| Abstract: | Empirical data sets of Artiodactyla (Antilocapridae, Bovidae, Cervidae, Suidae), Carnivora (Mustelidae) and Rodentia (Sciuridae, Cricetidae, Arvicolidae, Muridae), obtained by horizontal starch el electrophoresis of 15–34 isoenzyme sstems, were used to calculate genetic distances and to construct phylogenetic trees by the following methods: Nei's D (corrected for small sample sizes) - UPGMA, FITCH, KITSCH (out of Felsenstein's PHYLIP-package); Rogers -distance - distance-Wanger tree; maximum likelihood approach (cavalli -Sforza -Edwards ); maximum parsimony method (wagner ); Hennigian cladogram. The results were re-examined using the statisticar methods of jackknife and bootstrap. The following problems became apparent and were studied in more detail: inconstancy of molecular evolutionary rate among taxa, non-uniformity of evolutionary rate among isoenzymes, possible convergence of alloenzymes, different evolutionary histories of taxa (radiations/bottlenecks), methodological influences sample sizes / rare alleles, comparability of data sets). The results show, that many branches of the various phylogenetic trees are fairly constant. The ambiguous position of the remaining OTU's is due to insufficient evidence in the primary data rather than to theroperties of cluster algorithms. However, since these problematic cases are also uncertain in phylogenies based on morphological characters and palaeontological results, even an increased data set may not lead to a cyear decision unless additional taxa of crucial importance are examined. Molecular evolutionary rate among taxa seems to be accelerated in some cases, possibly due to random fixation of different alleles during bottlenecks, when a highly polymorpic ancestral form underwent a series of adaptive radiations. Isoenzymes can be divided into groups with different evolutionary rates. Thus, data sets are only comparable with respect to genetic variability and differentiation, when they contain a similar amount of representatives of each of these categories. |
