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Impact of 21st Century Climate Change on Baltic Sea Fish ... - BALTEX

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<str<strong>on</strong>g>Impact</str<strong>on</strong>g> <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>21st</str<strong>on</strong>g> <str<strong>on</strong>g>Century</str<strong>on</strong>g> <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g><strong>on</strong> <strong>Baltic</strong> <strong>Sea</strong> <strong>Fish</strong> and <strong>Fish</strong>eriesNordic Marine Academy course<str<strong>on</strong>g>Impact</str<strong>on</strong>g>s <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g><strong>on</strong> the <strong>Baltic</strong> <strong>Sea</strong>- From Science to PolicyJuly 27 – August 5, 2009Brian R. MacKenzieTechnical University <str<strong>on</strong>g>of</str<strong>on</strong>g> Denmark and University <str<strong>on</strong>g>of</str<strong>on</strong>g> AarhusNati<strong>on</strong>al Institute for Aquatic ResourcesDK-2920 CharlottenlundDenmarkbrm@aqua.dtu.dkArtwork: G. Gorick


Outline1. General fish populati<strong>on</strong> dynamics-trends <str<strong>on</strong>g>of</str<strong>on</strong>g> fish abundances and landings-fishing trends and impacts <strong>on</strong> populati<strong>on</strong>s and communities2. C<strong>on</strong>sequences <str<strong>on</strong>g>of</str<strong>on</strong>g> climate variability for fish - general3. What has happened already – oceanographic and fish examples4. What could happen in future-future and historical perspectives5. Foodwebs and cascading effects+ 3 Exercises to be completed by 3 pm.


Variati<strong>on</strong>s in Spawner Biomass <str<strong>on</strong>g>of</str<strong>on</strong>g>3 <strong>Fish</strong> Species in the <strong>Baltic</strong> <strong>Sea</strong>Spawner Biomass (1000s t)200015001000500CodSpratHerring01968 1976 1984 1992 2000 2008ICES 2008


Millennial Scale Variati<strong>on</strong>s in <strong>Fish</strong> BiomassBaumgartner et al. 1992


Trends in Exploitati<strong>on</strong> and Adult Biomass in27 European Demersal Populati<strong>on</strong>sOverall l<strong>on</strong>g-term significant-increase in fishing mortality(F = ca. 2-3 x nat. mortality)-decline in adult biomass (SSB)-large number <str<strong>on</strong>g>of</str<strong>on</strong>g> stocks in EUwaters overexploited (EEA)Sparholt, Bertelsen, Lassen 2007ICES J. Mar. Sci.


<strong>Fish</strong>ing Down Marine Food Webs-fishing has removed big species and big individuals-cascading effects <strong>on</strong> food webs and lower trophic levelsnow becoming evident, also in <strong>Baltic</strong> <strong>Sea</strong>Pauly et al. 1998, SciencePauly 2000, Ambio; Myers et al. 2007; Casini et al. 2009


Effects <str<strong>on</strong>g>of</str<strong>on</strong>g> <strong>Fish</strong>ing <strong>on</strong> <strong>Fish</strong> Populati<strong>on</strong>sThe obvious…death <str<strong>on</strong>g>of</str<strong>on</strong>g> fish, regulati<strong>on</strong>/reducti<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> populati<strong>on</strong> sizeThe less obvious…changes in size/age compositi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> populati<strong>on</strong>s-size/age structures become truncated inheavily exploited populati<strong>on</strong>s-can affect reproductive successExploited spp.-exploited populati<strong>on</strong>s more variable thanunexploited populati<strong>on</strong>sN<strong>on</strong>exploited spp.-more vulnerable to fishing, climatevariability and human impacts.Hsieh et al. 2006; Cal. CurrentNature


Recovering Marine Food Webs andPopulati<strong>on</strong>sPauly et al. 1998, SciencePauly 2000, Ambio-recoveries are slow, maybe impossible-will become more difficult if climate change and otherhuman activities reduce productivity <str<strong>on</strong>g>of</str<strong>on</strong>g> surviving populati<strong>on</strong>s.


<strong>Baltic</strong> <strong>Sea</strong> – hydrographic gradientsaffect species distributi<strong>on</strong>s and biology-permanenthalocline,seas<strong>on</strong>althermocline-few speciesSalinity Temperature-fish biomass dominatedby 3 species (sprat,herring and cod)Salinity-salinity restrictsreproducti<strong>on</strong> by FW andmarine species(e. g., cod)


<strong>Baltic</strong> <strong>Sea</strong> <strong>Fish</strong> Biodiversity-relatively few species, compared with otherregi<strong>on</strong>al seas <str<strong>on</strong>g>of</str<strong>on</strong>g> similar size (North, Black<strong>Sea</strong>s):Number <str<strong>on</strong>g>of</str<strong>on</strong>g> marine fish species250No. species200150100500EEA 2002<strong>Baltic</strong> <strong>Sea</strong>Black <strong>Sea</strong>North <strong>Sea</strong>


Spawner Biomass <str<strong>on</strong>g>of</str<strong>on</strong>g> 3 Key <strong>Fish</strong> SpeciesSpawner Biomass (1000s t)200015001000500CodSpratHerring01968 1976 1984 1992 2000 2008ICES 2008


Species Interacti<strong>on</strong>s am<strong>on</strong>g<strong>Baltic</strong> <strong>Fish</strong> and Zooplankt<strong>on</strong>Artwork: G. Gorick


Species Interacti<strong>on</strong>s: Cod & Clupeids in the <strong>Baltic</strong>-predator-prey spatial distributi<strong>on</strong>s, stomach analysescannibalism <strong>on</strong> juvenilespredati<strong>on</strong><strong>on</strong> spratpredati<strong>on</strong> <strong>on</strong>juvenile herringAll interacti<strong>on</strong>s being modelled in ICES stockassessment.Köster, Uzars, Plikshs, Möllmann, Neuenfeldt et al.


Species Interacti<strong>on</strong>s: Cod & Clupeids in the <strong>Baltic</strong>predati<strong>on</strong> <strong>on</strong> sprat & cod eggscannibalism<strong>on</strong> eggsfood competiti<strong>on</strong>for zooplankt<strong>on</strong>Köster, Uzars, Plikshs, Möllmann, Neuenfeldt, Feldman, Viitasalo, Aro, Flinkman, Hanss<strong>on</strong> et al.


Estimating Effects <str<strong>on</strong>g>of</str<strong>on</strong>g><str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> <strong>on</strong> <strong>Fish</strong>??How to do it?-understand processes affecting ecology and lifehistories-identify historical relati<strong>on</strong>ships in nature-(possible precedents for future?)-estimate or find out what the hydrographic c<strong>on</strong>diti<strong>on</strong>s will be infuture-expect surprises (n<strong>on</strong>linear effects, threshold resp<strong>on</strong>ses,species invasi<strong>on</strong>s, etc.)


C<strong>on</strong>sequences <str<strong>on</strong>g>of</str<strong>on</strong>g> <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> <strong>on</strong> <strong>Fish</strong>1. Direct effects <strong>on</strong> fish physiology, phenology and lifehistory-growth, survival, reproducti<strong>on</strong>, migrati<strong>on</strong> are all sensitiveto temperature & salinityGT, S2. Indirect effects <strong>on</strong> fish ecology (”food web effects”)-changes in abundance <str<strong>on</strong>g>of</str<strong>on</strong>g> food-interacti<strong>on</strong>s with predators, competitors,pathogens (new relative spatial – temporal distributi<strong>on</strong>s)


Data Sources: Ocean M<strong>on</strong>itoring-compiled and analyseddaily SST measurements fromlightships, lighthouses and harbour sampling-data were collected daily by pr<str<strong>on</strong>g>of</str<strong>on</strong>g>essi<strong>on</strong>altechnicians and meteorologists with calibratedInstruments-started 1860s-1880sSkagen LightvesselPainting: Carl Locher 1892Source: Skagens Kunstmuseum


Measuring Sites and Areas* *-Christiansø, Denmark 1880-1979-Skagen, Denmark 1880-1998-Torungen, Norway 1867-2003-Marsdiep, Netherlands 1861-2007+*** = SST measured daily= Hadley Centre (opportunistic data)


L<strong>on</strong>g-term Temperature Variability in<strong>Baltic</strong> and North <strong>Sea</strong>sSummer (JAS) SST 1880-2003Summer SST, So. <strong>Baltic</strong>191817161514131880 1900 1920 1940 1960 1980 2000MacKenzie & Schiedek 2007Global <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.-temperatures during 1990s-2000s are warmest sincemeasurements began in 1860s-1880s-same pattern with winter, summer, annually averaged data


Comparis<strong>on</strong> with Global & Regi<strong>on</strong>alWarming Expectati<strong>on</strong> in 21 st <str<strong>on</strong>g>Century</str<strong>on</strong>g>-expectati<strong>on</strong>: ca. 3º C/100 years = 0.03º C/yr (Kerr 2004; BACC 2007)Rate <str<strong>on</strong>g>of</str<strong>on</strong>g> change <str<strong>on</strong>g>of</str<strong>on</strong>g> SST ( 0 C yr -1 ;+ 2 SE)0.090.060.030.00MacKenzie & Schiedek 2007Global <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.B B A B Bquarter vs avg. increaseJFM AMJ JAS OND Ann.<strong>Sea</strong>s<strong>on</strong>-annual rate <str<strong>on</strong>g>of</str<strong>on</strong>g> warming similarto expectati<strong>on</strong>-summers have warmed 2-3x fasterthan expected-seas<strong>on</strong>al differences in warming willhave important c<strong>on</strong>sequencesfor ecological processes(e. g., timing <str<strong>on</strong>g>of</str<strong>on</strong>g> events, probability <str<strong>on</strong>g>of</str<strong>on</strong>g>completi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> lifehistories, trophiclinkages, …)


Extreme YearsSST, Q319Torungen1817161514131860 1880 1900 1920 1940 1960 1980 2000Year-define extreme yearsfrom frequencydistributi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> observati<strong>on</strong>s…No. Observati<strong>on</strong>s30252015105Lower 10 th%ile“cold” yearUpper 10 th%ile“warm” year-repeat for each sitefor each quarter012.0 12.8 13.6 14.4 15.2 16.0 16.8 17.6 18.4 19.2 20.0<strong>Sea</strong> surface temperature (Q3; Torungen)MacKenzie & Schiedek 2007Global <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.


Decadal Probability <str<strong>on</strong>g>of</str<strong>on</strong>g> Extremely Cold andWarm Years0.30.20.11860s1870s1880s1890s1900s1910s1920s1930s1940s1950s1960s1970s1980s1990s2000s0.0Annual1860s1870s1880s1890s1900s1910s1920s1930s1940s1950s1960s1970s1980s1990s2000sProbability (T < 10th percentile)Decade0.80.60.40.20.0AnnualProbability (T > 90th percentile)Decade-extreme cold years becoming rarer -extreme warm years becoming comm<strong>on</strong>MacKenzie & Schiedek 2007Global <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.


Effects <str<strong>on</strong>g>of</str<strong>on</strong>g> Past Oceanographic Variability <strong>on</strong><strong>Fish</strong> and Food WebExamples


Sprat in the <strong>Baltic</strong> <strong>Sea</strong>Photo: Muus and Nielsen 1999-small clupeid (max. BL = 10-12 cm)<strong>Baltic</strong> <strong>Sea</strong>-zooplanktivore-prey for juvenile and adult cod, but also predator<str<strong>on</strong>g>of</str<strong>on</strong>g> cod eggs-important commercial species (100s kt/yr since 1974)


Sprat Recruitment and SpawnerBiomass Trends320Spawner Biomass(1000s t)16001200800400Rec.S.B.24016080Recruitment(age 1; 10 9 )01974 1980 1986 1992 19980ICES 2001Spawner biomass and recruitmentnot related (ICES 2001).


<strong>Baltic</strong> Sprat Egg Survival andTemperature (Lab Studies)% Survival to Hatch(mean + sd)8060402001 3 5 7 9 11 13 15TemperatureNissling 2004-egg survival is higher in warmer water (> 5 C)


Zooplankt<strong>on</strong> C<strong>on</strong>centrati<strong>on</strong>sHigher in Warm SpringsZooplankt<strong>on</strong> C<strong>on</strong>c.(no./litre; May)1612840'80'82'83'73'72'74 '75'76'87'71'85 '86'63'66 '62 '64'77'81 '67 '65 '61 '88'78'69'60'700 1 2 3 4 5 6 7'89 '90 Temperature (May; 56-65 m)Temperature (May; 56-65 m)Zooplankt<strong>on</strong> C<strong>on</strong>c.(No./litre; May)604530150'790 1 2 3 4 5Temperature (May; 56-65 m)'80'81'82'83Zooplankt<strong>on</strong> C<strong>on</strong>c.(no./litre; May)2520151050'86'90'92'74 '75'59 '61'83 '88'73 '89'65'72'78 '64'82'66 '80 '62 '60 '84 '76'91 '71'79'77'81'70 '68'67'87'85'63'58'56 '690 1 2 3 4 5 6 7MacKenzie et al. 1996


Variability in Prey Abundance forLarval Sprat-preferred prey <str<strong>on</strong>g>of</str<strong>on</strong>g> larval sprat is Acartia naupliiand copepodites (Voss et al. 2003)-spring Acartia abundance has been high in 1990s(Möllmann et al 2000):Abundance anomaly3210-1-2-3Acartia spp.1960 1965 1970 1975 1980 1985 1990 199543210-1-2-3-4Temp. anomalyMöllmann et al. 2000


L<strong>on</strong>g-term Temperature VariabilitySpring T at 45-65 m;1955-2003Summer (JAS) SST1880-2003May Temperature(45-65 m; Bornholm Basin)654321Summer SST, So. <strong>Baltic</strong>1918171615141301952 1960 1968 1976 1984 1992 2000 2008MacKenzie & Köster 2004:Ecology1880 1900 1920 1940 1960 1980 2000MacKenzie & Schiedek 2007:Global <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.-warm c<strong>on</strong>diti<strong>on</strong>s during 1990s-2000s


Temperature – Recruitment Relati<strong>on</strong>ship for<strong>Baltic</strong> Sprat 1973-2004( )Ln recruitment131211R 2 = 26%adj.P = 0.00178694103829180968476 81781019383887597951029973 92100 988910474901079858777MacKenzie & Köster 2004 EcologyMacKenzie et al. 2008 CJFAS91 2 3 4 5 6May Temperature (45-65 m; Bornholm Basin)-warm temperature promotes growth and survival<str<strong>on</strong>g>of</str<strong>on</strong>g> eggs and larvae, partly via zooplankt<strong>on</strong> community


<str<strong>on</strong>g>Climate</str<strong>on</strong>g>-Hydrography-RecruitmentLinks in the <strong>Baltic</strong> <strong>Sea</strong> 1955-2004Winter climate (NAO)---Ice coverage---Spring temperaturesMartin Visbeckhttp://www.ldeo.columbia.edu/NAOGRAS AS,http://www.gras.ku.dkMacKenzie & Köster 2004Ecology 85: 784-794+++Sprat recruitmentAll links P < 0.01


Temperature-Recruitment Relati<strong>on</strong>shipGeographic c<strong>on</strong>siderati<strong>on</strong>s:Muus & Nielsen 1999MacKenzie & Köster 2004Ecology 85: 785-794Ln Ln Recruitment33221100-1-1-2-2-3-3<strong>Baltic</strong> <strong>Sea</strong>(spring-summer <strong>Baltic</strong> <strong>Sea</strong> spawners)(spring-summer spawners)Black <strong>Sea</strong>(winter spawners)0 2 4 6 8 10 120 2 4 6 8Water Temperature10 12Water Temperature


Management Applicati<strong>on</strong>:Risk <str<strong>on</strong>g>of</str<strong>on</strong>g> Stock Collapse under Different Fand <str<strong>on</strong>g>Climate</str<strong>on</strong>g> ScenariosProbability (Spawner Biomass < B PA )2015T = 2.4; F = 1.2*F SQ= F PAT = 2.4; F = F SQT = 3.7; F = F SQ10502000 2002 2004 2006 2008 2010Mean T - SD,FpaMean T - SD,FsqMean T, FsqMacKenzie & Köster 2004EcologyRisk <str<strong>on</strong>g>of</str<strong>on</strong>g> a stock decline increases in cold climateeven at precauti<strong>on</strong>ary fishing levels (F PA ).


<strong>Baltic</strong> Sprat in a Future Warmer <str<strong>on</strong>g>Climate</str<strong>on</strong>g>?Sprat RecruitmentTemperatureIn 2100, spring SST likelyca. 3 o warmer (Meier 2006).


Survival <str<strong>on</strong>g>of</str<strong>on</strong>g> <strong>Baltic</strong> Salm<strong>on</strong> and Temperature-highest survival at intermediate temperatures (1972-1999)-lower survival in future, warmer <strong>Baltic</strong>?Jutila et al. 2005


Effects <str<strong>on</strong>g>of</str<strong>on</strong>g> Temperature Warming <strong>on</strong><strong>Fish</strong> Phenology: Migrati<strong>on</strong> TimingGarfish (Bel<strong>on</strong>e bel<strong>on</strong>e; hornhecht) enterthe <strong>Baltic</strong> in spring to spawn and feed.Emigrate in fall to North <strong>Sea</strong>.Compare arrival and departure timesin different years with SST.Jacobsen, MacKenzie, Richards<strong>on</strong> in prep.


Timing <str<strong>on</strong>g>of</str<strong>on</strong>g> Garfish Migrati<strong>on</strong>Depends <strong>on</strong> SST 1986-2003Arrival to <strong>Baltic</strong>Departure from <strong>Baltic</strong>214820869846938688Week Number191817161587 94 9296 95 103 101 88919397 89 99 100 901023 4 5 6 7 8 9Week Number4442403887 98 94 9792 90 91 96 95 100102 10310189999 10 11 12 13 14Average Temperature ( o C ) March-May-4 week variati<strong>on</strong> in arrival times am<strong>on</strong>gyears-garfish arrive earlier in warmyearsAverage Temperature ( o C ) September-November-7 week variati<strong>on</strong> in departure timesam<strong>on</strong>g year-garfish depart earlier in warmyearsJacobsen, MacKenzie, Richards<strong>on</strong> in prep.


<str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> & Anchovy inBelt <strong>Sea</strong>-Kattegat 1994-2005North <strong>Sea</strong> SST (JAS)17161514131860 1890 1920 1950 1980 2010Proporti<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> stati<strong>on</strong>s with anchovyin Kattegat-Belt <strong>Sea</strong>0.50.40.30.20.10.0R 2 = 0.39P = 0.021998199620002005200420011994199520021999 1997200315.0 15.5 16.0 16.5 17.0 17.52003MacKenzie, Nielsen,Lassen in prep.Summer SST in North <strong>Sea</strong> ( 0 C)


Anchovy Spawning in Kattegat-ichthyoplankt<strong>on</strong> samples for Kattegat lightshipNo. Anchovy Eggs/haul10864201928 1930 1932 1934 1936 1938 1940 1942Summer SST, So. <strong>Baltic</strong>191817161514131880 1900 1920 1940 1960 1980 2000Heegard 1947MacKenzie and Schiedek 2007-are probably spawning in Kattegat again.


“Southern” Species in the Western <strong>Baltic</strong>Swordfish Xiphias gladius, 66 kgLittle BeltSeptember, 2006Bornholm, July 2008P. Møller, Uni. Cop.Bullet tuna Auxis rocheiLubeck Bay, western <strong>Baltic</strong>July 2008


Will Warm Invaders Reproducein the <strong>Baltic</strong>?-in 2100, can we expect afish community likee. g., Bay <str<strong>on</strong>g>of</str<strong>on</strong>g> Biscay in thecentral <strong>Baltic</strong>?-anchovy, giltheadseabream, red mullet,swordfish…?Depends <strong>on</strong> salinity tolerances and adaptati<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g>individual species and populati<strong>on</strong>s…Artwork: G. Gorick-cod as case study


Cod Spawning Areas in the <strong>Baltic</strong> <strong>Sea</strong>-in deep basins (ichthyoplankt<strong>on</strong> surveys; spawning adults)-salinity must be highenough to allow eggsto float-in shallow and northern areaseggs, salinity is too low. Eggssink to bottom and d<strong>on</strong>ot survive or cannot befertilized successfully(Nissling, Vallin, Westin papers)


Cod Spawner Biomass and RecruitmentSome good news!:-SSB increasing for first time in > 10 years8001000Spawner Biomass (1000s t)600400200SSBRecruits800600400200Recruits; milli<strong>on</strong>s <str<strong>on</strong>g>of</str<strong>on</strong>g> age 2ICES 200901968 1976 1984 1992 2000 20080


Cod Spawner Biomass and <strong>Fish</strong>ing Mortality<strong>Fish</strong>ing mortality has decreased:8001.6Spawner Biomass (1000s t)600400200SSB<strong>Fish</strong>ingmortality1.41.21.00.80.60.40.2<strong>Fish</strong>ing mortality Fbar01968 1976 1984 1992 2000 20080.0ICES 2009


Cod Recruitment per Spawner4Recruits/Spawner3210ICES 2009 1968 1976 1984 1992 2000 2008-record high R/S in recent years (average or above – average)


Parent – Offspring Relati<strong>on</strong>ships(Spawner-recruit)Exercise 1:Does cod recruitment depend <strong>on</strong> biomass <str<strong>on</strong>g>of</str<strong>on</strong>g> cod adults?Is the relati<strong>on</strong>ship stable (similar) over time?Check with latest ICES data (2009).


Exercise Results:Cod Spawner Biomass – Recruitmentrec9000008000007000006000005000004000003000002000001000000y = 0.5145x + 140413R 2 = 0.28280 200000 400000 600000 800000ssbrecruitment residuals600000y = 360.17x 2 - 1E+06x + 1E+09500000R 2 = 0.27024000003000002000001000000-1000001960 1970 1980 1990 2000 2010-200000-300000ssbSignificant time trendin residuals:Mostly positive pre-1980and mostly negative1981-present.


Period-Specific Relati<strong>on</strong>ships1966-1980 1981-2007rec9000008000007000006000005000004000003000002000001000000y = 0.832x + 195216R 2 = 0.47710 200000 400000 600000 800000ssbrec9000008000007000006000005000004000003000002000001000000y = 0.3027x + 108355R 2 = 0.45980 200000 400000 600000 800000ssb-differences in slopes indicate differences in recruit prodn. per spawner-different levels <str<strong>on</strong>g>of</str<strong>on</strong>g> productivity-implies that vulnerabililty to exploitati<strong>on</strong> varies over time (F c<strong>on</strong>sideredsustainable in some time periods may not be sustainable under otherless productive periods)


Exercise 1: C<strong>on</strong>clusi<strong>on</strong>sAbundance <str<strong>on</strong>g>of</str<strong>on</strong>g> fish populati<strong>on</strong>s vary over time.Their dynamics and productivities vary over time.These variati<strong>on</strong>s have implicati<strong>on</strong>s for how they should beexploited.


Why Does R/S Vary?-c<strong>on</strong>sider ecosystem processes affecting survival andgrowth <str<strong>on</strong>g>of</str<strong>on</strong>g> early lifehistory stages-eggs, larvae, young juveniles


Cod Spawning Areas in the <strong>Baltic</strong> <strong>Sea</strong>-in deep basins (ichthyoplankt<strong>on</strong> surveys; spawning adults)-salinity must be highenough to allow eggsto float-in shallow and northern areaseggs, salinity is too low. Eggssink to bottom and d<strong>on</strong>ot survive or cannot befertilized successfully(Nissling, Vallin, Westin papers)


Cod Reproducti<strong>on</strong> and <strong>Baltic</strong> Oceanography:010Oxygen c<strong>on</strong>tent (ml/l)0 2 4 6 8 10Salinity (psu)7 9 11 13 15 17 19Depth (m)2030405060708090SalinityOxygen-low O 2 and salinity limits cod reproductive habitatin the eastern <strong>Baltic</strong> <strong>Sea</strong> (Plikshs et al. 1993; Wieland et al. 1994)


Variability in Cod Reproductive VolumeS > 11 pptO 2> 2 ml/lReproductive volume (km3)70060050040030020010001950 1960 1970 1980 1990 2000 2010Reproductive volume (km3)40030020010001950 1960 1970 1980 1990 2000 2010Reproductive volume (km3)1501005001950 1960 1970 1980 1990 2000 2010Plikshs et al. 1993, pers. comm.MacKenzie et al. 2000


Reproductive Volume Depends <strong>on</strong> Hydrographicand Climatic Processes:-exchange (inflows) with the North <strong>Sea</strong>60Matthäus and Schinke 1998Inflow intensity (Q)5040302010very str<strong>on</strong>gstr<strong>on</strong>gmoderateweakWorld War IWorld War II01880 1900 1920 1940 1960 1980 2000Year


Salinity, Zooplankt<strong>on</strong> and Larval Cod Preyn<strong>on</strong>-seas<strong>on</strong>al anomalies <str<strong>on</strong>g>of</str<strong>on</strong>g> biomass (ln mg/m 3 )3210-1-2-3-4-53210-1-2-3-43210-1-2-3Pseudocalanus el<strong>on</strong>gatusTemora l<strong>on</strong>gicornisAcartia spp.1960 1965 1970 1975 1980 1985 1990 1995210-1-243210-1-2-3-443210-1-2-3-4nsa salinity (psu)nsa temperature (°C)Pseudocalanusis preferred prey<str<strong>on</strong>g>of</str<strong>on</strong>g> larval cod in <strong>Baltic</strong><strong>Sea</strong> (Hinrichsen et al.2002)-abundance declineswhen salinity fallsMöllmann et al. 2000


Stock – Recruitment Relati<strong>on</strong>shipsInfluenced by Envir<strong>on</strong>mental VariabilityTotal repro. volume (km 3 )7006005004003002001000326 + 147 171 + 921968 1976 1984 1992 2000 2008Recruits (age 2; 10 6 )1000800600400200071727766106 707367746910568103 107 98 91104 9293 99 9796 100 90102 101 94 8887 95 89767578860 200 400 600 80085Spawner biomass (kt)79 8081828384-producti<strong>on</strong> rate (R/S) varies over time-different levels <str<strong>on</strong>g>of</str<strong>on</strong>g> producti<strong>on</strong> and recoverydepending <strong>on</strong> regimeJarre-Teichmann et al. 2000 (updated)


Oxygen Depleti<strong>on</strong> Rate Following aMajor <strong>Baltic</strong> Inflow (Jan. 2003)depth [m]102030405060marchaprilmayjulyaugustsummerspring-processes (rates,O 2 solubility) aretemperaturedependent.7080902 3 4 5 6 7 8 9 10Oxygen c<strong>on</strong>centrati<strong>on</strong> (ml x l -1 )-based <strong>on</strong> grid <str<strong>on</strong>g>of</str<strong>on</strong>g> 20-30 stati<strong>on</strong>s(ICES 2004)


<strong>Sea</strong>s<strong>on</strong>al Variability in Reproductive Volumeand TemperatureReproductive Volume(mean + 2 s.e.; km 3 )20018016014012041 41 45 454541J F M A M J J A S O N DDifference in Reproductive Volume(May - August; km 3 )200150100500-50-100-150-200R 2 = 32%P = 0.0002'67'92'77 '73'65 '72 '88'90'85 '70'58'68 '81'83'61 '71 '75'66'64'78'80 '91 '52'87'54 '55'60'53'56 '69 '57'82'89'62'79'85 '76'86 '63'74'590 1 2 3 4 5 6 7Temperature (May; 56-65 m)MacKenzie et al. 1996


Physical - Biogeochemical ProcessesAffect Reproductive Volume-all processes affectingsalinity and oxygenc<strong>on</strong>centrati<strong>on</strong>Artwork: G. Gorick-inflows-primary producti<strong>on</strong>-sinking <str<strong>on</strong>g>of</str<strong>on</strong>g> POC-decompositi<strong>on</strong> <str<strong>on</strong>g>of</str<strong>on</strong>g> POC-temperature-etc.


Coupled NPZD – 3D hydrographic modelincluding NH 4 and H 2 SOxygenreaerati<strong>on</strong>Phytoplankt<strong>on</strong>Zooplankt<strong>on</strong>WaterexchangeUptakeNutrientsPrimary producti<strong>on</strong>:oxygen releaseDetritusWaterexchangeMineralisati<strong>on</strong>:oxygen demandSettlingSettlingEntrainmentnutrient exchangeWaterexchangeNutrientsMineralisati<strong>on</strong>oxygen demand:DetritusSettlingWaterexchangeSediment


Oceanographic Modeling <str<strong>on</strong>g>of</str<strong>on</strong>g> <strong>Sea</strong> Circulati<strong>on</strong>,2002SalinityO 2


Modelled (IOW) and Field Estimates <str<strong>on</strong>g>of</str<strong>on</strong>g> CodReproductive VolumeBornholmGdanskModelField obs.GotlandUNCOVER-main variati<strong>on</strong>s seem to be in both series in most areas, butsome systematic differences also present and causes need to be identified.


Inter-annual Variability inCod Reproductive VolumeTotal repro. volume (km 3 )700 326 + 147 171 + 9260050040030020010001968 1976 1984 1992 2000 2008M. Plikshs, pers. comm.Inflow intensity (Q)605040302010very str<strong>on</strong>gstr<strong>on</strong>gmoderateweakWorld War IWorld War II01880 1900 1920 1940 1960 1980 2000YearMatthäus and Schinke 1998


high<str<strong>on</strong>g>Climate</str<strong>on</strong>g> Variability and <strong>Fish</strong>ing Lead to Regime Shiftsin the <strong>Baltic</strong> EcosystemCoddominatedWhat happens next??Populati<strong>on</strong> levellow-wait for more inflows andcold weather?-fish out the clupeid predators<str<strong>on</strong>g>of</str<strong>on</strong>g> cod eggs?-dominance by invasiveJellyfish?timehighSpratdominated-release hatchery-reared cod?Köster et al. 2003Sci. Mar.1970searly1980s1990searly2000s


Future <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> and <strong>Baltic</strong> Cod


Future <strong>Baltic</strong> Surface TemperatureWinterSummerDJFJJA-<strong>Baltic</strong> surface temperature expected to become2-4 C warmer in winter and summerDöscher and Meier 2004BACC 2007


Future <strong>Baltic</strong> Salinity in 2070-2100C<strong>on</strong>trol: 1960-1990Scenario 1: 2070-2100 Scenario 2: 2070-2100Range = 0-30 PSURange <str<strong>on</strong>g>of</str<strong>on</strong>g> decrease= 0 - 6 PSURange <str<strong>on</strong>g>of</str<strong>on</strong>g> decrease= 0 - 0.8 PSUMeier et al. 2006BACC 2007-regi<strong>on</strong>al scale projecti<strong>on</strong>s uncertain but salinityexpected to fall or remain same


<str<strong>on</strong>g>Climate</str<strong>on</strong>g> Variability and <strong>Baltic</strong> CodReproductive SuccessWarm temperatures affect reproductive volume:-higher rates <str<strong>on</strong>g>of</str<strong>on</strong>g> biological producti<strong>on</strong> andoxygen c<strong>on</strong>sumpti<strong>on</strong> (metabolism)at higher temperatures-reduced oxygen solubility athigher temperaturesLower salinity could reduce reproductive volume-if salinity < 11 PSU


Exercise 2: <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Impact</str<strong>on</strong>g>s <strong>on</strong> <strong>Baltic</strong> Codin <str<strong>on</strong>g>21st</str<strong>on</strong>g> <str<strong>on</strong>g>Century</str<strong>on</strong>g>-calculate 80-year projecti<strong>on</strong>s <str<strong>on</strong>g>of</str<strong>on</strong>g> cod biomass under differentexploitati<strong>on</strong> and climate scenarios.To address uncertainty in the salinity projecti<strong>on</strong>s, c<strong>on</strong>ductthe runs using different assumpti<strong>on</strong>s <str<strong>on</strong>g>of</str<strong>on</strong>g> salinity decline.-no decline, but random variati<strong>on</strong>-25% decline, with random variati<strong>on</strong>-50% decline, with random variati<strong>on</strong>-for 3 combinati<strong>on</strong>s <str<strong>on</strong>g>of</str<strong>on</strong>g> F (0.5, 1, 2)


Scenarios for GroupsGroup Salinity F (relative to SQ)all Random variati<strong>on</strong> 0.5, 1, 21 decline by 25%; var = 0.4 0.5, 1, 22 decline by 25%; var = 0.8 0.5, 1, 23 decline by 50%; var = 0.4 0.5, 1, 24 decline by 50%; var = 0.8 0.5, 1, 2


Uncertainty <str<strong>on</strong>g>of</str<strong>on</strong>g> Projected Salinity-assume 50% decline with random variability <str<strong>on</strong>g>of</str<strong>on</strong>g> rate <str<strong>on</strong>g>of</str<strong>on</strong>g>decline-assume past variability = 0.412.010.0Sallinity (z > 100 m)8.0Run 16.0Run 504.0Run 100Run 1502.0 Run 200mean <str<strong>on</strong>g>of</str<strong>on</strong>g> 2000.02000 2020 2040 2060 2080 2100


Uncertainty <str<strong>on</strong>g>of</str<strong>on</strong>g> Projected Spawner Biomass1400000Series1SSB12000001000000800000600000400000Series3Series5-make histogram <str<strong>on</strong>g>of</str<strong>on</strong>g>SSB in 2089 (N = 200estimates)20000002000 2020 2040 2060 2080 21002520Frequency1510501000 10000 100000 1000000 10000000Log spawner biomass (t)


Scenarios for GroupsGroup Salinity F (relative to SQ)all Random variati<strong>on</strong> 0.5, 1, 21 decline by 25%; var = 0.4 0.5, 1, 22 decline by 25%; var = 0.8 0.5, 1, 23 decline by 50%; var = 0.4 0.5, 1, 24 decline by 50%; var = 0.8 0.5, 1, 2


Projected Cod Biomass for Average andDeclining Salinity800000Random varying salinity800000Declining salinity600000F = 0.5 SQF = 1 SQ600000F = 0.5 SQF = 1 SQSSB400000F = 2 SQSSB400000F = 2 SQ20000020000002000 2020 2040 2060 2080 210002000 2020 2040 2060 2080 2100


Projected Effects <str<strong>on</strong>g>of</str<strong>on</strong>g> Salinity and F <strong>on</strong><strong>Baltic</strong> Cod Spawner Biomass800000F = 0.5 SQ800000F = 1 SQSSB600000400000randomdeclineSSB600000400000randomdecline20000020000002000 2020 2040 2060 2080 210002000 2020 2040 2060 2080 2100800000F = 2 SQSSB600000400000randomdecline20000002000 2020 2040 2060 2080 2100


Exercise 2: C<strong>on</strong>clusi<strong>on</strong>s re. <strong>Baltic</strong> Cod in<str<strong>on</strong>g>21st</str<strong>on</strong>g> <str<strong>on</strong>g>Century</str<strong>on</strong>g>-abundance will depend <strong>on</strong> both F and salinity-abundances higher when F lower and salinity higher-sensitive to climate model projecti<strong>on</strong>s <str<strong>on</strong>g>of</str<strong>on</strong>g> salinity


Future <str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> Threatens MarineSpecies in the <strong>Baltic</strong> and Belt <strong>Sea</strong>s-cod-sprat-plaice-soleMacKenzie et al. 2007Glob. <str<strong>on</strong>g>Change</str<strong>on</strong>g> Biol.Lower salinity (Meier 2006) will shrink marine habitats in the <strong>Baltic</strong>


<str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g> and Eutrophicati<strong>on</strong>Interacti<strong>on</strong>s-are complex-understanding is still limited-some examples <str<strong>on</strong>g>of</str<strong>on</strong>g> the interacti<strong>on</strong>s follow…


Cod in a Future Low-Nutrient <strong>Baltic</strong>?Fewer sprat& herringLess preyReduced carryingcapacity for codReducedeutrophicati<strong>on</strong>


<strong>Baltic</strong> Cod C<strong>on</strong>diti<strong>on</strong> Decreasesat Low Prey Abundance (1983-2002)C<strong>on</strong>diti<strong>on</strong> (Fult<strong>on</strong>’s K)1,00,90,8P=0,00125-39 cmP=0,001observed Kpredicted K0,70 5 10 15 20 25 301,040-60cmP=0,001P=0,0010,90,80,70 5 10 15 20 25 3070-89 cmP=0,0011,0P=0,0010,90,80,70 5 10 15 20 25 30>80 cm1,00,90,80,70 5 10 15 20 25(SSB Herring + SSB Sprat )/SSB Cod-reduced prey/cod could affect cod growth and reproducti<strong>on</strong>Richter and MacKenzie in prep.


Cod in a Future Low-Nutrient <strong>Baltic</strong>?Reducedeutrophicati<strong>on</strong>Fewer sprat& herringLess preyReduced carryingcapacity for codLess decomp.<str<strong>on</strong>g>of</str<strong>on</strong>g> organic matterBetter O 2 inspawning areasIncreased repro.success & recr.


<str<strong>on</strong>g>Climate</str<strong>on</strong>g> <str<strong>on</strong>g>Change</str<strong>on</strong>g>, Eutrophicati<strong>on</strong>,and Cod in the Future <strong>Baltic</strong>:Increased precipitati<strong>on</strong>and run<str<strong>on</strong>g>of</str<strong>on</strong>g>f loading<str<strong>on</strong>g>of</str<strong>on</strong>g> nutrients; warmer TReduced nutrientloading; more stormsFrequent and l<strong>on</strong>gerperiods <str<strong>on</strong>g>of</str<strong>on</strong>g> anoxia?Fewer and shorterperiods <str<strong>on</strong>g>of</str<strong>on</strong>g> anoxia?MacKenzie et al. 2002CJFAS-outcome not clear-requires process modelling


<strong>Baltic</strong> <strong>Sea</strong> Management and C<strong>on</strong>servati<strong>on</strong>Policy Objectives (BSAP 2007)-reduce nutrient loading-rebuild seal populati<strong>on</strong>s-negative c<strong>on</strong>sequences for cod??(lowering overall productivity <str<strong>on</strong>g>of</str<strong>on</strong>g> system andincreasing abundance <str<strong>on</strong>g>of</str<strong>on</strong>g> a cod predator)-c<strong>on</strong>sider ecosystem <str<strong>on</strong>g>of</str<strong>on</strong>g> the past…look for past evidence<str<strong>on</strong>g>of</str<strong>on</strong>g> abundances and distributi<strong>on</strong>s (develop baselines)-archives, paleo data, etc.


Cod <strong>Fish</strong>ing in the Southern <strong>Baltic</strong>, 1602Exercise 3: Guess how many cod were caught and wherefrom this tax record:132456Source: Maibritt Bager, Univ. So. DK


Cod <strong>Fish</strong>ing in the Southern <strong>Baltic</strong>, 16023. 100 dried cod(tax rate perhousehold)3121. Skatte torsk-taxcod2. One man44. <strong>Fish</strong>ing village- Snogebæk5. Total driedcod566. 4½ M 300 pieces(4800 cod)Source: Maibritt Bager, Univ. So. DK


Cod Tax Paid to Hammershus, BornholmNumber <str<strong>on</strong>g>of</str<strong>on</strong>g> cod9000800070006000500040003000200010000Tax <str<strong>on</strong>g>of</str<strong>on</strong>g> cod fishing effort Hammershus County1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610Photo: A. MaciejewskaHolm and Bager 2002-cod were abundant incommercially relevant quantities-source <str<strong>on</strong>g>of</str<strong>on</strong>g> revenue to the King


Range Variability <str<strong>on</strong>g>of</str<strong>on</strong>g> Eastern <strong>Baltic</strong> Cod-c<strong>on</strong>tracti<strong>on</strong> and low biomass duringlow salinity periods (infrequentNorth <strong>Sea</strong> inflows)Aro & Sjöblom 1983; MacKenzie et al. 2000; Köster et al. 2005-expansi<strong>on</strong> and high biomass duringhigher salinity periods (frequentNorth <strong>Sea</strong> inflows)-improves recruitment-reduces cannibalism and competiti<strong>on</strong>.


Annual Cod Exports from Southern Finlandto Sweden 1556-1635Cod exported fromFinland to Sweden (t)25201510501560 1575 1590 1605 1620 1635MacKenzie et al. 2007 <strong>Fish</strong>. Res.


Annual Cod Exports from Southern Finlandto Sweden 1556-16352525Finnish cod landings (t)49H1 & 49H2201510501975 1976 1977 1978 1979Cod exported fromFinland to Sweden (t)201510501560 1575 1590 1605 1620 1635-landings 400 years ago were higher than during 1976-78-<strong>on</strong>ly get cod landings in SW Finland when biomass is highor salinity is high (such periods usually coincide)MacKenzie et al. 2007 <strong>Fish</strong>. Res.


Swedish Cod <strong>Fish</strong>ery 1550s-1750s-c<strong>on</strong>ducted short prelim. search <str<strong>on</strong>g>of</str<strong>on</strong>g> Swedisharchives for area near Stockholm-period 1550s-1750sStockholmSödermanland-some data recovered-compare with recent Swedishlandings in same ICES squaresMacKenzie et al. 2007 <strong>Fish</strong>. Res.


Central-Northern Swedish Cod Landings,1550s-1750s20Cod landings (t)(1998-2005: mean + 2 se)16128401556155715581559mid-1700s1998-2005-Swedish local fishery caught ca. 10 t / year during sametime period as cod was being imported from Finland (twogeographically-separated fisheries <str<strong>on</strong>g>of</str<strong>on</strong>g> similar magnitude atnearly same time)MacKenzie et al. 2007 <strong>Fish</strong>. Res.


<strong>Baltic</strong> Ecosystem Status During 1550-1630C<strong>on</strong>temporary knowledge suggests it couldhave been “cod-hostile” (!):Primary Producti<strong>on</strong>(106 t C/yr)Lower 1 º Prodn.Elmgren 198960504030201001900 1980High seal predati<strong>on</strong> & compet.<strong>Fish</strong> c<strong>on</strong>sumed bymarine mammals (kt/yr)3503002502001501005001900 1980Elmgren 1989-but cod biomass was high and widespread in <strong>Baltic</strong>(supported ec<strong>on</strong>omically important fisheriesin northern and southern <strong>Baltic</strong>)MacKenzie et al. 2007 <strong>Fish</strong>. Res.


Cod in a Hostile <strong>Baltic</strong>?How could there be important fisheries in the (northern) <strong>Baltic</strong>in an apparently cod-hostile ecosystem?Hypotheses:1. Better salinity and oxygen c<strong>on</strong>diti<strong>on</strong>s? (positive effects <strong>on</strong> recruitmentand spatial distributi<strong>on</strong>)-needs paleo-evidence2. <strong>Fish</strong>ing effort and mortality rates were much lower than now.-allowed cod biomass to remain high, despite potentially lower 1º prodn.and higher predati<strong>on</strong> rates and food competiti<strong>on</strong> due to seals-is very likely (simpler technologies, no fishing <str<strong>on</strong>g>of</str<strong>on</strong>g>fshore, etc.)MacKenzie et al. 2007 <strong>Fish</strong>. Res.


C<strong>on</strong>clusi<strong>on</strong>s<strong>Baltic</strong> cod vulnerable to several human impacts and theirinteracti<strong>on</strong>s-exploitati<strong>on</strong>, climate change, eutrophicati<strong>on</strong>, etc.<str<strong>on</strong>g>Climate</str<strong>on</strong>g> change likely to affect biodiversity <str<strong>on</strong>g>of</str<strong>on</strong>g> fish community-community “fresher, warmer”, esp. if salinity falls by 50%Many uncertainties remain – need process knowledge,observati<strong>on</strong>s and models.


Food Webs and Trophic CascadesPauly 2000


Trophic Cascades in Marine Foodwebs-loss <str<strong>on</strong>g>of</str<strong>on</strong>g> large sharks <str<strong>on</strong>g>of</str<strong>on</strong>g>f east coast USA since 1950s:


Trophic Cascades in Marine Foodwebs-led to increase <str<strong>on</strong>g>of</str<strong>on</strong>g> prey (smaller sharks and rays):


Trophic Cascades in Marine Foodwebs-and to decrease <str<strong>on</strong>g>of</str<strong>on</strong>g> prey’s prey…


Trophic Cascade in a Marine FoodwebNBig sharksSmall sharksYearBig sharksNSmall sharksScallopsYearNScallopsScallopsSmall sharksYearMyers et al. 2007Big sharks


Variati<strong>on</strong>s in Spawner Biomass <str<strong>on</strong>g>of</str<strong>on</strong>g>3 <strong>Fish</strong> Species in the <strong>Baltic</strong> <strong>Sea</strong>Spawner Biomass (1000s t)200015001000500CodSpratHerring01968 1976 1984 1992 2000 2008ICES 2008


Hydrographic Effects <strong>on</strong> Trophic Interacti<strong>on</strong>sin the <strong>Baltic</strong> <strong>Sea</strong>Oxic bottom layer-more cod-cod feeding <strong>on</strong> benthic inverts.-cod occupying deep layerAnoxic bottom layer-fewer cod-cod feeding <strong>on</strong> clupeids-no cod in deep layerArtwork: G. Gorick


Cascading Effects in the <strong>Baltic</strong> <strong>Sea</strong>Piscivore-zooplanktivoreZooplanktivore - zooplankt<strong>on</strong>Zooplankt<strong>on</strong>-chlorophyllCasini et al. 2008Proc. Roy. Soc. L<strong>on</strong>d.


Cod Abundance and Cascading EffectsWhen cod abundant,cascading effects absent.When cod rare,cascading effects present.Casini et al. 2009PNAS


Cod Abundance and Cascading Effectsin a Warmer, Fresher <strong>Baltic</strong> <strong>Sea</strong>Hypothesis:In a (future?) warmer and fresher <strong>Baltic</strong>:-expect more sprat-expect fewer codcan we expect these cascading effects to strengthen?


Regime shifts in the <strong>Baltic</strong> ecosystemhighCoddominatedWhat happens next??Populati<strong>on</strong> levellow-wait for more inflows andcold weather?-fish out the clupeid predators<str<strong>on</strong>g>of</str<strong>on</strong>g> cod eggs?-dominance by invasiveJellyfish?timehighSpratdominated-release hatchery-reared cod?Köster et al. 2003Sci. Mar.1970searly1980s1990searly2000s


C<strong>on</strong>clusi<strong>on</strong>s<strong>Baltic</strong> cod vulnerable to several human impacts and theirinteracti<strong>on</strong>s-exploitati<strong>on</strong>, climate change, eutrophicati<strong>on</strong>, etc.<str<strong>on</strong>g>Climate</str<strong>on</strong>g> change likely to affect biodiversity <str<strong>on</strong>g>of</str<strong>on</strong>g> fish community-community “fresher, warmer”, esp. if salinity falls by 50%Roles <str<strong>on</strong>g>of</str<strong>on</strong>g> changes in pH and sea level unclearMany uncertainties remain – need process knowledge,observati<strong>on</strong>s and models.


Early 20th <str<strong>on</strong>g>Century</str<strong>on</strong>g> Cod BiomassC. Humborg 2009Eero et al. 2008 CJFAS

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