Individual dispersal and population genetics of the alpine longhorn beetle Rosalia alpina inhabiting Magura National Park, Poland

Individual dispersal and population genetics of the alpine longhorn beetle Rosalia alpina inhabiting Magura National Park, Poland | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Individual dispersal and population genetics of the alpine longhorn beetle Rosalia alpina inhabiting Magura National Park, Poland Józef J. Różański, Damian Nowak, Konrad Krasoń, Jarosław Sochacki, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9424736/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract This study focused on the individual dispersal ability and population genetics of the alpine longhorn beetle, Rosalia alpina , in Magura National Park (MNP), Carpathians, southeastern Poland. Populations of this valuable and highly endangered saproxylic beetle are in severe decline worldwide. One of the main causes of this phenomenon is the degradation and fragmentation of the species’ natural habitat, which is thought to result in inbreeding within local populations and consequently limit their genetic diversity. The methods employed in the study included radiotelemetry and a mark-and-recapture technique to investigate dispersal ability, as well as genetic analyses to assess the genetic status of the local beetle population. The study showed that alpine beetles dispersed at most 845 meters, with most recaptured individuals found within 30 meters of their marking site. These results indicate that alpine beetles generally travel short distances, and under certain conditions may not migrate at all. Genetic studies indicate that the low dispersal ability of R. alpina in MNP corresponds with a relatively high inbreeding coefficient and a low effective population size. Despite this, the population shows a panmictic structure, with gene flow occurring among sampling sites across the park. A comparison with a Slovak population studied in 2013 shows that the Magura National Park population exhibits higher genetic variability, highlighting its importance as a reservoir of genetic diversity and the need for strong conservation measures. dispersal genetics population decline population health Rosalia alpina Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction The highly endangered Alpine longhorn beetle, Rosalia alpina , which has an IUCN status of vulnerable (VU), is considered a flagship beetle species (Di Nicola and Poloni 2021 ) and is widely recognized as an icon of European saproxylic biodiversity (Drag et al. 2011 ). It is also listed in Annexes II and IV of the Habitats Directive (Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora; Campanaro et al. 2017 ), as well as in the Red List of Saproxylic Beetles in Europe (Cálix et al. 2018 ; Lachat et al. 2013 ). Rosalia alpina is a large longhorn beetle belonging to the order Coleoptera and the family Cerambycidae (Campanaro et al. 2017 ). Its most characteristic feature is its coloration pattern, which includes a blue background with up to six black spots on the elytra and one on the pronotum, the shape and size of which are individually specific. This trait is believed to play a role in effective camouflage against the background, as well as in thermoregulation (Kostić et al. 2016 ; Pavlović et al. 2018 ). The coloration pattern also facilitates ecological studies of this species, as individual identification is essential for analyzing population size, dispersal, habitat preferences, and behavior (Caci et al. 2013 ). Another characteristic feature of R . alpina is its antennae, the length of which represents the most reliable indicator of sexual dimorphism: in males, the antennae are significantly longer than the body, whereas in females they are only slightly longer than the body (Michalcewicz and Ciach 2012a ; Campanaro et al. 2017 ). Rosalia alpina is one of the key saproxylic invertebrates inhabiting Magura National Park in the Polish Carpathians. Its presence is closely associated with the availability of dead wood in forest ecosystems, as the species spends most of its life – both egg and larval stages – within decaying wood (Campanaro et al. 2017 ). The beetle predominantly develops in European beech Fagus sylvatica (Cizek et al. 2009 ; Castro et al. 2013 ; Castro and Fernández 2016; Drag et al. 2018 ), but it has also been recorded in wych elm Ulmus glabra (Ciach et al. 2007 ; Michalcewicz et al. 2011 ), European ash Fraxinus excelsior (Michalcewicz and Ciach 2012b ), and sycamore Acer pseudoplatanus (Michalcewicz et al. 2013 ). Other host tree species include hornbeam, lime, chestnut, walnut, and oak. Habitat preferences of R. alpina appear to vary across its geographical range (Russo et al. 2011 ; Bosso et al. 2013 ; Ciach and Michalcewicz 2014 ). R. alpina is widely regarded as an indicator of forest habitat quality, particularly in beech-dominated forests. Since the body size of xylophagous beetles is influenced by host tree species as well as the quantity and quality of breeding material, biometric traits of adult R. alpina may serve as reliable indicators of both the attractiveness of breeding substrates and overall habitat quality (Michalcewicz and Ciach 2012a ). Aside from its intrinsic value and its contribution to biological diversity, the protection of the Alpine longhorn beetle is necessary due to the collapse in its population size and distribution within the country (Adamski et al. 2013 ). It is believed that the historical range of the beetle coincided with that of the common beech, covering a significant part of Poland (Michalcewicz and Ciach 2015 ). This range has progressively shrunk, as inferred from data on the species’ distribution in the 20th century. Earlier reports indicate that the beetle was present in the Carpathians, the Holy Cross Mountains, Roztocze, and isolated lowland sites in the northern and western parts of the country (Michalcewicz and Ciach 2015 ). As a result of this contraction, the species is now found only in isolated sites in the Carpathians (Michalcewicz and Ciach 2015 ). The species is not only disappearing in Poland; similar population declines have been observed in other parts of Europe (Campanaro et al. 2017 ; Bosso et al. 2018 ). The main cause of the beetle’s decline is the loss and fragmentation of its natural habitat. In many parts of its range, the species is now restricted to small patches of broadleaf mountain forests rich in senescent trees and abundant decaying wood (Campanaro et al. 2017 ). Previous studies indicate that most areas suitable for the occurrence of R. alpina are not protected (Bosso et al. 2013 , 2018 ). The loss of dead wood in forests and year-round forest management, including activities conducted during the insect’s mating season, may also contribute to population decline. Beech trees harvested and stored in wood stacks from June to July are readily colonized by Alpine longhorn beetles, which lay eggs in this material. As a result, wood stacks become ecological traps, since the colonized wood is subsequently removed for processing, thereby nullifying the insects’ reproductive efforts (Adamski et al. 2016 ). Consequently, attempts are being made to improve the population status of the Alpine longhorn beetle and other saproxylic beetles in Europe, with particular attention given to the Carpathian Mountain Range (Mirea et al. 2021 ). However, these actions appear insufficient, as the declining population trend persists. Therefore, it is essential to expand and update knowledge on the biology and ecology of this beetle in order to enhance active conservation efforts for this highly valuable insect. There is still limited knowledge regarding the species’ dispersal capabilities, the effects of habitat fragmentation on population isolation, and the level of genetic variability across its range. So far these aspects have been studied in only a few populations (Drag et al. 2013, 2015 ; Molfini et al. 2018 ). Understanding the environmental requirements of the Alpine longhorn beetle, the spatial range of individual movements and population genetic structure is essential for planning active conservation measures and for designating protected areas, such as Magura National Park, one of the species’ most important strongholds in Poland. Material and Methods Study site Studies were conducted in Beskid Niski, in southeastern Poland, within Magura National Park (MNP). 95% of the MNP area is covered with forests, while only 5% consists of meadows. Two altitudinal zones are present in Magura NP: the lowland zone (up to 550 m a.s.l.) and the lower montane zone (up to 846 m a.s.l.). The main forest type in the park is the Dentario glandulosae–Fagetum forest, dominated by European beech Fagus sylvatica and, secondarily, silver fir Abies alba . Geologically, MNP is composed of sedimentary rocks, specifically conglomerates, sandstones, and clay shales, forming part of the Carpathian Flysch Belt. The climate of MNP is transitional between continental and Atlantic types. Between 2009 and 2019, annual temperatures ranged from 6.2°C to 7.3°C, while total annual precipitation ranged between 800 and 900 mm during this period (Różański et al. 2019). Genetic structure The first part of the research aimed to conduct genetic analyses to assess the genetic structure and diversity of the Alpine longhorn beetle population inhabiting Magura National Park. In the initial stage, during fieldwork carried out in the summer of 2023, genetic material was collected from 104 individuals of R. alpina across twelve study sites within the park (Fig. 1). Genetic material was collected from 101 living individuals and 3 deceased specimens. The samples were subsequently transported to the Museum and Institute of Zoology of the Polish Academy of Sciences in Warsaw for genetic analysis. Isolation was performed using the Insect DNA Tissue Kit (Macherey-Nagel). Genomic DNA was extracted from a small fragment of leg tissue collected from 104 Rosalia alpina individuals. Multiplex PCR amplifications were performed in a 10 µl reaction volume using the Multiplex PCR Master Mix (Qiagen), containing 1× Master Mix, 0.2 µM of each primer, and approximately 20 ng of template DNA. Thermal cycling conditions were as follows: an initial activation step at 95 °C for 15 min; 45 cycles of denaturation at 94 °C for 30 s, annealing at 54 °C for 90 s, and extension at 72 °C for 60 s; followed by a final extension at 72°C for 10 min. Sequencing was performed on an Applied Biosystems 3500 XL sequencer, and genotypes were analyzed using GeneMapper software (Applied Biosystems). All individuals were genotyped at eight loci using microsatellite markers developed by Drag et al. (2015). The RA08 locus was excluded due to consistent amplification failure across all samples. Microsatellite loci were amplified in two multiplex PCR reactions, with Multiplex 1 including loci RA11 (HEX), RA13 (HEX), RA28 (HEX), RA29 (FAM), and RA37 (HEX), and Multiplex 2 comprising loci RA15 (TAMRA), RA23 (ROX), and RA40 (FAM). Genotyping was successful for 98 individuals. The obtained results were analyzed at two levels: for the population as a whole (N = 98) and subdivided into 12 groups based on the location of individual capture (‘B’ – Baranie Stack of Wood, ‘BW’ – Baranie Elm, ‘C’ – Ciechania, ‘G’ – Grab, ‘H’ – Hałbów, ‘HK’ – Huta Krempska, ‘J’ – Jaworze, ‘K’ – Krempna, ‘KO’ – Kolanin, ‘N’ – Nieznajowa, ‘P’ – Polany, ‘S’ – Słodkie). Due to the small size of four groups (‘HK’, ‘N’, ‘K’, and ‘G’), some analyses – particularly those sensitive to unequal sample sizes – were performed on the eight largest groups. Whether the population met the assumptions of Hardy–Weinberg equilibrium was tested using Genepop on the Web 4.7 (Raymond and Rousset 1995; Rousset 2008). Basic population parameters – such as the number of alleles, number of private alleles, expected and observed heterozygosity, and genetic distances – were calculated using GenAlEx 6.5 (Peakall and Smouse 2006, 2012) and FSTAT v.2.9.4 (Goudet 1995, 2001). Genetic distances between groups were also calculated in FSTAT v.2.9.4, and the significance of differences was tested using permutation tests with Bonferroni correction for multiple comparisons. Bayesian clustering analysis was performed in Structure 2.3.4 (Pritchard et al. 2000; Hubisz et al. 2009), testing the division of the studied population into clusters ranging from K = 1 to K = 15 with 10 replicates. The analysis used 100,000 Markov chain Monte Carlo (MCMC) iterations, with 50,000 iterations after burn-in, applying the “loci prior” option and excluding the four smallest groups. The results were subsequently analyzed in StructureSelector (Li and Liu 2018) to determine the optimal number of clusters using the Evanno method and to visualize the averaged Bayesian results. Principal Coordinate Analysis (PCoA) based on genetic distances was conducted in GenAlEx 6.5, including all groups. Signs of population bottlenecks were assessed using Bottleneck 1.2.02 (Piry et al. 1999) for the population as a whole, and effective population size was estimated using LDNE (Waples and Do 2008), considering only alleles with a frequency above 0.02. Relatedness among individuals, calculated using the DyadML coefficient, was computed in COANCESTRY (Wang 2011) and visualized in plots divided by groups. Dispersal data collection The part of the research on dispersal ability was conducted during the four summer seasons; between 24 June and 22 August 2022, 4 July and 22 August 2023, 15 June and 2 August 2024, and 25 June and 12 August 2025, depending on the annual activity of R. alpina . Fieldwork was carried out between 10 a.m. and 2 p.m. The dispersal abilities of the Alpine longhorn beetle were studied by using two methods: radio telemetry and individual visual marking (Fig. 2). The radio telemetry method involved equipping selected individuals with ultra-light transmitters that emitted a radio signal (Fig. 3). During fieldwork, the locations of the insects were monitored and tracked using radio receivers. The lightest available transmitters (ATS T15 Tiny Transmitter), weighing approximately 0.15 g, were used and ten individuals were marked by using this method. Telemetry marking had not previously been attempted on the Alpine longhorn beetle, so the research was experimental in nature and the outcomes were unpredictable. The study clearly indicated a strong impact of the transmitters on the dispersal abilities of the marked individuals. Two of the three tagged beetles did not fly at all, and the transmitters were subsequently removed from their pronota. One particularly large individual made several efforts to fly with the transmitter attached, but on each occasion it descended directly to the ground, landing after only a few meters. Subsequently, this individual intentionally removed the transmitter by pressing it against peeling bark, which resulted in partial removal of the cuticle on the pronotum. Consequently, further attempts to use the telemetry method were abandoned. Given that the main objective of the research was to determine dispersal parameters, telemetry marking was discontinued, and the focus shifted primarily to an alternative mark–recapture method involving the use of colored markers (Fig. 2). In this method, a distinct set of colors was assigned to each marking location, and the exact position (using GPS) and sex of each individual were recorded. A total of 752 individuals participated in the study, and the majority were marked across all study locations (Fig. 1) using permanent markers (Tobby, Grand, and UniPaint). When marking was unsuccessful, individuals were identified based on the individual-specific spot pattern on the elytra and pronotum. Each individual was photographed to facilitate this identification. To analyze individual dispersal, the distance between the marking site and the subsequent recapture location was measured. Observations of beetles recorded multiple times on the same day within 30 meters of a previous observation were excluded from the analysis. The main study site for this part of the research was the “Baranie Stack of Wood,” where observations were conducted in all four years (2022–2025). The primary objective at this location was to determine whether timber stacks might attract R. alpina and limit its dispersal abilities. In 2022, the study was conducted exclusively at this site. Additionally, between 2023 and 2025, the area surrounding the “Baranie Stack of Wood,” as well as other locations within the MNP (Fig. 1), was surveyed to track beetle movement. Due to logistical constraints, data collection – except at the “Baranie Stack of Wood” site, which was visited regularly throughout the entire R. alpina activity season – was not systematic. Instead, it focused on opportunistic observations aimed at estimating the flight distances of beetles in the vicinity of each individual’s initial sighting. Based on the recorded distances, an inverse power function (IPF) was calculated separately for each sex. Only individuals that moved at least 30 m were included in the analysis. The function describes the probability (I) of movement over a distance D as I=C⋅D −n (1) . The function was fitted by regressing the natural logarithms of the cumulative fractions of individuals moving a given or greater distance (ln I) against the linearized distance expression, i.e., lnC−n⋅(lnD). The functions were fitted separately for males and females, and differences between the slopes and intercepts of the fitted functions were subsequently tested (Zar 1996; Drag et al. 2011). Differences between the two sexes were also examined using the Mann–Whitney U test. All calculations were performed using Microsoft Excel and PAST 3.2. All these studies were conducted as part of the conservation activities of Magura National Park, with permission obtained from the Minister of Climate and Environment of Poland. Results Genetic structure Out of the 104 individuals of Rosalia alpina , 98 were successfully genotyped. For the remaining individuals, either no readings were obtained or readings were obtained for fewer than four microsatellite loci. All individuals included in the genetic study are listed in the supplementary materials (Online Resource 1). The number of alleles at the analyzed loci ranged from 5 to 8 (mean 5.750 ± 0.412). The mean number of effective alleles was 2.347 ± 0.262, which results from the fact that, in many cases, alleles occurred at very low frequencies. All loci showed observed heterozygosity lower than expected and a relatively high degree of inbreeding. The mean observed heterozygosity for the entire population was 0.401 ± 0.071, while the expected heterozygosity was 0.518 ± 0.073. The inbreeding coefficient was 0.274 ± 0.060. Individual groups exhibited similar levels of genetic variation (Tab. 1). The highest number of private alleles was observed in the ‘B’ group. The groups ‘S’ and ‘H’ showed the lowest allelic richness. The groups ‘P’ and ‘S’ had the lowest mean inbreeding coefficients. The population was found not to be in Hardy–Weinberg equilibrium (p < 0.0001). Bayesian clustering analysis showed that the population is genetically uniform in terms of structure. Despite the formal support for two-cluster senario (K = 2) when considering model‐selection criteria (e.g., ΔK and Puechmaille estimators), the Q‐matrix (Fig. 4) shows extensive admixture and highly similar ancestry proportions across all sampling sites. There is no clear population‐level separation into two discrete genetic groups; instead, one cluster dominates with only a minor contribution of the second cluster. Principal coordinates analysis (PCoA) indicated some heterogeneity within the studied population that is not related to spatial structure. Genetic distances between the groups were very low and not statistically significant. Only the genetic distance between the ‘P’ and ‘C’ was statistically significant and slightly higher, although it remained low (0.12; Tab. 2). This pattern is also reflected in the PCoA results (Fig. 5), where most individuals from ‘C’ (pink diamonds) are located on the right side of the plot, while most individuals from ‘P’ (brown triangles) are located on the left side. The estimated effective population size was 181 individuals, with a 95% confidence interval of 80.1–7094.5. No signs of a population bottleneck were detected. The expected number of loci showing an excess of heterozygosity relative to the number of alleles was 4.74, whereas only one locus exhibited heterozygosity excess. In contrast, seven loci showed a statistically significant heterozygosity deficit relative to the number of alleles, which was highly significant (Wilcoxon test, p < 0.004). Relatedness among individuals within the studied groups was relatively high, as illustrated in the diagrams, where highly related individuals are marked in red (Fig. 6A–H). Most of the studied groups contained several pairs of highly related individuals. Dispersal ability Given current technological capabilities, the tested telemetry method proved ineffective for determining the dispersal of the species and was therefore replaced by a visual marking method using colored markers, which provided the expected results. Using this method, 752 individuals from various locations within Magura National Park (Fig. 1) were identified, and the sex was determined for 748 of them. All individuals included in the dispersal study, along with their first and subsequent observations and the distances from their previous locations, are listed in the supplementary materials (Online Resource 1). Throughout all years of the study, the number of males significantly exceeded that of females (Fig. 7), and in total it constituted 68,4% of the identified individuals. There was interannual variation in the probability of recapturing individuals, ranging from 16.9% in 2024 to 31.9% in 2022 (Tab. 3). Most recaptured individuals (approximately 88.7%) had not moved more than 30 m. Some individuals remained in the same location and were recaptured repeatedly. At the “Baranie Stack of Wood” site, one individual was recorded 13 times between 29 July and 13 August 2023. Two others were each recorded 10 times at this site: the first between 3 and 22 August 2022, and the second between 21 July and 11 August 2023. In the forest, one individual was documented five times within a 30 m radius between 31 July and 8 August 2023, followed by other individuals, which were observed three to four times each within the same radius. The maximum recorded dispersal distance for a single individual (female) was 845 m, followed by 428 m for two individuals (one male and one female) and 325 m for another individual (male). In general, the proportion of dispersing beetles decreased with increasing distance (Fig. 8). There was no significant difference in dispersal distance between males and females (P = 0.51, Mann-Whitney U test). The average distances between individuals included in the analysis were 147.4 meters for males (N = 11) and 196.9 meters for females (N = 8). The median distance was 55 meters for both males (N = 11) and females (N = 8). The IPF function showed identical probabilities of movement beyond 100 m for both sexes, but differences increased with distance (Tab. 4). The probability of movement over a distance of 500 m was almost twice as high in females as in males (Tab. 4), with females exhibited higher mobility than males, reaching nearly twice the maximum dispersal distance (Fig. 8). Discussion The MNP population appears to be panmictic, indicating gene flow among the sampling locations (Wright 1978 ; Hartl and Clark 2007 ). This is supported by both the low and statistically non-significant F ST genetic distances between groups from different localities and the Bayesian clustering analysis conducted in STRUCTURE (Pritchard et al. 2000 ; Evanno et al. 2005 ), which detected no genetic structure within the population. Principal Coordinates Analysis (PCoA) based on genetic distances among individuals revealed a small cluster of individuals and a few outliers that are somewhat distinct from the rest of the population; however, this pattern is not related to sampling locations (Gower 1966 ; Legendre and Legendre 2012 ) and does not indicate spatial structure. The most likely explanation is that these individuals carry alleles at very low frequencies, as private alleles were present in some groups despite the lack of significant genetic differentiation among them. Importantly, relatedness within localities was relatively high, and most sampling groups contained multiple closely related pairs. This pattern is consistent with localized breeding aggregations embedded within a broader panmictic framework – a configuration that can maintain apparent homogeneity while simultaneously elevating inbreeding risk at the microspatial scale. The Rosalia alpina population in Magura National Park (MNP) exhibits a moderate level of genetic variability. Observed heterozygosity was lower than expected, and the inbreeding coefficient was relatively high. However, bottleneck tests provided no evidence of a recent drastic population decline. Interestingly, results concerning the relationship between observed alleles and heterozygosity – a statistically significant heterozygosity deficit relative to the number of observed alleles – may even suggest that the population is currently in an expansion phase. This interpretation is indirectly supported by the observed departure from Hardy–Weinberg equilibrium, although the pattern could also be influenced by factors such as asymmetric gene flow or other ecological processes. Under mutation–drift models (IAM/TPM), such a pattern may reflect recent demographic expansion following a historically reduced effective size, during which rare alleles accumulate faster than heterozygosity approaches equilibrium. Thus, the absence of a bottleneck signal should not be interpreted as demographic stability but rather as an indication that a population decline, if it occurred, may fall outside the temporal detection window of heterozygosity-based tests. While expansion of the Alpine longhorn beetle into lowland areas has been observed in Central Europe, Drag et al. ( 2015 ) documented a significant decline in genetic diversity with increasing latitude. The estimated effective population size of R. alpina was relatively low, amounting to 181 individuals, with a wide upper confidence limit (7,095), reflecting statistical uncertainty rather than demographic security. By comparison, the protected scarab beetle Cheirotonus formosanus , which also exhibits significant inbreeding, has an estimated effective population size exceeding 20,000 individuals (Huang et al. 2024 ). Although direct interspecific comparisons should be interpreted cautiously, this contrast highlights the demographic vulnerability of the MNP population. Compared to results from the Slovak population (Drag et al. 2013), where 45 individuals were analyzed, the MNP population exhibits higher genetic variability in terms of allele number, allelic richness, and heterozygosity. This suggests that the population in MNP represents a valuable reservoir of genetic diversity for the species, which warrants conservation. It is also important to consider that, due to insect life-history strategies – such as high reproductive capacity and rapid generation turnover – habitat fragmentation may affect population structure and observed genetic variability only after a considerable time lag. Consequently, endangered insect species may not immediately exhibit drastic signs of reduced genetic variability (Webster et al. 2023 ). In this context, the results are not entirely encouraging, as the observed level of genetic variability in the studied population is moderate and the effective population size is relatively low. However, the absence of evidence for a population bottleneck should not be interpreted as a justification for reducing conservation efforts for local R. alpina populations, both in Magura National Park and in the surrounding areas of the Beskid Niski. Due to the ineffectiveness of the telemetry method, a mark–recapture approach was employed in our study, as it is considered an effective way to obtain quantitative population data necessary for assessing the conservation status of protected species, including beetles (Rossi de Gasperis 2017). With respect to individual dispersal abilities, the maximum observed dispersal distance in our study was 845 meters, which is approximately half of the longest recorded movement for Rosalia alpina (1,628 meters) observed in the Czech Republic (Drag et al. 2011 ). In both cases, the greatest distances were recorded for females; however, overall, no statistically significant difference in total dispersal distances between the sexes was detected. It is worth noting that both in our study and that of Drag et al. ( 2011 ), females exhibited lower recapture rates than males. Several explanations may account for this pattern. First, behavioral differences between the sexes are likely important: males are more active and move more frequently between trees, whereas females are able to copulate and begin oviposition shortly after emerging from the wood (Drag et al. 2011 ). Additionally, males tend to have a longer residence time in the population (up to approximately 24 days) compared to females (approximately 15 days), which increases their probability of recapture (Drag et al. 2011 ). Finally, males of Rosalia alpina produce aggregation pheromones that attract both sexes, making them focal points of interactions within the population (Žunič Kosi et al. 2017 ). As a result, males may be more exposed and therefore more likely to be detected and recaptured. Our results, as demonstrated by the IPF function, indicating a higher probability of long-distance movement in females, are also consistent with the findings of Drag et al. ( 2011 ). The observation that some individuals were recorded multiple times at the same location suggests that certain individuals may exhibit only minimal movement, which further supports the results indicating a relatively high inbreeding coefficient within the population inhabiting Magura National Park. This pattern was particularly evident at the “Baranie Stack of Wood” site, suggesting that wood stacks may function as a form of ecological traps for beetles, as proposed in previous studies (Adamski et al. 2016 ). It is worth noting, however, that at the “Baranie Stack of Wood” site, the wood is placed solely for R. alpina and is not removed afterward. The spatial data collected allow for the determination of the maximum distances traveled by the beetles, which, when combined with knowledge of the species' biology, enables the assessment of their dispersal capacities and, consequently, the potential for population recovery in the event of significant habitat improvement, particularly in regions affected by habitat fragmentation. Conclusion At the genetic level, the Rosalia alpina population in Magura National Park is characterized by only moderate genetic variability and a relatively low effective population size. Although no signal of a recent bottleneck was detected, the combination of reduced observed heterozygosity, elevated inbreeding, and limited Ne suggests a demographically persistent but genetically vulnerable population. The absence of a strong spatial genetic structure indicates ongoing gene flow at the scale studied; however, the elevated relatedness within localities points to microspatial kin clustering, which may increase the risk of inbreeding over time in studied subpopulations. Functional dispersal capacity appears to be strongly constrained. Most individuals moved no more than 30 m, and the maximum recorded distance (845 m) represents an extreme movement rather than a typical movement. Such limited routine dispersal reduces the likelihood of effective recolonization and may restrict genetic rescue in increasingly fragmented landscapes. Although occasional long-distance movements may facilitate gene flow, they are unlikely to fully counterbalance the effects of habitat isolation on genetic structure. Taken together, these findings suggest that the population is not currently collapsing but may be operating close to a threshold at which genetic erosion could accumulate. Therefore, apparent demographic persistence should not be equated with long-term resilience. Maintaining habitat continuity and preventing further habitat fragmentation in the Beskid Niski region will be critical for preserving the genetic diversity and evolutionary potential of R . alpina population. Declarations Acknowledgements We are grateful to the PGE Polish Energy Group S.A. Foundation for funding the portion of this research concerning population genetics and the use of telemetry to study the dispersal abilities of R. alpina in Magura National Park. Author contributions Józef J. Różański: Conceptualization; Methodology; Investigation – genetic and dispersal data collection; Data curation; Analysis – dispersal data analysis; Writing – original draft preparation, review & editing; Visualization – Figures 2, 3, 7, and 8, Table 3. Damian Nowak: Funding acquisition; Conceptualization; Methodology; Investigation – genetic and dispersal data collection; Writing – review & editing. Konrad Krasoń: Investigation – genetic and dispersal data collection; Analysis – dispersal data analysis; Writing – review & editing; Visualization – Figure 1, Table 4. Jarosław Sochacki: Conceptualization; Methodology; Investigation – genetic and dispersal data collection; Writing – review & editing. Agnieszka Gancarz: Investigation – dispersal data collection; Writing – review & editing. Waldemar Wojtas: Investigation – dispersal data collection; Writing – review & editing. Magdalena Witek: Conceptualization; Methodology; Data curation; Analysis – genetic and dispersal data analysis; Writing – review & editing. Anna Sztencel-Jabłonka: Conceptualization; Methodology; Data curation; Analysis – genetic data analysis; Writing – review & editing; Visualization – Figures 4, 5, and 6, Tables 1 and 2. Funding This research was partially funded by the PGE Polish Energy Group S.A. Foundation. Data availability All data supporting the findings of this study are included in the article and its Supplementary Material. Competing interests The authors declare no competing interests. Orcid Józef J. Różański, https://orcid. org/0000-0001-9484-560X Anna Sztencel-Jabłonka, https://orcid.org/0000-0002-7374-2190 Magdalena Witek, https://orcid.org/0000-0002-6172-8981 References Adamski P, Bohdan A, Michalcewicz J, Ciach M, Witkowski Z (2016) Timber stacks: potential ecological traps for an endangered saproxylic beetle, the Rosalia alpina . J Insect Conserv 20:1099-1105. 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PLoS ONE 12(8): e0183279. https://doi.org/10.1371/journal.pone.0183279 Tables Tab. 1 Genetic variation in individual groups from different locations. N – sample size; Na – mean number of alleles; PA – number of private alleles; AR – mean allelic richness after rarefaction to the smallest sample size; Ho – mean observed heterozygosity; He – mean expected heterozygosity; F – mean inbreeding coefficient. Group (location): ‘B’ – Baranie Stack of Wood, ‘BW’ –Baranie Elm, ‘C’ – Ciechania, ‘H’ – Hałbów, ‘J’ – Jaworze, ‘KO’ – Kolanin, ‘P’ – Polany, ‘S’ – Słodkie Group (Location) N Na PA AR Ho He F B 19 3.625 6 3.21 0.395 0.550 0.260 BW 11 3.375 2 2.67 0.390 0.492 0.250 J 9 2.750 2.94 0.355 0.441 0.275 KO 10 3.125 1 3.75 0.412 0.505 0.187 C 10 3.250 3.21 0.383 0.459 0.196 S 11 3.250 2 1.88 0.409 0.468 0.088 P 11 2.625 3.71 0.376 0.419 0.093 H 10 3.375 2 1.75 0.450 0.501 0.130 Tab. 2 Genetic F ST distances between groups (locations). Statistically significant results are indicated in bold (p < 0.0018, 560 permutations). Groups (locations): ‘B’ – Baranie Stack of Wood, ‘BW’ – Baranie Elm, ‘C’ – Ciechania, ‘H’ – Hałbów, ‘J’ – Jaworze, ‘KO’ – Kolanin, ‘P’ – Polany, ‘S’ – Słodkie B BW J KO C S P H B 0.00 0.00 0.02 0.01 0.04 0.03 0.03 0.00 BW 0.00 0.04 0.01 0.04 0.01 0.06 0.03 J 0.00 0.00 0.07 0.01 0.00 0.00 KO 0.00 0.03 0.01 0.04 0.02 C 0.00 0.03 0.12 0.06 S 0.00 0.05 0.01 P 0.00 0.00 H 0.00 Tab. 3 Number of R. alpina individuals identified and recaptured during the dispersal study (2022–2025) in Magura National Park. Year Individuals identified (n) Recaptures (n) Individuals recaptured (n) Individuals recaptured (%) 2022 182 140 58 31,9 134♂ 48♀ 126♂ 14♀ 53♂ 5♀ 39.6♂ 10.4♀ 2023 200 95 38 19,0 131♂ 69♀ 83♂ 12♀ 29♂ 9♀ 22.1♂ 13.0♀ 2024 207 59 35 16,9 152♂ 53♀ 54♂ 5♀ 32♂ 3♀ 21.1♂ 5.7♀ 2025 163 61 37 22,7 95♂ 66♀ 49♂ 12♀ 28♂ 9♀ 29.5♂ 13.6♀ Total 752 355 168 22,3 512♂ 236♀ 312♂ 43♀ 142♂ 26♀ 27.7♂ 11.0♀ Individuals identified (n) – all individuals recorded during the study, including both marked individuals and those recognized based on spot patterns; Recaptures (n) – total number of recapture events, including multiple recaptures of the same individuals; Individuals recaptured (n) – total number of individuals that were recaptured at least once; Individuals recaptured (%) – percentage of individuals that were recaptured Tab. 4 Results of fitting the inverse power function (IPF) to movements of the Rosalia longicorn and predicted probability of movements to 100 m, 300 m, 500 m. N♂ = 11; N♀ = 8 sex IPF: ln I= ln C (+/- S.E) – n (+/- S.E.)*ln D R 2 100 (m) 300 (m) 500 (m) Max dist (m) ♂ ln I= -2.83 (+/- 0.25)-0.95(+/-0.25)*lnD 0.95 0.53 0.19 0.11 428 ♀ ln I=-2.06(+/-0.42)-0.62(+/-0.26)*lnD 0.99 0.53 0.27 0.20 845 Additional Declarations No competing interests reported. Supplementary Files OnlineResource1.xlsx Online Resource 1 Complete dataset listing all individuals participating in the study, including the first and subsequent observations of each insect, as well as the distance from the previous location. In the first four sections, where alpine longhorn beetles are labeled R. a., these beetles are from the ‘Baranie Stack of Wood’ location. * indicates alpine longhorn beetles from which genetic material was obtained for the study Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 12 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 17 Apr, 2026 Submission checks completed at journal 17 Apr, 2026 First submitted to journal 15 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9424736","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626393595,"identity":"1e9ddadc-a28f-46e6-a6fd-a22040dad893","order_by":0,"name":"Józef J. Różański","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACxgYIbcDGDmVJMIMpCyK08BxA0SJB0DYDBokEBmS1uLUwzz58+MPPHXXGfJKvEz9+bbtnL9nOe+wB4w7cWhj70hIMe88cNmOTzt0sLdtWnDibmS/dgPEMHi09PAYJvG0HbIBaNkhLtiUkyDHzmEkwtuHXcvBvW50Nm+TZzb+BWuyJ0WLYzNvGbMYmwbtN8mNbAuNswlrYkpll2w4bs/HkbrNmOJeQOLOZL00iEY9fDHuYD39821ZnOL/97OabP8oS7CXOnz0m8XGHDW4tDUgcZh4wBSQTG7AphgB5FFf+gGmBJYpRMApGwSgYBUAAAD77SreDMh5vAAAAAElFTkSuQmCC","orcid":"","institution":"Magura National Park","correspondingAuthor":true,"prefix":"","firstName":"Józef","middleName":"J.","lastName":"Różański","suffix":""},{"id":626393596,"identity":"3bfb51f0-cb1f-46c9-9dc0-135897ceb142","order_by":1,"name":"Damian Nowak","email":"","orcid":"","institution":"Magura National Park","correspondingAuthor":false,"prefix":"","firstName":"Damian","middleName":"","lastName":"Nowak","suffix":""},{"id":626393597,"identity":"4188c87c-04fb-41f3-93c3-380f20cef094","order_by":2,"name":"Konrad Krasoń","email":"","orcid":"","institution":"Magura National Park","correspondingAuthor":false,"prefix":"","firstName":"Konrad","middleName":"","lastName":"Krasoń","suffix":""},{"id":626393598,"identity":"99e7c27e-4c15-45c0-815a-a05a9633396a","order_by":3,"name":"Jarosław Sochacki","email":"","orcid":"","institution":"Magura National Park","correspondingAuthor":false,"prefix":"","firstName":"Jarosław","middleName":"","lastName":"Sochacki","suffix":""},{"id":626393599,"identity":"2a0d02fb-7e47-47a4-9606-264da9ff34b8","order_by":4,"name":"Agnieszka Gancarz","email":"","orcid":"","institution":"Magura National Park","correspondingAuthor":false,"prefix":"","firstName":"Agnieszka","middleName":"","lastName":"Gancarz","suffix":""},{"id":626393600,"identity":"346f67f1-5a6e-4dac-819c-19890fc44c1f","order_by":5,"name":"Waldemar Wojtas","email":"","orcid":"","institution":"Magura National Park","correspondingAuthor":false,"prefix":"","firstName":"Waldemar","middleName":"","lastName":"Wojtas","suffix":""},{"id":626393601,"identity":"38ed3088-c596-48ef-8e22-1125e1bcebf5","order_by":6,"name":"Magdalena Witek","email":"","orcid":"","institution":"Museum and Institute of Zoology","correspondingAuthor":false,"prefix":"","firstName":"Magdalena","middleName":"","lastName":"Witek","suffix":""},{"id":626393602,"identity":"b9ad5307-6687-417a-b9df-fb15e5f77e2c","order_by":7,"name":"Anna Sztencel-Jabłonka","email":"","orcid":"","institution":"Museum and Institute of Zoology","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Sztencel-Jabłonka","suffix":""}],"badges":[],"createdAt":"2026-04-15 09:47:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9424736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9424736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108023461,"identity":"bd9d1f41-9e4c-4dfc-95ab-6c8d6ea77a6b","added_by":"auto","created_at":"2026-04-28 14:49:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":511487,"visible":true,"origin":"","legend":"\u003cp\u003e\u0026nbsp;See image above for figure legend.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/c0eaaee384bc4440af0f8e37.png"},{"id":108181161,"identity":"92fe022c-897c-4dc7-9451-e7c1c70b85bc","added_by":"auto","created_at":"2026-04-30 08:58:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1690254,"visible":true,"origin":"","legend":"\u003cp\u003eA male alpine longhorn beetle \u003cem\u003eRosalia alpina\u003c/em\u003emarked with a color marker. Photo J.J. Różański\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/a03899f31870026d65990734.png"},{"id":108023462,"identity":"f51cf0c9-01cc-4d06-bf48-66ec92e95dcf","added_by":"auto","created_at":"2026-04-28 14:49:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":910557,"visible":true,"origin":"","legend":"\u003cp\u003eA male alpine longhorn beetle \u003cem\u003eRosalia alpina\u003c/em\u003e tagged with a radiotelemetry transmitter. This method proved ineffective due to the size of the transmitter, despite it being the smallest available on the market. Photo J.J. Różański\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/16a44a4c3108a49eb7511f9b.png"},{"id":108181446,"identity":"cbe4c02b-7380-4ceb-808a-677d7d9107ee","added_by":"auto","created_at":"2026-04-30 08:58:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":12515,"visible":true,"origin":"","legend":"\u003cp\u003eSTRUCTURE assignment (Q) bar plot for two-cluster scenario (K = 2). Each vertical bar represents an individual, and the colored segments indicate the estimated proportions of assignment (Q) to the two inferred genetic clusters. Individuals are grouped by sampling site. 1 –‘B’, 2 – ‘BW’, 3 – ‘C’, 4 – ‘H’, 5 – ‘J’, 6 – ‘KO’, 7 – ‘P’, 8 – ‘S’\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/e33326b3f3072ade4b5553cd.png"},{"id":108023465,"identity":"f856f719-6f01-47fc-9e48-dc033b0a2ac3","added_by":"auto","created_at":"2026-04-28 14:49:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":29814,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Coordinates Analysis (PCoA) of individuals based on genetic distances. Letters denote the locations where DNA samples were collected. ‘B’ – Baranie Stack of Wood, ‘BW’ – Baranie Elm, ‘C’ – Ciechania, ‘G’ – Grab, ‘H’ – Hałbów, ‘HK’ – Huta Krempska, ‘J’ – Jaworze, ‘K’ – Krempna, ‘KO’ – Kolanin, ‘N’ – Nieznajowa, ‘P’ – Polany, \u003cbr\u003e\n‘S’ – Słodkie\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/d5968a8593c49fcce6a72d44.png"},{"id":108023469,"identity":"b45faf4e-fbed-4190-976d-5077bb37358c","added_by":"auto","created_at":"2026-04-28 14:49:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":390463,"visible":true,"origin":"","legend":"\u003cp\u003eDegree of relatedness among individuals in the: \u003cstrong\u003eA)\u003c/strong\u003e‘B’ group, \u003cstrong\u003eB)\u003c/strong\u003e ‘BW’ group, \u003cstrong\u003eC)\u003c/strong\u003e ‘C’ group, \u003cstrong\u003eD)\u003c/strong\u003e ‘P’ group, \u003cstrong\u003eE)\u003c/strong\u003e‘KO’ group, \u003cstrong\u003eF)\u003c/strong\u003e ‘J’ group, \u003cstrong\u003eG)\u003c/strong\u003e ‘H’ group, \u003cstrong\u003eH)\u003c/strong\u003e ‘S’ group\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/c73d3a186a9191800be6c861.png"},{"id":108181203,"identity":"38b29bc4-7035-47f2-b73e-308258ec5650","added_by":"auto","created_at":"2026-04-30 08:58:23","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":81554,"visible":true,"origin":"","legend":"\u003cp\u003eDemography of \u003cem\u003eR. alpina\u003c/em\u003e in Magura National Park across successive study years (2022–2025), as well as for all years combined\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/e61f53d7627baf6c589ebfb4.png"},{"id":108181400,"identity":"462a3016-20cb-4099-88ac-f099dcd7dfc1","added_by":"auto","created_at":"2026-04-30 08:58:36","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":302529,"visible":true,"origin":"","legend":"\u003cp\u003eDispersal distances (m) of individual \u003cem\u003eR. alpina\u003c/em\u003e recaptured during the study (2022–2025) in Magura National Park, shown separately for males (♂) and females (♀). Bars represent the percentage of dispersing individuals at a given distance: \u003cstrong\u003eA)\u003c/strong\u003erelative to all recaptures (N = 352); \u003cstrong\u003eB\u003c/strong\u003e) relative to all recaptured individuals (N = 171)\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/fbfd9314b0e1b8ba880cc2ec.png"},{"id":109249342,"identity":"2a30429a-d3cd-4d33-9b52-5e33152813da","added_by":"auto","created_at":"2026-05-14 08:48:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4788485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/b7a8079c-134d-485e-a16d-9072f40a8009.pdf"},{"id":108181377,"identity":"de7d3ea1-cf45-4e2d-a2f0-6275443c9237","added_by":"auto","created_at":"2026-04-30 08:58:35","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":157782,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOnline Resource 1 \u003c/strong\u003eComplete dataset listing all individuals participating in the study, including the first and subsequent observations of each insect, as well as the distance from the previous location. In the first four sections, where alpine longhorn beetles are labeled R. a., these beetles are from the ‘Baranie Stack of Wood’ location. * indicates alpine longhorn beetles from which genetic material was obtained for the study\u003c/p\u003e","description":"","filename":"OnlineResource1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9424736/v1/e03ccfb5240acb5cfab9da42.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Individual dispersal and population genetics of the alpine longhorn beetle Rosalia alpina inhabiting Magura National Park, Poland","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe highly endangered Alpine longhorn beetle, \u003cem\u003eRosalia alpina\u003c/em\u003e, which has an IUCN status of vulnerable (VU), is considered a flagship beetle species (Di Nicola and Poloni \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and is widely recognized as an icon of European saproxylic biodiversity (Drag et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). It is also listed in Annexes II and IV of the Habitats Directive (Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora; Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), as well as in the Red List of Saproxylic Beetles in Europe (C\u0026aacute;lix et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lachat et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eRosalia alpina\u003c/em\u003e is a large longhorn beetle belonging to the order Coleoptera and the family Cerambycidae (Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Its most characteristic feature is its coloration pattern, which includes a blue background with up to six black spots on the elytra and one on the pronotum, the shape and size of which are individually specific. This trait is believed to play a role in effective camouflage against the background, as well as in thermoregulation (Kostić et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pavlović et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The coloration pattern also facilitates ecological studies of this species, as individual identification is essential for analyzing population size, dispersal, habitat preferences, and behavior (Caci et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Another characteristic feature of \u003cem\u003eR\u003c/em\u003e. \u003cem\u003ealpina\u003c/em\u003e is its antennae, the length of which represents the most reliable indicator of sexual dimorphism: in males, the antennae are significantly longer than the body, whereas in females they are only slightly longer than the body (Michalcewicz and Ciach \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e; Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eRosalia alpina\u003c/em\u003e is one of the key saproxylic invertebrates inhabiting Magura National Park in the Polish Carpathians. Its presence is closely associated with the availability of dead wood in forest ecosystems, as the species spends most of its life \u0026ndash; both egg and larval stages \u0026ndash; within decaying wood (Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The beetle predominantly develops in European beech \u003cem\u003eFagus sylvatica\u003c/em\u003e (Cizek et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Castro et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Castro and Fern\u0026aacute;ndez 2016; Drag et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), but it has also been recorded in wych elm \u003cem\u003eUlmus glabra\u003c/em\u003e (Ciach et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Michalcewicz et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), European ash \u003cem\u003eFraxinus excelsior\u003c/em\u003e (Michalcewicz and Ciach \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012b\u003c/span\u003e), and sycamore \u003cem\u003eAcer pseudoplatanus\u003c/em\u003e (Michalcewicz et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Other host tree species include hornbeam, lime, chestnut, walnut, and oak. Habitat preferences of \u003cem\u003eR. alpina\u003c/em\u003e appear to vary across its geographical range (Russo et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Bosso et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ciach and Michalcewicz \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). \u003cem\u003eR. alpina\u003c/em\u003e is widely regarded as an indicator of forest habitat quality, particularly in beech-dominated forests. Since the body size of xylophagous beetles is influenced by host tree species as well as the quantity and quality of breeding material, biometric traits of adult \u003cem\u003eR. alpina\u003c/em\u003e may serve as reliable indicators of both the attractiveness of breeding substrates and overall habitat quality (Michalcewicz and Ciach \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAside from its intrinsic value and its contribution to biological diversity, the protection of the Alpine longhorn beetle is necessary due to the collapse in its population size and distribution within the country (Adamski et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). It is believed that the historical range of the beetle coincided with that of the common beech, covering a significant part of Poland (Michalcewicz and Ciach \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This range has progressively shrunk, as inferred from data on the species\u0026rsquo; distribution in the 20th century. Earlier reports indicate that the beetle was present in the Carpathians, the Holy Cross Mountains, Roztocze, and isolated lowland sites in the northern and western parts of the country (Michalcewicz and Ciach \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). As a result of this contraction, the species is now found only in isolated sites in the Carpathians (Michalcewicz and Ciach \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe species is not only disappearing in Poland; similar population declines have been observed in other parts of Europe (Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bosso et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The main cause of the beetle\u0026rsquo;s decline is the loss and fragmentation of its natural habitat. In many parts of its range, the species is now restricted to small patches of broadleaf mountain forests rich in senescent trees and abundant decaying wood (Campanaro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Previous studies indicate that most areas suitable for the occurrence of \u003cem\u003eR. alpina\u003c/em\u003e are not protected (Bosso et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The loss of dead wood in forests and year-round forest management, including activities conducted during the insect\u0026rsquo;s mating season, may also contribute to population decline. Beech trees harvested and stored in wood stacks from June to July are readily colonized by Alpine longhorn beetles, which lay eggs in this material. As a result, wood stacks become ecological traps, since the colonized wood is subsequently removed for processing, thereby nullifying the insects\u0026rsquo; reproductive efforts (Adamski et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consequently, attempts are being made to improve the population status of the Alpine longhorn beetle and other saproxylic beetles in Europe, with particular attention given to the Carpathian Mountain Range (Mirea et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, these actions appear insufficient, as the declining population trend persists. Therefore, it is essential to expand and update knowledge on the biology and ecology of this beetle in order to enhance active conservation efforts for this highly valuable insect.\u003c/p\u003e \u003cp\u003eThere is still limited knowledge regarding the species\u0026rsquo; dispersal capabilities, the effects of habitat fragmentation on population isolation, and the level of genetic variability across its range. So far these aspects have been studied in only a few populations (Drag et al. 2013, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Molfini et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Understanding the environmental requirements of the Alpine longhorn beetle, the spatial range of individual movements and population genetic structure is essential for planning active conservation measures and for designating protected areas, such as Magura National Park, one of the species\u0026rsquo; most important strongholds in Poland.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003cem\u003eStudy site\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudies were conducted in Beskid Niski, in southeastern Poland, within Magura National Park (MNP). 95% of the MNP area is covered with forests, while only 5% consists of meadows. Two altitudinal zones are present in Magura NP: the lowland zone (up to 550 m a.s.l.) and the lower montane zone (up to 846 m a.s.l.). The main forest type in the park is the \u003cem\u003eDentario glandulosae\u0026ndash;Fagetum\u003c/em\u003e forest, dominated by European beech \u003cem\u003eFagus sylvatica\u003c/em\u003e and, secondarily, silver fir \u003cem\u003eAbies alba\u003c/em\u003e. Geologically, MNP is composed of sedimentary rocks, specifically conglomerates, sandstones, and clay shales, forming part of the Carpathian Flysch Belt. The climate of MNP is transitional between continental and Atlantic types. Between 2009 and 2019, annual temperatures ranged from 6.2\u0026deg;C to 7.3\u0026deg;C, while total annual precipitation ranged between 800 and 900 mm during this period (R\u0026oacute;żański et al. 2019). \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGenetic structure \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe first part of the research aimed to conduct genetic analyses to assess the genetic structure and diversity of the Alpine longhorn beetle population inhabiting Magura National Park. In the initial stage, during fieldwork carried out in the summer of 2023, genetic material was collected from 104 individuals of \u003cem\u003eR. alpina\u003c/em\u003e across twelve study sites within the park (Fig. 1). Genetic material was collected from 101 living individuals and 3 deceased specimens. The samples were subsequently transported to the Museum and Institute of Zoology of the Polish Academy of Sciences in Warsaw for genetic analysis. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIsolation was performed using the Insect DNA Tissue Kit (Macherey-Nagel). Genomic DNA was extracted from a small fragment of leg tissue collected from 104 \u003cem\u003eRosalia alpina\u003c/em\u003e individuals. Multiplex PCR amplifications were performed in a 10 \u0026micro;l reaction volume using the Multiplex PCR Master Mix (Qiagen), containing 1\u0026times; Master Mix, 0.2 \u0026micro;M of each primer, and approximately 20 ng of template DNA. Thermal cycling conditions were as follows: an initial activation step at 95 \u0026deg;C for 15 min; 45 cycles of denaturation at 94 \u0026deg;C for 30 s, annealing at 54 \u0026deg;C for 90 s, and extension at 72 \u0026deg;C for 60 s; followed by a final extension at 72\u0026deg;C for 10 min. Sequencing was performed on an Applied Biosystems 3500 XL sequencer, and genotypes were analyzed using GeneMapper software (Applied Biosystems). All individuals were genotyped at eight loci using microsatellite markers developed by Drag et al. (2015). The RA08 locus was excluded due to consistent amplification failure across all samples. Microsatellite loci were amplified in two multiplex PCR reactions, with Multiplex 1 including loci RA11 (HEX), RA13 (HEX), RA28 (HEX), RA29 (FAM), and RA37 (HEX), and Multiplex 2 comprising loci RA15 (TAMRA), RA23 (ROX), and RA40 (FAM). Genotyping was successful for 98 individuals. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe obtained results were analyzed at two levels: for the population as a whole (N = 98) and subdivided into 12 groups based on the location of individual capture (\u0026lsquo;B\u0026rsquo; \u0026ndash; Baranie Stack of Wood, \u0026lsquo;BW\u0026rsquo; \u0026ndash; Baranie Elm, \u0026lsquo;C\u0026rsquo; \u0026ndash; Ciechania, \u0026lsquo;G\u0026rsquo; \u0026ndash; Grab, \u0026lsquo;H\u0026rsquo; \u0026ndash; Hałb\u0026oacute;w, \u0026lsquo;HK\u0026rsquo; \u0026ndash; Huta Krempska, \u0026lsquo;J\u0026rsquo; \u0026ndash; Jaworze, \u0026lsquo;K\u0026rsquo; \u0026ndash; Krempna, \u0026lsquo;KO\u0026rsquo; \u0026ndash; Kolanin, \u0026lsquo;N\u0026rsquo; \u0026ndash; Nieznajowa, \u0026lsquo;P\u0026rsquo; \u0026ndash; Polany, \u0026lsquo;S\u0026rsquo; \u0026ndash; Słodkie). Due to the small size of four groups (\u0026lsquo;HK\u0026rsquo;, \u0026lsquo;N\u0026rsquo;, \u0026lsquo;K\u0026rsquo;, and \u0026lsquo;G\u0026rsquo;), some analyses \u0026ndash; particularly those sensitive to unequal sample sizes \u0026ndash; were performed on the eight largest groups. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhether the population met the assumptions of Hardy\u0026ndash;Weinberg equilibrium was tested using Genepop on the Web 4.7 (Raymond and Rousset 1995; Rousset 2008). Basic population parameters \u0026ndash; such as the number of alleles, number of private alleles, expected and observed heterozygosity, and genetic distances \u0026ndash; were calculated using GenAlEx 6.5 (Peakall and Smouse 2006, 2012) and FSTAT v.2.9.4 (Goudet 1995, 2001). Genetic distances between groups were also calculated in FSTAT v.2.9.4, and the significance of differences was tested using permutation tests with Bonferroni correction for multiple comparisons. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBayesian clustering analysis was performed in Structure 2.3.4 (Pritchard et al. 2000; Hubisz et al. 2009), testing the division of the studied population into clusters ranging from K = 1 to K = 15 with 10 replicates. The analysis used 100,000 Markov chain Monte Carlo (MCMC) iterations, with 50,000 iterations after burn-in, applying the \u0026ldquo;loci prior\u0026rdquo; option and excluding the four smallest groups. The results were subsequently analyzed in StructureSelector (Li and Liu 2018) to determine the optimal number of clusters using the Evanno method and to visualize the averaged Bayesian results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrincipal Coordinate Analysis (PCoA) based on genetic distances was conducted in GenAlEx 6.5, including all groups. Signs of population bottlenecks were assessed using Bottleneck 1.2.02 (Piry et al. 1999) for the population as a whole, and effective population size was estimated using LDNE (Waples and Do 2008), considering only alleles with a frequency above 0.02. Relatedness among individuals, calculated using the DyadML coefficient, was computed in COANCESTRY (Wang 2011) and visualized in plots divided by groups. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDispersal data collection\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe part of the research on dispersal ability was conducted during the four summer seasons; between 24 June and 22 August 2022, 4 July and 22 August 2023, 15 June and 2 August 2024, and 25 June and 12 August 2025, depending on the annual activity of \u003cem\u003eR. alpina\u003c/em\u003e. Fieldwork was carried out between 10 a.m. and 2 p.m. The dispersal abilities of the Alpine longhorn beetle were studied by using two methods: radio telemetry and individual visual marking (Fig. 2). The radio telemetry method involved equipping selected individuals with ultra-light transmitters that emitted a radio signal (Fig. 3). During fieldwork, the locations of the insects were monitored and tracked using radio receivers. The lightest available transmitters (ATS T15 Tiny Transmitter), weighing approximately 0.15 g, were used and ten individuals were marked by using this method. Telemetry marking had not previously been attempted on the Alpine longhorn beetle, so the research was experimental in nature and the outcomes were unpredictable. The study clearly indicated a strong impact of the transmitters on the dispersal abilities of the marked individuals. Two of the three tagged beetles did not fly at all, and the transmitters were subsequently removed from their pronota. One particularly large individual made several efforts to fly with the transmitter attached, but on each occasion it descended directly to the ground, landing after only a few meters. Subsequently, this individual intentionally removed the transmitter by pressing it against peeling bark, which resulted in partial removal of the cuticle on the pronotum. Consequently, further attempts to use the telemetry method were abandoned. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven that the main objective of the research was to determine dispersal parameters, telemetry marking was discontinued, and the focus shifted primarily to an alternative mark\u0026ndash;recapture method involving the use of colored markers (Fig. 2). In this method, a distinct set of colors was assigned to each marking location, and the exact position (using GPS) and sex of each individual were recorded. A total of 752 individuals participated in the study, and the majority were marked across all study locations (Fig. 1) using permanent markers (Tobby, Grand, and UniPaint). When marking was unsuccessful, individuals were identified based on the individual-specific spot pattern on the elytra and pronotum. Each individual was photographed to facilitate this identification. To analyze individual dispersal, the distance between the marking site and the subsequent recapture location was measured. Observations of beetles recorded multiple times on the same day within 30 meters of a previous observation were excluded from the analysis. The main study site for this part of the research was the \u0026ldquo;Baranie Stack of Wood,\u0026rdquo; where observations were conducted in all four years (2022\u0026ndash;2025). The primary objective at this location was to determine whether timber stacks might attract \u003cem\u003eR. alpina\u003c/em\u003e and limit its dispersal abilities. In 2022, the study was conducted exclusively at this site. Additionally, between 2023 and 2025, the area surrounding the \u0026ldquo;Baranie Stack of Wood,\u0026rdquo; as well as other locations within the MNP (Fig. 1), was surveyed to track beetle movement. Due to logistical constraints, data collection \u0026ndash; except at the \u0026ldquo;Baranie Stack of Wood\u0026rdquo; site, which was visited regularly throughout the entire \u003cem\u003eR. alpina\u003c/em\u003e activity season \u0026ndash; was not systematic. Instead, it focused on opportunistic observations aimed at estimating the flight distances of beetles in the vicinity of each individual\u0026rsquo;s initial sighting. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBased on the recorded distances, an inverse power function (IPF) was calculated separately for each sex. Only individuals that moved at least 30 m were included in the analysis. The function describes the probability (I) of movement over a distance D as I=C\u0026sdot;D\u003csup\u003e\u0026minus;n (1)\u003c/sup\u003e. The function was fitted by regressing the natural logarithms of the cumulative fractions of individuals moving a given or greater distance (ln I) against the linearized distance expression, i.e., lnC\u0026minus;n\u0026sdot;(lnD). The functions were fitted separately for males and females, and differences between the slopes and intercepts of the fitted functions were subsequently tested (Zar 1996; Drag et al. 2011). Differences between the two sexes were also examined using the Mann\u0026ndash;Whitney U test. All calculations were performed using Microsoft Excel and PAST 3.2.\u003c/p\u003e\n\u003cp\u003eAll these studies were conducted as part of the conservation activities of Magura National Park, with permission obtained from the Minister of Climate and Environment of Poland.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eGenetic structure \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOut of the 104 individuals of \u003cem\u003eRosalia alpina\u003c/em\u003e, 98 were successfully genotyped. For the remaining individuals, either no readings were obtained or readings were obtained for fewer than four microsatellite loci. All individuals included in the genetic study are listed in the supplementary materials (Online Resource 1). The number of alleles at the analyzed loci ranged from 5 to 8 (mean 5.750 \u0026plusmn; 0.412). The mean number of effective alleles was 2.347 \u0026plusmn; 0.262, which results from the fact that, in many cases, alleles occurred at very low frequencies. All loci showed observed heterozygosity lower than expected and a relatively high degree of inbreeding. The mean observed heterozygosity for the entire population was 0.401 \u0026plusmn; 0.071, while the expected heterozygosity was 0.518 \u0026plusmn; 0.073. The inbreeding coefficient was 0.274 \u0026plusmn; 0.060.\u003c/p\u003e\n\u003cp\u003eIndividual groups exhibited similar levels of genetic variation (Tab. 1). The highest number of private alleles was observed in the \u0026lsquo;B\u0026rsquo; group. The groups \u0026lsquo;S\u0026rsquo; and \u0026lsquo;H\u0026rsquo; showed the lowest allelic richness. The groups \u0026lsquo;P\u0026rsquo; and \u0026lsquo;S\u0026rsquo; had the lowest mean inbreeding coefficients. The population was found not to be in Hardy\u0026ndash;Weinberg equilibrium (p \u0026lt; 0.0001).\u003c/p\u003e\n\u003cp\u003eBayesian clustering analysis showed that the population is genetically uniform in terms of structure. Despite the formal support for two-cluster senario (K = 2) when considering model‐selection criteria (e.g., \u0026Delta;K and Puechmaille estimators), the Q‐matrix (Fig. 4) shows extensive admixture and highly similar ancestry proportions across all sampling sites. There is no clear population‐level separation into two discrete genetic groups; instead, one cluster dominates with only a minor contribution of the second cluster.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrincipal coordinates analysis (PCoA) indicated some heterogeneity within the studied population that is not related to spatial structure. Genetic distances between the groups were very low and not statistically significant. Only the genetic distance between the \u0026lsquo;P\u0026rsquo; and \u0026lsquo;C\u0026rsquo; was statistically significant and slightly higher, although it remained low (0.12; Tab. 2). This pattern is also reflected in the PCoA results (Fig. 5), where most individuals from \u0026lsquo;C\u0026rsquo; (pink diamonds) are located on the right side of the plot, while most individuals from \u0026lsquo;P\u0026rsquo; (brown triangles) are located on the left side.\u003c/p\u003e\n\u003cp\u003eThe estimated effective population size was 181 individuals, with a 95% confidence interval of 80.1\u0026ndash;7094.5. No signs of a population bottleneck were detected. The expected number of loci showing an excess of heterozygosity relative to the number of alleles was 4.74, whereas only one locus exhibited heterozygosity excess. In contrast, seven loci showed a statistically significant heterozygosity deficit relative to the number of alleles, which was highly significant (Wilcoxon test, p \u0026lt; 0.004).\u003c/p\u003e\n\u003cp\u003eRelatedness among individuals within the studied groups was relatively high, as illustrated in the diagrams, where highly related individuals are marked in red (Fig. 6A\u0026ndash;H). Most of the studied groups contained several pairs of highly related individuals.\u003c/p\u003e\n\u003cp\u003eDispersal ability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven current technological capabilities, the tested telemetry method proved ineffective for determining the dispersal of the species and was therefore replaced by a visual marking method using colored markers, which provided the expected results. Using this method, 752 individuals from various locations within Magura National Park (Fig. 1) were identified, and the sex was determined for 748 of them. All individuals included in the dispersal study, along with their first and subsequent observations and the distances from their previous locations, are listed in the supplementary materials (Online Resource 1). Throughout all years of the study, the number of males significantly exceeded that of females (Fig. 7), and in total it constituted 68,4% of the identified individuals. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was interannual variation in the probability of recapturing individuals, ranging from 16.9% in 2024 to 31.9% in 2022 (Tab. 3). Most recaptured individuals (approximately 88.7%) had not moved more than 30 m. Some individuals remained in the same location and were recaptured repeatedly. At the \u0026ldquo;Baranie Stack of Wood\u0026rdquo; site, one individual was recorded 13 times between 29 July and 13 August 2023. Two others were each recorded 10 times at this site: the first between 3 and 22 August 2022, and the second between 21 July and 11 August 2023. In the forest, one individual was documented five times within a 30 m radius between 31 July and 8 August 2023, followed by other individuals, which were observed three to four times each within the same radius. The maximum recorded dispersal distance for a single individual (female) was 845 m, followed by 428 m for two individuals (one male and one female) and 325 m for another individual (male). In general, the proportion of dispersing beetles decreased with increasing distance (Fig. 8).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was no significant difference in dispersal distance between males and females (P = 0.51, Mann-Whitney U test). The average distances between individuals included in the analysis were 147.4 meters for males (N = 11) and 196.9 meters for females (N = 8). The median distance was 55 meters for both males (N = 11) and females (N = 8). The IPF function showed identical probabilities of movement beyond 100 m for both sexes, but differences increased with distance (Tab. 4). The probability of movement over a distance of 500 m was almost twice as high in females as in males (Tab. 4), with females exhibited higher mobility than males, reaching nearly twice the maximum dispersal distance (Fig. 8). \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe MNP population appears to be panmictic, indicating gene flow among the sampling locations (Wright \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1978\u003c/span\u003e; Hartl and Clark \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). This is supported by both the low and statistically non-significant F\u003csub\u003eST\u003c/sub\u003e genetic distances between groups from different localities and the Bayesian clustering analysis conducted in STRUCTURE (Pritchard et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Evanno et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which detected no genetic structure within the population. Principal Coordinates Analysis (PCoA) based on genetic distances among individuals revealed a small cluster of individuals and a few outliers that are somewhat distinct from the rest of the population; however, this pattern is not related to sampling locations (Gower \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1966\u003c/span\u003e; Legendre and Legendre \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and does not indicate spatial structure. The most likely explanation is that these individuals carry alleles at very low frequencies, as private alleles were present in some groups despite the lack of significant genetic differentiation among them. Importantly, relatedness within localities was relatively high, and most sampling groups contained multiple closely related pairs. This pattern is consistent with localized breeding aggregations embedded within a broader panmictic framework \u0026ndash; a configuration that can maintain apparent homogeneity while simultaneously elevating inbreeding risk at the microspatial scale.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eRosalia alpina\u003c/em\u003e population in Magura National Park (MNP) exhibits a moderate level of genetic variability. Observed heterozygosity was lower than expected, and the inbreeding coefficient was relatively high. However, bottleneck tests provided no evidence of a recent drastic population decline. Interestingly, results concerning the relationship between observed alleles and heterozygosity \u0026ndash; a statistically significant heterozygosity deficit relative to the number of observed alleles \u0026ndash; may even suggest that the population is currently in an expansion phase. This interpretation is indirectly supported by the observed departure from Hardy\u0026ndash;Weinberg equilibrium, although the pattern could also be influenced by factors such as asymmetric gene flow or other ecological processes. Under mutation\u0026ndash;drift models (IAM/TPM), such a pattern may reflect recent demographic expansion following a historically reduced effective size, during which rare alleles accumulate faster than heterozygosity approaches equilibrium. Thus, the absence of a bottleneck signal should not be interpreted as demographic stability but rather as an indication that a population decline, if it occurred, may fall outside the temporal detection window of heterozygosity-based tests. While expansion of the Alpine longhorn beetle into lowland areas has been observed in Central Europe, Drag et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) documented a significant decline in genetic diversity with increasing latitude.\u003c/p\u003e \u003cp\u003eThe estimated effective population size of \u003cem\u003eR. alpina\u003c/em\u003e was relatively low, amounting to 181 individuals, with a wide upper confidence limit (7,095), reflecting statistical uncertainty rather than demographic security. By comparison, the protected scarab beetle \u003cem\u003eCheirotonus formosanus\u003c/em\u003e, which also exhibits significant inbreeding, has an estimated effective population size exceeding 20,000 individuals (Huang et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although direct interspecific comparisons should be interpreted cautiously, this contrast highlights the demographic vulnerability of the MNP population.\u003c/p\u003e \u003cp\u003eCompared to results from the Slovak population (Drag et al. 2013), where 45 individuals were analyzed, the MNP population exhibits higher genetic variability in terms of allele number, allelic richness, and heterozygosity. This suggests that the population in MNP represents a valuable reservoir of genetic diversity for the species, which warrants conservation. It is also important to consider that, due to insect life-history strategies \u0026ndash; such as high reproductive capacity and rapid generation turnover \u0026ndash; habitat fragmentation may affect population structure and observed genetic variability only after a considerable time lag. Consequently, endangered insect species may not immediately exhibit drastic signs of reduced genetic variability (Webster et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this context, the results are not entirely encouraging, as the observed level of genetic variability in the studied population is moderate and the effective population size is relatively low. However, the absence of evidence for a population bottleneck should not be interpreted as a justification for reducing conservation efforts for local \u003cem\u003eR. alpina\u003c/em\u003e populations, both in Magura National Park and in the surrounding areas of the Beskid Niski.\u003c/p\u003e \u003cp\u003eDue to the ineffectiveness of the telemetry method, a mark\u0026ndash;recapture approach was employed in our study, as it is considered an effective way to obtain quantitative population data necessary for assessing the conservation status of protected species, including beetles (Rossi de Gasperis 2017). With respect to individual dispersal abilities, the maximum observed dispersal distance in our study was 845 meters, which is approximately half of the longest recorded movement for \u003cem\u003eRosalia alpina\u003c/em\u003e (1,628 meters) observed in the Czech Republic (Drag et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In both cases, the greatest distances were recorded for females; however, overall, no statistically significant difference in total dispersal distances between the sexes was detected. It is worth noting that both in our study and that of Drag et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), females exhibited lower recapture rates than males. Several explanations may account for this pattern. First, behavioral differences between the sexes are likely important: males are more active and move more frequently between trees, whereas females are able to copulate and begin oviposition shortly after emerging from the wood (Drag et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Additionally, males tend to have a longer residence time in the population (up to approximately 24 days) compared to females (approximately 15 days), which increases their probability of recapture (Drag et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Finally, males of \u003cem\u003eRosalia alpina\u003c/em\u003e produce aggregation pheromones that attract both sexes, making them focal points of interactions within the population (Žunič Kosi et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As a result, males may be more exposed and therefore more likely to be detected and recaptured. Our results, as demonstrated by the IPF function, indicating a higher probability of long-distance movement in females, are also consistent with the findings of Drag et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe observation that some individuals were recorded multiple times at the same location suggests that certain individuals may exhibit only minimal movement, which further supports the results indicating a relatively high inbreeding coefficient within the population inhabiting Magura National Park. This pattern was particularly evident at the \u0026ldquo;Baranie Stack of Wood\u0026rdquo; site, suggesting that wood stacks may function as a form of ecological traps for beetles, as proposed in previous studies (Adamski et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It is worth noting, however, that at the \u0026ldquo;Baranie Stack of Wood\u0026rdquo; site, the wood is placed solely for \u003cem\u003eR. alpina\u003c/em\u003e and is not removed afterward.\u003c/p\u003e \u003cp\u003eThe spatial data collected allow for the determination of the maximum distances traveled by the beetles, which, when combined with knowledge of the species' biology, enables the assessment of their dispersal capacities and, consequently, the potential for population recovery in the event of significant habitat improvement, particularly in regions affected by habitat fragmentation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAt the genetic level, the \u003cem\u003eRosalia alpina\u003c/em\u003e population in Magura National Park is characterized by only moderate genetic variability and a relatively low effective population size. Although no signal of a recent bottleneck was detected, the combination of reduced observed heterozygosity, elevated inbreeding, and limited Ne suggests a demographically persistent but genetically vulnerable population. The absence of a strong spatial genetic structure indicates ongoing gene flow at the scale studied; however, the elevated relatedness within localities points to microspatial kin clustering, which may increase the risk of inbreeding over time in studied subpopulations.\u003c/p\u003e \u003cp\u003eFunctional dispersal capacity appears to be strongly constrained. Most individuals moved no more than 30 m, and the maximum recorded distance (845 m) represents an extreme movement rather than a typical movement. Such limited routine dispersal reduces the likelihood of effective recolonization and may restrict genetic rescue in increasingly fragmented landscapes. Although occasional long-distance movements may facilitate gene flow, they are unlikely to fully counterbalance the effects of habitat isolation on genetic structure.\u003c/p\u003e \u003cp\u003eTaken together, these findings suggest that the population is not currently collapsing but may be operating close to a threshold at which genetic erosion could accumulate. Therefore, apparent demographic persistence should not be equated with long-term resilience. Maintaining habitat continuity and preventing further habitat fragmentation in the Beskid Niski region will be critical for preserving the genetic diversity and evolutionary potential of \u003cem\u003eR\u003c/em\u003e. \u003cem\u003ealpina\u003c/em\u003e population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the PGE Polish Energy Group S.A. Foundation for funding the portion of this research concerning population genetics and the use of telemetry to study the dispersal abilities of \u003cem\u003eR. alpina\u003c/em\u003e in Magura National Park. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ\u0026oacute;zef J. R\u0026oacute;żański: Conceptualization; Methodology; Investigation \u0026ndash; genetic and dispersal data collection; Data curation; Analysis \u0026ndash; dispersal data analysis; Writing \u0026ndash; original draft preparation, review \u0026amp; editing; Visualization \u0026ndash; Figures 2, 3, 7, and 8, Table 3.\u003c/p\u003e\n\u003cp\u003eDamian Nowak: Funding acquisition; Conceptualization; Methodology; Investigation \u0026ndash; genetic and dispersal data collection; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eKonrad Krasoń: Investigation \u0026ndash; genetic and dispersal data collection; Analysis \u0026ndash; dispersal data analysis; Writing \u0026ndash; review \u0026amp; editing; Visualization \u0026ndash; Figure 1, Table 4.\u003c/p\u003e\n\u003cp\u003eJarosław Sochacki: Conceptualization; Methodology; Investigation \u0026ndash; genetic and dispersal data collection; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAgnieszka Gancarz: Investigation \u0026ndash; dispersal data collection; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eWaldemar Wojtas: Investigation \u0026ndash; dispersal data collection; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eMagdalena Witek: Conceptualization; Methodology; Data curation; Analysis \u0026ndash; genetic and dispersal data analysis; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAnna Sztencel-Jabłonka: Conceptualization; Methodology; Data curation; Analysis \u0026ndash; genetic data analysis; Writing \u0026ndash; review \u0026amp; editing; Visualization \u0026ndash; Figures 4, 5, and 6, Tables 1 and 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was partially funded by the PGE Polish Energy Group S.A. Foundation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e All data supporting the findings of this study are included in the article and its Supplementary Material.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOrcid \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ\u0026oacute;zef J. R\u0026oacute;żański, https://orcid. org/0000-0001-9484-560X \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnna Sztencel-Jabłonka, https://orcid.org/0000-0002-7374-2190\u003c/p\u003e\n\u003cp\u003eMagdalena Witek, https://orcid.org/0000-0002-6172-8981\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdamski P, Bohdan A, Michalcewicz J, Ciach M, Witkowski Z (2016) Timber stacks: potential ecological traps for an endangered saproxylic beetle, the \u003cem\u003eRosalia alpina\u003c/em\u003e. J Insect Conserv 20:1099-1105. \u003c/li\u003e\n\u003cli\u003eAdamski P, Holly M, Michalcewicz J, Witkowski Z (2013) Zanikanie nadobnicy alpejskiej \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) (Coleoptera: Cerambycidae) w Polsce \u0026ndash; wybrane mechanizmy procesu. In: W Ząbecki (ed), Rola i udział owad\u0026oacute;w w funkcjonowaniu ekosystem\u0026oacute;w leśnych, Krak\u0026oacute;w: Wydawnictwo Uniwersytetu Rolniczego w Krakowie pp 185-200 \u003c/li\u003e\n\u003cli\u003eBosso L, Rebelo H, Garonna AP, Russo D (2013) Modelling geographic distribution and detecting conservation gaps in Italy for the threatened beetle \u003cem\u003eRosalia alpina\u003c/em\u003e. J Nat Conserv 21:72-80. \u003c/li\u003e\n\u003cli\u003eBosso L, Smeraldo S, Rapuzzi P, Gianfranco S, Garonna AP, Russo D (2018) Nature protection areas of Europe are insufficient to preserve the threatened beetle \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae): evidence from species distribution models and conservation gap analysis. Ecol Entomol 43:192-203.\u003c/li\u003e\n\u003cli\u003eCaci G, Biscaccianti AB, Cistrone L, Bosso L, Garonna AP, Russo D (2013) Spotting the right spot: computer-aided individual identification of the threatened cerambycid beetle \u003cem\u003eRosalia alpina\u003c/em\u003e. J Insect Conserv 17:787-795. \u003c/li\u003e\n\u003cli\u003eC\u0026aacute;lix M, Alexander KNA, Nieto A, Dodelin B, Soldati F, Telnov D, Vazquez-Albalate X, Aleksandrowicz O, Audisio P, Istrate P, Jansson N, Legakis A, Liberto A, Makris C, Merkl O, Mugerwa Pettersson R, Schlaghamersky J, Bologna MA, Brustel H, Buse J, Nov\u0026aacute;k V, Purchart L (2018) European Red List of Saproxylic Beetles. Brussels, Belgium: IUCN.\u003c/li\u003e\n\u003cli\u003eCampanaro A, Redolfi De Zan L, Hardersen S, Antonini G, Chiari S, Cini A, Mancini E, Mosconi F, Rossi de Gasperis S, Sabbatini Peverieri G (2017) Guidelines for the monitoring of \u003cem\u003eRosalia alpina\u003c/em\u003e. Nat Conserv 20:165-203. \u003c/li\u003e\n\u003cli\u003eCastro A, de Murgu\u0026iacute;a LM, Fern\u0026aacute;ndez Perez J, Casis A (2013) Size and quality of wood used by \u003cem\u003eRosalia alpina\u003c/em\u003e (Linnaeus, 1758) (Coleoptera: Cerambycidae) in beech woodlands of Gipuzkoa (northern Spain). Munibe Cienc Nat 60:77-100. \u003c/li\u003e\n\u003cli\u003eCastro A, Fern\u0026aacute;ndez Perez J (2016) Tree selection by the endangered beetle \u003cem\u003eRosalia alpina\u003c/em\u003e in a lapsed pollard beech forest. J Insect Conserv 20:201-214. \u003c/li\u003e\n\u003cli\u003eCiach M, Michalcewicz J, Fluda M (2007) The first report on development of \u003cem\u003eRosalia alpina\u003c/em\u003e (LINNAEUS, 1758) (Coleoptera: Cerambycidae) in wood of \u003cem\u003eUlmus\u003c/em\u003e L. in Poland. Pol J Entomol 76:101-105.\u003c/li\u003e\n\u003cli\u003eCiach M, Michalcewicz J (2014) Pastureland copses as habitats for a primeval forest relict: a unique location of the Rosalia Longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) (Coleoptera: Cerambycidae) in the Polish Carpathians. Pol J Entomol 83:71-77. \u003c/li\u003e\n\u003cli\u003eCizek L, Schlaghamersk\u0026yacute; J,Bo\u0026oslash;uck\u0026yacute; J, Hauck D, Cizek JH, Schlaghamersk\u0026yacute; L, Hauck J (2009) Range expansion of an endangered beetle: Alpine Longhorn \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae) spreads to the lowlands of Central Europe. Entomol Fenn 20 (3). DOI:10.33338/ef.84478. \u003c/li\u003e\n\u003cli\u003eDi Nicola MR, Poloni R (2021) First documentation of males\u0026rsquo; fights in rosalia longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (Linnaeus, 1758) (Coleoptera, Cerambycidae). Entomol Rev 100:993-999. \u003c/li\u003e\n\u003cli\u003eDrag L, Hauck D, B\u0026eacute;rces S, Michalcewicz J, Jelaska L\u0026Scaron;, Aurenhammer S, Cizek L (2015) Genetic differentiation of populations of the threatened saproxylic beetle Rosalia longicorn, \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae) in Central and South-east Europe. Biol J Linn Soc 116:911-925. \u003c/li\u003e\n\u003cli\u003eDrag L, Hauck D, Pokluda P, Zimmermann K, Cizek L (2011) Demography and dispersal ability of a threatened saproxylic beetle: a mark-recapture study of the rosalia longicorn (\u003cem\u003eRosalia alpina\u003c/em\u003e). PLoS ONE 6 (6): e21345. https://doi:10.1371/journal.pone.0021345\u003c/li\u003e\n\u003cli\u003eDrag L, Hauck D, Rican O, Schmitt T, Shovkoon DF, Godunko RJ, Curletti G, Cizek L (2018) Phylogeography of the endangered saproxylic beetle Rosalia longicorn, \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera, Cerambycidae), corresponds with its main host, the European beech (\u003cem\u003eFagus sylvatica\u003c/em\u003e, Fagaceae). J Biogeogr 45:2631-2644. \u003c/li\u003e\n\u003cli\u003eDrag L, Zima JJr, Cizek L (2013) Characterization of nine polymorphic microsatellite loci\u003c/li\u003e\n\u003cli\u003efor a threatened saproxylic beetle \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae). Conserv Genet Resour 5: 903-905. https://doi: 10.1007/s12686-013-9929-1 \u003c/li\u003e\n\u003cli\u003eEvanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters using the software STRUCTURE: a simulation study. 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J Hered 115:292-301. https://doi.org/10.1093/jhered/esae006\u003c/li\u003e\n\u003cli\u003eHubisz MJ, Falush D, Stephens M, Pritchard JK (2009) \u003cem\u003eInferring weak population structure with the assistance of sample group information\u003c/em\u003e\u003cem\u003e. \u003c/em\u003eMol Ecol Resour 9:1322-1332.\u003c/li\u003e\n\u003cli\u003eKostić I, Pavlović D, Lazović V, Vasiljević D, Stojanović D, Knežević D, Tomić L, Dikić G, Pantelić D (2016) Thermal and camouflage properties of \u003cem\u003eRosalia alpina\u003c/em\u003e longhorn beetle with structural coloration. 7\u003csup\u003eth\u003c/sup\u003e International Scientific Conference on Defensive Technologies, Belgrade, Serbia 6\u0026ndash;7 October 2016. \u003c/li\u003e\n\u003cli\u003eLachat T, Ecker K, Duelli P, Wermelinger B (2013) Population trends of \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) in Switzerland: A lasting turnaround? J Insect Conserv 17:653-662. https://doi: 10.1007/s10841-013-9549-9\u003c/li\u003e\n\u003cli\u003eLegendre P, Legendre L (2012) Numerical Ecology, Developments in Environmental Modelling. 3rd Edition, Elsevier, Amsterdam, 419.\u003c/li\u003e\n\u003cli\u003eLi YL, Liu JX (2018) StructureSelector: A web based software to select and visualize the optimal number of clusters using multipe methods. Mol Ecol Resour 18:176-177. \u003c/li\u003e\n\u003cli\u003eMichalcewicz J, Bodziarczyk J, Ciach M (2013) Development of the rosalia longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) (Coleoptera: Cerambycidae) in the sycamore maple \u003cem\u003eAcer pseudoplatanus\u003c/em\u003e L. - the first report from Poland. Pol J Entomol 82:19-24. \u003c/li\u003e\n\u003cli\u003eMichalcewicz J, Ciach M, Bodziarczyk J (2011) The unknown natural habitat of \u003cem\u003eRosalia alpina \u003c/em\u003e(L.) (Coleoptera: Cerambycidae) and its trophic association with the mountain elm \u003cem\u003eUlmus glabra\u003c/em\u003e in Poland \u0026ndash; a change of habitat and host plant. Pol J Entomol 80:23-31. \u003c/li\u003e\n\u003cli\u003eMichalcewicz J, Ciach M (2012a) Biometry of adult rosalia longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) (Coleoptera: Cerambycidae) from the Polish Carpathians: a preliminary study. Pol J Entomol 81:311-320. \u003c/li\u003e\n\u003cli\u003eMichalcewicz J, Ciach M (2012b) Rosalia longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (L.) (Coleoptera: Cerambycidae) uses roadside European ash trees \u003cem\u003eFraxinus excelsior\u003c/em\u003e L. \u0026ndash; an unexpected habitat of an endangered species. Pol J Entomol 81:49-56.\u003c/li\u003e\n\u003cli\u003eMichalcewicz J, Ciach M (2015) Current distribution of the Rosalia longicorn \u003cem\u003eRosalia alpina\u003c/em\u003e (LINNAEUS, 1758) (Coleoptera: Cerambycidae) in Poland. Pol J Entomol 84:9-20. \u003c/li\u003e\n\u003cli\u003eMirea MD, Manolache S, Pioarca-Ciocanea CM, Nita A, Miu IV, Popescu VD, Brodie BS, Dragomir MI, Militaru I, Chiriac S, Rozylowic L (2021) Conservation of saproxylic beetles in the Carpathians. Res Ideas Outcomes 7:e63874. \u003cbr\u003e https://doi: 10.3897/rio.7.e63874\u003c/li\u003e\n\u003cli\u003eMolfini M, Redolfi De Zan L, Campanaro A, Rossi de Gasperis S (2018) A first assessment of genetic variability in the longhorn beetle \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae) from the Italian Apennines. Eur Zool J 85:36-45.\u003c/li\u003e\n\u003cli\u003ePavlović D, Vasiljević D, Salatić B, Lazović V, Dikić G, Tomić L, Ćurčić S, Milovanović P, Todorović D, Pantelić DV (2018) Photonic structures improve radiative heat exchange of \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae). J Thermal Biol 76:126-138. \u003c/li\u003e\n\u003cli\u003ePeakall R, Smouse PE (2006) GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288-295. \u003c/li\u003e\n\u003cli\u003ePeakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537-2539.\u003c/li\u003e\n\u003cli\u003ePiry S, Luikart G, Cornuet JM (1999) Computer note. BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data. J Hered 90:502-503. https://doi.org/10.1093/jhered/90.4.502 \u003c/li\u003e\n\u003cli\u003ePritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945-959.\u003c/li\u003e\n\u003cli\u003eRaymond M, Rousset F (1995) GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism. J Hered 86:248-249. https://doi.org/10.1093/oxfordjournals.jhered.a111573 \u003c/li\u003e\n\u003cli\u003eRossi de Gasperis S, Carpaneto GM, Nigro G, Antonini G, Chiari S, Cini A, Mancini E, Mason F, Mosconi F, Redolfi De Zan L, Roversi PF, Sabbatini Peverieri G, Solano E, Campanaro A (2017) Computer-aided photographic identification of \u003cem\u003eRosalia alpina\u003c/em\u003e (Coleoptera: Cerambycidae) applied to a mark-recapture study. Insect Conserv Divers 10:54-63. \u003c/li\u003e\n\u003cli\u003eRousset F (2008) GENEPOP\u0026rsquo;007: A complete re-implementation of the GENEPOP software for Windows and Linux. Mol Ecol Resour 8:103-106. https://doi.org/10.1111/j.1471-8286.2007.01931.x\u003c/li\u003e\n\u003cli\u003eR\u0026oacute;żański JJ, Nowak D, Sochacki J, Krasoń K (2019) Magurski Park Narodowy \u0026ndash; znaczenie dla nauki. Kosmos 68:621-631. \u003c/li\u003e\n\u003cli\u003eRusso D, Cistrone L, Garonna AP (2011) Habitat selection by the highly endangered long-horned beetle \u003cem\u003eRosalia alpina\u003c/em\u003e in Southern Europe: A multiple spatial scale assessment. J Insect Conserv 15:685-693. \u003c/li\u003e\n\u003cli\u003eWang J (2011) COANCESTRY: A program for simulating, estimating and analyzing relatedness and inbreeding coefficients. Mol Ecol Resour 11:141-145.\u003c/li\u003e\n\u003cli\u003eWaples RS, Do C (2008) LDNE: A program for estimating effective population size from data on linkage disequilibrium. Mol Ecol Resour 8:753-756. https://doi.org/10.1111/j.1755-0998.2007.02061.x\u003c/li\u003e\n\u003cli\u003eWebster MT, Beaurepaire A, Neumann P, Stolle E (2023) Population genomics for insect conservation. Annu Rev Anim Biosci 11:115-140. \u003c/li\u003e\n\u003cli\u003eWright S (1978) Evolution and the genetics of populations, Volume 4: variability within and among natural populations. University of Chicago Press. \u003c/li\u003e\n\u003cli\u003eZar JH (1996) Biostatistical Analysis. 3rd Edition, Prentice Hall, Upper Saddle River, 662 p. \u003c/li\u003e\n\u003cli\u003eŽunič Kosi A, Zou Y, Hoskovec M, Vrezec A, Stritih N, Millar JG (2017) Novel, male-produced aggregation pheromone of the cerambycid beetle \u003cem\u003eRosalia alpina\u003c/em\u003e, a priority species of European conservation concern. PLoS ONE 12(8): e0183279. https://doi.org/10.1371/journal.pone.0183279\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTab. 1\u003c/strong\u003e Genetic variation in individual groups from different locations. N \u0026ndash; sample size; Na \u0026ndash; mean number of alleles; PA \u0026ndash; number of private alleles; AR \u0026ndash; mean allelic richness after rarefaction to the smallest sample size; Ho \u0026ndash; mean observed heterozygosity; He \u0026ndash; mean expected heterozygosity; F \u0026ndash; mean inbreeding coefficient. Group (location): \u0026lsquo;B\u0026rsquo; \u0026ndash; Baranie Stack of Wood, \u0026lsquo;BW\u0026rsquo; \u0026ndash;Baranie Elm, \u0026lsquo;C\u0026rsquo; \u0026ndash; Ciechania, \u0026lsquo;H\u0026rsquo; \u0026ndash; Hałb\u0026oacute;w, \u0026lsquo;J\u0026rsquo; \u0026ndash; Jaworze, \u0026lsquo;KO\u0026rsquo; \u0026ndash; Kolanin, \u0026lsquo;P\u0026rsquo; \u0026ndash; Polany, \u0026lsquo;S\u0026rsquo; \u0026ndash; Słodkie\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"528\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Location)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.275\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 15.1515%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e3.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 12.1212%;\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTab. 2\u003c/strong\u003e Genetic F\u003csub\u003eST\u003c/sub\u003e distances between groups (locations). Statistically significant results are indicated in\u0026nbsp;\u003cstrong\u003ebold\u003c/strong\u003e (p \u0026lt; 0.0018, 560 permutations). Groups (locations): \u0026lsquo;B\u0026rsquo; \u0026ndash; Baranie Stack of Wood, \u0026lsquo;BW\u0026rsquo; \u0026ndash; Baranie Elm, \u0026lsquo;C\u0026rsquo; \u0026ndash; Ciechania, \u0026lsquo;H\u0026rsquo; \u0026ndash; Hałb\u0026oacute;w, \u0026lsquo;J\u0026rsquo; \u0026ndash; Jaworze, \u0026lsquo;KO\u0026rsquo; \u0026ndash; Kolanin, \u0026lsquo;P\u0026rsquo; \u0026ndash; Polany, \u0026lsquo;S\u0026rsquo; \u0026ndash; Słodkie \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" valign=\"bottom\" style=\"width: 11.1111%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTab. 3\u003c/strong\u003e Number of \u003cem\u003eR. alpina\u003c/em\u003e individuals identified and recaptured during the dispersal study (2022\u0026ndash;2025) in Magura National Park.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndividuals identified (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecaptures (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndividuals recaptured (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndividuals recaptured (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e31,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e134♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e48♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e126♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e14♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e53♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e39.6♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e10.4♀\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e19,0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e131♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e69♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e83♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e29♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e22.1♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e13.0♀\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e16,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e152♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e53♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e54♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e32♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e3♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e21.1♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e5.7♀\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e22,7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e95♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e66♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e49♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e12♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e28♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e9♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e29.5♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e13.6♀\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e22,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e512♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e236♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e312♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e43♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e142♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e26♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e27.7♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e11.0♀\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIndividuals identified (n) \u0026ndash; all individuals recorded during the study, including both marked individuals and those recognized based on spot patterns; Recaptures (n) \u0026ndash; total number of recapture events, including multiple recaptures of the same individuals; Individuals recaptured (n) \u0026ndash; total number of individuals that were recaptured at least once; Individuals recaptured (%) \u0026ndash; percentage of individuals that were recaptured \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTab. 4\u003c/strong\u003e Results of fitting the inverse power function (IPF) to movements of the Rosalia longicorn and predicted probability of movements to 100 m, 300 m, 500 m. N♂ = 11; N♀ = 8\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 295px;\"\u003e\n \u003cp\u003eIPF: ln I= ln C (+/- S.E) \u0026ndash; n (+/- S.E.)*ln D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100 \u0026nbsp;(m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e300 (m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e500 (m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax dist (m)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e♂\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 295px;\"\u003e\n \u003cp\u003eln I= -2.83 (+/- 0.25)-0.95(+/-0.25)*lnD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e428\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 36px;\"\u003e\n \u003cp\u003e♀\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 295px;\"\u003e\n \u003cp\u003eln I=-2.06(+/-0.42)-0.62(+/-0.26)*lnD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-insect-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jico","sideBox":"Learn more about [Journal of Insect Conservation](http://link.springer.com/journal/10841)","snPcode":"10841","submissionUrl":"https://submission.nature.com/new-submission/10841/3","title":"Journal of Insect Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"dispersal, genetics, population decline, population health, Rosalia alpina","lastPublishedDoi":"10.21203/rs.3.rs-9424736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9424736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study focused on the individual dispersal ability and population genetics of the alpine longhorn beetle, \u003cem\u003eRosalia alpina\u003c/em\u003e, in Magura National Park (MNP), Carpathians, southeastern Poland. Populations of this valuable and highly endangered saproxylic beetle are in severe decline worldwide. One of the main causes of this phenomenon is the degradation and fragmentation of the species\u0026rsquo; natural habitat, which is thought to result in inbreeding within local populations and consequently limit their genetic diversity. The methods employed in the study included radiotelemetry and a mark-and-recapture technique to investigate dispersal ability, as well as genetic analyses to assess the genetic status of the local beetle population. The study showed that alpine beetles dispersed at most 845 meters, with most recaptured individuals found within 30 meters of their marking site. These results indicate that alpine beetles generally travel short distances, and under certain conditions may not migrate at all. Genetic studies indicate that the low dispersal ability of \u003cem\u003eR. alpina\u003c/em\u003e in MNP corresponds with a relatively high inbreeding coefficient and a low effective population size. Despite this, the population shows a panmictic structure, with gene flow occurring among sampling sites across the park. A comparison with a Slovak population studied in 2013 shows that the Magura National Park population exhibits higher genetic variability, highlighting its importance as a reservoir of genetic diversity and the need for strong conservation measures.\u003c/p\u003e","manuscriptTitle":"Individual dispersal and population genetics of the alpine longhorn beetle Rosalia alpina inhabiting Magura National Park, Poland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-28 14:49:10","doi":"10.21203/rs.3.rs-9424736/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:00:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T08:56:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"193669367614336739807547109887979779847","date":"2026-04-28T07:20:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170814263876299851899612601968448883426","date":"2026-04-20T14:09:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T06:39:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-17T14:41:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-17T14:41:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Insect Conservation","date":"2026-04-15T09:17:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-insect-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jico","sideBox":"Learn more about [Journal of Insect Conservation](http://link.springer.com/journal/10841)","snPcode":"10841","submissionUrl":"https://submission.nature.com/new-submission/10841/3","title":"Journal of Insect Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cb09b081-a350-4e40-aed4-cc09ee2a83e8","owner":[],"postedDate":"April 28th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-12T15:00:41+00:00","index":11,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T08:56:21+00:00","index":10,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T14:49:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-28 14:49:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9424736","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9424736","identity":"rs-9424736","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}