup.3]) x [10.sup.4], (2)

Omjer spolova u svakom mjesecu ili klasi veličine izračunat je kao omjer broja ženki i ukupnog broja ženki i muškaraca. Hi-kvadrat testovi korišteni su za testiranje značajnih razlika u omjeru spolova među mjesecima i veličinama. Omjeri spolova također su regresirani prema duljini pomoću logističke regresije (DeMartini i sur., 2000.).

Mikroskopske karakteristike histoloških presjeka i najnaprednije skupine oocita korištene su za određivanje stadija jajnika (Hunter i Macewicz, 1985 West, 1990 Arocha, 2002 Arocha i Barrios, 2009). Za muškarce, klasifikacija razvoja testisa temeljila se na stupnju spermatogeneze, razvoju sjemenovoda i sastavu zametnih stanica (Grier, 1981. Ratty i sur., 1990. deSylva i Breder, 1997.). Svaki očuvani uzorak tkiva od 150 [mm.3] ugrađen je u parafin, izrezan na 7 µm i obojen Mayerovim hematoksilinom i eozinom. Dinamika procesa sazrijevanja jajnika procijenjena je ispitivanjem načina u distribuciji veličine i frekvencije cijelih oocita (prema Hunter i Macewicz, 1985., Arocha, 2002. Arocha i Barrios, 2009.). Intervali pouzdanosti od 95% za udio jajnih stanica svakog promjera prema stadiju zrelosti jajnika dobiveni su bootstrap postupkom u kojem je svaki skup pseudo podataka konstruiran slučajnim odabirom cijelih oocita sa zamjenom. Promjene tijekom vremena u srednjem promjeru najnaprednije skupine jajnih stanica, vrijednosti GSI (za osobe veće od [većih od ili jednakih] EFL od 180 cm radi poboljšanja vremenskih varijacija) i sastav faza razvoja jajnika procijenjene su kako bi se odredilo sezona mrijesta.

Udio zrele ribe u svim procijenjenim klasama riba, definiran kao zrelost, razvijen je iz uzoraka ulovljenih tijekom sezone mrijesta (Murua i sur., 2003.). Ženke su definirane kao spolno zrele ako su imale rano žumanjkaste, uznapredovale, migratorne jezgre ili hidratizirane oocite (Hunter i Macewicz, 2003. Arocha i Barrios, 2009.), dok su mužjaci definirani kao spolno zreli ako imaju sekundarne spermatocite, spermatocite ili spermatozoida. Prisutnost postovulacijskih folikula (POF) u jajnicima i spermatozoida u sjemenovodima uzeta je kao dokaz nedavnog mrijesta ženki i mužjaka. Atresija žumanjkastih oocita također je zabilježena kod zrelih, ali reproduktivno neaktivnih ženki. Vjerojatnost da je [i.sup.th] riba bila zrela ([P.sub.i]) modelirana je logističkom krivuljom:

[P.sub.i] = 1/(1 + [e.sup.-ln(19)([EFL.sub.i] - [EFL.sub.50])/([EFL.sub.50]. [EFL.sub.95])])], (3)

gdje je [EFL.sub.i] = EFL ribe i i [EFL.sub.50] i [EFL.sub.95] = EFL pri kojima je 50% i 95% skupa dostiglo zrelost.

[EFL.sub.50] i [EFL.sub.95] procijenjeni su maksimiziranjem funkcije log vjerojatnosti i pretpostavkom binomne distribucije pogreške s AD Model Builderom (Fournier, 2000.).

Annual fecundity was estimated from the number of oocytes released per spawning (batch fecundity), the percentage of females spawning per day (spawning fraction), and the duration of the spawning season (Hunter and Macewicz, 2003 Murua et al., 2003) because blue marlin spawn multiple times during the season and have indeterminant fecundity (see Results section). There are two methods for estimating the batch fecundity: 1) the hydrated oocyte method and 2) the oocyte size-frequency method (see Hunter et al., 1985). The oocyte size-frequency method was employed because the sample size for the batch fecundity estimates from the hydrated oocyte method is insufficient for later analysis of the relationship between batch fecundity and EFL or RW (fewer samples have migratory nucleus and hydrated oocytes been observed). The most advanced yolked, migratory nucleus, and hydrated oocytes that were destined to be spawned were identified for individuals on the basis of size-frequency distributions of whole oocytes (larger than 1000 microns). Batch fecundity was then back-calculated gravimetrically by the product of gonad weight and oocyte density, where oocyte density was the mean number of oocytes per gram of three ovarian tissues with no early postovulatory follicles (Hunter et al., 1985). Relative batch fecundity was expressed as batch fecundity divided by the round weight of the fish.

The spawning frequency of blue marlin was estimated indirectly by the inverse of the spawning fraction because direct monitoring of the spawning frequency of pelagic fish during the spawning season is difficult. The spawning fraction was calculated as the proportion of fish that spawned each day during the spawning season. There are two approaches to determine this average (Hunter and Macewicz, 1985): 1) the postovulatory follicle method and 2) the hydrated oocyte method. Indirect methods for estimating spawning frequency are based on four assumptions: 1) females are spawning asynchronously throughout the spawning season 2) fishes do not immigrate to or emigrate from the spawning ground 3) the POFs of blue marlin are histologically detectable for no more than 24 hours or all hydrated oocytes are spawned in less than 24 hours (as observed for yellowfin tuna Schaefer, 1996) and 4) the POFs do not degenerate continuously if a fish is caught and put into the refrigerator immediately.

Gonad samples, size distribution, and sex ratios

No significant differences in MOD were found between each lobe or layer within each individual blue marlin (split-plot ANOVA F=0.41, df=l and 52, P>0.05 F=l.30, df=2 and 51 P>0.05), although there were differences in MOD between the ovaries (F=49.97, df=2 and 52, P<0.05). Similar results were found in the analysis of oocyte number. Thus the gonad samples were collected from the random location of ovaries throughout this study (most from the posterior portion). Of the 1001 sampled fish, 406 were female (size range: 124.1-275 cm EFL), 463 were male (size range: 121-232 cm EFL), and sex could not be determined for the remaining 132 fish. Most of the sampled fish were between 140 and 220 cm EFL (Fig. 1). Blue marlin exhibit sexual dimorphism in growth. Specifically, almost all sampled blue marlin larger than 180 cm EFL were female (Fig. 1). The relationship between the female proportion ([P.sub.f]) and EFL can be described by the logistic function (Fig. 1):

[P.sub.f] = 1 / (1 + [e.sup.-ln(19)[(EFL-175.16)/23.59])].

The sex ratio for the entire study deviated from the expected 1:1 ratio ([chi square]=4.93, df=1, P<0.01) and varied among months (more males in the September 2000 [0.32], October 2000 [0.23], and May 2001 [0.31] collections, and more females in the November 2001 collection [0.67]).

Oogenesis and ovarian development

The most advanced group of oocytes for each ovary were classified as 1) unyolked--oocytes that had not begun vitellogenesis (chromatin nucleolar oocytes and perinucleolar oocytes, Fig. 2A) 2) early yolked--oocytes in the early vitellogenic stage (previtellogenic oocytes, Fig. 2A) 3) advanced yolked--oocytes in an advanced vitellogenic stage (vitellogenic oocytes, Fig. 2B) and 4) hydrated--unovulated hydrated oocyte stage (hydrated oocytes, Fig. 2B). Furthermore, the presence or absence of postovulatory follicles and atresia of yolked oocytes were identified and recorded for the determination of ovarian maturation (Fig. 2C).

The ovaries of 394 females could be staged into six ovarian development stages based on microscopic characteristics and the most advanced group of oocytes (Fig. 2 and Table 1). Ovaries were classified as immature (OM1) if they were packed with unyolked oocytes, maturing (OM2) when the unyolked oocytes were growing to early yolked oocytes, and mature (OM3) if they contained advanced yolked oocytes, but did not exhibit atresia. Ovaries that contained a migratory nucleus and hydrated oocytes, but for which no POFs were found, or for which there were unovulated hydrated oocytes and POFs, were classified as spawning-spawned (OM4). Ovaries with early yolked, advanced yolked, and atretic oocytes were assigned to the recovery stage (OM5). For resting ovaries (OM6), the unyolked oocytes were not packed as orderly as those in immature ovaries, and a few atretic oocytes were observed occasionally.

Spermatogenesis and testicular development

The testes of 442 males could be staged into five testicular development stages by microscopic characteristics and the composition of germ cells. The five cellular stages were based on 1) spermatogonia (Fig. 3A) 2) primary spermatocytes (Fig. 3B) 3) secondary spermatocytes (Fig. 3B) 4) spermatid (Fig. 3C) and 5) spermatozoa (Fig. 3C). Testes were classified as immature (TM1) if they contained spermatogonia and primary spermatocytes, and no spermiogenesis was observed. The testes were regarded as maturing (TM2) when they contained spermatogonia, secondary spermatocytes, spermatid, and spermatozoa (<50% of total number). Testes were staged as mature (TM3) if the lobular lumens contained more than 50% spermatozoa, and the vas deferens was full of spermatozoa. Males were classified as having spawned (TM4) if the numbers of spermatozoa were decreasing in the lobular lumens and a few unspawned spermatozoa were observed in the vas deferens. Resting testes (TM5) were similar to immature testes, although a few unspawned spermatozoa were observed in the vas deferens.

GSI (gonadosomatic index) was relatively high between May and September for females, and between April and September for males (Fig. 4 boxplots). The condition factor, an index reflecting the interaction between biotic and abiotic factors on physiological condition, exhibited a pattern that was roughly the inverse of that of the GSI of males (Fig. 4 points-lines). There was a significant relationship between the MOD (mean oocyte diameter) and the GSI: MOD = 291.80+327.90 Ln(GSI) ([r.sup.2]=0.79, n=191), and we propose that MOD is a valid index for determining reproductive activity. Few ovaries containing vitellogenic oocytes (excluding the samples with atretic oocytes) were observed in January, February, and November. However, there was evidence for yolk accumulation between March and September based on the monthly variation of the percentage of vitellogenic ovaries and the MOD (Fig. 5). Mature ovaries were first seen in March, and females with spawning stage ovaries were observed from May to September (Fig. 6A). Postspawning females (i.e., the recovery stage) were observed from May to December. For males, mature testes were observed throughout the sampling period, and males with spawned testes were observed from March to December (Fig. 6B). The information in Figures 4, 5, and 6 together imply that the major spawning season for blue marlin in western Pacific is from May to September.

That oocytes of various developmental stages were present at the same time in an ovary was based on histological examination and is also evident from Figure 7, which shows that there were several modes in the distributions of oocyte diameter. There was a single distribution mode for diameters of early-stage oocytes: 25-35 [micro]m for chromatin nuclear oocytes and 45-165 [micro]m for peri-nuclear oocytes of immature fish. Two modes (corresponding to CN and PN) were evident in the oocyte distribution for resting fish (Fig. 7B). The number of previtellogenic oocytes (PV 190-330/[micro]m) began increasing with the development of the ovary for maturing fish (Fig. 7C). Vitellogenic oocytes (VT 250-800 [micro]m) and hydrated oocytes (800-1200 [micro]m) appeared in the oocyte distribution when fish matured, and ocytes of several stages were present in the oocyte diameter distribution for these fish (Fig. 7D). However, there was a gap at an oocyte diameter at roughly 1000 [micro]m. This gap indicates that oocytes larger than this size may be spawned soon (Fig. 7D). Modes corresponding to vitellogenic and unovulated hydrated oocytes were observed with the appearance of postovulatory follicles after spawning (Fig. 7E). PNs were most abundant for fish in the recovering stage, although there were also some PVs and VTs in their ovaries (Fig. 7F). Overall, Figure 7 indicates that oocytes grew in an asynchronous manner and that individual female blue marlin spawn multiple times during the spawning season.

Maturity ogives were estimated for females and males caught during the spawning season (May to September). The relationship between the fraction mature and size can be described by a logistic curve with lengths at 50% and 95% maturity ([EFL.sub.50] and [EFL.sub.95]) of 179.76 [+ or -] 1.01 cm EFL (estimate [+ or -] standard error, SE) and 194.2 [+ or -] 1.01 cm EFL (n=394), respectively. For males, [EFL.sub.50] and [EFL.sub.95] were 130 [+ or -] 1 and 130.13 [+ or -] 46.56 cm EFL (n=442, Fig. 8).

There was a clear gap in the oocyte distribution for mature ovaries at 1000 [micro]m (Fig. 7D), and the oocytes of most advanced mode (composed of the most advanced yolked, migratory nucleus, and nonovulated hydrated oocytes) were considered to be those of the spawning batch. Batch fecundity, estimated for the 26 mature ovaries with no early postovulatory follicles, ranged from 2.11 to 13.50 million eggs (6.94 [+ or -] 0.54 mean [+ or -] SE).

The relationships between batch fecundity (BF) and EFL, and between BF and RW were BF = 3.29 x [10.sup.-12] [EFL.sup.5.31] ([r.sup.2]=0.70 Fig. 9A) and BF = 1.59x [10.sup.-3] [RW.sup. 1.73] ([r.sup.2]=0.67 Fig. 9B), respectively. The batch fecundity of blue marlin was size related, and fecundity increased nonlinearly with body size. The relative fecundity of blue marlin ranged from 115 to 25 mature eggs per gram of female body weight (55.45 [+ or -] 3.36).

The spawning fractions were estimated as the proportion of mature females with POFs or hydrated oocytes during the spawning season (May to September, 150 days). There was no significant difference in the spawning fraction among months within the spawning season for the postovulatory follicle and hydrated oocyte methods ([chi square]=3.62, df=4, P>0.05 [chi square]=1.97, df=4, P>0.05). There was also no significant difference in the spawning fraction between different size groups (<200 and [greater than or equal to]200 cm EFL) for these methods ([chi square]=0.29, df=l, P>0.05 [chi square]=0.03, df=l, P>0.05). Finally, there was no difference between the two methods in terms of the monthly spawning fraction (chi-squared independence tests [chi square]=3.54, df=4, P>0.05). The spawning fraction of mature females based on the postovulatory method was 0.41 (n=164 data combined over months), which indicates that each female would have spawned on average once every 2.4 days, or 62 times during the spawning season (Table 2). In contrast, 34% of the mature females had hydrated oocytes during the spawning season, which is equivalent to a mean spawning interval of 2.9 days, or a spawning frequency of 51 times (Table 2). Annual fecundity was estimated as 120-769 million eggs based on the product of batch fecundity and the average spawning frequency from the two methods (57 times).

Size distribution and sex ratio

The sizes of blue marlin caught by Taiwanese offshore longliners in the western Pacific Ocean were primarily between 140 and 220 cm EFL. However, blue marlin are sexually dimorphic animals 170 cm and less are generally males and those larger than 180 cm are generally female. Shung (1975) obtained similar results for blue marlin in the South China Sea (Pratas Islands). Reproductively active male blue marlin in the eastern Pacific Ocean are often smaller than 220 cm EFL, but all animals 230 cm EFL and larger are female (Kume and Joseph, 1969). Several billfish species, such as sailfish (Chiang et al., 2006b), blue marlin (Wilson et al., 1991) and swordfish (DeMartini et al., 2000 Wang et al., 2003) have been shown to exhibit sexually dimorphic growth. Several hypotheses have been proposed to explain this, including 1) sex change or a sex-specific mortality rate (deSylva, 1974) 2) sex-specific growth rates (Wilson et al., 1991 Sun et al., 2002) and 3) sex-specific natural mortality rates (Skillman and Yong, 1976 Sun et al., 2005). Histological analyses indicated that sex-change does not occur in blue marlin. Furthermore, Chen (2001) showed that growth of blue marlin differs between females and males. Thus, this dimorphism is most likely caused by sex-specific growth and mortality rates. However, there is a need to examine the degree to which sexual dimorphism is due to each of these latter two factors. Departure from a 1:1 sex ratio is not expected for most fish species even though females dominate the large size classes. The sample was male-biased for the non-spawning season. However, the sex ratio during the putative spawning season (May-September) was more balanced ([chi square]=0.07, df=l, P>0.05). This may imply that mature females migrate to the spawning grounds during the spawning season. The exact spawning area of blue marlin in the western Pacific Ocean needs to be identified in the future in order to fully evaluate this hypothesis.

Maturity classification and gonad maturation

Misclassification of whether a female is mature will contribute error to the estimation of the maturity ogive, spawning season, batch fecundity and spawning frequency, and hence to uncertainty when estimating size-at-maturity and egg production. In this study, the use of histological techniques to study gonad maturation provided a more precise outcome than have traditional macroscopic techniques. The spawning season for females was estimated by using GSI and histology and by identifying oogenesis as well as the temporal variation of the mean diameter of the most advanced group of oocytes. The size-frequency distributions of whole oocytes (cross calibrated with histological characteristics) for the different maturation stages provided a fuller understanding of the dynamics of ovarian maturation and the spawning pattern of a fish that produces multiple batches. The size-frequency distributions of whole oocytes, which can be constructed by using a dissecting microscope, can serve as a quick way to determine the ovarian development stage when histological data are not available. The condition factor is usually related to fish health, and a roughly inverse pattern between the temporal variation of the GSI and condition factor was found in male blue marlin, which may imply a lower feeding activity during the spawning season as has been argued for some other pelagic migratory fishes (i.e., school mackerel, Begg and Hopper, 1997).

The [EFL.sub.50] for female blue marlin was estimated to be 179.76 cm, and the smallest size at which any female was mature was 157.8 cm EFL. For males, there was considerable uncertainty regarding [EFL.sub.50] owing to a lack of samples in the size range when male blue marlin are maturing (i.e., within the transition from immature to mature) (Fig. 8). However, male blue marlin larger than 131 cm EFL (size-at-onset-of-maturity) were all mature. The size-at-maturity of blue marlin appears to vary across different regions of the Pacific Ocean. For example, the size-at-onset-of-maturity for male blue marlin was roughly 130-140 cm EFL in the western Pacific Ocean (Nakamura, 1985), and females 171-180 cm EFL have GSI values larger than three (i.e., have reached sexual maturation) in the eastern Pacific Ocean (Uosaki and Bayliff, 1999). This variation among areas may be due to environmental or genetic effects or simply sampling error. In this study, [EFL.sub.50] for females was based on large sample sizes and a broad size range of fish collected throughout the spawning season, and maturity was determined by histology. Thus, the results of this study should provide an accurate representation of the size-at-maturity of blue marlin in the western Pacific Ocean.

Blue marlin have indeterminate fecundity, exhibit an asynchronous oocyte development pattern, and spawn multiple times during the spawning season (Hunter and Macewicz, 2003 Murua et al., 2003). The major spawning season seems to be from May to September based on MOD, the GSI values, and staging of ovaries. Shung (1975) indicated that blue marlin spawn between February and November (with high activity in June and September) in the South China Sea, and Hopper (1990) argued that blue marlin spawn primarily between May and September in Hawaiian waters. Kume and Joseph (1969) indicated that blue marlin spawn from December to January in the South Pacific Ocean. In the Atlantic Ocean, the spawning season for blue marlin is May through September, but most activity is between July and August according to data collected near Puerto Rico (Erdman, 1968), although Yeo (1978) indicated that blue marlin spawn at temperatures of 26-29[degrees]C from April to September in the western North Atlantic. These estimates of spawning season would indicate that blue marlin have an extended spawning season and may be more reproductively active during summer, perhaps because of higher temperatures at that time.

It has been argued that more accurate estimates of batch fecundity can be obtained by using only oocytes in the migratory nucleus and hydrated stages (sailfish, Istiophorus platypterus Chiang et al., 2006a). Unfortunately, few ovary samples with migratory nuclei or hydrated oocytes were observed in our study. However, the oocyte distributions exhibited clear modes, including oocytes at sizes that are ready to be spawned. The oocyte size-frequency method usually yields results similar to those based on counts of hydrated oocytes if females with highly advanced oocytes are used (Hunter et al., 1985). In this study, the gonad tissues were collected and preserved for further examination. Batch fecundity is usually back-calculated gravimetrically as the product of the oocyte density per gram of the preserved tissue and the total fresh weight of the ovary. However, Ramon and Bartoo (1997) indicated that preserved ovaries of mature albacore tuna (Thunnus alalunga) lost an average of 2% of their fresh weight. The effect of preservation on weight lost may bias the estimation of batch fecundity by the gravimetric method and may also bias identification of the most advanced-stage oocytes. Thus, gonad weights for fresh and preserved samples should be compared in order to more fully evaluate the gravimetric and other (e.g., volumetric) methods.

Individual estimates of batch fecundity ranged from 2.11 to 13.50 million eggs (6.94 [+ or -] 0.54 size range 174-242 cm EFL). Batch fecundity of blue marlin is estimated to be larger than that of the black marlin (Makaira indica) in the waters off Taiwan (0.32-3.2 million eggs Liu, 2007), than that of sailfish in eastern Taiwan waters (0.2-2.48 million eggs Chiang et al., 2006a), and that of swordfish (Xiphias gladius) in the waters off eastern Australia (1.16-2.50 million eggs Young et al., 2003).

We assumed that the hydrated oocytes of blue marlin were spawned in less than 24 hours (the hydrated oocyte method) and that the POFs were detectable for no more than 24 hours (the postovulatory follicle method), given observations for other pelagic fish (yellowfin tuna, Thunnus albacares Schaefer, 1996). However, these assumptions need to be verified in the future. The mean time between consecutive spawning events was 2.4 days based on the postovulatory follicle (POF) method (2.9 days based on the hydrated oocyte method). There was no significant difference in spawning fraction among months, which indicates that females were spawning asynchronously throughout the spawning season. Furthermore, there is no relationship between the monthly spawning fraction and the two methods, which may indicate that the estimates of the spawning frequency are accurate. However, there are two caveats which need to be examined when applying the POF method. First, the degeneration of POFs varies among species and may be influenced by the preferred spawning temperature of a species (Chiang et al., 2006a). Second, the fish we collected from the fish market may have been caught a few days earlier. Because of that, it is possible that the POFs degenerated before we obtained the fish and therefore the fraction of ovaries with POFs may have been underestimated.

Conclusion and recommendations

This study provides reproductive parameters and their associated uncertainty as inputs for use in stock assessments of blue marlin in the western Pacific Ocean. The analyses were based on large samples from Taiwanese offshore longliners that cover broad areas in the western Pacific Ocean. Consequently, the estimates should be reliable. However, collecting by ships a greater number of specimens over the entire stock's spatial distribution (especially for hydrated ovaries, and testes during the spawning season) is recommended so that estimates of male size-at-maturity and egg production will be more robust. The spatial variation in some of the reproductive parameters could be explored further by using data collected over a broader spatial domain and hence an exploration could be conducted to determine whether this variation is related to abiotic or biotic factors. We recommend that the methods used in this study be applied to estimate reproductive parameters for billfish and other pelagic fish.

The authors express sincere gratitude to A. E. Punt, School of Aquatic and Fishery Sciences, University of Washington, for his valuable comments and comprehensive editing of an earlier version of this manuscript. The authors also thank the four anonymous reviewers for their constructive comments. This study was partially financially supported by the National Science Council and the Fisheries Agency, Council of Agriculture, Taiwan, through grants NSC89-2316-B-002-038 and 90AS-1.4.5-FA-F2(3) to Chi-Lu Sun.

Manuscript submitted 29 September 2008.

Manuscript accepted 3 June 2009.

The views and opinions expressed or implied in this article are those of the author and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA.

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Geoff Goodenow, May 9, 2004

NOAA Teacher at Sea
Geoff Goodenow
Onboard NOAA Ship Oscar Elton Sette

May 2 – 25, 2004

Mission: Swordfish Assessment Survey
Geographical Area:
Hawaiian Islands
Date:
May 9, 2004

Lat: 18 39 N
Long: 158 17 W
Sky: A few more cumulus clouds around today (40% cover) but they didn’t seem to get in the way of the sun too often. Some thin stratus and cirrus around too.
Air temp: 26 C
Barometer: 1011.5
Wind: 120 degrees at 3.5 Knots
Relative humidity: 56 %
Sea temp: 27.1 C
Depth: 959.3 m

The sea was very,very smooth throughout the day.

Science and Technology Log

The line last night was put out at Swordfish Seamount (500 meters deep), about 35 miles south of Cross. It was a bit longer than usual. Longline retrieval began 0800 and was not complete until 1130. Both the length and our better fortune accounted for the longer effort. We brought in 7 on the line today including 4 sharks. Species included the following: 1 snakefish (Gempylus serpens – 104 cm long and about 7 cm wide with a big eye, pointy snout and lined with very sharp teeth– dead), oceanic white tipped shark (Carcharhinus longimanus) alive, 157 cm and nasty a blue shark (Prionace glauca), alive, 132 cm and 32.5 kg, rather docile onboard, very pretty coloration — grayish belly softly blending to a blue dorsally a big eye thresher shark (Alopias superciliosus — love that name) a bit of life in him but not much, 136 cm + tailfin, 51 kg, its curved tail fin nearly the length of his body a silky shark ( ? ) alive an ono or wahoo, a dolphinfish and an escolar. I took some samples of blue shark and thresher shark teeth. A pretty exciting and busy morning. For most of these fish their fate in our hands was the same as usual. But the real excitement was bringing on the live sharks. As they are drawn near the ship, netting held in place on a 3 foot by 6 foot rectangular metal frame is lower to the water by a winch. The fish is brought onto it and hoisted aboard. There are a few seconds of near terror as this thrashing animal hits the deck wielding danger at both ends of its body. A mattress like cover is thrown over each end and weighted down by human bodies (mine was not one of them today, but I’ll take my turn eventually how many people do you know who have ridden a shark?).

The oceanic white and the silky were tagged with the pop ups. To do this a hole is drilled through the base of the dorsal fin. Line looped through that hole attaches the pop up to the animal. Fin clips and blood samples (if possible) are taken as are any remoras attached to the sharks. Then another moment of fear — restraints are withdrawn and animal is sent overboard as quickly as possible. Description of the satellite pop up tags: Each is about 12 inches tall. At the base is a light sensor, above that a cylindrical housing about 1 inch diameter, next a swollen area about 1.75 inch diameter (the pressure sensor) above which is an antenna about 6 inches long. Each costs about $4000.00 including about $300 satellite time to upload data. Since a signal cannot be sent through seawater to the satellite, the units acquire and store data until a preset pop up date (8 months is about max given battery power of the unit). Then they are released automatically, pop to the surface, find a satellite and dump info to it. The system allows us to track fishes vertical movements (by pressure changes) and horizontal movements by measuring ambient light levels. The latter tells us daylength which can be used to estimate latitude to perhaps within a degree and time of dusk and dawn, which when compared to Greenwich can indicate longitude.

But what if the animal dies before the 8 months are passed? If the animal is headed to the depths, at 1200 meters pressure causes release of the pop up. If no vertical change is detected over 4 days (animal has died in shallow water), they release. Other things can happen that disable the pop ups. They might get broken or eaten by other animals. Only about i in 3 tagged swordfish and big eye thresher sharks are heard from if tagged. Those animals go surface to 600 meters often and rapidly subjecting tags to quick temperature and pressure changes that might disrupt operation of the device. In spite of the obstacles, data is gathered from about 60% of the pop up tags deployed. An alternative is small archival tags that get implanted right onto the animal. These cost only $800 and have much greater storage capacity than pop ups so can provide much more data. However, these must be recovered — the fish have to be recaught in order to get the info from the tag. That’s a tough order in this big ocean and recovery rate is indeed low. Setting longline again tonight in same area. At 2042 we are at lat 18 16 N and long 158 27 W.

Personal Log

Last night was spectacular. Brilliant stars horizon to horizon — a star show above, including the Southern Cross, that was equaled in beauty and wonder by the light show in the water. Bioluminescent organisms were ablaze off stern. It looked like the Milky Way in the water but with the stars turning on and off and swirling about in a frenzy. Some were mere points of light, sometimes things flashed as a light bulb going quickly on and off, and once in a while a ghostly basketball sized sphere tumbled through the view. It was hard to know whether to look up or down for fear of missing the next dazzling event.

And yes, there was a small crowd at the bow to admire the moonrise at about 2345. The ship as always held its position near the longline set. As such we are sort of at the mercy of the sea, just rocking and rolling as it moves beneath us. It is to me a very pleasant motion, one that just rocks you gently to sleep. I have never been on a cruise ship, but friends who have tell me there is no (or little) sense of motion to the ship. Perhaps this is comforting to some, but I like the total experience (within reasonable limits, of course) and these last two nights have been perfect in all respects. I am handing off my duties as brake and bait man to others this evening so that I might digest and organize some of the info passed to me by Kerstin and others in the last couple days.

Here are a couple relating to ocean currents. Look at a chart that shows ocean currents along the US east coast (southern and mid-Atlantic states) and for the US west coast (Washington to California). What is the general direction of the flow along each coast? Along which coast, especially in summer, would you expect ocean water to be warmer? Zašto?

I have given you daily temperature readings for the sea water here at about 18 degrees north. The Galapagos Islands straddle the equator far to the east of here off the west coast of South America. You would most likely expect the water there to be warmer on average than around the Hawaiian Islands. Is it? If not, what accounts for the difference?


Acknowledgements

We thank D. McGillicuddy, G. Lawson, and G. Flierl for helpful discussions while developing this work and C. H. Lam for contributing code. This work was funded by awards to CDB from the Martin Family Society of Fellows for Sustainability Fellowship at the Massachusetts Institute of Technology, the Grassle Fellowship and Ocean Venture Fund at the Woods Hole Oceanographic Institution, and the NASA Earth and Space Science Fellowship. Computational support was provided by the AWS Cloud Credits for Research programme. Funding for the development of HYCOM has been provided by the National Ocean Partnership Programme and the Office of Naval Research. CDB and PG acknowledge support from the NASA New Investigator Programme award 80NSSC18K0757. JF and PA were supported by FCT Grants (SFRH/BPD/66532/2009, DRCTM3.1.a/F/062/2016, and FCT/IF/01640/2015, respectively) and by Fundação para a Ciêcia e Tecnologia (FCT) through the strategic project UID/MAR/04292/2013 Granted to MARE.


Reproductive biology of blue marlin Makaira nigricans around Yonaguni Island, southwestern Japan

We studied the spawning seasonality and gonadal development of blue marlin Makaira nigricans using specimens captured around Yonaguni Island in southwestern Japan between February 2003 and February 2006. The mean (±SD) lower jaw–fork length of females (234 ± 24 cm) was greater than that of males (191 ± 12 cm). The smallest mature female and male were 183 and 160 cm, respectively. Most of the 717 females had immature ovaries. However, in March and from May to September, the ovaries of 26 females contained oocytes with yolk globules, hydrated oocytes, or postovulatory follicles. Most males had testes with a large amount of spermatozoa throughout the year. The occurrence of mature blue marlin at Yonaguni Island suggests that spawning occurs here. The mean condition factors (fatness of the fish) of both sexes decreased from March to June or July, presumably as they expended energy to reproduce. We discuss our results in the context of migration theory for blue marlin in the western North Pacific Ocean.

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Acknowledgements

The authors thank J. Hutchings, A. Rosenberg, B. Hall, D. Bowen, E. Susko, L. Lucifora, Z. Lucas, C. Muir, and three anonymous referees for helpful comments and discussions, W. Blanchard for statistical advice, and the late R. Myers for his influence and inspiration. Financial support was provided by the Lenfest Ocean Program and NSF grant OCE00745606.

Appendix S1 IUCN regional conservation status of chondrichthyans.

Appendix S2 Queensland shark netting catch series.

Appendix S3 Parameter estimates of shark netting trends in South Africa.

Appendix S4 List of elasmobranch local extinctions.

Appendix S5 Parameter estimates of linear models in Fig. 6b–d.

Appendix S6 Parameter estimates of linear models in Fig. 6f–h.

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