Severe climatic changes during the Pleistocene shaped the distributions of temperate-adapted species. These species survived glaciations in classical southern refuges with more temperate climates, as well as in western and eastern peripheral Alpine temperate areas. We hypothesized that the European wildcat (Felis silvestris silvestris) populations currently distributed in Italy differentiated in, and expanded from two distinct glacial refuges, located in the southern Apennines and at the periphery of the eastern Alps. This hypothesis was tested by genotyping 235 presumed European wildcats using a panel of 35 domestic cat-derived microsatellites. To provide support and controls for the analyses, 17 know wildcat x domestic cat hybrids and 17 Sardinian wildcats (F. s. libyca) were included. Results of Bayesian clustering and landscape genetic analyses showed that European wildcats in Italy are genetically subdivided into three well-defined clusters corresponding to populations sampled in: (1) the eastern Alps, (2) the peninsular Apennines, and (3) the island of Sicily. Furthermore, the peninsular cluster is split into two subpopulations distributed on the eastern (Apennine mountains and hills) and western (Maremma hills and lowlands) sides of the Apennine ridge. Simulations indicated Alpine, peninsular, and Sicilian wildcats were isolated during the Last Glacial Maximum. Population subdivision in the peninsula cluster of central Italy arose as consequence of a more recent expansions of historically or ecologically distinct European wildcat subpopulations associated with distinct the Continental or Mediterranean habitats. This study identifies previously unknown European wildcat conservation units and supports a deep phylogeographical history for Italian wildcats.
In modern taxonomy, DNA barcoding is particularly useful where biometric parameters are difficult to determine or useless owing to the poor quality of samples. These situations are frequent in parasitology. Here, we present an integrated study, based on both DNA barcoding and morphological analysis, on cestodes belonging to the genus Taenia, for which biodiversity is still largely underestimated. In particular, we characterized cestodes from Italian wildcats (Felis silvestris silvestris), free-ranging domestic cats (Felis silvestris catus) and hybrids populations. Adult taeniids were collected by post-mortem examinations of the hosts and morphologically identified as Taenia taeniaeformis. We produced cox1 barcode sequences for all the analysed specimens, and we compared them with reference sequences of individuals belonging to the genus Taenia retrieved from GenBank. In order to evaluate the performance of a DNA barcoding approach to discriminate these parasites, the strength of correlation between species identification based on classical morphology and the molecular divergence of cox1 sequences was measured. Our study provides clear evidence that DNA barcoding is highly efficient to reveal the presence of cryptic lineages within already-described taeniid species. Indeed, we detected three well-defined molecular lineages within the whole panel of specimens morphologically identified as T. taeniaeformis. Two of these molecular groups were already identified by other authors and should be ranked at species level. The third molecular group encompasses only samples collected in Italy during this study, and it represents a third candidate species, still morphologically undescribed.
Although the behavioural ecology of the European wildcat (
The wildcat is an elusive species that is threatened with extinction in many areas of its European distribution. In Sicily the wildcat lives in a wide range of habitats; this study was done on Mount Etna. In 2006, after an exploration of the study area, we used camera traps with the aim of obtaining photographs of the wildcat. After this pilot study we used the experience and data collected to develop a protocol to provide an estimation of the density of the wildcat's population using capture-recapture analyses and the natural coat-marking system to recognize different specimens. We placed two trapping lines adjacent to each other that were run in two consecutive data collection periods. Camera traps worked together for 671 trap-days and we obtained 27 pictures of wildcats, from which we were able to determine 9 different specimens. Then we constructed the history capture of each individual and we used the software CAPTURE to generate an estimation of the density of our study area (0.93 ± 0.13 wildcat per 100 ha). This value is higher than those calculated in other studies: many possible events could determine this high density in the wildcat population.
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