Baltic Sea (Central) - Ecology

This section is a modified excerpt from the ICES/HELCOM Working Group of Integrated Assessment of the Baltic Sea describing an integrated trend analysis of the state and dynamics of the Central Baltic Sea ecosystem (Diekmann and Möllmann 2010). The integrated analysis included 59 variables: 17 physical, 8 nutrient, 16 phytoplankton, 6 zooplankton, and 12 fish and fisheries related datasets. All data-series were compiled to one estimate per year and covered in maximum the period 1974 to 2007. An overview of the temporal changes of all Central Baltic Sea time series is presented in Fig. 1. Variables are sorted according to their first principle component (PC1) loadings of a principle component analysis (PCA), generating a pattern with variables at the top showing an increasing trend over time (green-red) with highest values in the recent 15 years, to variables at the bottom showing the opposite trend (red-green) with highest values in the late 1970s to early 1980s. The first group of variables comprises e.g. sprat, Acartia spp., T. longicornis, dinoflagellates and temperature measures. Decreasing values were found e.g. for cod and herring spawning stock biomass and recruitment, P. acuspes biomass, salinity measures and the magnitude of the maximum ice extend. Variables with less clear temporal trends are found in the centre of the plot, some of them showing relatively low values in the 1970s/1980s, high values between 1988 and 1993, and again low values afterwards. This group consists mainly of indicator time series related to nutrients and phytoplankton variables; for some of them measurements in the 1970s were missing, which might slightly negatively affect the respective sorting procedure.

The ordination of yearly measures by a standardised PCA resulted in 27.0 and 14.1% of explained variance on the first two Principal Components (PCs) (Fig. 2). Year scores of PC1 display a rapid change from positive to negative values in the early 1990s. The development of PC2 is characterized by a steady decrease until the early 1990s and a sharp increase afterwards. The two-dimensional phase-space (PC1 vs. PC2) demonstrates that changes in ecosystem states most likely occurred in 1987/88. This was confirmed by a sequential regime shift detection test (STARS) as well as by the results of chronological clustering. Both methods additionally identified a smaller shift in the early to mid-1980s, possibly caused by the sudden drop of herring and cod SSB and recruitment time series. This preceded the main shift that was detectable in the majority of all variables. Following the 1993 inflow event, a small shift was observed using STARS on PC2 scores. Since then the ecosystem state of the Central Baltic Sea remained rather stable and variable fluctuations were comparatively small.

The relative changes of the variables over time and in relation to the observed ecosystem shifts can be derived from the factor loadings on the first two principal components. PC1 mainly reflects temperature (high negative loadings on PC1, meaning an increasing trend over time) and salinity (high positive loadings on PC1, meaning a decreasing trend over time). Highest negative PC1 loadings of biotic time series were found for species known to have profited from the recent warming, e.g. sprat (MacKenzie and Köster 2004), Acartia spp. and T. longicornis (Möllmann et al. 2003) as well as Bornholm Basin dinoflagellates (Wasmund et al. 1998). In contrast, species which have suffered from the decrease in salinity, e.g. cod (Köster et al. 2005), P. acuspes (Möllmann et al. 2003) and herring (Möllmann et al. 2005) are negatively correlated to the previous group. Another factor that obviously contributed to the decline of the cod and herring stocks was the high fishing pressure (represented as the fishing mortality coefficient F). F-values for both species have highly negative loadings on PC1, while the biomass development of both stocks are negatively correlated to the fishing pressure and load positively on PC1. PC2 mainly reflects changes which occurred in the deep water, i.e. during the long stagnation period until 1993, which decreased deepwater salinity and oxygen saturation (high positive loadings on PC2). In contrast, deepwater nutrients increased in this period (high negative loadings on PC2). After the reversal of the conditions following the 1993 inflow, the same deepwater trends were observed until the recent inflow in 2003. Generally, the pronounced change in the late 1980s seems to be driven by an increase in temperature as a result of the change in atmospheric forcing reflected by increasing values of the BSI time series. It affected all ecosystem components and pushed the system into a new state. The smaller shift in 1993-94 was mainly due to deepwater related processes, changes in nutrient loadings (decrease in 1993) and increases in salinity and oxygen concentrations following the 1993 inflow event. It is thus more a shift in abiotic conditions rather than a change of the whole ecosystem.

Long-term performance (since the 1970s) of the state of different components of the Central Baltic Sea environment indicates that the state of eutrophication has considerably worsened since at least the early 1970s, and only marginal improvement in a few state indicators has been observed in recent years (Fig. 3). Despite a substantial reduction in riverine and direct point source inputs of nutrients since the 1990s, the overall status of eutrophication does not indicate a corresponding improvement. In contrast, evaluations of most of the indicators describing the status of hazardous substances have become more positive, despite unfavorable developments in residuals of some brominated and fluorinated compounds in biota. Long-term dynamics of indicators within the biodiversity segment were more variable and changes in the overall biodiversity status were therefore less conclusive. Some indicators displayed a consistently negative status over the decades studied (e.g., ringed seals); populations of several seabirds and also grey seal, which have suffered under heavy human impacts, have recovered with a several-fold increase in abundance, but several fish populations exhibited variable and species-specific patterns. Pressures that influence biodiversity were also variable. These pressures include different dynamics and levels of exploitation of fish populations, still high nutrient loads, and increased intensity of maritime transport, as well as reduced input of toxic pollution and general progress in nature protection (Ojaveer, Eero 2011).