Abstract
INTRODUCTION The European Union Water Framework Directive aims at protecting, enhancing, and restoring all bodies of surface water with the ultimate aim of achieving good surface water status by 2015. In order to implement the directive, all member states have to assess the status of their coastal areas and develop or use existing classification systems to support future monitoring. Consequently, classification will be a key part of the implementation of the Directive (European Commission, 2000). It is known that aquatic ecosystems are complex mixtures of plants and animals. Aquatic systems may respond to variations in their physical, chemical, and biological environments in many very different ways because these assemblages typically include organisms with a wide range of physiological tolerances, feeding modes, and trophic interactions (e.g. Bonsdorff & Pearson, 1999; Kotta et al., 2008). This is also the reason why plant and animal assemblages are rarely similar between sites, and their interactions with prevailing physical, chemical, and biological environments determine their responses to human-induced stresses (Kotta et al., 2007; Veber et al., 2009; Lauringson et al., 2012). Classification systems seek to describe all these interactions and artificially divide the observed continua into discrete classes using statistical manipulations. While classification systems have considerable value as management concepts, it has to be remembered that they are at best an approximation of actual ecological quality (e.g. Southworth et al., 2004; Bolliger & Mladenoff, 2005). In the northeastern Baltic Sea, harsh environmental conditions result in a low number of benthic species (Bonsdorff & Pearson, 1999); nevertheless, these species can be considered very tolerant to various disturbances including anthropogenic stresses (Kotta et al., 2007, 2009). Thus, it becomes of utmost challenge to separate natural variability from human-induced changes that have occurred since the so-called pre-eutrophication era. In fact, benthic studies in the pre-eutrophication era are rare and often hampered by the lack of quantitative estimates (see also Kotta & Kotta, 1995; Eriksson et al., 1998; Kovtun et al., 2009). The extent to which the benthic life has deteriorated compared with the pre-eutrophication era is difficult to assess given the lack of comprehensive data sets. In this respect, the earlier documentation by A. Jarvekulg in the Central Databases of the Estonian Marine Institute provides a unique opportunity to compare the benthic macroinvertebrate communities over the last 50 years, and these data can be used to record the sensitivity values of zoobenthic taxa as well as to define the high quality status for zoobenthic communities. Biological water quality indices developed for the brackish water conditions raise the issue of the Estuarine Quality Paradox, as estuaries are naturally highly stressed environments and inhabited by stress-tolerant biota (Dauvin, 2007; Elliott & Quintino, 2007) that has to cope with both high natural loads of organic matter and decreased salinity. The most widely used biotic indices such as Marine Biotic Index (AMBI) and biological quality index (BQI) were developed for marine areas, and their use in brackish waterbodies has been found problematic in several cases (Borja et al., 2009; Munari & Mistri, 2010). The salinity in the Baltic Sea ranges from over 25 in the entrance to less than 1 in the innermost ends and represents the main large-scale structuring factor for benthic communities (Voipio, 1981). The salinity gradient has caused problems in using the Shannon diversity index (H'), AZTI's AMBI, and BQI in the more saline southern part of the Baltic Sea (Zettler et al., 2007), and problems were also encountered in using the AMBI in the less saline, very species-poor part of the sea (e.g. Perus et al., 2007). In the Baltic Sea, several modified approaches have been tested for the ecological quality assessment in recent years (Perus et al. …
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