Search

Aim To compare predictions of the habitat suitability model (HSM) for wolves Canis lupus in Poland with actual wolf distribution in western Poland after 15 years of recolonization. Location Western Poland (WPL, ca. 136,000 km2), west of the 18°48′E meridian. Methods Data on wolf occurrence (8,057 records) were gathered in 2001–2016. Wolf presence in 10 × 10 km cells was classified as follows: (1) permanent occurrence with reproduction, (2) permanent occurrence with no reproduction and (3) sporadic occurrence (interpreted as dispersing individuals). These cells were compared to all 10 × 10 km cells in WPL with respect to the probability of wolf occurrence as predicted by the HSM and habitat variables important for wolves. For temporal analysis, data were divided into two 8-year subsets: the initial and later phases of wolf recovery. Results Wolves were recorded in 259 cells (19.8% of the study area). The pairs and packs settled in areas predicted by the HSM to have good and very good habitat, in cells characterized by high forest cover and low densities of roads. Wolf groups that reproduced were found in the best-quality habitats characterized by denser forest cover and markedly lower shares of anthropogenic structures. Dispersing individuals were mostly recorded in unsuitable and suboptimal habitats, and they avoided both the poorest and the best habitats. In the initial phase of wolf recovery, cells selected by wolves for settling down and those used by dispersing wolves did not differ in their habitat parameters. However, in the later phase, as WPL became more saturated with wolf packs, dispersing individuals were recorded in less suitable habitats. Main conclusions The HSM for Polish wolves predicted with high accuracy the areas later occupied by wolf groups in the western part of the country. A similar approach may also be useful to predict the future distribution of wolves in the lowlands of central and western Europe where environmental conditions are comparable and recolonizing wolves originate from the same source population.

Following protection measures implemented since the 1970s, large carnivores are currently increasing in number and returning to areas from which they were absent for decades or even centuries. Monitoring programmes for these species rely extensively on non-invasive sampling and genotyping. However, attempts to connect results of such studies at larger spatial or temporal scales often suffer from the incompatibility of genetic markers implemented by researchers in different laboratories. This is particularly critical for long-distance dispersers, revealing the need for harmonized monitoring schemes that would enable the understanding of gene flow and dispersal dynamics. Based on a review of genetic studies on grey wolves Canis lupus from Europe, we provide an overview of the genetic markers currently in use, and identify opportunities and hurdles for studies based on continent-scale datasets. Our results highlight an urgent need for harmonization of methods to enable transnational research based on data that have already been collected, and to allow these data to be linked to material collected in the future. We suggest timely standardization of newly developed genotyping approaches, and propose that action is directed towards the establishment of shared single nucleotide polymorphism panels, next-generation sequencing of microsatellites, a common reference sample collection and an online database for data exchange. Enhanced cooperation among genetic researchers dealing with large carnivores in consortia would facilitate streamlining of methods, their faster and wider adoption, and production of results at the large spatial scales that ultimately matter for the conservation of these charismatic species.

The central-European population of wolves Canis lupus has its western border of contiguous range in eastern Poland. Protected since 1998, Polish wolves began to expand towards the west. Based on large-scale data on wolf abundance (2000–2006) and geographic information system (GIS) tools, we built a habitat suitability model (HSM) for the species in Poland. The best model, selected by the Akaike information criterion, of the resource selection function (RSF) by wolves included percentage cover of forests, meadows and marshes (positively correlated to wolf abundance) and road density (negatively correlated), and explained 53% of the total variation in the wolf abundance index in a 10 � 10 km cell grid. That RSF was then used to evaluate the whole country in terms of suitability for wolves. Potential wolf range appeared to consist of 24 patches of good habitat (predicted relative probability of wolf occurrence Z30%), including six patches already occupied and 17 new ones. In total, habitat suitable for wolves covers at least 20–24% of Poland, compared with 16% of the country’s area now occupied by the species. HSM was validated with historical data on wolf occurrence in 1950–2006. The areas selected by our model and those inhabited by wolves in at least one decade overlapped in 81–86%. Furthermore, the probability of wolf occurrence predicted by the model correlated positively with the number of decades the wolves were actually recorded in the area. Based on the empirical relationship between patch size and wolf numbers, we estimated that Poland could support a population of 1450–1540 wolves, two to three times larger than the current estimate. HSM needs to be supplemented with a GIS-based connectivity analysis among patches, which in turn should be validated by molecular genetics studies on dispersing wolves. Because of broadly similar geographic conditions, the model may be applicable to eastern Germany, Belarus Republic and the Baltic States (Lithuania, Latvia, Estonia).