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(2009): Ostsee-Makrozoobenthos Ostsee-Makrozoobenthos- Klassifizierungssystem für die Wasserrahmenrichtlinie Referenz-Artenlisten, Bewertungsmodell und Monitoring Auftraggeber: Universität Rostock Institut für Aquatische Ökologie 18051 Rostock Bearbeitung: MARILIM Gewässeruntersuchung Heinrich-Wöhlk-Straße 14 24232 Schönkirchen Dipl.-Biol. Th. Meyer, T. Berg, K. Fürhaupter 3. überarbeitete Fassung vom 20. Januar 2009 Leben wäre unerträglich, wenn Ereignisse zufällig und auf eine völlig unvorhersagbare Art und Weise eintreten würden. Andererseits wäre es uninteressant, wenn alles deterministisch und vollständig vorhersagbar wäre. Jedes Phänomen ist eine interessante Mischung aus beidem. Gerade diese macht das Leben kompliziert, aber nicht uninteressant Frei nach Jerzy Neyman (1894-1981) 1 Ostsee-Makrozoobenthos – Klassifizierungssytem MARILIM Gewässeruntersuchung 2 Inhaltsverzeichnis 1 Overview 4 2 Einleitung 7 3 Grundlagen 8 3.1 Summarischer Überblick über das Bewertungsmodell . 8 3.2 Modularität des Bewertungsmodells . 9 3.3 Ökologisches Prinzip . 9 3.4 Grundsätzliche Probleme einer ökologischen Bewertung . 11 4 Typologie 12 4.1 Wassertypen und Wasserkörper . 12 4.2 Bewertungseinheiten . 12 5 Referenzartenlisten 15 5.1 Salzgehalt . 15 5.2 Substrat . 17 5.3 Zonierung . 17 5.4 Unterscheidung zwischen inneren und äußeren Gewässern . 17 5.5 Taxonomisch schwierige Taxa . 18 5.6 Überschneidungen in Referenzlisten . 20 6 Das Bewertungsmodell 21 6.1 Die Bewertungsindizes . 21 6.1.1 Artenvielfalt . 21 6.1.2 Abundanz . 27 6.1.3 Störungsempfindliche Taxa . 33 6.1.4 Tolerante Taxa . 39 6.2 Zusammensetzung zum MarBIT-Index . 43 6.2.1 Normierung der Klassen . 43 6.2.2 Ableitung des MarBIT-Index . 44 7 Interkalibrierung 46 7.1 Arten-Sensitivitäten . 46 7.2 Der dänische WRRL-Index . 46 7.2.1 Verhalten des dänischen Index . 47 7.2.2 Vergleich des dänischen Index mit MarBIT . 48 8 Monitoring 52 8.1 Richtlinien des Monitorings . 52 8.1.1 Räumliche Auflösung . 52 8.1.2 Vertikale Auflösung . 53 8.1.3 Zeitliche Auflösung . 54 8.1.4 Definition und Trennung der Habitate . 54 8.2 Bewertung der Wasserkörper mit MarBIT . 56 8.2.1 Habitatdominanzen . 56 8.2.2 Verschneidung der Bewertungen der Habitate . 57 8.2.3 Korrektur der Bewertung für unbesiedelte Bereiche . 59 8.2.4 Häufigkeit der Bewertungen . 60 Ostsee-Makrozoobenthos – Klassifizierungssytem MARILIM Gewässeruntersuchung 3 8.2.5 Verbleibende Probleme . 60 8.3 Praktische Probenahme . 61 8.3.1 Technik und Geräte . 61 8.3.2 Zu erfassende Parameter . 62 8.4 Taxonomie und Qualitätssicherung . 63 8.4.1 Taxonomische Auflösung . 64 8.4.2 Taxonomische Literatur . 64 8.5 Steckbriefe und Vorschlagsliste . 70 8.5.1 Innerste Gewässer . 71 8.5.2 Innere Gewässer . 72 8.5.3 Mittlere Gewässer . 74 8.5.4 Rügensche Gewässer . 75 8.5.5 Flussmündungen . 76 8.5.6 Buchten . 78 8.5.7 Darß bis Polen . 79 8.5.8 Mecklenburger Bucht . 81 8.5.9 Kieler Bucht . 82 8.5.10 Becken . 84 8.5.11 Flensburger Außenförde . 86 9 Literatur 87 A Referenzartenlisten 91 B Ökologische Literatur 125 Ostsee-Makrozoobenthos – Klassifizierungssytem MARILIM Gewässeruntersuchung 4 1 Overview MarBIT is a multi-metric assessment system to rate the biological quality of macrozoobenthos communities in the German part of the Baltic Sea according to the requirements of the Water Framework Directive (WFD). The assessment system is based solely on ecological principles and gives an assessment according to the four metrics or criteria defined by the WFD: fauna composition, abundance, proportion of taxa sensitive to disturbance, and proportion of taxa that are pollution indicators. The approach uses a classification scheme with five classes, type or water body specific reference conditions, and is applicable to all habitats. The system defined three habitats: soft bottom, phytal, and hard bottom. Reference conditions The reference conditions are based on the available knowledge on the autecology of the species living in the Baltic coastal communities. This knowledge was taken from an extensive review of scientific literature and both recent and historical monitoring data. All data have been verified and stored in a database uniformly. The environmental abiotic parameters along the German Baltic coast cover a very wide ran- ge of values. For example, salinity ranges from nearly zero in the inner waters to around 20 at the border to Denmark. Therefore a set of parameters is defined for each water body, that re- presents the range of abiotic parameters within the specified area. These parameters are mainly salinity, exposure, water depth, and substrate/habitat. Some areas require further restricting parameters to be fully defined. Subsequently, all taxa will be included in the reference species lists, when their autecology falls within the pre-defined ranges for the water bodies. Using this modelling approach, there are no artefacts from historical data sets or expert judgement. The method The fundamental principle of the assessment system is the fact that biological sy- stems increase in complexity when they develop normally. On the other hand, disturbance from human activities reduces complexity. The four WFD metrics for the assessment of the ecological status are used to measure this complexity and thus give an estimation of the complexity as a substitue for the ecological status. This is the ecological endpoint used in the MarBIT system. Each of the four WFD metrics is represented by a separate index in the MarBIT system. Each index results in an estimation of the ecological status with respect to this metric alone and to the specific endpoint. The system is designed to minimise interference and redundancy of the metrics. Further, the indices try to use a maximum of information from the sample data. Most traditional indices work on aggregated sample information, like number of species, total abundance, or total biomass. This leads to a loss of information before the index is applied. The MarBIT system preserves information as long as possible by using indices that utilize the distribution of sample values over the given range. As an example, the calculation for the the index for fauna composition does not only take the number of species into account but also their taxonomical relationships. Fauna composition Fauna composition is assessed using the newly developed taxonomic spread index (TSI). It works on the presence/absence of taxa from the reference species lists. Basically, all taxa found in a sample constitute a taxonomic tree where the species and higher taxonomic levels are related to each other. Starting from 0, each taxon present in a sample will increase the index value, if the taxon generates a new branch in the taxonomic tree. Thus, the TSI correlates with the number of taxa present. The amount, by which the index increases, de- pends on the taxonomic level of the corresponding taxon. A higher taxonomic level results in a larger addition. This calculation method means that the maximum value, the TSI can reach for Ostsee-Makrozoobenthos – Klassifizierungssytem MARILIM Gewässeruntersuchung 5 a sample is the TSI value of the reference species list, while the minimum value is 0 when no taxa are present. Higher taxonomic levels contribute a higher amount to the index because they normally mean the addition of a different functional group. These groups add more ecological value to the fauna community than just another species of the same genus, that shares most characteristics of the sibling taxa already present. Abundance The abundance is assessed utilizing the distribution of the individual abundance values from the sampled taxa. For a benthic community that is controlled by a large amount of factors with a similar influence and no dominating factor, the abundances of the species tend to follow a log-normal distribution. This distribution is the reference value. The index is calculated as the amount by which the sample data derive from the log-normal model. This is done using the Lilliefors statistical test. Sensitive taxa Taxa from the reference species lists that are sensitive to disturbance or polluti- on are identified using their known autecology. The proportion of these taxa with respect to the complete reference taxa list designates the reference conditions. The sensitive taxa are among the first to undergo a decline when environmental conditions worsen, because they have fe- west abilities to adapt to these changes quickly. Therefore a lesser fraction of sensitive taxa in the sample compared to the reference species list results in a lower index value. Derived from the normative definitions of the WFD for sensitive taxa, different fraction ranges are assigned to the various status classes. Tolerant taxa Taxa from the reference species lists that are tolerant to disturbance or pollution are identified using their known autecology. The proportion of these taxa with respect to the complete reference taxa list designates the reference conditions. The tolerant taxa are the most abundant species along the German Baltic Coast and are present everywhere. They are capable of adapting to bad or changing environmental conditions quickly. A higher fraction of tolerant taxa in a sample compared to the reference conditions leads to a lower index value. Again, the class boundaries are derived from the normative definitions of the WFD. Deriving the EQR Each of the four described indices yields a separate index value. Before deriving the EQR, these values are transformed to a standardised range from 0 to 1. This is done using a piecewise linear transformation and makes the indices comparable. After the transfor- mation all four indices have values between 0 and 1 and their class boundaries are normalised to 0, 0.2, 0.4, 0.6, 0.8, and 1 thus forming equally large classes. At this stage, all four ecological endpoints can be compared with each other and their various contributions to the EQR can be clearly seen. It is possible to deduce all ecological implications at this point. For the WFD reporting, one EQR value is needed. This is taken from the four individual in- dices by calculating the median value of the transformed indices.
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