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This article appeared in a journal published by Elsevier. The attachedcopy is furnished to the author for internal non-commercial researchand education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling orlicensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of thearticle (e.g. in Word or Tex form) to their personal website orinstitutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies areencouraged to visit:
Egg production of turbot, Scophthalmus maximus, in the Baltic Sea
Anders Nissling a,⁎, Ann-Britt Florin b, Anders Thorsen c, Ulf Bergström b
a Ar Research Station, Department of Biology, Gotland University, SE-621 67 Visby, Swedenb Institute of Coastal Research, Department of Aquatic Resources, Swedish University of Agricultural Sciences, SE-742 42 Öregrund, Swedenc Institute of Marine Research, P.O. Box 1870, Nordnes, N-5817 Bergen, Norway
a b s t r a c ta r t i c l e i n f o
Article history:Received 19 January 2012Received in revised form 17 July 2012Accepted 19 July 2012Available online 2 August 2012
In the brackish water Baltic Sea turbot spawn at ~6–9 psu along the coast and on offshore banks in ICES SD24–29, with salinity influencing the reproductive success. The potential fecundity (the stock of vitellogenicoocytes in the pre-spawning ovary), egg size (diameter and dry weight of artificially fertilized 1-day-oldeggs) and gonad dry weight were assessed for fish sampled in SD 25 and SD 28. Multiple regression analysisidentified somatic weight, or total length in combination with Fulton's condition factor, as main predictors offecundity and gonad dry weight with stage of maturity (oocyte packing density or leading cohort) as an ad-ditional predictor. For egg size, somatic weight was identified as main predictor while otolith weight (proxyfor age) was an additional predictor. Univariate analysis using GLM revealed significantly higher fecundityand gonad dry weight for turbot from SD 28 (3378–3474 oocytes/g somatic weight) compared to thosefrom SD 25 (2343 oocytes/g somatic weight), with no difference in egg size (1.05±0.03 mm diameter and46.8±6.5 μg dry weight; mean±sd). The difference in egg production matched egg survival probabilitiesin relation to salinity conditions suggesting selection for higher fecundity as a consequence of poorer repro-ductive success at lower salinities. This supports the hypothesis of higher size-specific fecundity towards thelimit of the distribution of a species as an adaptation to harsher environmental conditions and lower offspringsurvival probabilities. Within SD 28 comparisons were made between two major fishing areas targetingspawning aggregations and a marine protected area without fishing. The outcome was inconclusive and isdiscussed with respect to potential fishery induced effects, effects of the salinity gradient, effects of specificyear-classes, and effects of maturation status of sampled fish.
Reproduction is a costly activity with large energy investment intoegg production and spawning behavior. Resources therefore have tobe balanced between reproduction and somatic growth as well asmaintenance of resources for post spawning survival with the aim tomaximize the life-time production of offspring. Thus, reproductivecharacteristics and strategies evolve in response to environmental con-ditions giving rise to differences in life-history traits among species andpopulations in relation to their geographical distribution. Further, thereis a trade-off between production of few but large eggs or numerousbut small, as well as between few or many egg batches during thespawning season (e.g. Kjesbu and Witthames, 2007; Rijnsdorp andVingerhoed, 1994; Stearns, 2000; Wotton, 1998). Flatfishes in general,including turbot (Scophthalmus maximus), display a high longevity andbatch-spawning, i.e. maximization of fitness involves egg productionover a long period of time in response to varying conditions duringthe spawning season and between years (Cushing, 1990; Hjort, 1914).
In the Baltic Sea, a large brackish water area, water exchange is re-stricted by shallow straights in the Sound and the Belt-seas (ICES SD22 and 23; Fig. 1a). Accordingly, salinity in the surface water is lowthroughout the Baltic Sea, decreasing from ~9 psu (practical salinityunits) in the southwest (SD 24) to merely ~3 psu in the north (SD31). The system is strongly affected by highly irregular inflow eventsdetermining e.g. salinity conditions and thus species compositionwith effects on ecosystem level (e.g. Segerstråle, 1969; Voipio, 1981).Hence, spatial (south–north) variability and temporal (inflow events)variability in salinity conditions affect the reproductive success and con-sequently both abundance and distribution of marine fishes, includingturbot (Nissling et al., 2002; Ojaveer et al., 1985). In terms of adapta-tions, salinity represents a major evolutionary force for marine fishesin the Baltic Sea, with Baltic populations displaying higher tolerance tolow salinities, e.g. regarding fertilization success and egg development,compared to their counterparts outside the Baltic Sea, i.e. form specificpopulations (Nissling and Westin, 1997; Nissling et al., 2002, 2006;Thorsen et al., 1996). Further, variable brackish water conditions,negatively affecting the reproductive success, involve selection forhigh fecundity in Baltic Sea populations (Kändler and Pirwitz, 1957;Nissling and Dahlman, 2010).
j ourna l homepage: www.e lsev ie r .com/ locate /seares
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In the Baltic Sea, turbot is distributed mainly in the Baltic proper(SD 24–29) but may occur up to the Bothnian Sea (SD 30) (Bagge,1981). Genetic studies revealed no differences within the Baltic Sea(Florin and Höglund, 2007; Nielsen et al., 2004), whereas tagging ex-periments suggest the occurrence of local populations (Aneer andWestin, 1990; Florin and Franzén, 2010). Spawning occurs at shallowdepths along the coast and on offshore banks from late May to July.Contrary to marine environments, where turbot produce pelagiceggs, eggs in the Baltic are demersal (Nissling et al., 2006). As op-posed to several flatfishes with low recruitment variability in accor-dance with the “concentration hypothesis” (Beverton, 1995), theyear-class strength of turbot in the Baltic Sea is known to be morevariable (Florin et al., 2011; Molander, 1954), presumably due tovarying abiotic conditions affecting offspring survival prior to settle-ment in the nursery areas; e.g. the viable hatch is affected by salinitywith significantly lower egg survival at b7 psu and no surviving eggsat 5 psu (Nissling et al., 2006).
Turbot is an important target species for the local small-scalecoastal commercial fisheries in the Baltic Sea. In SD 28 the fisherydeveloped in the 1980s peaking in the mid 1990s with at presentsubstantially lower landings (ICES, 2011). Landings on the islandGotland, SD 27–28 (the main study area), are shown as supplementa-ry data (Appendix A). At Gotland the fishery is directed mainly tospawning aggregations (73% of landings during 1994–2010), anddue to sexual growth dimorphism mainly females are caught (Florinet al., 2011). In SD 25 the development is similar with turbot landingspeaking in the 1990s–early 2000s with currently lower landings(ICES, 2011).
In the present study egg production was studied along the salinitygradient (~7.5–6 psu) from mid SD 25 to northern SD 28 (Fig. 1b),
corresponding to the salinity range where a decrease in the viablehatch has been experimentally shown (Nissling et al., 2006). In addi-tion comparisons were made between two major fishing areas and amarine protected area (MPA) without fishing off Gotland in SD 28.Thus, the aim was to assess both adaptations to local salinityconditions and potential effects of fishing mortality on life-historytrade-offs such as between egg production and somatic growth, andbetween production of many small eggs or few large.
2. Material and methods
2.1. Sampling and measurements
Sampling of fish was conducted on spawning aggregations atthree locations in 2007, at the Hoburgs bank (HB), off Eastern Gotland
Fig. 1. a. The Baltic Sea with ICES subdivisions (SD). b. Positions of sampling locations (KK, HB, EG and GS) and mean (±sd) salinities at 0–10 m depth during June–July in1995–2011, at nine monitoring stations in the Baltic Sea. Data obtained from the Swedish Meteorological and Hydrological Institute database SHARK (within the monitoringprogram coordinated by the Swedish Environmental Protection Agency). Dotted line shows the approximate 7 psu isohaline (after Barnes, 2005).
Table 1Sampling locations, depth range (m) and date of catches of pre-spawning andspawning turbot, Scophthalmus maximus, in the present study.
Location Acronym ICESSD
Positions Depth Datepre-spawningfish
Datespawningfish
Hanö bight KK 25 N56 05E15 32
8–20 3/5 2010 8/6 2010
Hoburgs bank HB 28 N56 45E18 30
10–25 6/6 2007
Eastern Gotland EG 28 N57 32E18 51
10–2510–18
6/6 200711/5 2010
14/6 2010
Gotska sandön GS 28 N58 22E19 15
10–253–25
5/6 200728/5 2010
23/6 2010
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(EG) and off Gotska sandön (GS), the latter being a no-take marine re-serve, all in ICES SD 28, and at three locations in 2010, outside Karls-krona in the Hanö bight (KK) in ICES SD 25 and at EG and GS (Fig. 1).In 2007 fish were sampled using gill-nets with a series of mesh-sizesup to 120 mm bar-length within the framework of a fish monitoringprogram (Florin et al., 2011), whereas in 2010 fish were caughtby contracted fishermen, using gill-nets with mesh-sizes of 110–120 mm bar-length. In 2007 sampling was directed to pre-spawningfish for estimation of fecundity, whereas in 2010 both pre-spawningand spawning individuals were sampled for assessment of fecundityand sizes of spawned eggs respectively. Positions, sampling datesand depth ranges are given in Table 1 and estimated fishing pressureat the respective location in ICES SD 28 (obtained from Florin et al.,2011) is shown as supplementary data (Appendix B).
Sampled fish were all in late vitellogenesis conditions (ovary fill-ing most of the body cavity with visible individual oocytes). In2007, total length (±1 mm; Lt) and somatic weight [±1 g (intestineand gonad removed); Ws] were measured, otoliths removed, andsampled gonads frozen in the field. Gonad wet (±0.01 g) and dry(48 h at 60 °C; ±0.0001 g; Gdw) weights were then assessed afterthawing. Two samples (or if required four; see below), one fromeach gonad lobe, were weighted (±0.0001 g) and used for estimationof fecundity. In 2010 caught fish were transported to the Ar ResearchStation (fish from SD 28) or the Institute of Marine Research (fishfrom SD 25) and Lt andWsmeasured, otoliths removed and the in av-erage weight determined (±0.0001 g). Gonad wet weight wasassessed (±0.01 g), a sub-sample (±0.0001 g) preserved in 3.6%buffered formaldehyde for fecundity estimation, and gonad dryweight determined (48 h at 60 °C; ±0.0001 g; Gdw). Fish condition(Cf) was calculated as Fulton's condition factor [(Ws/Lt3)∗100] andage assessed by otolith readings using the stain and slice method(ICES, 2008). In total 70, 50 and 70 fish from HB, EG and GS, respec-tively were analyzed in 2007, and in 2010, 48, 46 and 42 fish fromKK, EG and GS, respectively.
2.2. Fecundity estimations
Turbot display multimodal vitellogenesis with successively matur-ing oocytes, i.e. vitellogenic oocytes of different sizes are present inthe gonad. In estimating fecundity, maturing vitellogenic oocytes tobe spawned in the up-coming season have to be discriminated fromresting oocytes not undergoing vitellogenesis (Bromley et al., 2000;Jones, 1974). In turbot recruitment of vitellogenic oocytes ceasesfrom February/March (Bromley et al., 2000; Caputo et al., 2001)with spawning occurring from April to August with a peak in June–July (e.g. Jones, 1974). Thus, turbot is considered a determinatespawner with a finite number of vitellogenic oocytes being selected(Bromley et al., 2000; Caputo et al., 2001; Jones, 1974). Hence, the po-tential fecundity (Fp), as opposed to the “realized fecundity” (thenumber of eggs spawned), was determined gravimetrically by assess-ment of the number of oocytes≥175 μm, corresponding to oocytescontaining vitellogenin, i.e. expected to be spawned in the season(Jones, 1974). Sub-samples from 2007 were treated by gently shakingin isotonic water for separation of oocytes; oocytes still appearingin aggregations were separated under a stereo-microscope. Thenthe number of oocytes (≥175 μm) was counted manually undera stereo-microscope using a micrometer scale, and the totalfecundity was calculated. A sub-sample typically contained 511±144 (mean±sd) vitellogenic oocytes. If the difference in Fp of thetwo samples exceeded 10%, two additional samples were processedand the mean fecundity was used in further analysis. Differences inFp between sub-samples averaged 5.1, 7.8 and 5.3% for HB, EG andGS, respectively.
Oocytes in sub-samples from 2010 were initially separated by suck-ing them in and out of a Pasteur pipette (Thorsen and Kjesbu, 2001).Subsequently the oocytes were spread out in 5–11 portions, depending
on the sample size (0.0609–0.2046 g) in a counting chamber(11×8 mm) and the remaining oocyte-aggregations were separatedusing needles under a stereo-microscope. The sample portions werethen photographed (QImaging Micropublisher 5 Mpx camera) undera stereo-microscope at 7.5× (Olympus SZX 12 Stereo-microscopewith a SZX-ILLB200 light source), as single layers covered by water.Image resolution was 0.206 pixels/μm. The images were later analyzedusing the open source image analysis program ImageJ (http://rsb.info.nih.gov/ij); first the majority of the oocytes in the size ranging from250 to 950 μmwere counted and the size was measured automaticallyusing particle analysis (Thorsen and Kjesbu, 2001), then the remainingmaturing oocytes were counted manually down to a size of 175 μm(Fig. 2). On average, a sub-sample contained 2749±1103 (mean±sd) vitellogenic oocytes. In total 25 fish from the respective locationwere analyzed for Fp.
2.3. Assessment of maturation status
Discrepancies in maturity levels of fish may hamper comparisons ofthe Fp as the stock of vitellogenic oocytes may be down-regulated byatresia during the maturation process (e.g. Kennedy et al., 2007;Kurita et al., 2003), and for a species with multimodal vitellogenesis,if not all vitellogenic oocytes have yet not been recruited to the stock(e.g. Bromley et al., 2000; Caputo et al., 2001). Obviously, differencesin maturity levels may occur among sampling locations and samplingtimes, but differences in maturity status also exist among individualfish sampled at the same occasion (see Thorsen et al., 2006). Thus,standardization of data is required to provide unbiased fecundity com-parisons to ensure analyzed fish being in similar levels of maturity.Ultimately oocyte diameter of the leading cohort shows the maturationstatus (Kjesbu, 1994), but the mean oocyte size may also be used as anindication of maturity status (Thorsen et al., 2006). Lacking data on oo-cyte diameter in the samples from 2007, packing densities (n oocytes/ggonad weight; Od) were used as an indicator of maturity level assuggested by Thorsen and Kjesbu (2001). Oocyte packing density andmean oocyte diameter are highly correlated (Thorsen and Kjesbu,2001). The significance of potential differences in maturity status onFp-estimations was then elucidated by plotting Od against the relativepotential fecundity (Fp per Ws; Frp); the latter for reducing effects re-lated to variation in fish size. Positive relationships between Frp and Odindicate effects of fish in different maturity statuses, i.e. require inclu-sion of Od in further analysis of Fp (see Thorsen et al., 2006). In the2010 samples oocyte diameter of the leading cohort was used in
Fig. 2. Image showing maturing oocytes. Circles indicate criterion used in judging ma-turing (vitellogenic) ambiguous oocytes; included oocytes (solid line) and excludedoocytes (dashed line).
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judgingmaturation status, calculated as the 95th percentile diameter ofvitellogenic oocytes.
2.4. Egg size measurements
For assessment of egg size, fish were stripped and fertilizationperformed artificially by mixing eggs and semen in water of 10 psuat 12 °C (Nissling et al., 2006). At day one, 200 fertilized eggsdisplaying normal cell morphology were rinsed twice (~10 s) in dis-tilled water and egg dry weight (±0.0001 g; Edw) determined afterincubation for 24 h at 60 °C, and further, 30 eggs preserved in 3.6%buffered formaldehyde for measurement of egg diameter under astereo-microscope at 50×magnification using a micrometer scale. Al-though all fish were caught early in the spawning season thegonadosomatic index [GSI; gonad dry weight (48 h at 60 °C)/somaticweight] was calculated and used as an indication of stage ofspawning. In total 6, 32 and 21 egg samples from different femaleswere obtained from KK, EG and GS, respectively.
2.5. Statistics
Statistical treatments were conducted using SPSS 17.0. Apart fromthe analyses of potential relationships between Od and the relativepotential fecundity all data were ln-transformed before statisticaltreatments. The relationship between the explanatory variables fishlength (Lt), somatic weight (Ws), age, condition (Cf; Fulton's condi-tion factor) and oocyte packing density (Od) or diameter of leadingcohort (Lc), and the response variables Fp or Gdw for the respectivelocation and year, was analyzed by multiple linear regression analy-sis. As Ws, or Lt in combination with Cf, normally result in similar co-efficients of determination in modeling Fp (see Thorsen et al., 2006)the analysis was run using either Ws or Lt and Cf combined as defaultpredictors, with stepwise addition of age and Od (fish sampled in2007) or Lc (fish sampled in 2010).
Differences in Fp and Gdw, respectively among sampling locationswere analyzed by general linear models (GLM), with sampling loca-tion as fixed factor and the predictors Lt, Ws, age, Cf, and Od (samplesobtained in 2007) or Lc (samples from 2010), as well as the potentialinteraction between sampling location and the respective variable, ascovariates. The model (based on the lowest residual sum of squares)was run stepwise with subsequent removal of non-significant(p>0.05; starting with the highest) variables until only significantpredictors were included in the respective model.
3. Results
3.1. Description of analyzed fish
Length (Lt), somatic weight (Ws), otolith weight (OTw), age (byotolith readings) and condition (Cf; Fulton's condition factor) ofpre-spawning fish from the respective sampling location and year in-cluded in the analysis of fecundity are given as supplementary data(Appendix C). Some discrepancies in the material occur. E.g. in 2007the fish from GS were smaller (Lt and Ws) compared to fish fromHB and EG. Contrary, in 2010 fish from EG and GS were of equalsizes whereas fish from KK were larger and on average older. Thesomewhat narrower size ranges of fish sampled in 2010 comparedto in 2007 reflect the gill-nets used, a wider series of mesh-sizeswas used in 2007 than in 2010. No difference in Cf occurred betweenfish sampled in 2007 and 2010 respectively (df=1, F=1.97, p=0.161) but within years Cf differed (df=2, F=11.53, pb0.001 in2007 and df=2, F=7.13, pb0.01 in 2010) with significantly lowerCf for fish from GS in 2007 and for fish from EG in 2010. The age com-position of fish sampled in 2007 and 2010, respectively is shown assupplementary data (Appendix D). In 2007 the age composition atthe respective location (HB, EG and GS) was similar, with the majority
of individuals aged 4–7 years, whereas the majority of fish sampled in2010 were 5–8 years with a somewhat higher mean age of fish fromKK.
Length, weight and condition for spawning fish used in assess-ment of egg size are shown as supplementary data (Appendix E).Concomitant to the above, fish from KK were comparatively larger.No differences in Cf were detected (df=2, F=2.38, p=0.101) indi-cating females in similar stage of spawning.
3.2. Growth pattern
Fig. 3 shows length (Lt) at age for fish from the respective location,HB, EG and GS (Florin et al., 2011; based on sampling in 2006–2009 atEG and GS, and in 2006–2008 at HB) and KK (present study). Growthpattern for ages 3–9 differed between locations with significantlysmaller fish from GS (pb0.001) compared to from HB and EG (p=0.08; Florin et al., 2011). Further, comparing Lt at age (ages 5–9) forfish from KK (present study) and HB and EG, respectively (datafrom Florin et al., 2011) revealed different growth patterns betweenlocations (df=2, F=8.864, pb0.001) with significantly highergrowth of fish from KK [pb0.001 (HB) and pb0.05 (EG); pair-wisecomparisons] compared to HB and EG (p=0.233).
3.3. Evaluation of predictors
For unbiased estimations of fecundity, standardization of data withrespect to discrepancies in maturity levels is required (see above). Dueto the methods used in 2007 and 2010, respectively, maturation statuswas assessed as oocyte diameter of leading cohort (Lc) in 2010 but asoocyte packing density (Od; n oocytes/g gonad weight) in 2007.Based on data from 2010 the relationship between Lc and Od isshown in Fig. 4, yielding a close relationship (df=1, F=143.0,pb0.001), i.e. both Lc and Od are valid indicators of maturation status.Accordingly, for fish sampled in 2007 potential discrepancies in matu-rity levels were evaluated by plotting of Od against the relative fecun-dity resulting in significant positive relationships for all locations(pb0.001, pb0.05 and pb0.001 for HB, EG and GS, respectively) indi-cating fish in different statuses (Fig. 5) potentially affecting estimationof fecundity. Accordingly, Od was considered in further analysis of po-tential fecundity (Fp) and gonad dry weight (Gdw). There was a signif-icant interaction between Od and location, indicating differences inmaturity between fish from the respective location (df=2, F=6.059,pb0.01), 11,012±3012, 12,115±3014 and 14,965±3381 (mean±sd) n oocytes/g gonad weight for HB, EG and GS, respectively. There-fore only fish fulfilling the criterion mean Od±1 sd was used to mini-mize potential effects of maturation status in analysis of Fp and Gdw.Similarly, maturation status differed among fish caught in 2010 usingLc in assessing potential discrepancies (df=2, F=10.17, pb0.001),
200220240260280300320340360380400
3 4 5 6 7 8 9
Age (year)
To
tal t
eng
th (
mm
)
KK HB EG GS
Fig. 3. Length at age of turbot, Scophthalmus maximus, from SD 25 (KK; present study)and SD 28 (HB, EG and GS; Florin et al., 2011). Age determined by otolith readings.
80 A. Nissling et al. / Journal of Sea Research 84 (2013) 77–86
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439±70, 447±44 and 489±49 μm (mean±sd) for KK, EG and GS,respectively. This was valid also when only fish included in analysisof Fp were considered (df=2, F=4.35, p=0.016), i.e. Lc was consid-ered in the analysis of Fp and Gdw. For fish sampled in 2010 no rela-tionship occurred between relative fecundity and maturation status(Lc), F=0.297, p=0.591; F=0.088, p=0.769; F=0.015, p=0.902,for KK, EG and GS respectively (Fig. 6), suggesting unbiased estimationsof fecundity.
For each location and sampling occasion the relationship betweenthe independent variables (Lt, Ws, Cf, age and Od or Lc, respectively)and Fp and Gdw, as dependent variables is shown in Table 2. Ws or Ltin combination with Cf, explained Fp and Gdw equally well, with Od(samples from 2007) or Lc (samples from 2010) and age as additionalpredictors.
In comparing Fp and Gdw among locations, no interaction oc-curred between Od and location for Fp (p=0.424) or between Odand location for Gdw (p=0.298) in the final GLM (subsequent re-moval of non-significant variables) for fish sampled in 2007. Od washowever retained in the analysis of Fp due to a significant relation-ship between Fp and Od (pb0.001) but excluded in analyzing Gdw(0.172). Concerning analysis of Fp among locations for fish sampledin 2010, no relationship was discovered between Fp and Lc (p=0.365) and no interaction occurred between Lc and location (p=0.895). Thus, Lc was excluded in the final GLM. On the contrary, inthe analysis of Gdw, although no interaction was found between Lcand location (p=0.340), there was a strong relationship betweenGdw and Lc (pb0.001), i.e. Lc was retained in the final model.
Concerning fish used to evaluate potential differences in egg size,no differences between locations occurred in gonadosomatic index(GSI; assessed as Gdw/Ws) (df=2, F=0.034, p=0.967) indicatingfish in similar stage of spawning. Regression analysis revealed no re-lationship between egg dry weight (Edw) and Cf (df=1, F=1.12,p=0.295) or between Edw and GSI (df=1, F=0.816, p=0.370),whereas Edw was significantly related to both fish size and age; F=4.49, pb0.05 for Ws, F=3.72, p=0.058 for Lt and F=5.32, pb0.05for OTw, respectively. Hence, Lt, Ws and OTw were considered infurther analysis.
3.4. Egg size
The size of measured eggs was 1.05±0.03 mm and 46.8±6.5 μgwith a close relationship between egg diameter and egg dry weight,df=1, F=12.15, pb0.001 with eggs from all locations pooled. TheGLM (Ws and OTw as independent variables in the final model)yielded no differences in Edw among locations (F=1.559, p=0.220;p=0.452-0.783 in pair-wise comparisons), averaging 45.0±1.9,47.8±6.2 and 45.1±4.9 μg (mean±sd) for KK, EG and GS,respectively.
R² = 0,6621
250
300
350
400
450
500
550
600
650
15000 20000 25000 30000 35000 40000 45000 50000
Oocyte packing density
Lea
din
g c
oh
ort
Fig. 4. Relationship between oocyte packing density (n oocytes/g gonad weight) andoocyte diameter of leading cohort (μm), calculated as the 95th percentile diameter ofvitellogenic oocytes, of turbot, Scophthalmus maximus, in the present study.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
900011000130001500017000
Oocyte packing density
Fp
/Ws
HB EG GS
Fig. 5. Relationship between relative potential fecundity and maturity status (assessedas oocyte packing density) of turbot, Scophthalmus maximus, from HB, EG and GS (SD28) sampled in 2007 (counting of oocytes manually under a stereomicroscope). Matu-rity status increasing from left to right.
0500
100015002000250030003500400045005000
300 350 400 450 500 550 600 650
Leading cohort
Fp
/Ws
KK EG GS
Fig. 6. Relationship between relative potential fecundity and maturity status (assessedas oocyte diameter of leading cohort) of turbot, Scophthalmus maximus, from KK (SD25), and from EG and GS (SD 28) sampled in 2010 (counting of oocytes using animage analysis system). Maturity status increasing from left to right.
Table 2Outcome of multiple regression analysis of potential fecundity (Fp) and gonad dryweight (Gdw) as function of total length (Lt), somatic weight (Ws), age, Fulton's con-dition factor (Cf) and maturation status assessed as either oocyte density (Od; 2007) ordiameter of leading cohort (Lc; 2010) for turbot, Scophthalmus maximus, at differentsampling locations in ICES SD 25 and SD 28 (Fig. 1), showing significant predictorsand adjusted R-square for the best model.
Location Fp Gdw
Predictors R2 Predictors R2
Fish sampled in 2007HB Ws, Od
Lt, Cf, Od0.7990.796
Ws, ageLt, Cf, age
0.7920.789
EG Ws, OdLt, Cf, Od
0.8710.868
Ws, OdLt, Cf, Od
0.8340.830
GS Ws, OdLt, Cf, Od
0.9100.909
Ws, OdLt, Cf, Od
0.8770.876
Fish sampled in 2010KK Ws
Lt, Cf0.7770.772
Ws, LcLt, Cf, Lc
0.8830.880
EG WsLt
0.6840.686
Ws, Lc, ageLt, Cf, Lc, age
0.9040.904
GS Ws, ageLt, Cf, age
0.7520.769
Ws, LcLt, Cf, Lc
0.8080.806
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3.5. Fecundity
In Fig. 7 the relationship between observed Fp and Ws is shownfor fish sampled in 2007, i.e. location HB, EG and GS within SD 28.The outcome of the GLM (Ws and Od as independent variables) isgiven in Table 3. Fp differed significantly between locations withfish from GS displaying significantly higher Fp, pb0.01 and pb0.05,compared to HB and EG (p=0.974); pair-wise comparisons. Here,modeled size-specific Fp averaged 2163, 2198 and 2473 oocytes/gWs for HB, EG and GS, respectively. Thus, in this analysis Fp was sig-nificantly higher at GS, the MPA, compared to the fished areas, HB andEG.
Observed potential fecundity (Fp) for fish from KK (SD 25) and forfish from EG and GS (SD 28) sampled in 2010 is shown in Fig. 8 to-gether with modeled Fp for the respective area. In Table 4 the resultsof the GLM (Ws as independent variable) are given. Fp was signifi-cantly lower for fish from KK compared to EG and GS (pb0.001 inboth cases; pair-wise comparisons) whereas there was no differencebetween fish from EG and GS (p=0.937). Size-specific Fp, derivedfrom the model, had means of 2343, 3378 and 3474 oocytes/g Wsfor KK, EG and GS, respectively. Hence, fish from SD 25 (KK), repro-ducing at >7 psu, displayed significantly lower Fp compared to fishfrom SD 28 (EG and GS), reproducing at b7 psu, with no differencebetween the MPA (GS) and fished area (EG) within SD 28.
As evident from above, estimates of Fp differed considerably be-tween sampling years, i.e. between the methods applied, being signif-icantly higher when the image analysis system was used. Comparisonof size-specific Fp at locations sampled in both 2007 and 2010, i.e. fishfrom EG and GS, results in 33% higher Fp for fish from EG and 28%higher Fp for fish from GS when analyzed using images, preventinginter-annual comparisons within locations.
Based on fish sampled in 2010 Fp was best described by thefunction:
Fp ¼ e5:820 þWs1:298
for turbot from ICES SD 25 (size range 335–1142 g Ws), and thefunction:
Fp ¼ e7:745 þWs1:061
for fish from SD 28 (size range 301–1057 g Ws; EG and GS pooled).
3.6. Gonad dry weight
To further evaluate inter-location differences in egg production,gonad dry weight (Gdw) in relation to maturation status was com-pared (Gdw/Ws versus oocyte packing density and oocyte diameterof leading cohort for samples from 2007 and 2010, respectively;
Fig. 9). Analyzing Gdw (GLM with Ws as independent variable)among locations within SD 28, sampled in 2007, resulted in signifi-cantly higher Gdw for fish from GS compared to that from both HB(pb0.05) and EG (pb0.01) (Table 5). In inter-area (SD 25 vs SD 28)comparisons, i.e. locations sampled in 2010, analysis (Ws and Lc as in-dependent variables) yielded a significant difference in Gdw betweenfish from locations KK, EG and GS, with considerably lower Gdw forfish from KK (SD 25), pb0.001 and pb0.001 compared to fish fromEG and GS (SD 28), respectively (pair-wise comparisons) (Table 6).Gdw also differed between EG and GS with fish from the formerdisplaying somewhat higher Gdw (pb0.05). However, narrowing dis-crepancies in maturity status by using only individuals with Lc±1 sd(mean±standard deviation), resulted in no difference between EGand GS (p=0.091) whereas the difference between KK and EG andbetween KK and GS, respectively remained (pb0.001 and pb0.001).
The results reflect the uncertainty involved in using gonad weightas a measure of egg production in maturing gonads, in particular in aspecies displaying multimodal vitellogenesis with successively ma-turing oocytes. However, concomitant to estimations of Fp, evaluationof Gdw revealed major differences between fish from SD 25 (KK) andfrom SD 28 (EG and GS), whereas potential intra-area differences inSD 28 were less evident.
4. Discussion
The annual population egg production represents the reproduc-tive potential of a stock and is thus the basis for stock–recruitment re-lationships. For the viable egg production, however, also egg qualityaspects such as egg size influencing both egg and larval survival prob-abilities (e.g. Marteinsdottir and Steinarsson, 1998; Trippel et al.,1997) should be considered. Both fecundity and the size of eggsproduced vary with female size/age and condition, i.e. with thestock structure, and further, may vary among populations due to
12
12.5
13
13.5
14
14.5
15
15.5
16
5 5.5 6 6.5 7 7.5
Somatic weight (ln g)
Po
ten
tial
fec
un
dit
y (l
n n
)
HB EG GS
Fig. 7. Observed potential fecundity of turbot, Scophthalmus maximus, from HB, EG andGS (SD 28) sampled in 2007 (counting of oocytes manually under a stereomicroscope).
Table 3Results of the GLM analysis of potential fecundity in relation to somatic weight for tur-bot, Scophthalmus maximus, from ICES SD 28 (for locations see Fig. 1), and the mean po-tential fecundity (ln) with 95% confidence interval for fish from the respectivesampling location in 2007.
Fig. 8. Observed potential fecundity of turbot, Scophthalmus maximus, from KK (SD 25)and from EG and GS (SD 28) sampled in 2010 (counting of oocytes using an imageanalysis system), and modeled potential fecundity for KK (solid line) and EG and GS(pooled; dashed line).
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adaptations to environmental conditions, both abiotic (e.g. salinityand temperature) and biotic (food availability and predation) (seeRijnsdorp and Witthames, 2005). Moreover, as stock parameterssuch as maturity and growth pattern may be altered by fishing mor-tality (e.g. Grift et al., 2003; van Walraven et al., 2010; Walsh et al.,2006), also fecundity and egg size may be affected. Hence, as matura-tion, growth and condition within a population are governed by spa-tial and temporal variability in environmental conditions, the viableegg production of a stock is influenced by the spatial distribution ofspawners (e.g. Morgan and Rideout, 2008) and varies betweenyears, potentially influencing the year-class strength. In the BalticSea, opportunities for successful reproduction of turbot vary bothspatially (along the salinity gradient) and over years (inflow events)in accordance to salinity conditions (Nissling et al., 2006). According-ly, information on viable egg production in different areas is essential
for understanding stock development mechanisms and for imple-mentation of appropriate management measures.
The present study showed, in accordance to what has been foundfor both turbot (Howell and Scott, 1989; Jones, 1974; McEvoy andMcEvoy, 1991) and several other fishes that both fecundity andsize of eggs increase with female size/age, i.e. that population struc-ture may be an important factor affecting recruitment variability.Inter-area comparison revealed considerably higher investment ingonad production of fish from SD 28 compared to from SD 25manifested as both higher fecundity and gonad dry weight but withno difference in egg size. The higher gonad production for fish fromSD 28 involved lower somatic growth (Fig. 3). Hence, as differencesin the life-history parameters were discovered the present study sug-gests that turbot from SD 25 and SD 28, respectively should be man-aged as two separate stocks.
Assessment of fecundity of fish sampled in 2007 vs. 2010 yieldedconsiderably lower estimates, ~30%, when full manual counting wasperformed. This inter-annual discrepancy cannot be due to differencesin fish condition, as fish were found to be in similar condition in 2007and 2010, but to methodological shortcomings. Fecundity of turbot inthe Baltic Sea has been assessed for fish from SD 26 by Stankus(2003), reporting a size-specific fecundity of 2034 oocytes/g somaticweight, i.e. somewhat lower compared to the present study. Althoughthe method applied is not presented in detail, it is evident fromabove that differences in methodology may hamper inter-study com-parisons. For species with unimodal vitellogenesis, i.e. with only onestage of developing oocytes, differences in methods used might beless critical than for those displaying multimodal vitellogenesis withsuccessively maturing batches of oocytes, i.e. with different sizedvitellogenic oocytes present in the gonad, like turbot. Obviously, the hi-atus between non-vitellogenic and vitellogenic oocytes (≥175 μm;Jones, 1974) may, depending on the stage of maturity, be small(Bromley et al., 2000), i.e. the discrimination between developing andnot developing oocytes may be critical. In this respect assessment of fe-cundity by diameter measurements and following counting using an
Table 4Results of the GLM analysis of potential fecundity in relation to somatic weight for tur-bot, Scophthalmus maximus, from ICES SD 25 and SD 28 (for locations see Fig. 1), andthe mean potential fecundity (ln) with 95% confidence interval for fish from the re-spective sampling location in 2010.
Fish sampled in 2010
F p
33.08 b0.001
Location n Average 95% c.i.
KK 25 14.20 14.12–14.27EG 25 14.57 14.49–14.64GS 25 14.59 14.52–14.67
0123456789
1011
900011000130001500017000
Oocyte packing density
Gd
W/W
s
HB EG GS
0
1
2
3
4
5
6
7
8
300 350 400 450 500 550 600 650
Leading cohort
Gd
w/W
s
KK EG GS
a
b
Fig. 9. a. Gonadosomatic index vs maturation status (assessed as oocyte packing densi-ty) of turbot, Scophthalmus maximus, from HB, EG and GS (SD 28) sampled in 2007.b. Gonadosomatic index vs maturation status (assessed as oocyte diameter of leadingcohort) of turbot, Scophthalmus maximus, from KK (SD 25) and from EG and GS(SD 28) sampled in 2010.
Table 5Results of the GLM analysis of gonad dry weight in relation to somatic weight for tur-bot, Scophthalmus maximus, from ICES SD 28 (for locations see Fig. 1), and the meangonad dry weight (ln) with 95% confidence interval for fish from the respective sam-pling location in 2007.
Table 6Results of the GLM analysis of gonad dry weight in relation to somatic weight for tur-bot, Scophthalmus maximus, from ICES SD 25 and SD 28 (for locations see Fig. 1), andthe mean gonad dry weight (ln) with 95% confidence interval for fish from the respec-tive sampling location in 2010, analyzed at two different ranges of gonad maturationstatus evaluated by diameter of the leading cohort.
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image based analysis provide several advantages; images can easily berechecked, ambiguous oocytes may be evaluated at a higher magnifica-tion and calibration between readers performed using individual im-ages. Thus, estimated fecundity derived for fish sampled in 2007 isprobably underestimated.
In the present study fecundity differed among sampling locationsin both 2010 (SD 25 vs SD 28) and 2007 (HB and EG vs GS withinSD 28). Potentially, discrepancies in maturation among fish from therespective location may result in inter-location differences due to ei-ther down regulation of vitellogenic oocytes by atresia (e.g. Kennedyet al., 2007; Kurita et al., 2003), or to not all vitellogenic oocytes yetbeing recruited, or, eventually if spawning has already started andone or more batches of eggs have been released. For turbot recruit-ment of vitellogenic oocytes to the stock occur up to February/March (Bromley et al., 2000), i.e. after this the number of vitellogenicoocytes represents the potential fecundity. Concerning occurrence ofatresia, no information exists about timing or prevalence and magni-tude for turbot. According to ongoing studies, however, atresia seemsto be insignificant in prespawning individuals but may be high to-wards/from onset of spawning (Nissling and Thorsen, unpublished).For 2010 the inter-area differences should not be due to discrepanciesin maturity levels as no relationship was found between oocyte diam-eter of leading cohort and relative potential fecundity (Fig. 6). Fur-ther, the fish were sampled in May, i.e. well after recruitment ofvitellogenic oocytes, and fish from SD 25, displaying lower fecundity,were less mature (Lc in average 439 μm at KK; SD 25 vs 447 and489 μm at EG and GS; SD 28), i.e. the observed difference cannot bedue to eggs being released. Concerning inter-location differences ob-served for fish sampled within SD 28 in 2007 on the other hand, dif-ferences due to discrepancies in maturation cannot be disregarded.As evident in Fig. 5 there is a relationship between oocyte packingdensity (indicator of maturity) and relative potential fecundity withfish from GS being in average less mature; Od 14,966 n oocytes/ggonad weight compared to 11,012 and 12,115 n oocytes/g gonadweight at HB and EG, respectively. Potentially, the lower fecundityat HB and EG in 2007 may be a result of down-regulation by atresiaas sampling was conducted shortly before spawning in early Junewith fish at HB and EG being on average more mature compared toat GS. Hence, provided that vitellogenic vs. non-vitellogenic oocytesare correctly judged, the present study suggests that comparisons ofthe potential fecundity in turbot may be evaluated in pre-spawningfish from March, when no more vitellogenic oocytes are recruited(Bromley et al., 2000), but that estimations may be affected by atresiaoccurring from shortly prior to onset of spawning and onwards(Nissling and Thorsen, unpublished).
According to the hypothesis of Bagenal (1966), studying plaicePleuronectes platessa, size-specific fecundity within a species shouldvary with lower fecundity in the center and higher fecundity towardsthe limits of the distribution as an adaptation to harsher environmen-tal conditions and lower offspring survival probabilities. This patternhas been questioned by Rijnsdorp (1991) and Rijnsdorp andWitthames (2005) arguing that fecundity of plaice is fairly constantthroughout its range, but with the Baltic Sea as an exception. Thepresent study on turbot supports the idea put forward by Bagenal(1966). Our study did not only reveal considerably highersize-specific fecundity of turbot in the Baltic Sea (~2300–3500 -oocytes/g somatic weight) compared to what has been reported forturbot in the North Sea, 1078 oocytes/g somatic weight (Jones,1974; manual counting) and 1124±114 (Bromley et al., 2000;counting of gonad slices mounted on slides using an image analysissystem), but also higher fecundity towards the limit of the distribu-tion within the Baltic Sea, with a mean of ~2300 oocytes/g somaticweight in SD 25 vs. ~3400–3500 in SD 28, although comparisons ofsize specific fecundity along the salinity gradient within SD 28 was in-conclusive (see below). In contrast to other flatfishes in the Baltic Sea,for which an increase in egg size has been shown in accordance with
increased buoyancy at lower salinities (e.g. Nissling et al., 2002) forturbot no inter-area difference in egg size, averaging 1.05±0.03 mm, was found. Further, this figure corresponds to what hasbeen reported for turbot in the North Sea, 1.02 mm (see Jones,1974) and 1.03±0.02 (McEvoy and McEvoy, 1991; derived from fig-ures given in Table 1). The strategy of producing demersal eggs prob-ably implies a lower selection pressure for large eggs as egg size is lesscritical than for pelagic eggs at brackish water conditions.
The higher egg production of turbot in SD 28 compared to SD 25matches the decrease in egg survival probabilities of turbot in the Bal-tic Sea in relation to salinity (Nissling et al., 2006), with salinitiesabove 7 psu in SD 25 and below 7 psu in SD 28 (Fig. 1b), suggestingselection for higher fecundity as a consequence of poorer reproduc-tive success at lower salinities. The present study thus suggests thatthe higher investment in gonad production is reversed by poorer so-matic growth and lower maximum length. According to Jones (1974)female turbot in the North Sea reach maturation at 4.5 years and~46 cm, whereas females from the Baltic Sea (SD 28) mature fromage 3 at ~23–27 cm length (Fig. 3). Further, maximum length (L∞;von Bertalanffy's equation) is ~53.5 cm (Stankus, 2003) for femaleturbot in the Baltic Sea compared to ~65 cm in the North Sea(Jones, 1974). Regarding potential differences in somatic growthwithin the Baltic Sea, the results in Florin et al. (2011), togetherwith those in the present study (Fig. 3), suggest poorer growth to-wards the north, i.e. corresponding to higher investment in gonadproduction.
Fishing mortality involves both phenotypic and genotypic changes(summarized by Rochet, 2009); evolutionary changes in life historytraits may induce an increase in reproductive investment (gonadweight and fecundity) balanced by a decreased growth rate. Thismeans that populations subject to high fishing mortality can beexpected to display an increased size specific fecundity and decreasedsize at maturity. In ICES SD 28 off Gotland, a fishery targeting turbotevolved in the early 1990s (supplementary data; Appendix A). Bythe early 2000s high fishing mortality had resulted in truncatedsize-structure of the stock and decreased CPUEs (Fiskeriverket,2010). Comparison of size-specific fecundity between the two majorfishing areas (HB and EG) and the unfished marine protected area(GS) was inconclusive. The samples obtained in 2007 suggested ahigher size-specific fecundity (~13%) at the unfished MPA comparedto the fished areas, potentially an effect of an intense spawning fish-ery as discussed in Rochet (2009), i.e. selection for later maturationand thus at a larger size, accompanied with lower fecundity, in thefished areas. The pattern observed in 2007 may, however, also becaused by the decrease in salinity towards the north (see Fig. 1b) po-tentially involving selection for higher fecundity and poorer growthat GS (psu ~6.1–6.6) compared to at EG and HB (psu ~6.6–7.0) in ac-cordance with the results in the present study. To evaluate this thor-oughly, in the absence of estimations before the fishery peaked in the1990s, assessment of fecundity of fish from e.g. SD 29, at the limit ofthe distribution in the Baltic Sea, is required. Hence, due to the salin-ity gradient it might be difficult to disentangle fishery induced effectsand adaptations to prevailing salinity conditions on life history traitsas size-specific fecundity by intra-location comparisons in the BalticSea; rather a time series of size-specific fecundity at the same locationshould be established. The observed difference in Fp was however notverified by the results from 2010; no difference in Fp or Gdw betweenEG (fished area) and GS (MPA). Size/age at maturation, affectingsize-specific fecundity, may differ between individual year-classes inrelation to growth history in early stages (Rijnsdorp and Witthames,2005). E.g. for plaice in the North Sea it has been shown thatinter-annual differences in growth rate during the 0-group stageinvolve alterations in size and age at maturity (Modin, 2000;Rijnsdorp, 1993). Potentially this is reflected in the observed pattern,with small high-fecund fish occurring at GS in 2007 (see Fig. 7). Thecomparison between years is however hampered by the use of
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different gears, meaning that small fish were lacking in the 2010 data,and further, potentially by differences in time of sampling, eventuallyaffecting the outcome for samples obtained in 2007 as discussedabove.
Turbot in the Baltic Sea is suggested to have local populations withlimited motility (Florin and Franzén, 2010) although no genetic dif-ferences have been detected (Florin and Höglund, 2007; Nielsen etal., 2004). The present study suggests that differences in life-historyparameters as size-specific fecundity along with egg performancesat different environmental conditions (Nissling et al., 2006) may beused to reveal population structures in the Baltic Sea.
5. Conclusions
Analysis revealed significant differences in the potential fecunditybetween turbot from ICES SD 25 and SD 28 with higher size-specific fe-cundity for fish from SD 28 but with no difference in egg size. Thehigher allocation of resources into gonad production was balanced bylower growth. The difference in fecundity matched egg survival proba-bilities in relation to salinity conditions suggesting selection for higherfecundity as a consequence of poorer reproductive success at lower sa-linities. The outcome of the analysis of size-specific fecundity in fishedand unfished areas within SD 28 suggested difficulties in separatingfishery induced effects from salinity adaptations in the Baltic Sea.
Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.seares.2012.07.009.
Funding sources
The investigation was financially supported by the WWF and theGotland University, and by The County Administrative Board Gotlandand the Swedish National Board of Fisheries who financed the sam-pling program.
Acknowledgments
Many thanks to Filipa da Silva, Marie Jacobsson and Rebecca Retzfor the analysis of samples, and to the helping hands at the Instituteof Marine Research, Bergen, the Institute of Coastal Research,Öregrund, the Institute of Coastal Research, Simpevarp and the Insti-tute of Marine Research, Karlskrona.
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