The relative effects of increased seal predation, a 15% decline in salinity and increased fishing up to 0.9 on projected cod spawner biomass in 2089.

<p>The fractions represent the relative contributions to the decline in biomass that is expected to occur relative to the biomass estimated assuming low seal predation, unchanged salinity and fishing mortality at 0.3.</p

Temporal development of cod spawner biomass [<b>52</b>] (line), salinity in the deep layer of the Baltic Sea (>100 m in Landsort Deep; bars [<b>31</b>]) and grey seal abundance in the Baltic Sea (red circles )[<b>42</b>].

<p>Inset shows map of the Baltic Sea with ICES Subdivisions indicated.</p

Temporal development of the projected median cod spawner biomass in the eastern Baltic Sea for different combinations of forcings (exploitation, seal predation, climate change induced salinity decline).

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0018998#s2" target="_blank">Methods</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0018998#pone-0018998-t001" target="_blank">Table 1</a> for modelling details.</p

Scenarios employed to simulate cod population dynamics in the eastern Baltic Sea (ICES Subdivisions 25–32) during the 21^st century for different combinations of exploitation, salinity (as a consequence of expected climate change) and seal predation.

<p>The categories “low” for the seal predation rate refer to the present level of seal predation which is part of the overall natural mortality <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0018998#pone.0018998-ICES8" target="_blank">[37]</a>; i. e., no additional seal predation mortality was imposed on cod for these simulations. The seal predation category “increasing” refers to the increasing predation on cod from seals that occurs as the seal population increases during the 21^st century to its historical abundance level. This additional predation is added to other sources of natural mortality for cod. The long-term mean for salinity is for the period 1974–2006.</p

Cluster-tree combining most closely related variables estimated from scree test at Eigen values.

<p>Closest variable groups are indicated with the vertical line crossing the x-axis. In x-axis the proportion of variance explained within the formed single group is presented.</p

Monthly trade dynamics of the Baltic herring in Narva fish market.

<p>Expressed as a percentage of the total traded species raw biomass, for the years 1689, 1690, 1694 and 1695.</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

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

Amounts of locally consumed species (kg) traded by different ethnic groups in Narva (1694–1695).

<p>Amounts of locally consumed species (kg) traded by different ethnic groups in Narva (1694–1695).</p

Figure 4

<p>Long term dynamics of biotic variables as mean abundance of copepod <i>nauplii</i> (a), mean abundance of adult <i>Eurytemora affinis</i> (b), maximum abundance of female <i>Eurytemora affinis</i> and nauplii (c), number of herring recruitment (d), mean abundance of herring larvae (e). Dotted lines indicate the position of the shift detected in a single variables by shiftogram analyses. Empty dots denote the year when missing value replacement procedure was applied.</p