By applying second‐generation sequencing technologies to microsatellite genotyping, sequence information is produced which can result in high‐resolution population genetics analysis populations and increased replicability between runs and laboratories. In the present study, we establish an approach to study the genetic structure patterns of two European hedgehog species Erinaceaus europaeus and E. roumanicus . These species are usually associated with human settlements and are good models to study anthropogenic impacts on the genetic diversity of wild populations. The short sequence repeats genotyping by sequence (SSR‐GBS) method presented uses amplicon sequences to determine genotypes for which allelic variants can be defined according to both length and single nucleotide polymorphisms (SNPs). To evaluate whether complete sequence information improved genetic structure definition, we compared this information with datasets based solely on length information. We identified a total of 42 markers which were successfully amplified in both species. Overall, genotyping based on complete sequence information resulted in a higher number of alleles, as well as greater genetic diversity and differentiation between species. Additionally, the structure patterns were slightly clearer with a division between both species and some potential hybrids. There was some degree of genetic structure within species, although only in E. roumanicus was this related to geographical distance. The statistically significant results obtained by SSR‐GBS demonstrate that it is superior to electrophoresis‐based methods for SSR genotyping. Moreover, the greater reproducibility and throughput with lower effort which can be obtained with SSR‐GBS and the possibility to include degraded DNA into the analysis, allow for continued relevance of SSR markers during the genomic era.

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In this paper we study properties of the fundamental domain [Fscr ]β of number systems, which are defined in rings of integers of number fields. First we construct addition automata for these number systems. Since [Fscr ]β defines a tiling of the n-dimensional vector space, we ask, which tiles of this tiling ‘touch’ [Fscr ]β. It turns out that the set of these tiles can be described with help of an automaton, which can be constructed via an easy algorithm which starts with the above-mentioned addition automaton. The addition automaton is also useful in order to determine the box counting dimension of the boundary of [Fscr ]β. Since this boundary is a so-called graph-directed self-affine set, it is not possible to apply the general theory for the calculation of the box counting dimension of self similar sets. Thus we have to use direct methods.

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Von Bertalanffy proposed the differential equation m′(t) = p × m(t)a − q × m(t) for the description of the mass growth of animals as a function m(t) of time t. He suggested that the solution using the metabolic scaling exponent a = 2/3 (Von Bertalanffy growth function VBGF) would be universal for vertebrates. Several authors questioned universality, as for certain species other models would provide a better fit. This paper reconsiders this question. Based on 60 data sets from literature (37 about fish and 23 about non-fish species) it optimizes the model parameters, in particular the exponent 0 ≤ a < 1, so that the model curve achieves the best fit to the data. The main observation of the paper is the large variability in the exponent, which can vary over a very large range without affecting the fit to the data significantly, when the other parameters are also optimized. The paper explains this by differences in the data quality: variability is low for data from highly controlled experiments and high for natural data. Other deficiencies were biologically meaningless optimal parameter values or optimal parameter values attained on the boundary of the parameter region (indicating the possible need for a different model). Only 11 of the 60 data sets were free of such deficiencies and for them no universal exponent could be discerned.