Development of a stressor index A wide range of Physical Lake Habitat Survey methods to describe the morphology and habitat complexity of lake shores exists, for example in Germany the HML [HydroMorphology Lakes] protocol developed by Ostendorp et al. (2004, 2008). This method is based on the classification of the naturalness of littoral and riparian structures in aerial photographs combined with field assessments. Similar methods have been also developed by the Ministry for Agriculture, Nature Conservation and Consumer Protection Mecklenburg-Vorpommern in Germany (Ministerium für Landwirtschaft, Naturschutz und Verbraucherschutz Mecklenburg-Vorpommern 2004) and in Italy by Xxxxxxxxx et al. (2010) (SFI = Lake Shorezone Functionality Index). In the UK, intensive research has been done to develop a Lake Habitat Survey (LHS) method (Xxxxx et al. 2004, 2005, 2006; Xxxxx 2008), analogous to the widely applied River Habitat Survey (RHS, Xxxxx et al. 1997, 1998a, 1998b, 2000). The LHS protocol is not based on aerial photographs, but covers an extensive array of environmental parameters that are assessed by field visits. The basic LHS protocol allows the calculation of the Lake Habitat Quality Assessment (LHQA) Score which assesses habitat diversity, physical structure and the presence of ecologically valuable habitats (Xxxxx et al. 2004, 2006). However, since the LHQA scores assign a value to the whole lake, Xx Xxxx & Irvine (2009) developed a sampling site-specific LHQA Score, the HabQA that is derived from 10 parameters at the sampling site (i.e. habplot in the terminology of the LHS manual) level in order to assess the single sites (for a detailed description see McGoff et al. 2009). The HabQA correlated well with taxa richness (Xxxxxxx correlation, r = 0.62), but its development was based on only one lake (Xxxxx Xxxxx in the Republic of Ireland) and hence required further testing. We tested the general suitability of the HabQA on 11 lakes in Germany and Denmark that were sampled within the WISER WP 3.3 and found a lower correlation with taxa richness (Xxxxxxxx Rank correlation, Rho = 0.4) than in the study of McGoff et al. (2009) (Xxxxx, Xxxxx and Gräwe unpublished results). Furthermore, several values of components of the HabQA differ from the data from Xxxxx Xxxxx. Xxxxx Xxxxx contains a high number and diversity of wetlands, whereas in the 11 German and Danish WISER lakes almost no wetlands occurred. Another parameter is the presence of a trash line that is more frequently present ...
