作者: Armin Lorenz
DOI:
关键词: Multidimensional scaling 、 Drainage basin 、 Benthic zone 、 Geography 、 Sampling (statistics) 、 Fauna 、 Abundance (ecology) 、 Hydrology 、 Altitude 、 STREAMS
摘要: The present thesis analyses aquatic macroinvertebrates communities in terms of three main purposes: a stream typology for Germany, the possibility to assess hydromorphological degradation streams and variability applicability common sampling procedure. In first chapter benthic invertebrate samples from near-natural Germany were investigated distinguish types necessary taxonomic resolution typological questions. Non-metric Multidimensional Scaling (NMS) served define type groups. At genus level, located lowlands differ lower mountainous areas Alps. species Alps can be distinguished areas. Catchment size, altitude, geology slope sites formed major gradients different macroinvertebrate communities. Best discrimination resulted complete taxa lists, abundance data level resolution. second new Multimetric Index assessment mid-sized was developed, which focuses on impact fauna. development process system included (1) generation index (“German Fauna Index”), (2) selection faunal metrics, correlate (3) combination selected metrics into Index. “German Index” is based taxa, predominantly occur at certain morphological class. last deals with testing an “electronic subsampling technique” samples. It how strongly number individuals analysed influences results. For 152 (“reference samples”) 100 subsamples sizes 100, 200, 300, 500 700 generated randomly. general, metric results increases decreasing subsample size. Individual show sensitivity More than 40 % 100-individuals are classified quality class compared reference samples, but less 20 700-individual subsamples. A certainty > obtained size 300 lowland streams, whereas needed achieve same confidence mountain streams. Metrics, rely absolute abundances or classes higher changing depend relative abundances. Thus, reliability related type. These chapters lead synthesis German derived studies over mountains regions statistical proposed method.