The influence of environmental conditions on early life stages of flounder (Platichthys flesus) in the central Baltic Sea

Journal of Sea Research 75 (2013) 77–84

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The influence of environmental conditions on early life stages of flounder (Platichthys flesus) in the central Baltic Sea Didzis Ustups a, b,⁎, Bärbel Müller-Karulis a, c, Ulf Bergstrom b, Andrej Makarchouk a, Ivo Sics a a b c

Institute of Food Safety, Animal Health and Environment “BIOR”, Riga, Latvia Swedish University of Agricultural Sciences, Department of Aquatic Resources, Oregrund, Sweden Baltic Nest Institute, Stockholm Resilience Center, Stockholm University, Stockholm, Sweden

a r t i c l e

i n f o

Article history: Received 2 December 2011 Received in revised form 1 May 2012 Accepted 1 May 2012 Available online 8 May 2012 Keywords: Baltic Sea Reproductive Volume Flounder Eggs Larvae

a b s t r a c t Flounder (Platichthys flesus) is a temperate marine fish that is well adapted to the brackish waters of the Baltic Sea. There are two sympatric flounder populations in the Baltic Sea, pelagic and demersal spawners, which differ in their spawning habitat and egg characteristics. In the present study, pelagic spawning flounder of the central Baltic Sea was studied. We examined whether variations in hydrological regime can explain fluctuations in flounder early life stages that have occurred over the past 30 years (1970–2005). Using generalized additive modeling to explain the abundance of flounder eggs and larvae in a Latvian ichthyoplankton dataset, we evaluate the hypothesis that the available reproductive volume, defined as the water column with dissolved oxygen larger than 1 ml/l and salinity between 10.6 and 12 PSU, affects the survival of flounder ichthyoplankton and determines recruitment success. Both reproductive volume and spawning stock biomass were significant factors determining flounder ichthyoplankton abundance. Different measures of water temperature did not contribute significantly to the variability of eggs or larvae. However, recruitment did not correlate to the supply of larvae. The findings presented in this study on the relationship between flounder reproduction, spawning stock biomass and reproductive volume, as well as the lack of correlation to recruitment, are valuable for the understanding of flounder ecology in the Baltic Sea, and for developing the management of the species. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Flounder (Platichthys flesus) is a temperate marine fish that, compared to other pleuronectid species, is well adapted to the brackish waters of the semi-enclosed Baltic Sea (Nissling and Dahlman, 2010; Nissling et al., 2002). Flatfishes exhibit significant year to year variation in recruitment, as is characteristic for many marine fishes, however recruitment variations are more moderate than for gadoids and herring (Leggett and Frank, 1997). Variations in climate and hydrology are key factors that determine species distribution, stock size and recruitment in flatfish populations (Leggett and Frank, 1997; Van der Veer et al., 2000; Wegner et al., 2003). In flatfish stocks, variations of egg and larvae survival are often dominated by density independent factors operating at local scale (Leggett and Frank, 1997) while according to the concentration hypothesis recruitment of flatfish may approach the carrying capacity of their habitat in years when settlement is high, and this limitation may then moderate the population size (Beverton, 1995). Size and ⁎ Corresponding author at: Daugavgrivas 8, Riga, Latvia. Tel.: + 371 67610766; fax: + 371 67616946. E-mail address: [email protected] (D. Ustups). 1385-1101/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.seares.2012.05.001

quality of nursery grounds then further influence recruitment success (Gibson, 1994; Le Pape et al., 2007; Rochette et al., 2010). Since the decline of cod abundance in the 1980s (Eero et al., 2007; Koster et al., 2003), flounder is one of the dominant demersal fish species in the eastern Baltic Sea. However, in the mid 1980s, due to unfavorable hydrological conditions and high fishing mortality, the Eastern Gotland flounder stock (Vitins, 1980) was critically low and specialized flounder fishery was banned during 1985–1989. After that, the flounder stock has gradually recovered. There are two sympatric flounder populations in the Baltic Sea, which differ in their spawning habitat and egg characteristics (Florin and Höglund, 2008; Nissling and Dahlman, 2010). Demersal spawners produce small and heavy eggs which develop at the bottom of shallow banks and coastal areas in the northern part of the Baltic Proper. Pelagic spawners spawn at 70–130 m depth, and their eggs are neutrally buoyant at 10.6–12.0 PSU salinity and require oxygen concentrations of 1–2 ml/l for development (Anon., 1978; Nissling et al., 2002; Vitins, 1980). The oxygen content also determines the distribution of spawning flounder (Grauman, 1981). Consequently, as for all marine teleosts with pelagic eggs in the Baltic Sea, their recruitment success is based on the ability to produce eggs that can float in the low saline and therefore less dense water (Nissling et al., 2002).

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The current Baltic Sea is a young, brackish water body, with low and changeable salinity and harsh temperature conditions in winter. The narrow, shallow transition area consisting of the Kattegat and the Belt Sea greatly restricts the water exchange with the North Sea giving the water in the Baltic Sea a residence time of 25–35 years (Matthäus and Schinke, 1999). The water column consists of two different water masses: the outflowing low-saline Baltic water above and the more saline deep water below the halocline (Ojaveer and Kalejs, 2005). Salinity conditions for the development of pelagic spawner flounder eggs are generally met only below the halocline. Conditions for life in the deep water of the Baltic Sea are strongly influenced by inflows of highly saline and oxygenated water from the North Sea. These major Baltic inflows are episodic in character, and are the major mechanism by which the central Baltic deep water is renewed (Matthaus and Franck, 1992; Schinke and Matthaus, 1998). Major inflows transport substantial amounts of saline and oxygenated water into the Baltic deep basins, while during the stagnation periods between major inflows, oxygen concentrations below the halocline gradually decrease as a result of oxygen consumption by degrading organic matter (see for example Elmgren, 2001). At the same time, bottom water salinity steadily declines, as diffusion and entrainment transport salt through the halocline (Meier et al., 2006). The variable salinity and oxygen conditions in the bottom water, especially during prolonged stagnation periods, have been shown to determine the hatching success of cod eggs (MacKenzie et al., 2000) and to affect the recruitment of cod (Cardinale and Arrhenius, 2000). Given the physiological constraints on reproduction of pelagic spawning flounder (Nissling et al., 2002), similar effects can be expected on the flounder in the Central Baltic Sea. The aim of the present study is to examine whether variations in hydrological regime can explain the fluctuations in flounder early life stages that have occurred over the past 30 years. We evaluate the hypothesis that the available reproductive volume, defined as the water column with dissolved oxygen larger than 1 ml/l and salinity between 10.6 and 12 PSU, affects the survival of flounder eggs and larvae and determines recruitment process. 2. Material and methods 2.1. Study population According to the ICES/HELCOM Workshop on Flatfish in the Baltic Sea (ICES, 2010) pelagic flounder makes up 90% of flounder landings in the Baltic Sea. Three of the five Baltic pelagic flounder stocks are located in ICES subdivisions (SD) 22–25 in the Southern Baltic Sea, and a fourth in the Gulf of Gdansk (SD 26). The fifth population (subject of our study) is located in the Eastern Gotland Basin, and is referred to as the Eastern Gotland population. The Eastern Gotland flounder population is located mainly in ICES Subdivision 28. Spawning takes place in March–April on the Western and Eastern slope of the Gotland Deep (Vitins, 1976, 1980). The egg

stage is relatively short (5–7 days, Hutchinson and Hawkins, 2004). After hatching larvae are transported mainly by wind driven drift to coastal areas, where metamorphosis occurs (Grauman, 1981). The nursery grounds of the Eastern Gotland flounder population are located on shallow sandy beaches or offshore banks (Florin et al., 2011; Nissling et al., 2007; Ustups et al., 2007; Vitins, 1989). Juveniles (0-group) usually appear in the nursery grounds in July (BIOR, unpublished data). 2.2. Ichthyoplankton sampling Regular ichthyoplankton sampling in the Eastern Gotland Basin was carried out by the Latvian Institute of Food Safety, Animal Health and Environment “BIOR” (and its predecessors) from 1970 to 2005 (Table 1). Surveys were executed each year between April and July. To target pelagic spawning flounder samples were collected in 13 ICES rectangles (Table 1) and a regular grid of stations was introduced in the early 1990s (Makarchouk, 1997). Sampling was performed in the whole water column with an IKS-80 ichthyoplankton net, with an opening of 0.5 m 2 and mesh size of 500 μm. Samples were conserved in 2.5% unbuffered formaldehyde solution with seawater and processed in the laboratory. The samples were analyzed in Bogorov trays under a microscope with a measuring scale (Rass and Kazanova, 1965). All flounder eggs and larvae caught were counted. Flounder eggs were identified according to Kazanova (1954). Flounder eggs are 1.1–1.43 mm in diameter, i.e. they are much smaller than the eggs of cod, but larger than those of dab. They have no oil drops (as those of rockling), and the yolk is unsegmented (as it is in sprat eggs). Flounder eggs are more transparent than other pelagic eggs in the Baltic Sea. The chorion is thicker than in eggs of dab, and rather big black pigments appear on the embryo. Larvae of flounder have a leaf-shaped body. Guts have loops; anteanal distance is 35–40%. There are a number of scattered melanophores concentrated along the ventral sides of the body (Kazanova, 1954). 2.3. Reproductive volume Flounder reproductive volume, i.e. the water body with suitable conditions for survival and development of flounder eggs (based on Plikshs et al., 1993), was calculated as the volume of water with salinity between 10.7 and 12 PSU and oxygen concentrations larger than 1 ml/l in the Eastern Gotland Basin. Hydrographic observations were taken from the ICES oceanographic database (www.ices.dk/ocean/INDEX. asp). To obtain sufficient spatial coverage, especially at the northern edge of the basin, the reproductive volume was estimated in bimonthly time-steps, resulting in three volume estimates (January/February, March/April, and May/June) for each year. For each two-month period the reproductive volume was calculated in three steps. First, we linearly interpolated salinity and oxygen measurements in each hydrographic profile to obtain estimates at all sampling horizons contained in the profile set. To reduce computation time, profiles located within 25 km

Table 1 Total amount of samples used in the study. Number of ichthyoplankton stations shows the amount of observations by ICES rectangles used in GLM models. Number of stations is presented in blocks of five years. Number of reproductive volume stations shows amount of hydrological stations used in reproductive volume calculations. Years

Ichthyoplankton Rectangle 41G8

1970–1974 1975–1979 1980–1984 1985–1989 1990–1994 1995–1999 2000–2004 Total

2 3 3 1 7 3 19

Total 41G9 16 16 15 17 11 13 12 100

41H0 8 12 12 6 6 9 53

42G8 8 1 1

7 5 22

42G9

42H0

43G9

43H0

44G9

44H0

44H1

45H0

45H1

12 4 6 14 8 15 12 71

14 9 9 17 10 14 12 85

12 5 6 3 7 12 10 55

14 12 16 18 9 13 12 94

9 3 2 2 1 4 4 25

13 12 11 15 5 9 10 75

2 9 8 8 5 2 3 37

10 9 10 16 4

8 10 6 8 4

49

36

120 101 105 131 70 102 92 721

Reproductive volume

246 242 291 658 486 209 86 2218

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distance of each other were replaced by their averages during the vertical interpolation step. We then interpolated the filled profile data horizontally on a regular grid to generate salinity and oxygen fields for each sampling horizon in the profile set. Next, we identified the water layer with suitable salinity and oxygen conditions for the development of flounder eggs in each grid cell and summed their volumes. A 4000×4000 depth grid of the Eastern Gotland Basin, based on a 1000×1000 m grid in ETRS-LAEA coordinates from the Baltic GIS Portal (http://gis.ekoi.lt/gis) was used for horizontal interpolations. Profile data were weighted according to the inverse of their squared distance to the grid cell location, using triple weights in west–east direction. In the analyses of egg distribution we used average reproductive volume from January to April, which included also the period before spawning, since the hydrological conditions before spawning determine the distribution of adult flounder. At the end of this period (in April) flounder eggs were recorded. The larval distribution was monitored until June. In July flounder metamorphosis occurred.

2.4. Water temperature Water temperature data from the central part of the Eastern Gotland Basin (station BY15, 57° 20′ 0″ N, 20° 03′ 0″ E, see Fig. 1) were used to represent temperature conditions in the study area. Temperature data were taken from the ICES oceanographic database (www.ices.dk/ocean/ INDEX.asp) and averaged for different water layers: 1) surface — 0 to 10 m (April–May), 2) above the halocline — 40 to 60 m (January– February) and 3) halocline temperature — 80–100 m (January– February). Flounder spawning takes place at the bottom, where after the fertilized eggs are pelagic and flounder larvae gradually migrate to the surface level. Therefore water temperatures in the halocline and above the halocline were tested to explain egg distribution, while surface temperature was used for larvae.

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2.5. Spawning stock biomass and recruitment Flounder spawning stock biomass of Eastern Gotland population from age-structured extended survivor analysis (XSA) was used to represent adult flounder abundance in the Central Baltic Sea (Gårdmark et al., 2007). Spawning stock biomass data were available from 1987 to 2004 (Fig. 2). Two time series were used to relate the abundance of planktonic flounder larvae to recruitment. The first recruitment series (abundance of 2 year old flounder in 1985–2003) was obtained from a flounder stock assessment (Gårdmark et al., 2007). The second estimate of recruitment success (abundance of 1 year old flounder in 1986–2003) was provided by the Latvian flounder juvenile survey on coastal nursery grounds (Vitins, 1989).

2.6. Egg and larval abundance modeling The original sampling data from 721 stations had a 9.7% and 20.3% prevalence of eggs and larvae, respectively. To reduce the zero inflation in the data we therefore aggregated the ichthyoplankton data by calculating mean abundance by month. Then we developed generalized additive models (GAM) to describe the effects of environmental conditions on egg and larval abundance. GAM (Hastie and Tibshirani, 1990) is a semi-parametric data analysis method that applies nonlinear smooth functions, usually in the form of regression splines, to describe the response of the target variable to one or several covariates. Similar to generalized linear models (GLM), which are the linear counterpart of GAM, GAM allows the use of categorical predictors in combination with continuous predictors. As in GLM, responses to all predictors are additive. GAM model fitting was done using the R package mgcv (Wood, 2006), which provides routines for optimum selection of the degree of smoothness of the regression splines. All predictor combinations were

45H0

45H1

44G9

44H0

44H1

43G9

43H0

42G8

42G9

42H0

41G8

41G9

41H0

Depth > 250 m 200 - 250 m 150 - 200 m 100 - 150 m 50 - 100 m 0 - 50 m

Fig. 1. Study area in the Eastern Gotland Basin with ICES statistical rectangles from which flounder egg and larvae data were used.

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1000 800 600 400 200 0

Suitable volume, km3

6000 2000 0

4000

SSB, tons

8000

10000

80

1970

1974

1978

1982

1986

1990

1994

1998

2002

Fig. 2. Temporal dynamics of flounder spawning stock biomass (line) and reproductive volume in the Eastern Gotland Basin. Bimonthly conditions during the first and second half of the year are depicted with black and light gray bars, respectively. Triangles mark years with major Baltic inflows.

tested to identify a final model composed of the best predictor set. Model selection was based on generalized cross-validation (GCV) in combination with predictor significance. The selected final models are presented in Table 2. As data were overdispersed (overdispersion coefficient 3.08 and 4.24 for eggs and larvae, respectively) and zero-inflated, a quasiPoisson distribution was applied. To improve linearity between the variables and to reduce the relationship between the mean and the variance, predictors were log transformed. Residuals were analyzed to test for departure from the model assumptions or other anomalies in the data or in the model fit using graphical methods (Cleveland, 1993). Prior to running the models, variance inflation factors were examined for both model sets to avoid the inclusion of variables with a high level of multicollinearity (VIF > 5, Zuur et al., 2007). Finally, model residuals were checked for normality using graphical methods. For the predictor variables, we focused on winter and spring data since they cover the most important period for flounder ichthyoplankton development. Separate models were built for eggs and larvae. The hypothesized predictors included in the egg model were: reproductive volume from January to April, wintertime water temperature in the halocline layer (January–February, 80–100 m), and above the halocline (January–February, 40–60 m), Eastern Gotland flounder population spawning stock biomass (SSB) and sampling month. To capture the gradient in proximity to the inflowing salt water, we included distance from the southern boundary of the Eastern Gotland Basin into the dataset. For the larval model the hypothesized predictors were reproductive volume from January to June, surface water temperature in spring (April–May, 0–10 m), flounder SSB, sampling month and distance from the southern basin boundary. Due to the limited length of the SSB time series, only the years 1987–2004 were used in the models. The sample size was 28 and 43 observations, for eggs and larvae, respectively. Finally, to test the Table 2 Finally selected generalized additive models relating flounder ichthyoplankton (egg and larvae) to spawning stock biomass and hydrological conditions. GCV — general cross-validation criterion. Model and predictors

P-value

GCV

Deviance explained

Egg model SSB

0.000002

0.0833

54.6

Larvae model Volume + SSB Volume (1970–2004)

0.006; 0.001 0.001

0.138 1.17

39.1 38.0

significance of reproductive volume alone for larvae during the entire sampling period, a GAM model was built for the years 1970–2005 (sample size — 87). 3. Results 3.1. Reproductive volume Flounder reproductive volume is driven by the temporal dynamics of saltwater inflows into the Baltic Sea (Fig. 2). During the 1970s, major Baltic inflows occurred frequently. Salinity and oxygen conditions in the southern part of the Eastern Gotland Basin were usually suitable for the development of flounder eggs and during most years suitable conditions occurred also in the central part of the basin. During this time period the suitable water layer was mostly located between 80 and 110 m water depth. Frequently suitable oxygen conditions extended deeper than the 12 PSU isohaline at which flounder eggs attain positive buoyancy, especially in the southern part of the basin. During these occasions salinity determined the lower boundary of the suitable spawning layer. Starting with a gap in inflows during the beginning of the 1980s, the Eastern Gotland Basin began to freshen. The suitable reproductive layer shifted to deeper parts of the water column and the reproductive volume started to decline. In the southern part of the basin now seafloor depth as well as declining oxygen concentrations in the bottom water determined the lower boundary of the reproductive layer, whereas in the deeper central basin now oxygen conditions almost permanently limited the extent of the reproductive layer. The reproductive volume decreased further during the late 1980s and beginning of 1990s, until the 1993 inflow reventilated the Eastern Gotland Basin. The 1993 inflow oxygenated the central part of the basin to the bottom and created salinity conditions at which flounder eggs were able to float between 100 and 190 m water depth. The increase in the total reproductive volume was only moderate though, because this depth range contributes only a small fraction of the total volume of the Eastern Gotland Basin. In addition, the 1993 inflow lifted the upper boundary of the spawning layer only slightly so that in the southern part of the basin seafloor depth still limited the flounder spawning volume. Finally, in 1995 already worsening oxygen conditions strongly reduced the suitable water layer in the Central Gotland Basin and starting from 1999, the Central Gotland Basin did not provide suitable conditions for the development of flounder eggs. Deteriorating oxygen conditions also limited the reproductive volume in the southern part of the basin. The subsequent major Baltic inflow in 2003 improved spawning conditions only in the southern part of the basin, while in the central basin

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the renewed water was more saline than is suitable for the development of flounder eggs. The spatial distribution of the reproductive volume in Gotland Basin was not equal. In the years with favorable hydrological conditions suitable areas cover all slopes of the Gotland Deep while in unfavorable years these conditions appear only in small areas or are totally absent (Fig. 3).

3.2. Abundance of flounder ichthyoplankton For egg abundance, only spawning stock biomass (SSB) was retained in the final model (Table 2). The model explained 54.6% of the total deviance in egg abundance. The response to increasing spawning stock biomass was positive and followed an asymptotic curve (Fig. 4a). For larval abundance, the final GAM model included spawning stock biomass (SSB) and reproductive volume (Table 2). The larvae model explained 39.1% of the total deviance. As expected,

a

81

larval abundance increased both with SSB and reproductive volume (Fig. 4b,c). Water temperature and distance to the southern basin boundary did not explain any significant variability in egg and larval abundance in the models. For the entire dataset (1970–2005), reproductive volume alone was used to predict larval abundance (Fig. 5). Larval abundance was positively related to reproductive volume and the model explained 38.0% of the total deviance (Table 2). GAM model estimate shows increase of larvae abundance if reproductive volume is higher than 100 km3. Distribution of the final models residuals did not violate the normality and homogeneity assumption. 3.3. Recruitment success Larvae data from the ichthyoplankton surveys were compared to recruitment estimates from XSA and the coastal flatfish juvenile survey to study the effect of larval supply on recruitment success (Fig. 6). For both time series, correlations were negative and nonsignificant (p = 0.33 and p = 0.64 for survey and XSA data, respectively). The recruitment estimates from the XSA (2 year old flounder) show a gradual increase from the beginning of the time series until 2002. No clear trend was observed in the juvenile data (1 year old flounder) from coastal areas. The two recruitment time series showed similar trends during the last five years, but they were not correlated (p = 0.74). 4. Discussion

Thickness (m) High : 50 Low : 0

b

Thickness (m) High : 50 Low : 0

Fig. 3. Spatial distribution of reproductive volume in Eastern Gotland Basin during (a) favorable (March–April 1976) and (b) less favorable (March–April 1995) hydrological conditions.

This study demonstrates that both SSB and reproductive volume are significant factors in determining flounder ichthyoplankton abundance in the Central Baltic, but that the effect of larval supply on recruitment seems to be weak. This information is valuable for the understanding of flounder ecology in the Baltic Sea, and for developing the management of the species. For flounder eggs, the best GAM model included only SSB, indicating that the dependence of eggs on hydrological conditions was not important. For larvae, the best model included both SSB and reproductive volume. The results show that both stock size and environmental conditions are involved in determining larval production of flounder. The analysis of the whole data series from 1970 shows that the reproductive volume explains a fair part of the total variation in larval abundance, underscoring the effect of the environmental conditions on larval supply. The most critical conditions for flounder spawning were found in the late 1980s. Reproductive volume was zero in 1988–1990 and in 2001. However, also in years with total absence of reproductive volume flounder ichthyoplankton was found in the Eastern Gotland Basin. This could be explained by hydrological as well as biological factors. The available hydrological data might not fully resolve the patchiness of oxygen and salinity conditions in the Eastern Gotland Basin, therefore underestimating reproductive volume. Alternatively, larvae could have drifted from coastal spawning populations (Florin et al., 2011), which has a significantly lower salinity threshold for reproductive success (5–7 PSU, Nissling et al., 2002) into the Eastern Gotland Basin. Finally, another explanation could be that flounder eggs might actually tolerate oxygen levels below 1 ml l − 1. In the years with low reproductive volume only the southern part of the Eastern Gotland Basin is suitable for flounder reproduction. Suitable conditions for reproduction in the northern part of the area were found only in a few years following major inflows. In the 1970s–1980s when the hydrological situation in the Baltic Sea was better (major inflows every third year) successful spawning in the northern area could be observed more often. Flounder spawning stock biomass (Gårdmark et al., 2007) had a significant influence on the abundance of both eggs and larvae. SSB was

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4

82

−2 −4

Effects on larvae

−6

2 1 −2

−10

−1

−8

0

Effects on eggs

3

0

2

4

a

0

7.8

8.0

8.2

8.4

8.6

8.8

1

9.0

2

3

4

5

6

Reproductive volume(log)

Spawning stock biomass(log)

Fig. 5. Response shapes in the GAM model for flounder larvae abundance for 1970–2005. The dashed lines are approximate 95% pointwise confidence intervals, tick marks show the location of observations along the variable range, y-axes represent the effects of the respective variable.

0

1

low in the beginning of the study period but increased over time. The highest estimates were observed in the last two years, 2004–2005. The effect of flounder SSB on eggs is asymptotic and almost linear on larvae. This result confirms the importance of keeping the spawning stock at a certain level by management. Our analysis did not include commercial landings of flounder. The total landings in SD 28 varied from 174 to 6455 tons in the study period (ICES, 2011). Highest landings occurred in the 1970s–1980s when the Soviet Union maintained a specialized flounder fishery. In the latest years of the study period there was only little specialized flounder fishing in the Eastern Gotland Basin and flounder is mainly a by-catch in the mixed fishery (together with cod) and partly as a target in recreational and sport fishery. The market price of flounder is relatively low and commercial landings of flounder indicate market capacity rather than a real trend in the population abundance. We used water temperature as an additional factor influencing flounder early stage development as it has been demonstrated for flatfish in

−2

−1

Effects on larvae

2

b

7.8

8.0

8.2

8.4

8.6

8.8

9.0

Spawning stock biomass(log)

0.4 0.3

Larvae

0.1

6

0.0

5

Larvae XSA recruitment Survey recruitment

0.2

80 60

Survey

40 4

20

3

0

2

10000

1

0

−2 0

0.5

100

40000

XSA

20000

30000

1 0 −1

Effects on larvae

2

c

Reproductive volume(log) Fig. 4. Response shapes in the final GAM models for flounder egg (a) and larvae (b, c) abundance. The dashed lines are approximate 95% pointwise confidence intervals, tick marks show the location of observations along the variable range, y-axes represent the effects of the respective variables.

1986

1990

1994

1998

2002

Year Fig. 6. Comparison of the temporal pattern of abundance of flounder larvae (Larvae) and recruitment. XSA recruitment was obtained from stock assessment. Survey recruitment was provided by the Latvian flounder juvenile survey on coastal nursery grounds.

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other areas (Chambers et al., 2001; Koubbi et al., 2006) and for other demersal fishes from the Baltic Sea (Hinrichsen et al., 2002; Koster et al., 2003; Plikshs et al., 1993). However, for the early stage development of Baltic Sea flounder information on temperature effects is lacking. Therefore we did not include temperature into the reproductive volume calculation but added it in the statistical models as separate continuous factor to investigate temperature impact on egg and larvae distribution. In contrast to previous studies on other species, we did not find a temperature effect on Baltic Sea flounder eggs and larvae. Climate change can be anticipated to have a negative impact on flounder recruitment in the Baltic Sea, as the combined effects of changes in temperature, precipitation and bottom water oxygen consumption will decrease the reproductive volume. An increase in precipitation and runoff according to forecasts for the Baltic watershed (Meier, 2006) together with a change in the seasonality of runoff, could reduce the frequency of major Baltic inflows (MacKenzie et al., 2007). In addition, higher water temperatures in winter in the western Baltic will also reduce oxygen concentrations because of the lower solubility of oxygen in warmer water flowing from the western Baltic to eastern Baltic deep basins during winter (Hinrichsen et al., 2002). Further, higher bottom water temperatures will increase organic matter degradation, accelerating nutrient cycling and bottom water oxygen consumption (Meier et al., 2011). Interestingly, no correlation between larval abundance and recruitment, measured as abundance of juveniles from XSA and juvenile surveys, could be found. This means that even though there is a clear effect of environmental conditions on larval supply, this does not seem to propagate and affect recruitment of the stock. This result suggests that recruitment may be regulated in a post-settlement stage, probably in the shallow coastal nursery areas. In light of the expected impairment of conditions for flounder reproduction with future climate change, the need for establishing a stock assessment as a basis for management of Baltic Sea flounder is increasing. Even though currently there is no correlation between larval supply and recruitment, a lower larval production in the future due to a smaller reproductive volume may give rise to such a relationship. The findings presented in this study, on the relationship between flounder reproduction, spawning stock biomass and reproductive volume, as well as the current lack of correlation to recruitment, can provide helpful information for a future stock assessment of Baltic Sea flounder. Acknowledgments This work was partly supported by Latvian National Research Program “Climate Change Impact on the Water Environment of Latvia”; ESF grant ESS2004/3; “Regime Shifts in the Baltic Sea Ecosystem— Modelling Complex Adaptive Ecosystems and Governance Implications” financed by the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS); project PREHAB, with funding from the European Community's Seventh Framework Programme (FP/2007–2013) under grant agreement no. 217246 made with the joint Baltic Sea research and development programme BONUS and The Swedish Research Council. We would like to thank the anonymous reviewers for their helpful comments. References Anon., 1978. Report of the working group on assessment of demersal stocks in the Baltic. ICES CM 1978/H:3, pp. 1–37. Beverton, R.J.H., 1995. Spatial limitation of population size; the concentration hypothesis. Netherlands Journal of Sea Research 34, 1–6. Cardinale, M., Arrhenius, F., 2000. The influence of stock structure and environmental conditions on the recruitment process of Baltic cod estimated using a generalized additive model. Canadian Journal of Fisheries and Aquatic Sciences 57, 2402–2409. Chambers, R.C., Witting, D.A., Lewis, S.J., 2001. Detecting critical periods in larval flatfish populations. Journal of Sea Research 45, 231–242. Cleveland, W.S., 1993. Visualizing Data. Hobart Press, Summit, NJ.

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