Temporal development of coastal ecosystems in the Baltic Sea over the past two decades

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Polychlorinated dibenzo-<i>p</i>-dioxin, dibenzofuran and biophenyl content in selected groups of Baltic herring and sprat from Estonian coastal waters in 2006.

The concentrations of polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and dioxin-like polychlorinated biphenyls (DL-PCB) were determined in samples of Baltic herring (Clupea harengus membras) and sprat (Sprattus sprattus balticus) in 2006 from commercial catches in Estonian coastal waters, Baltic Sea. The dioxin content of the fish sampled in 2006 did not exceed the European Union's maximum permissible level for PCDD/Fs (4.0 pg WHO-TEQ/g fresh weight) and for the sum of PCDD/Fs and DL-PCBs (8.0 pg WHO-TEQ/g fresh weight). PCDD/Fs and the sum of PCDD/Fs and DL-PCBs content in herring were 2.12 and 3.84 pg WHO-TEQ/g of fresh weight respectively; the corresponding figures for sprat were 1.94 and 3.82 pg WHO-TEQ/g of fresh weight. Comparable with our earlier data on the content of dioxins in three to four year old herring and two to three year old sprat, these data show that two servings of fish per week are not at all harmful tothe health of the Estonian people; indeed, the opposite is more likely to be the case

Dual impact of temperature on growth and mortality of marine fish larvae in a shallow estuarine habitat

High individual growth and mortality rates of herring Clupea harengus membras and goby Pomatoschistus spp. larvae were observed in the estuarine habitat of the Gulf of Riga, Baltic Sea. Both instantaneous mortality (0.76–1.05) as well as growth rate (0.41–0.82 mm day-1) of larval herring were amongst highest observed elsewhere previously. Mortality rates of goby larvae were also high (0.57–1.05), while first ever data on growth rates were provided in this study (0.23–0.35 mm day-1). Our study also evidenced that higher growth rate of marine fish larvae did not result in lower mortalities. We suggest that high growth and mortality rates primarily resulted from a rapidly increasing and high (> 18 °C) water temperature that masked potential food-web effects. The explanation for observed patterns lies in the interactive manner temperature contributed: i) facilitating prey production, which supported high growth rate and decreased mortalities; ii) exceeding physiological thermal optimum of larvae, which resulted in decreased growth rate and generally high mortalities. Our investigation suggests that the projected climate warming may have significant effect on early life history stages of the dominating marine fish species inhabiting shallow estuarie

Feeding patterns of dominating small pelagic fish in the Gulf of Riga, Baltic Sea

We investigated the feeding of the dominant small pelagic fish—herring Clupea harengus membras and three-spined stickleback Gasterosteus aculeatus—in the Gulf of Riga (Baltic Sea) in the summers of 1999–2014. The share of empty stomachs, stomach fullness and taxonomic composition of fish diet was analysed. On average, large herring had the highest (19%) and small herring the lowest (6%) share of empty stomachs. Small (<1 mm) cladoceran Bosmina spp. was the most important prey for three-spined stickleback; preying on small (<1.5 mm) copepod Eurytemora affinis was the most efficient for small herring, while Bosmina spp. and E. affinis were equally important for the large herring, followed by the large (mean body length <2.0 mm) non-indigenous cladoceran Cercopagis pengoi. The number of prey taxa per stomach exhibited significant differences between the fish groups studied; the highest mean value was recorded for small herring and the lowest for three-spined stickleback (2.1 and 1.4 taxa, respectively). Although present, the fish group-specific spatial dynamics in feeding parameters (share of empty stomachs and feeding intensity) were weak compared to the observed interannual variation

Winter–spring climate effects on small-sized copepods in the coastal Baltic Sea

The general positive effect of warmer winters on the abundance of small-sized zooplankton in the following spring and early summer has been reported from different parts of the Baltic Sea, but the mechanism of this link is not clear. Although causal links cannot be deduced with confidence from observational data, sufficiently detailed analyses can nevertheless provide insights to the potential mechanisms. We present an example of such an analysis, scrutinizing the effects of winter and spring hydroclimate on the abundance of small-sized dominant calanoid copepods (Eurytemora affinis and Acartia spp.), using data from 2080 zooplankton samples collected over 55 years (1957–2012) from a shallow coastal habitat (Pärnu Bay, Gulf of Riga) in the Baltic Sea. Our results indicated that the milder winters brought about higher abundances, and reduced seasonality of small-sized copepods, whereas ambient sea surface temperature (SST) mostly affected the relative abundance of adult stages. The sliding window correlation tests revealed temporal shifts in the effects of controlling variables: with the continuous increase in SST, the effect of winter temperature on the abundance of Acartia spp. weakened. In contrast, E. affinis was consistently affected by SST, but the effect of winter temperature was more pronounced during the period of on average colder winters

Figure 3

<p>Long term dynamics of phenological variables as larval herring onset (a), timing of maximum abundance of herring larvae (b), larval herring retention time (c), timing of maximum abundance of <i>Eurytemora affinis</i> nauplii (d), timing of maximum abundance of <i>Eurytemora affinis</i> females (e), degree of mismatch between the timing of maximum abundance of herring larvae and <i>Eurytemora affinis</i> nauplii (f). Dotted lines indicate the position of the shift detected in single variables by shiftogram analyses. Empty dots denote the year when missing value replacement procedure was applied.</p

Figure 1

<p>The analysis algorithm (a) for the global approach by applying a PCA based on all variables and generating one shiftogram using the resulting PC1 only, (b) for the decomposed approach by applying three PCAs (one per each factor grouping) and thus generating three shiftograms based on the three resulting PC1's, (c) for the decomposed approach by additionally combining all PCs produced in (b) using multivariate regression and generating one shiftogram based on the predicted values of PC1 of the biotic PCs (see eq. 3).</p

Shiftogram based on Baltic Sea Index in winter.

<p>The vertical lines indicate the position of shift and abbrevations in the Y-axis are from the top: i) plot of the time series analysed (Indic.), ii) quality-of-fit plot (AICC), iii) empirical first order autocorrelation coefficient of the model residuals (AR(1)), iv) <i>p</i> value of the first order autocorrelation coefficient (p-A.), v) joint significance relating all parameters (p-joint), vi) power plot to indicate the risk of false no-warning (Power), vii) statistical test detecting the impulse like shift (p-im.), viii) statistical test detecting the break in slope (p-sl.), ix) statistical test detecting identical levels before and after the shock (p-le.), and x) statistical test detecting the variance before and after the shift (p-var.). For details please see the material and method section ‘<i>Constructing a shiftogram</i>’ or <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0091304#pone.0091304-Grger1" target="_blank">[24]</a></p

Description of time series.

<p>*Estonian Meterological and Hydrological Institute.</p><p>**p<0.01.</p><p>Description of the variables used in the current study. 1–7: hydroclimate, 8–13: phenology, 14–19: biota. Numbers before every particular category mean their aggregation for PCA analyses. For more detailed description of variables please see the material and methods.</p